Featured Publications
EXPLORE IDM’S CURRENT RESEARCH PUBLICATIONS
Michelle A Bulterys, Bradley Wagner, Mael Redard-Jacot, Anita Suresh, Nira R. Pollock, Emmanuel Moreau, Claudia M. Denkinger, Paul K. Drain, Tobias Broger
JOURNAL OF CLINICAL MEDICINE
Most diagnostic tests for tuberculosis (TB) rely on sputum samples, which are difficult to obtain and have low sensitivity in immunocompromised patients, patients with disseminated TB, and children, delaying treatment initiation. The World Health Organization (WHO) calls for the development of a rapid, biomarker-based, non-sputum test capable of detecting all forms of TB at the point-of-care to enable immediate treatment initiation. Lipoarabinomannan (LAM) is the only WHO-endorsed TB biomarker that can be detected in urine, an easily collected sample. This status update discusses the characteristics of LAM as a biomarker, describes the performance of first-generation urine LAM tests and reasons for slow uptake, and presents considerations for developing the next generation of more sensitive and impactful tests. Next-generation urine LAM tests have the potential to reach adult and pediatric patients regardless of HIV status or site of infection and facilitate global TB control. Implementation and scale-up of existing LAM tests and development of next-generation assays should be prioritized.
Stewart T. Chang, Violet N. Chihota, Katherine L. Fielding, Alison D. Grant, Rein M. Houben, Richard G. White, Gavin J. Churchyard, Philip A. Eckhoff, and Bradley G. Wagner
BMC MEDICINE
Background
Gold mines represent a potential hotspot for Mycobacterium tuberculosis (Mtb) transmission and may be exacerbating the tuberculosis (TB) epidemic in South Africa. However, the presence of multiple factors complicates estimation of the mining contribution to the TB burden in South Africa.
Methods
We developed two models of TB in South Africa, a static risk model and an individual-based model that accounts for longer-term trends. Both models account for four populations — mine workers, peri-mining residents, labor-sending residents, and other residents of South Africa — including the size and prevalence of latent TB infection, active TB, and HIV of each population and mixing between populations. We calibrated to mine- and country-level data and used the static model to estimate force of infection (FOI) and new infections attributable to local residents in each community compared to other residents. Using the individual-based model, we simulated a counterfactual scenario to estimate the fraction of overall TB incidence in South Africa attributable to recent transmission in mines.
Results
We estimated that the majority of FOI in each community is attributable to local residents: 93.9% (95% confidence interval 92.4–95.1%), 91.5% (91.4–91.5%), and 94.7% (94.7–94.7%) in gold mining, peri-mining, and labor-sending communities, respectively. Assuming a higher rate of Mtb transmission in mines, 4.1% (2.6–5.8%), 5.0% (4.5–5.5%), and 9.0% (8.8–9.1%) of new infections in South Africa are attributable to gold mine workers, peri-mining residents, and labor-sending residents, respectively. Therefore, mine workers with TB disease, who constitute ~ 2.5% of the prevalent TB cases in South Africa, contribute 1.62 (1.04–2.30) times as many new infections as TB cases in South Africa on average. By modeling TB on a longer time scale, we estimate 63.0% (58.5–67.7%) of incident TB disease in gold mining communities to be attributable to recent transmission, of which 92.5% (92.1–92.9%) is attributable to local transmission.
Conclusions
Gold mine workers are estimated to contribute a disproportionately large number of Mtb infections in South Africa on a per-capita basis. However, mine workers contribute only a small fraction of overall Mtb infections in South Africa. Our results suggest that curtailing transmission in mines may have limited impact at the country level, despite potentially significant impact at the mining level.
Prof Nicolas A Menzies, PhD, Gabriela B Gomez, PhD, Fiammetta Bozzani, MSc, Susmita Chatterjee, PhD, Nicola Foster, MPH, Ines Garcia Baena, MSc, Yoko V Laurence, MSc, Prof Sun Qiang, PhD, Andrew Siroka, PhD, Sedona Sweeney, MSc, Stéphane Verguet, PhD, Nimalan Arinaminpathy, DPhil, Andrew S Azman, PhD, Eran Bendavid, MD, Stewart T Chang, PhD, Prof Ted Cohen, DPH, Justin T Denholm, PhD, David W Dowdy, MD, Philip A Eckhoff, PhD, Jeremy D Goldhaber-Fiebert, PhD, Andreas Handel, PhD, Grace H Huynh, PhD, Marek Lalli, MSc, Hsien-Ho Lin, ScD, Sandip Mandal, PhD, Emma S McBryde, PhD, Surabhi Pandey, PhD, Prof Joshua A Salomon, PhD, Sze-chuan Suen, MS, Tom Sumner, PhD, James M Trauer, MBBS, Bradley G Wagner, PhD, Prof Christopher C Whalen, MD, Chieh-Yin Wu, MS, Delia Boccia, PhD, Vineet K Chadha, MD, Salome Charalambous, PhD, Daniel P Chin, MD, Prof Gavin Churchyard, PhD, Colleen Daniels, MA, Puneet Dewan, MD, Lucica Ditiu, MD, Jeffrey W Eaton, PhD, Prof Alison D Grant, PhD, Piotr Hippner, MSc, Mehran Hosseini, MD, David Mametja, MPH, Carel Pretorius, PhD, Yogan Pillay, PhD, Kiran Rade, MD, Suvanand Sahu, MD, Lixia Wang, MS, Rein M G J Houben, PhD, Michael E Kimerling, MD, Richard G White, PhD, Anna Vassall, PhD
THE LANCET
Background
The post-2015 End TB Strategy sets global targets of reducing tuberculosis incidence by 50% and mortality by 75% by 2025. We aimed to assess resource requirements and cost-effectiveness of strategies to achieve these targets in China, India, and South Africa.
Methods
We examined intervention scenarios developed in consultation with country stakeholders, which scaled up existing interventions to high but feasible coverage by 2025. Nine independent modelling groups collaborated to estimate policy outcomes, and we estimated the cost of each scenario by synthesising service use estimates, empirical cost data, and expert opinion on implementation strategies. We estimated health effects (ie, disability-adjusted life-years averted) and resource implications for 2016–35, including patient-incurred costs. To assess resource requirements and cost-effectiveness, we compared scenarios with a base case representing continued current practice.
Findings
Incremental tuberculosis service costs differed by scenario and country, and in some cases they more than doubled existing funding needs. In general, expansion of tuberculosis services substantially reduced patient-incurred costs and, in India and China, produced net cost savings for most interventions under a societal perspective. In all three countries, expansion of access to care produced substantial health gains. Compared with current practice and conventional cost-effectiveness thresholds, most intervention approaches seemed highly cost-effective.
Interpretation
Expansion of tuberculosis services seems cost-effective for high-burden countries and could generate substantial health and economic benefits for patients, although substantial new funding would be required. Further work to determine the optimal intervention mix for each country is necessary.
Figure 2 Incremental patient-incurred costs for 2016–35, for each intervention scenario, compared with the base case, by country and model.
Funding
Bill and Melinda Gates Foundation
Dr Rein M G J Houben, PhD, Nicolas A Menzies, PhD, Tom Sumner, PhD, Grace H Huynh, PhD, Nimalan Arinaminpathy, PhD, Jeremy D Goldhaber-Fiebert, PhD, Hsien-Ho Lin, PhD, Chieh-Yin Wu, MS, Sandip Mandal, PhD, Surabhi Pandey, PhD, Sze-chuan Suen, MS, Eran Bendavid, MD, Andrew S Azman, PhD, David W Dowdy, PhD, Nicolas Bacaër, PhD, Allison S Rhines, PhD, Prof Marcus W Feldman, PhD, Andreas Handel, PhD, Prof Christopher C Whalen, MD, Stewart T Chang, PhD, Bradley G Wagner, PhD, Philip A Eckhoff, PhD, James M Trauer, PhD, Justin T Denholm, PhD, Prof Emma S McBryde, PhD, Ted Cohen, DPH, Prof Joshua A Salomon, PhD, Carel Pretorius, PhD, Marek Lalli, MSc, Jeffrey W Eaton, PhD, Delia Boccia, PhD, Mehran Hosseini, MD, Gabriela B Gomez, PhD, Suvanand Sahu, MD, Colleen Daniels, MA, Lucica Ditiu, MD, Daniel P Chin, MD, Lixia Wang, MS, Vineet K Chadha, MD, Kiran Rade, MPhil, Puneet Dewan, MD, Piotr Hippner, MSc, Salome Charalambous, PhD, Prof Alison D Grant, Prof Gavin Churchyard, PhD, Yogan Pillay, PhD, L David Mametja, MPH, Michael E Kimerling, MD, Anna Vassall, PhD, Richard G White, PhD
THE LANCET
Background
The post-2015 End TB Strategy proposes targets of 50% reduction in tuberculosis incidence and 75% reduction in mortality from tuberculosis by 2025. We aimed to assess whether these targets are feasible in three high-burden countries with contrasting epidemiology and previous programmatic achievements.
Methods
11 independently developed mathematical models of tuberculosis transmission projected the epidemiological impact of currently available tuberculosis interventions for prevention, diagnosis, and treatment in China, India, and South Africa. Models were calibrated with data on tuberculosis incidence and mortality in 2012. Representatives from national tuberculosis programmes and the advocacy community provided distinct country-specific intervention scenarios, which included screening for symptoms, active case finding, and preventive therapy.
Findings
Aggressive scale-up of any single intervention scenario could not achieve the post-2015 End TB Strategy targets in any country. However, the models projected that, in the South Africa national tuberculosis programme scenario, a combination of continuous isoniazid preventive therapy for individuals on antiretroviral therapy, expanded facility-based screening for symptoms of tuberculosis at health centres, and improved tuberculosis care could achieve a 55% reduction in incidence (range 31–62%) and a 72% reduction in mortality (range 64–82%) compared with 2015 levels. For India, and particularly for China, full scale-up of all interventions in tuberculosis-programme performance fell short of the 2025 targets, despite preventing a cumulative 3·4 million cases. The advocacy scenarios illustrated the high impact of detecting and treating latent tuberculosis.
Interpretation
Major reductions in tuberculosis burden seem possible with current interventions. However, additional interventions, adapted to country-specific tuberculosis epidemiology and health systems, are needed to reach the post-2015 End TB Strategy targets at country level.
Grace H Huynh, Daniel Klein, Daniel P Chin, Bradley G Wagner, Philip A Eckhoff, Renzhong Liu, and Lixia Wang
BMC MEDICINE
Background: Significant progress in tuberculosis (TB) control has been achieved worldwide over the last two decades. Global TB mortality has fallen by 45%, and TB incidence is declining. Recently, the World Health Organization (WHO) established an ambitious post-2015 global strategy, the End TB Strategy. This strategy outlines a 2025 milestone of 50% reduction in incidence and 75% reduction in mortality, and an overall 2035 target of 90% reduction in incidence and 95% reduction in mortality. In order to reach these targets, countries will likely need to redouble their TB control efforts and perhaps adopt new TB control strategies.
Between 1992 and 2012, China made impressive progress in TB control. Prior to 1992, most TB patients were treated in private hospitals, where patients typically received low-quality care - improper treatment was widespread, and only approximately 20% of patients had supervised TB treatment. In addition, nearly 50% experienced interrupted or shortened treatment and there was little follow-up of patients who dropped out or relapsed after a treatment episode. Starting in 1992, China ramped up a high-quality directly observed treatment, short-course (DOTS)-based strategy in Center for Disease Control (CDC) public health clinics in 13 provinces covering half the population, requiring hospitals to refer suspected TB patients to the CDC system. In the early 2000s, the DOTS program was expanded nationwide and an Internet-based disease reporting system was introduced [8]-[11], further increasing referrals from the hospital to the CDC system. By 2010 it was estimated that approximately 80% of all TB patients were confirmed and treated within the CDC system [8],[9], where the treatment success rate was estimated to be 85%.
Methods: The present study utilizes the Disease Transmission Kernel (DTK) model developed by the Institute for Disease Modeling group at Intellectual Ventures. The model and all necessary input files are available by request at the Institute for Disease Modeling website. Additional file 1 details the model structure, assumptions, and a complete list of model inputs.
Conclusions: The combination of an aging demographic in China and the increasing role of reactivation disease represents a growing challenge to TB control as China considers its post-2015 strategy. We have constructed a mathematical model of TB transmission at the country level in China, taking into account aging of the population and estimating the contribution of reactivation to overall incidence. The nationwide roll-out of the DOTS program reduced the annual risk of infection(ARI) [81],[82] by improving treatment outcomes and reducing infectiousness from treatment experienced individuals. Given the high population coverage of DOTS in the CDC public health clinics, we estimate that new transmission is not the major driver of overall TB incidence. Rather, reactivation disease, combined with the growing elderly population, will be the major determinant of the decline in TB incidence and mortality over the next two decades.
Grace H Huynh, Daniel Klein, Daniel P Chin, Bradley G Wagner, Philip A Eckhoff, Renzhong Liu, and Lixia Wang
BMC MEDICINE
Background
In the last 20 years, China ramped up a DOTS (directly observed treatment, short-course)-based tuberculosis (TB) control program with 80% population coverage, achieving the 2015 Millennium Development Goal of a 50% reduction in TB prevalence and mortality. Recently, the World Health Organization developed the End TB Strategy, with an overall goal of a 90% reduction in TB incidence and a 95% reduction in TB deaths from 2015–2035. As the TB burden shifts to older individuals and China’s overall population ages, it is unclear if maintaining the current DOTS strategy will be sufficient for China to reach the global targets.
Methods
We developed an individual-based computational model of TB transmission, implementing realistic age demographics and fitting to country-level data of age-dependent prevalence over time. We explored the trajectory of TB burden if the DOTS strategy is maintained or if new interventions are introduced using currently available and soon-to-be-available tools. These interventions include increasing population coverage of DOTS, reducing time to treatment, increasing treatment success, and active case finding among elders > 65 years old. We also considered preventative therapy in latently infected elders, a strategy limited by resource constraints and the risk of adverse events.
Results
Maintenance of the DOTS strategy reduces TB incidence and mortality by 42% (95% credible interval, 27-59%) and 41% (5-64%), respectively, between 2015 and 2035. A combination of all feasible interventions nears the 2035 mortality target, reducing TB incidence and mortality by 59% (50-76%) and 83% (73-94%). Addition of preventative therapy for elders would enable China to nearly reach both the incidence and mortality targets, reducing incidence and mortality by 84% (78-93%) and 92% (86-98%).
Conclusions
The current decline in incidence is driven by two factors: maintaining a low level of new infections in young individuals and the aging out of older latently infected individuals who contribute incidence due to reactivation disease. While further reducing the level of new infections has a modest effect on burden, interventions that limit reactivation have a greater impact on TB burden. Tools that make preventative therapy more feasible on a large scale and in elders will help China achieve the global targets.
BIOGRAPHY
Robert S. Hart is the Director of IDM. Robert has a Ph.D. in Geophysics as well as a Master of Science degree in Geophysics from the California Institute of Technology (CalTech), and a Bachelor of Science degree in Earth and Planetary Sciences from the Massachusetts Institute of Technology (MIT). He has over thirty years of experience founding and managing high technology-based software firm as an executive officer and venture investor, as well as serving as a board director. He was most recently a founder and the CEO of Veratect Corporation, an open source data mining and analysis firm providing the earliest possible indicators of the emergence of infectious disease worldwide, but with a particular focus on the developing world. Prior to Veratect, highlights of Robert’s career include tenure as the CEO of Corazonx, a cardiac ultrasound software firm; General Partner at SeaPoint Ventures, a venture capital firm focusing on the wireless telecom industry; CEO of Tegic Communications, the developer of the predictive text input software used in most cellular phones; CEO of Optimas Corporation, a digital image analysis firm; and founder and CEO of Sierra Geophysics, a leading provider of applications software to the global oil and gas industry. Robert currently serves on a number of corporate and non-profit boards.
Robert Hart
Director, Disease Modeling
BIOGRAPHY
Nicole Bates is the Deputy Director of IDM Program Operations and has over ten years of experience in program and project management, as well as in the computer security field. She has a Bachelor of Arts degree in Political Economy, as well as French, from the University of California, Berkeley (UC Berkeley). Her political economy research focused on technology and its relationship to politics and economics; specifically the evolution of computer security crimes and cybersecurity as it relates to politics. Nicole also did extensive work with the UC Berkeley School of Public Health implementing new data analysis methods now widely used in Women, Infant, and Children (WIC) nutritional studies, as well as the Goldman School of Public Policy, where she coordinated board meetings, did financial campaign planning, and orchestrated a speaker series. Nicole has been an advocate for emerging technologies and their application in the developing world, and has spent the past ten years developing technical solutions designed for the public sector. She has worked in higher education, government, as well as corporate sectors where she focused on security and privacy issues. Additionally, she has drafted and improved security response procedures and established security forums aimed at increasing collaboration and the open discussion of issues. As a member of IDM’s management team, Nicole is focused on setting and planning on-going strategic objectives related to IDM’s mission, managing the program budget, monitoring project progress and planning, coordinating release cycles with IDM’s partners, as well as ensuring that partner feedback is incorporated into IDM’s software development lifecycle, documentation, and website functionality.
Nicole Bates
Deputy Director, IDM Program Operations
BIOGRAPHY
Guillaume Chabot-Couture is Deputy Director, Research Programs at the Institute for Disease Modeling. He has a Ph.D. in Applied Physics from Stanford University, where he focused on experimental and theoretical cuprate superconductor research. Guillaume has received two national post-graduate scholarships from the Natural Sciences and Engineering Research Council of Canada. In his spare time, Guillaume has served as a lecturer and leader for the Canadian Physics Olympiad. Guillaume’s research interests include vaccination campaign data analysis and modeling, disease risk estimation, financial projections, health economics, and weather modeling
PUBLICATIONS (12)
Background Measles causes significant childhood morbidity in Nigeria. Routine immunization (RI) coverage is around 40% country-wide, with very high levels of spatial heterogeneity (3–86%), with supplemental immunization activities (SIAs) at 2-year or 3-year intervals. We investigated cost savings and burden reduction that could be achieved by adjusting the inter-campaign…
The polio environmental surveillance (ES) system has been an incredible tool for advancing polio eradication efforts because of its ability to highlight the spatial and temporal extent of poliovirus circulation. While ES often outperforms, or is more sensitive than AFP surveillance, the sensitivity of the ES system has not been well characterized. Fundamental uncertainty of ES site sensitivity…
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
The oral polio vaccine (OPV) contains live-attenuated polioviruses that induce immunity by causing low virulence infections in vaccine recipients and their close contacts. Widespread immunization with OPV has reduced the annual global burden of paralytic poliomyelitis by a factor of 10,000 or more and has driven wild poliovirus (WPV) to the brink of eradication. However, in instances that have…
Background Pakistan is one of only three countries where poliovirus circulation remains endemic. For the Pakistan Polio Eradication Program, identifying high risk districts is essential to target interventions and allocate limited resources. Methods Using a hierarchical Bayesian framework we developed…
The globally synchronized removal of the attenuated Sabin type 2 strain from the oral polio vaccine (OPV) in April 2016 marked a major change in polio vaccination policy. This change will provide a significant reduction in the burden of vaccine-associated paralytic polio (VAPP), but may increase the risk of circulating vaccine-derived…
Background Wild type 2 poliovirus was last observed in 1999. The Sabin-strain oral polio vaccine type 2 (OPV2) was critical to eradication, but it is known to revert to a neurovirulent phenotype, causing vaccine-associated paralytic poliomyelitis. OPV2 is also transmissible and can establish…
Background Since the launch of the Global Polio Eradication Initiative, all but three countries (Nigeria, Pakistan, and Afghanistan) have apparently interrupted all wild poliovirus (WPV) transmission, and only one of three wild serotypes has been reported globally since 2012. Countrywide supplemental immunization…
Background The world is closer than ever to a polio-free Africa. In this end-stage, it is important to ensure high levels of population immunity to prevent polio outbreaks. Here, we introduce a new method of assessing vaccination campaign effectiveness and estimating immunity at the district-level. We demonstrate how this approach can be used to plan…
Monitoring the quality of supplementary immunization activities (SIAs) is a key tool for polio eradication. Regular monitoring data, however, are often unreliable, showing high coverage levels in virtually all areas, including those with ongoing virus circulation. To address this challenge, lot quality assurance sampling (LQAS) was introduced in 2009 as an additional…
Background One of the challenges facing the Global Polio Eradication Initiative is efficiently directing limited resources, such as specially trained personnel, community outreach activities, and satellite vaccinator tracking, to the most at-risk areas to maximize the impact of interventions. A validated predictive model of wild poliovirus circulation would greatly inform prioritization…
Understanding the environmental conditions of disease transmission is important in the study of vector-borne diseases. Low- and middle-income countries bear a significant portion of the disease burden; but data about weather conditions in those countries can be sparse and difficult to reconstruct. Here, we describe methods to assemble high-resolution gridded time series data sets of air…
Guillaume Chabot-Couture
Deputy Director, Research Programs
BIOGRAPHY
Dr. Edward Wenger directs the IDM global health research program, which includes analyses related to malaria, HIV, TB, pneumonia, enteric diseases, and emergent pathogens. Before joining the disease-modeling program in 2011, Dr. Wenger managed the development, validation, and release of reconstruction and simulation algorithms for the heavy-ion project of the CMS experiment at CERN. He supervised the processing and distribution of a petabyte of data from the first heavy-ion collision run, and directed the planning and execution of the first silicon-based analyses. Dr. Wenger graduated from Dartmouth College and received his Ph.D. in Physics from MIT.
PUBLICATIONS (28)
Background Malaria incidence has plateaued in Sub-Saharan Africa despite Seasonal Malaria Chemoprevention’s (SMC) introduction. Community health workers (CHW) use a door-to-door delivery strategy to treat children with SMC drugs, but for SMC to be as effective as in clinical trials, coverage must be high over successive seasons.…
Background Absolute numbers of COVID-19 cases and deaths reported to date in the sub-Saharan Africa (SSA) region have been significantly lower than those across the Americas, Asia, and Europe. As a result, there has been limited information about the demographic and clinical characteristics of deceased cases in the region, as well as the impacts of different case management…
Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness.…
Background While bed nets and insecticide spraying have had significant impact on malaria burden in many endemic regions, outdoor vector feeding and insecticide resistance may ultimately limit their contribution to elimination and control campaigns. Complementary vector control methods such as endectocides or systemic insecticides, where humans or…
Mathematical models of transmission dynamics are routinely fitted to epidemiological time series, which must inevitably be aggregated at some spatial scale. Weekly case reports of chikungunya have been made available nationally for numerous countries in the Western Hemisphere since late 2013, and numerous models have made use of…
Background Malaria transmission is both seasonal and heterogeneous, and mathematical models that seek to predict the effects of possible intervention strategies should accurately capture realistic seasonality of vector abundance, seasonal dynamics of within-host effects, and heterogeneity of exposure…
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Malaria transmission remains high in Sub-Saharan Africa despite large-scale implementation of malaria control interventions. A comprehensive understanding of the transmissibility of infections to mosquitoes may guide the design of more effective transmission reducing strategies. The impact of P. falciparum sexual stage immunity on the infectious reservoir for malaria has never been…
Background Mass drug administration (MDA) is a control and elimination tool for treating infectious diseases. For malaria, it is widely accepted that conducting MDA during the dry season results in the best outcomes. However, seasonal movement of populations into and out of MDA target areas is common in many places and…
Background Unlike in most pathogens, multiple-strain (polygenomic) infections of P. falciparum are frequently composed of genetic siblings. These genetic siblings are the result of sexual reproduction and can coinfect the same host when cotransmitted by the same mosquito. The degree with which coinfecting strains are…
Background reactive case detection is best poised to push a region to elimination. This study uses mathematical modelling to assess how baseline transmission intensity and local interconnectedness affect the impact of reactive activities in the context of other possible intervention packages. Methods…
Background Mass drug administration for elimination of Plasmodium falciparum malaria is recommended by WHO in some settings. We used consensus modelling to understand how to optimise the effects of mass drug administration in areas with low malaria transmission.…
The renewed effort to eliminate malaria and permanently remove its tremendous burden highlights questions of what combination of tools would be sufficient in various settings and what new tools need to be developed. Gene drive mosquitoes constitute a promising set of…
As more regions approach malaria elimination, understanding how different interventions interact to reduce transmission becomes critical. The Lake Kariba area of Southern Province, Zambia, is part of a multi-country elimination effort and presents a particular challenge as it is an interconnected region of variable transmission…
Efforts at elimination of scourges, such as malaria, are limited by the logistic challenges of reaching large rural populations and ensuring patient adherence to adequate pharmacologic treatment. We have developed an oral, ultra–long-acting capsule that dissolves in the stomach and deploys a star-shaped dosage form that releases drug while assuming a…
Mass campaigns with antimalarial drugs are potentially a powerful tool for local elimination of malaria, yet current diagnostic technologies are insufficiently sensitive to identify all individuals who harbor infections. At the same time, overtreatment of uninfected individuals increases the risk of accelerating emergence of drug resistance and losing community…
Background The phase 3 trial of the RTS,S/AS01 malaria vaccine candidate showed modest efficacy of the vaccine against Plasmodium falciparum malaria, but was not powered to assess mortality endpoints. Impact projections and cost-effectiveness estimates for longer timeframes than the trial follow-up and across a range of settings are needed to inform policy…
Since the year 2000, a concerted campaign against malaria has led to unprecedented levels of intervention coverage across sub-Saharan Africa. Understanding the effect of this control effort is vital to inform future control planning. However, the effect of malaria interventions across the varied epidemiological settings of Africa remains poorly understood owing to the…
In many countries health system data remain too weak to accurately enumerate Plasmodium falciparum malaria cases. In response, cartographic approaches have been developed that link maps of infection prevalence with mathematical relationships to predict the incidence rate of clinical malaria. Microsimulation (or ‘agent-based’) models represent a…
Background Elimination of malaria can only be achieved through removal of all vectors or complete depletion of the infectious reservoir in humans. Mechanistic models can be built to synthesize diverse observations from the field collected under a variety of conditions and subsequently used to query the infectious…
Modeling mosquito transmission of pathogens has a long history starting with the foundational work of Ross and Macdonald, who established the mathematical formalisms for modeling the transmission of malaria between a vector and a host population. The Ross–Macdonald model identifies five key quantities: mosquito population density, mosquito survival probabilities,…
To study the effects of malaria-control interventions on parasite population genomics, we examined a set of 1,007 samples of the malaria parasite Plasmodium falciparum collected in Thiès, Senegal between 2006 and 2013. The parasite samples were genotyped using a molecular barcode of 24 SNPs. About 35% of the samples grouped into subsets with identical barcodes, varying…
Background Antimalarial drugs are a powerful tool for malaria control and elimination. Artemisinin-based combination therapies (ACTs) can reduce transmission when widely distributed in a campaign setting. Modelling mass antimalarial campaigns can elucidate how to most effectively deploy drug-based interventions and…
Background A pre-erythrocytic vaccine could provide a useful tool for burden reduction and eventual eradication of malaria. Mathematical malaria models provide a mechanism for evaluating the effective burden reduction across a range of transmission conditions where such a vaccine might be deployed.…
Mathematical analyses and modelling have an important role informing malaria eradication strategies. Simple mathematical approaches can answer many questions, but it is important to investigate their assumptions and to test whether simple assumptions affect the results. In this note, four examples demonstrate both the effects of model structures and assumptions and…
Background With the encouraging advent of new malaria vaccine candidates, mathematical modelling of expected impacts of present and future vaccines as part of multi-intervention strategies is especially relevant. Methods The impact of potential malaria vaccines is presented utilizing the EMOD model, a comprehensive model of the vector life cycle coupled to a…
Background Many mathematical models have investigated the impact of expanding access to antiretroviral therapy (ART) on new HIV infections. Comparing results and conclusions across models is challenging because models have addressed slightly different questions and have reported different outcome metrics. This study compares the predictions of several mathematical models simulating the…
The expansion of tools against HIV transmission has brought increased interest in epidemiological models that can predict the impact of these interventions. The EMOD-HIV model was recently compared to eleven other independently developed mathematical models of HIV transmission to determine the extent to which they agree about the potential impact of expanded use of antiretroviral therapy in…
PROJECTS (3)
easyVA web portal for clinicians
Understanding the patterns and underlying causes of disease mortality remains an urgent question, to which IDM and BMGF have been dedicating more attention and effort. easyVA is a user-friendly web-based interface that will allow physicians to easily visualize questions and answers from verbal autopsies and enter the cause of death. easyVA will also enable an algorithm-based application for…
Shape-shifting Plasmodium parasitemiae: a novel approach for modeling malaria infection and immunity
Targeted interventions used to interrupt malaria transmission in an endemic population depend on an accurate description of the parasite burden: who is at risk for infection, who is infectious, and what is the appropriate response given data from both active and passive surveillance measures. Sampling of parasite densities in malaria-endemic settings gives limited information on the infection…
Intervention effect sizes and malaria elimination stratification in Southern Province, Zambia
Modern anti-malarial campaigns often layer multiple interventions, such as indoor residual spraying (IRS), distribution of insecticide-treated bed nets (ITN), mass drug campaigns (MDA), and deployment of community health workers (CHWs). However, when these interventions are combined in an operationally realistic way with spatially varying coverages and timings, it can be difficult to…
Edward Wenger
Deputy Director, Research Technology
BIOGRAPHY
Rob Baker is the Deputy Director, Software Test & IT Operations within IDM and brings over twenty years of experience in software development and validation to the group. He and his team are responsible for the test, validation, and quality control of all software components and systems developed by IDM, as well as the design, development, support, and maintenance of a wide variety of related technologies used by the IDM organization. Additionally, Rob is also working toward a degree in Information Systems to further his already impressive knowledge and experience. Prior to joining IDM, Rob worked in the wireless telecommunications industry, and has held various roles in many areas, including test project management, systems architecture, systems administration, database design, customer management, vendor management, voice-based software development, and data platform software development.
PUBLICATIONS (1)
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Rob Baker
Deputy Director, Software Test & IT Operations
BIOGRAPHY
Daniel J. Klein is Sr. Research Manager of the Applied Math Center, a cross-cutting team within IDM which supports modeling and analytics within IDM and on-behalf of our external partners. Since joining IDM in 2010, he has co-lead development of the EMOD-HIV model, published algorithms for stochastic model optimization and calibration, and presented modeling results to international stakeholders. Dr. Klein studied engineering at the Univ. of Wisconsin before earning a Ph.D. in Aeronautics & Astronautics with specialization in control theory from the Univ. of Washington. During 2018, he led various data science and strategy initiatives as a Senior Program Officer in the Global Development Strategy, Data, and Analytics team at the Bill & Melinda Gates Foundation. Prior to joining IDM, Dr. Klein was enjoying the sunshine of Santa Barbara, CA as a postdoctoral scholar with the Center for Control and Dynamical Systems at UCSB.
PUBLICATIONS (21)
Background Pre-exposure prophylaxis (PrEP) is highly effective in preventing HIV and has the potential to significantly impact the HIV epidemic. Given limited resources for HIV prevention, identifying PrEP provision strategies that maximize impact is critical. Methods We used a stochastic individual-based network model to evaluate the direct (infections prevented among PrEP…
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Western Kenya suffers a highly endemic and also very heterogeneous epidemic of human immunodeficiency virus (HIV). Although female sex workers (FSW) and their male clients are known to be at high risk for HIV, HIV prevalence across regions in Western Kenya is not strongly correlated with the fraction of women engaged in commercial sex. An agent-based network model of HIV transmission,…
Introduction In public health, it is critical to have a reasonable understanding of an epidemic disease in order to set pragmatic goals and design highly-impactful and cost-effective interventions. Mathematical models of these epidemiological processes can support decision making by forecasting disease spread in…
Objective To quantify the contribution of specific sexual partner age groups to the risk of HIV acquisition in men and women in hyperendemic region of South Africa. Design We conducted a population-based cohort study among women (15–49 years of age) and men (15–55 years of age) between…
Voluntary Medical Male Circumcision (VMMC) for human immunodeficiency virus (HIV) prevention has scaled up rapidly among young men in western Kenya since 2008. Whether the program has successfully reached uncircumcised men evenly across the region is largely unknown…
Background Generalized HIV epidemics propagate to future generations according to the age patterns of transmission. We hypothesized that future generations could be protected from infection using age-targeted prevention, analogous to the ring-fencing strategies used to control the spread of smallpox. Methods We modeled age-…
Background Mathematical models are widely used to simulate the effects of interventions to control HIV and to project future epidemiological trends and resource needs. We aimed to validate past model projections against data from a large household survey done in South Africa in 2012. Methods We compared ten model projections of HIV…
Background: Significant progress in tuberculosis (TB) control has been achieved worldwide over the last two decades. Global TB mortality has fallen by 45%, and TB incidence is declining. Recently, the World Health Organization (WHO) established an ambitious post-2015 global strategy, the End TB Strategy. This strategy outlines a 2025 milestone of…
The South African government is currently discussing various alternative approaches to the further expansion of antiretroviral treatment (ART) in public-sector facilities. Alternatives under consideration include the criteria under which a patient would be eligible for free care, the level of coverage with testing and care, how much of the care will be delivered…
Background In the last 20 years, China ramped up a DOTS (directly observed treatment, short-course)-based tuberculosis (TB) control program with 80% population coverage, achieving the 2015 Millennium Development Goal of a 50% reduction in TB prevalence and mortality. Recently, the World Health Organization developed the…
Background Migrant populations such as mine workers contributed to the spread of HIV in sub-Saharan Africa. We used a mathematical model to estimate the community-wide impact of targeting treatment and prevention to male migrants. Methods We augmented an individual-based network model, EMOD-HIV v0.8, to include an…
Background: New WHO guidelines recommend initiation of antiretroviral therapy for HIV-positive adults with CD4 counts of 500 cells per μL or less, a higher threshold than was previously recommended. Country decision makers have to decide whether to further expand eligibility for antiretroviral therapy accordingly. We aimed to assess the…
A priority of the Global Polio Eradication Initiative (GPEI) 2013–2018 strategic plan is to evaluate the potential impact on polio eradication resulting from expanding one or more Supplementary Immunization Activities (SIAs) to children beyond age five-years in polio endemic countries. It has been hypothesized that such expanded age group (EAG) campaigns could…
Decision makers in epidemiology and other disciplines are faced with the daunting challenge of designing interventions that will be successful with high probability and robust against a multitude of uncertainties. To facilitate the decision making process in the context of a goal-oriented objective (e.g., eradicate polio by ), stochastic models can be used to map the…
Objective EMOD-HIV v0.8 has been used to estimate the potential impact of expanding treatment guidelines to allow earlier initiation of antiretroviral therapy (ART) in sub-Saharan Africa with current or improved treatment coverage. In generating these results, a model must additionally make assumptions about the rates of dropout and re-initiation into ART programs before and after the…
Efficient planning and evaluation of human immunodeficiency virus (HIV) prevention programmes requires an understanding of what sustains the epidemic, including the mechanism by which HIV transmission keeps pace with the ageing of the infected population. Recently, more detailed population models have been developed which represent the epidemic with sufficient detail to characterize the…
Age mixing plays an important role in the formation of relationships within computer simulations of Human Immunodeficiency Virus (HIV) transmission. We present and analyze an algorithm that takes individuals seeking a heterosexual relationship, and forms pairs of a desired joint age mixing distribution. The rate at which eligible individuals seek relationships varies by age group and gender,…
Antiretroviral treatment (ART) for those infected with HIV can prevent onward transmission of infection, but biological efficacy alone is not enough to guide policy decisions about the role of ART in reducing HIV incidence. Epidemiology, economics, demography, statistics, biology and mathematical modelling will be central in framing key decisions in the optimal use of ART. PLoS Medicine, with…
Background Many mathematical models have investigated the impact of expanding access to antiretroviral therapy (ART) on new HIV infections. Comparing results and conclusions across models is challenging because models have addressed slightly different questions and have reported different outcome metrics. This study compares the predictions of several mathematical models simulating the…
The expansion of tools against HIV transmission has brought increased interest in epidemiological models that can predict the impact of these interventions. The EMOD-HIV model was recently compared to eleven other independently developed mathematical models of HIV transmission to determine the extent to which they agree about the potential impact of expanded use of antiretroviral therapy in…
Daniel Klein
Sr. Research Manager
BIOGRAPHY
Bradley Wagner has a Ph.D. in Applied Mathematics from McMaster University (Hamilton, Ontario, Canada), where he also has a Master of Science in Mathematics. Additionally, he has a Bachelor of Science in Mathematics as well as Chemistry from the University of British Columbia. Prior to joining IDM, Bradley was a postdoctoral fellow at the David Geffen School of Medicine at the University of California, Los Angeles (UCLA). Bradley’s postdoctoral research focused on the mathematical modeling of HIV drug resistance, while his Ph.D. research concentrated on the mathematical modeling of childhood infectious disease dynamics including the design of optimal vaccination strategies. His research within IDM is an extension of that previous work, with a focus on developing and implementing mathematical models of HIV and tuberculosis (TB) transmission and the goal of designing effective treatment and prevention programs.
PUBLICATIONS (11)
Most diagnostic tests for tuberculosis (TB) rely on sputum samples, which are difficult to obtain and have low sensitivity in immunocompromised patients, patients with disseminated TB, and children, delaying treatment initiation. The World Health Organization (WHO) calls for the development of a rapid, biomarker-based, non-sputum test capable of detecting all forms of TB at the point-of-care…
Background Lack of accurate data on the distribution of sub-national populations in low- and middle-income countries impairs planning, monitoring, and evaluation of interventions. Novel, low-cost methods to develop unbiased survey sampling frames at sub-national, sub-provincial, and even sub-district levels are urgently needed. This article details…
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Background Gold mines represent a potential hotspot for Mycobacterium tuberculosis (Mtb) transmission and may be exacerbating the tuberculosis (TB) epidemic in South Africa. However, the presence of multiple factors complicates estimation of the mining contribution to the TB…
Identifying the transmission sources and reservoirs of Streptococcus pneumoniae (SP) is a long-standing question for pneumococcal epidemiology, transmission dynamics, and vaccine policy. Here we use serotype to identify SP transmission and examine acquisitions (in the same household, local community, and county, or of unidentified origin…
Background The post-2015 End TB Strategy sets global targets of reducing tuberculosis incidence by 50% and mortality by 75% by 2025. We aimed to assess resource requirements and cost-effectiveness of strategies to achieve these targets in China, India, and South Africa. Methods We examined…
Background The post-2015 End TB Strategy proposes targets of 50% reduction in tuberculosis incidence and 75% reduction in mortality from tuberculosis by 2025. We aimed to assess whether these targets are feasible in three high-burden countries with contrasting epidemiology and previous programmatic achievements…
Background: Significant progress in tuberculosis (TB) control has been achieved worldwide over the last two decades. Global TB mortality has fallen by 45%, and TB incidence is declining. Recently, the World Health Organization (WHO) established an ambitious post-2015 global strategy, the End TB Strategy. This strategy outlines a 2025 milestone of…
Background In the last 20 years, China ramped up a DOTS (directly observed treatment, short-course)-based tuberculosis (TB) control program with 80% population coverage, achieving the 2015 Millennium Development Goal of a 50% reduction in TB prevalence and mortality. Recently, the World Health Organization developed the…
Background: New WHO guidelines recommend initiation of antiretroviral therapy for HIV-positive adults with CD4 counts of 500 cells per μL or less, a higher threshold than was previously recommended. Country decision makers have to decide whether to further expand eligibility for antiretroviral therapy accordingly. We aimed to assess the…
A priority of the Global Polio Eradication Initiative (GPEI) 2013–2018 strategic plan is to evaluate the potential impact on polio eradication resulting from expanding one or more Supplementary Immunization Activities (SIAs) to children beyond age five-years in polio endemic countries. It has been hypothesized that such expanded age group (EAG) campaigns could…
Bradley Wagner
Sr. Research Scientist

BIOGRAPHY
Caitlin Bever has a Ph.D. in Biological Engineering from the Massachusetts Institute of Technology (MIT), along with a Bachelor’s degree (B.Sc.) with Combined Honors in Physics and Astronomy from the University of British Columbia (UBC). Caitlin received a Medtronic Fellowship for her post-graduate work at MIT and the Rudy Haering Medal for outstanding graduating physics student from UBC. Her academic research focused on understanding how to select useful predictions from uncertain mathematical models of biology. Prior to joining IDM, Caitlin worked on a team at Entelos that built a novel model of atherosclerosis in mouse, paired with an analogous model of cardiovascular disease in human, which improved the design of pre-clinical experiments and identified key indicators for translating results from mouse to human. Caitlin was on assignment in Switzerland for a year and a half as a consultant for Entelos, after which she worked with the malaria modeling group at the Swiss Tropical and Public Health Institute. In her role there, she developed new methods for spatial modeling of entomological inoculation rates and co-wrote a WHO report on how country-specific considerations contribute to the impact of malaria vaccines. As a member of IDM’s research team, Caitlin leads the projects on malaria vaccines and human African trypanosomiasis (HAT) with a focus on disease eradication.
PUBLICATIONS (10)
Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness.…
Background While bed nets and insecticide spraying have had significant impact on malaria burden in many endemic regions, outdoor vector feeding and insecticide resistance may ultimately limit their contribution to elimination and control campaigns. Complementary vector control methods such as endectocides or systemic insecticides, where humans or…
Background Control of gambiense sleeping sickness relies predominantly on passive and active screening of people, followed by treatment. Methods Mathematical modeling explores the potential of 3 complementary interventions in high- and low-transmission settings. …
Background reactive case detection is best poised to push a region to elimination. This study uses mathematical modelling to assess how baseline transmission intensity and local interconnectedness affect the impact of reactive activities in the context of other possible intervention packages. Methods…
As more regions approach malaria elimination, understanding how different interventions interact to reduce transmission becomes critical. The Lake Kariba area of Southern Province, Zambia, is part of a multi-country elimination effort and presents a particular challenge as it is an interconnected region of variable transmission…
Mass campaigns with antimalarial drugs are potentially a powerful tool for local elimination of malaria, yet current diagnostic technologies are insufficiently sensitive to identify all individuals who harbor infections. At the same time, overtreatment of uninfected individuals increases the risk of accelerating emergence of drug resistance and losing community…
Background The phase 3 trial of the RTS,S/AS01 malaria vaccine candidate showed modest efficacy of the vaccine against Plasmodium falciparum malaria, but was not powered to assess mortality endpoints. Impact projections and cost-effectiveness estimates for longer timeframes than the trial follow-up and across a range of settings are needed to inform policy…
Background Plasmodium falciparum gametocytes are essential for malaria transmission. Malaria control measures that aim at reducing transmission require an accurate characterization of the human infectious reservoir. Methods We longitudinally determined human infectiousness to mosquitoes and P…
Modeling mosquito transmission of pathogens has a long history starting with the foundational work of Ross and Macdonald, who established the mathematical formalisms for modeling the transmission of malaria between a vector and a host population. The Ross–Macdonald model identifies five key quantities: mosquito population density, mosquito survival probabilities,…
Mathematical analyses and modelling have an important role informing malaria eradication strategies. Simple mathematical approaches can answer many questions, but it is important to investigate their assumptions and to test whether simple assumptions affect the results. In this note, four examples demonstrate both the effects of model structures and assumptions and…
PROJECTS (4)
Shape-shifting Plasmodium parasitemiae: a novel approach for modeling malaria infection and immunity
Targeted interventions used to interrupt malaria transmission in an endemic population depend on an accurate description of the parasite burden: who is at risk for infection, who is infectious, and what is the appropriate response given data from both active and passive surveillance measures. Sampling of parasite densities in malaria-endemic settings gives limited information on the infection…
Intervention effect sizes and malaria elimination stratification in Southern Province, Zambia
Modern anti-malarial campaigns often layer multiple interventions, such as indoor residual spraying (IRS), distribution of insecticide-treated bed nets (ITN), mass drug campaigns (MDA), and deployment of community health workers (CHWs). However, when these interventions are combined in an operationally realistic way with spatially varying coverages and timings, it can be difficult to…
Improving Intervention Impact Predictions by Merging Malaria Models
As global progress in reducing the burden of malaria slows, strategies for appropriately allocating resources for elimination and control become paramount. The past decade has seen the development of a range of versatile malaria transmission models capable of incorporating detailed climate and vector information into predictions of burden under a wide variety of intervention scenarios. At the…
Would a serology-based rapid diagnostic test improve malaria surveillance in low-transmission settings?
Existing rapid diagnostic tests (RDTs) detect current or very recent malaria infections, which means that surveillance programs conducted in regions where few individuals are infected may need to test large numbers of individuals to estimate the transmission intensity. RDTs that detect long-lasting antibodies (‘serology RDTs’) have been proposed as a tool that might help reduce the sampling…
VIDEOS (1)
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Senior Research Manager Caitlin Bever, PhD, discusses the challenges of preventing and treating malaria and how modeling plays a role in determining which interventions would be the most effective for a particular country.
Senior Research Manager Caitlin Bever, PhD, discusses the challenges of preventing and treating malaria and how modeling plays a role in determining which interventions would be the most effective for a particular country.
Caitlin Bever
Sr. Research Manager
BIOGRAPHY
Christian Wiswell manages the models test team at IDM. This team's mission is to provide software quality assurance to the models consumed by the IDM research team. Christian has Bachelor of Arts degrees in both History and Philosophy from the University of Kansas (Lawrence, KS). Christian has almost twenty years of experience in software quality, working on RESTful web services, desktop applications and new user interfaces at Microsoft, Google, and a couple of internet startups. While at Microsoft, he was brought onto the PixelSense (formerly Surface) project because of his background in software test and board gaming, and his work there generated two patent awards.
PUBLICATIONS (1)
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Christian Wiswell
Software Test Manager
BIOGRAPHY
Christopher Lorton has a Master of Science in Computer Science from Washington University, St. Louis, where he also obtained a Bachelor of Science in Physics. His master’s thesis focused on the parallel computation of neural networks (NN) for the recognition of handwritten characters. Christopher’s past work includes machine vision systems, digital media processing, cross-platform managed code runtime development, and the accelerated rendering of graphical user interfaces (GUI). Christopher’s current responsibilities as a development lead include simulation engine software development for an upcoming compartmental modeling framework, as well as the rapid prototyping of disease transmission models for the efficient simulation of those models.
PUBLICATIONS (3)
The compartmental modeling software (CMS) is an open source computational framework that can simulate discrete, stochastic reaction models which are often utilized to describe complex systems from epidemiology and systems biology. In this article, we report the computational requirements, the novel input model language, the available numerical solvers, and the output file format for CMS. In…
The compartmental modeling software (CMS) is an open source computational framework that can simulate discrete, stochastic reaction models which are often utilized to describe complex systems from epidemiology and systems biology. In this article, we report the computational requirements, the novel input model language, the available numerical solvers, and the output file format for CMS. In…
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
PROJECTS (1)
Shape-shifting Plasmodium parasitemiae: a novel approach for modeling malaria infection and immunity
Targeted interventions used to interrupt malaria transmission in an endemic population depend on an accurate description of the parasite burden: who is at risk for infection, who is infectious, and what is the appropriate response given data from both active and passive surveillance measures. Sampling of parasite densities in malaria-endemic settings gives limited information on the infection…
Christopher Lorton
Principal Engineering Manager
BIOGRAPHY
Hil Lyons has a Ph.D. in Statistics, as well as a Master of Science degree in Statistics, and a Bachelor of Science in Mathematics, from the University of Washington, Seattle. Hil’s research has included the stochastic modeling of the growth and death processes in tree stand data, as well as spatial point processes and applications of applied statistics. He has also worked extensively as a statistical consultant for a variety of academic research groups and departments, including a position as Assistant Director of the Department of Statistics consulting center at the University of Washington. As a result, he has expertise with a wide variety of modeling and applied statistics topics and methods. Within IDM, Hil’s work is focused on polio eradication efforts, where he provides statistical modeling, analysis, and interpretation of diverse data for robust and timely decision support.
PUBLICATIONS (7)
The polio environmental surveillance (ES) system has been an incredible tool for advancing polio eradication efforts because of its ability to highlight the spatial and temporal extent of poliovirus circulation. While ES often outperforms, or is more sensitive than AFP surveillance, the sensitivity of the ES system has not been well characterized. Fundamental uncertainty of ES site sensitivity…
Background Pakistan is one of only three countries where poliovirus circulation remains endemic. For the Pakistan Polio Eradication Program, identifying high risk districts is essential to target interventions and allocate limited resources. Methods Using a hierarchical Bayesian framework we developed…
The globally synchronized removal of the attenuated Sabin type 2 strain from the oral polio vaccine (OPV) in April 2016 marked a major change in polio vaccination policy. This change will provide a significant reduction in the burden of vaccine-associated paralytic polio (VAPP), but may increase the risk of circulating vaccine-derived…
Background Wild type 2 poliovirus was last observed in 1999. The Sabin-strain oral polio vaccine type 2 (OPV2) was critical to eradication, but it is known to revert to a neurovirulent phenotype, causing vaccine-associated paralytic poliomyelitis. OPV2 is also transmissible and can establish…
Background The world is closer than ever to a polio-free Africa. In this end-stage, it is important to ensure high levels of population immunity to prevent polio outbreaks. Here, we introduce a new method of assessing vaccination campaign effectiveness and estimating immunity at the district-level. We demonstrate how this approach can be used to plan…
Background Plasmodium falciparum gametocytes are essential for malaria transmission. Malaria control measures that aim at reducing transmission require an accurate characterization of the human infectious reservoir. Methods We longitudinally determined human infectiousness to mosquitoes and P…
Background One of the challenges facing the Global Polio Eradication Initiative is efficiently directing limited resources, such as specially trained personnel, community outreach activities, and satellite vaccinator tracking, to the most at-risk areas to maximize the impact of interventions. A validated predictive model of wild poliovirus circulation would greatly inform prioritization…
Hil Lyons
Research Manager

BIOGRAPHY
Affiliate Assistant Professor, Applied Mathematics, University of Washington Affiliate Assistant Professor, Mechanical Engineering, University of Washington Joshua Proctor is currently a research manager and senior research scientist at IDM leading the Data, Dynamics and Analytics (DDA) team. DDA is focused on applying modern data science, machine-learning, and statistical techniques to a wide-range of data sources, i.e., surveillance of infectious diseases, household surveys, genome sequencing of viruses or parasites, and demography. We aim to leverage the growing success of these modern analytic and numerical methods to advise on near-term public policy questions facing the global health community. In conjunction, we also identify the short-comings of current methodological approaches and develop novel, principled algorithms to face the challenges of surveillance data. Joshua Proctor earned a Ph.D. in Mechanical and Aerospace Engineering from Princeton. Before graduate school, Joshua earned a Bachelor of Science in Aeronautics and Astronautics Engineering, and a Bachelor of Arts in English Literature, both from the University of Washington, Seattle. His doctoral research focused on investigating the effects of neural feedback on rapidly running insects (specifically, cockroaches). The research required the development of complex mathematical models describing legged locomotion, the application of dimensionality reduction techniques, and the characterization of these nonlinear dynamical systems through bifurcation analyses [1,2]. The research led to several important discoveries about the role of neural feedback during running, while also inspiring better robotic designs for maneuverability, stability, and control. Joshua joined IDM in 2011 after his Ph.D. and contributed to the development of the compartmental modeling simulations software. This software package is soon to be released to the global health community. Joshua then joined the nascent Applied Mathematics group at IDM where he developed algorithms and novel mathematical methods for the study of infectious disease data. He became interested in equation-free modeling and data-driven analyses, inspired by the mathematical developments around fluid dynamics at Princeton University. Generally, equation-free modeling does not require a set of pre-determined, derived from first-principles equations. Instead, the time-series data is utilized to discover dynamic models and/or dynamic characteristics. This led to a number of important methodological innovations [3,4,5,6], including a book describing the mathematical method Dynamic Mode Decomposition [7]. These methodologies are poised to have a substantial impact on infectious disease modeling. During his previous position in the Applied Mathematics group, Joshua also focused on leveraging current data science and machine-learning methodologies for epidemiological and demographic applications. For example, he is interested in characterizing genomes of viruses or parasites and their metadata (GPS location, age, gender, sex, etc.) to better understand the transmission dynamics of infectious diseases [8,9]. Understanding these modern genomic data sets can help inform disease surveillance efforts for elimination and eradication efforts. Joshua is also interested in questions around demography, specifically in the family planning group and estimating child mortality.
PUBLICATIONS (39)
Traditional clinical prediction models focus on parameters of the individual patient. For infectious diseases, sources external to the patient, including characteristics of prior patients and seasonal factors, may improve predictive performance. We describe the development of a predictive model that integrates multiple sources of data in a principled statistical framework using a post-test…
Background Ambitious global goals have been established to provide universal access to affordable modern contraceptive methods. To measure progress toward such goals in populous countries like Nigeria, it’s essential to characterize the current levels and trends of family planning (FP) indicators such as unmet need and modern contraceptive prevalence…
The compartmental modeling software (CMS) is an open source computational framework that can simulate discrete, stochastic reaction models which are often utilized to describe complex systems from epidemiology and systems biology. In this article, we report the computational requirements, the novel input model language, the available numerical solvers, and the output file format for CMS. In…
Background Pediatric diarrhea can be caused by a wide variety of pathogens, from bacteria to viruses to protozoa. Pathogen prevalence is often described as seasonal, peaking annually and associated with specific weather conditions. Although many studies have described the seasonality of diarrheal disease, these studies have occurred predominantly in temperate regions. In tropical and…
China reported zero locally-acquired malaria cases in 2017 and 2018. Understanding the spatio-temporal pattern underlying this decline, especially the relationship between locally-acquired and imported cases, can inform efforts to maintain elimination and prevent re-emergence. This is particularly pertinent in Yunnan province, where the potential for local transmission is highest. Using a geo-…
The compartmental modeling software (CMS) is an open source computational framework that can simulate discrete, stochastic reaction models which are often utilized to describe complex systems from epidemiology and systems biology. In this article, we report the computational requirements, the novel input model language, the available numerical solvers, and the output file format for CMS. In…
Dynamic mode decomposition has emerged as a leading technique to identify spatiotemporal coherent structures from high-dimensional data, benefiting from a strong connection to nonlinear dynamical systems via the Koopman operator. In this work, two recent innovations that extend dynamic mode decomposition to systems with actuation and systems with heavily subsampled measurements are integrated…
Hybrid systems are traditionally difficult to identify and analyse using classical dynamical systems theory. Moreover, recently developed model identification methodologies largely focus on identifying a single set of governing equations solely from measurement data. In this article, we develop a new methodology, Hybrid-Sparse Identification of Nonlinear Dynamics, which identifies separate…
Background: Pediatric diarrhea can be caused by a wide variety of pathogens, from bacteria to viruses to protozoa. Pathogen prevalence is often described as seasonal, peaking annually and associated with specific weather conditions. Although many studies have described the seasonality of diarrheal disease, these studies have occurred predominantly in temperate regions. In tropical and resource…
Ambitious global goals have been established to provide universal access to affordable modern contraceptive methods. The UN's sustainable development goal 3.7.1 proposes satisfying the demand for family planning (FP) services by increasing the proportion of women of reproductive age using modern methods. To measure progress toward such goals in populous countries like Nigeria, it's essential…
Hybrid systems are traditionally difficult to identify and analyze using classical dynamical systems theory. Moreover, recently developed model identification methodologies largely focus on identifying a single set of governing equations solely from measurement data. In this article, we develop a new methodology, Hybrid-…
We develop a new generalization of Koopman operator theory that incorporates the effects of inputs and control. Koopman spectral analysis is a theoretical tool for the analysis of nonlinear dynamical systems. Moreover, Koopman is intimately connected to Dynamic Mode Decomposition (DMD), a method that discovers spatial-temporal coherent modes…
Containing the recent West African outbreak of Ebola virus (EBOV) required the deployment of substantial global resources. Operationally, health workers and surveillance teams treated cases, collected genetic samples, and tracked case contacts. Despite the substantial progress in analyzing and modeling EBOV epidemiological data, a complete…
Dynamic mode decomposition has emerged as a leading technique to identify spatiotemporal coherent structures from high-dimensional data, benefiting from a strong connection to nonlinear dynamical systems via the Koopman operator. In this work, two recent innovations that extend dynamic mode decomposition to systems with…
Understanding the interplay of order and disorder in chaos is a central challenge in modern quantitative science. Approximate linear representations of nonlinear dynamics have long been sought, driving considerable interest in Koopman theory. We present a universal, data-driven decomposition of chaos as an intermittently forced linear…
We propose a sparse regression method capable of discovering the governing partial differential equation(s) of a given system by time series measurements in the spatial domain. The regression framework relies on sparsity-promoting techniques to select the nonlinear and partial derivative terms of the governing equations that most accurately represent the…
We propose a sparse regression method capable of discovering the governing partial differential equation(s) of a given system by time series measurements in the spatial domain. The regression framework relies on sparsity-promoting techniques to select the nonlinear and partial derivative terms of the governing equations that most accurately represent the…
Ordinary and partial differential equations are widely used throughout the engineering, physical, and biological sciences to describe the physical laws underlying a given system of interest. We implicitly assume that the governing equations are known and justified by first principles, such as conservation of mass or…
Using a computational model of the Caenorhabditis elegans connectome dynamics, we show that proprioceptive feedback is necessary for sustained dynamic responses to external input. This is consistent with the lack of biophysical evidence for a central pattern generator, and recent experimental evidence that proprioception drives locomotion. The low…
We develop an algorithm for model selection which allows for the consideration of a combinatorially large number of candidate models governing a dynamical system. The innovation circumvents a disadvantage of standard model selection which typically limits the number candidate models considered due to the intractability of computing…
Identifying governing equations from data is a critical step in the modeling and control of complex dynamical systems. Here, we investigate the data-driven identification of nonlinear dynamical systems with inputs and forcing using regression methods, including sparse regression. Specifically, we generalize the sparse identification of nonlinear dynamics (SINDY) algorithm to include external…
This work develops compressed sensing strategies for computing the dynamic mode decomposition (DMD) from heavily subsampled or compressed data. The resulting DMD eigenvalues are equal to DMD eigenvalues from the full-state data. It is then possible to reconstruct full-state DMD eigenvectors using …
The increasing ubiquity of complex systems that require control is a challenge for existing methodologies in characterization and controller design when the system is high-dimensional, nonlinear, and without physics-based governing equations. We review standard model reduction techniques such as Proper Orthogonal Decomposition (POD) with…
Choosing a limited set of sensor locations to characterize or classify a high-dimensional system is an important challenge in engineering design. Traditionally, optimizing the sensor locations involves a brute-force, combinatorial search, which is NP-hard and is computationally intractable for even moderately large problems. Using recent advances in…
We consider the application of Koopman theory to nonlinear partial differential equations. We demonstrate that the observables chosen for constructing the Koopman operator are critical for enabling an accurate approximation to the nonlinear dynamics. If such observables can be found, then the dynamic mode decomposition…
Inferring the structure and dynamics of network models is critical to understanding the functionality and control of complex systems, such as metabolic and regulatory biological networks. The increasing quality and quantity of experimental data enable statistical approaches based on information theory for model selection and…
Extracting governing equations from data is a central challenge in many diverse areas of science and engineering. Data are abundant whereas models often remain elusive, as in climate science, neuroscience, ecology, finance, and epidemiology, to name only a few examples. In this work, we combine sparsity-promoting techniques and machine…
In this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to an invariant subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves functions of the state of a dynamical system.…
We develop a new method which extends Dynamic Mode Decomposition (DMD) to incorporate the effect of control to extract low-order models from high-dimensional, complex systems. DMD finds spatial-temporal coherent modes, connects local-linear analysis to nonlinear operator theory, and provides an equation-free architecture which is compatible with compressive sensing. In…
In this work, we explore finite-dimensional linear representations of nonlinear dynamical systems by restricting the Koopman operator to a subspace spanned by specially chosen observable functions. The Koopman operator is an infinite-dimensional linear operator that evolves observable functions on the state-space of a dynamical system. Dominant terms in the Koopman…
The ability to discover physical laws and governing equations from data is one of humankind’s greatest intellectual achievements. A quantitative understanding of dynamic constraints and balances in nature has facilitated rapid development of knowledge and enabled advanced technological achievements, including aircraft, combustion…
To study the effects of malaria-control interventions on parasite population genomics, we examined a set of 1,007 samples of the malaria parasite Plasmodium falciparum collected in Thiès, Senegal between 2006 and 2013. The parasite samples were genotyped using a molecular barcode of 24 SNPs. About 35% of the samples grouped into subsets with identical barcodes, varying…
Background The development and application of quantitative methods to understand disease dynamics and plan interventions is becoming increasingly important in the push toward eradication of human infectious diseases, exemplified by the ongoing effort to stop the spread of poliomyelitis. Methods Dynamic mode…
Complex systems exhibit dynamics that typically evolve on low-dimensional attractors and may have sparse representation in some optimal basis. Recently developed compressive sensing techniques exploit this sparsity for state reconstruction and/or categorical identification from limited measurements. We argue that data-driven dimensionality reduction methods integrate…
Although disease transmission in the near eradication regime is inherently stochastic, deterministic quantities such as the probability of eradication are of interest to policy makers and researchers. Rather than running large ensembles of discrete stochastic simulations over long intervals in time to compute these deterministic quantities, we…
We develop a new method which extends Dynamic Mode Decomposition (DMD) to incorporate the effect of control to extract low-order models from high-dimensional, complex systems. DMD finds spatial-temporal coherent modes, connects local-linear analysis to nonlinear operator theory, and provides an equation-free architecture which is compatible with compressive sensing. In…
Methods Thin smears from Plasmodium falciparum-infected and uninfected patients were imaged in both dark field (DF) unstained and bright field (BF) Giemsa-stained modes. The images were co-registered such that each parasite had thumbnails in both BF and DF modes, providing an accurate map between parasites and DF objects. This map was used to find the abundance of…
This work develops compressive sampling strategies for computing the dynamic mode decomposition (DMD) from heavily subsampled or output-projected data. The resulting DMD eigenvalues are equal to DMD eigenvalues from the full-state data. It is then possible to reconstruct full-state DMD eigenvectors using ℓ1-minimization or greedy algorithms. If full-state snapshots are available, it may…
The algorithm solves an l1-minimization to find the fewest entries of the full measurement vector that exactly reconstruct the discriminant vector in feature space. Once the sensor locations have been identified from the…
PROJECTS (1)
Improving Intervention Impact Predictions by Merging Malaria Models
As global progress in reducing the burden of malaria slows, strategies for appropriately allocating resources for elimination and control become paramount. The past decade has seen the development of a range of versatile malaria transmission models capable of incorporating detailed climate and vector information into predictions of burden under a wide variety of intervention scenarios. At the…
Joshua Proctor
Principal Research Scientist
BIOGRAPHY
Kevin McCarthy is the Research Manager for the measles research team at the Institute for Disease Modeling. Kevin has a Ph.D. in Physics from the Massachusetts Institute of Technology as well as a Bachelor degree in both Physics and Electrical Engineering from the University of California, San Diego. His research focus is on optimizing burden control activities and helping to clarify critical vaccination policy decisions relevant to achieving and maintaining measles eradication. Kevin joined the Institute in 2013, and before leading the measles effort, he worked on both malaria and polio. As a member of the polio team, Kevin developed methods to calibrate a spatio-temporal polio model investigating the dynamics of eradication in northern Nigeria, the potential risk of accidental or intentional oral polio vaccine use after synchronized cessation, and the consequences of localized inaccessibility for surveillance and vaccination activities. In malaria, he worked on calibration of the IDM intra-host malaria model and malaria vaccine efficacy studies. These calibrated models can be used to evaluate the expected efficacy of potential intervention campaigns and provide decision support to global health policymakers. Prior to IDM, Kevin’s research focused on astrophysics and particle physics, and his doctoral research was performed as a member of the Cryogenic Dark Matter Search collaboration.
PUBLICATIONS (10)
Measles vaccination is a cost-effective way to prevent infection and reduce mortality and morbidity. However, in countries with fragile routine immunization infrastructure, coverage rates are still low and supplementary immunization campaigns (SIAs) are used to reach previously unvaccinated children. During campaigns, vaccine is generally administered to every child, regardless of their…
Background Measles causes significant childhood morbidity in Nigeria. Routine immunization (RI) coverage is around 40% country-wide, with very high levels of spatial heterogeneity (3–86%), with supplemental immunization activities (SIAs) at 2-year or 3-year intervals. We investigated cost savings and burden reduction that could be achieved by adjusting the inter-campaign…
The polio environmental surveillance (ES) system has been an incredible tool for advancing polio eradication efforts because of its ability to highlight the spatial and temporal extent of poliovirus circulation. While ES often outperforms, or is more sensitive than AFP surveillance, the sensitivity of the ES system has not been well characterized. Fundamental uncertainty of ES site sensitivity…
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
The oral polio vaccine (OPV) contains live-attenuated polioviruses that induce immunity by causing low virulence infections in vaccine recipients and their close contacts. Widespread immunization with OPV has reduced the annual global burden of paralytic poliomyelitis by a factor of 10,000 or more and has driven wild poliovirus (WPV) to the brink of eradication. However, in instances that have…
The globally synchronized removal of the attenuated Sabin type 2 strain from the oral polio vaccine (OPV) in April 2016 marked a major change in polio vaccination policy. This change will provide a significant reduction in the burden of vaccine-associated paralytic polio (VAPP), but may increase the risk of circulating vaccine-derived…
Background Wild type 2 poliovirus was last observed in 1999. The Sabin-strain oral polio vaccine type 2 (OPV2) was critical to eradication, but it is known to revert to a neurovirulent phenotype, causing vaccine-associated paralytic poliomyelitis. OPV2 is also transmissible and can establish…
Background Since the launch of the Global Polio Eradication Initiative, all but three countries (Nigeria, Pakistan, and Afghanistan) have apparently interrupted all wild poliovirus (WPV) transmission, and only one of three wild serotypes has been reported globally since 2012. Countrywide supplemental immunization…
Background Elimination of malaria can only be achieved through removal of all vectors or complete depletion of the infectious reservoir in humans. Mechanistic models can be built to synthesize diverse observations from the field collected under a variety of conditions and subsequently used to query the infectious…
Background A pre-erythrocytic vaccine could provide a useful tool for burden reduction and eventual eradication of malaria. Mathematical malaria models provide a mechanism for evaluating the effective burden reduction across a range of transmission conditions where such a vaccine might be deployed.…
Kevin McCarthy
Sr. Research Manager
BIOGRAPHY
Dr. Mike Famulare is a Principal Research Scientist and Co-chair of Epidemiology at the Institute for Disease Modeling (IDM), an institute within Global Health at the Bill & Melinda Gates Foundation. Dr. Famulare's core discipline is using mathematical modeling to study infectious disease transmission and improve the utility of disease surveillance data. Since joining IDM in 2012, he has worked closely with partners in the Global Polio Eradication Initiative to assess the impacts of polio vaccination policies on poliovirus transmission in different settings. He is also a founding member of the Seattle Flu Study, an innovative collaboration in at-home, multi-pathogen, self-testing that identified the first case of community transmission of COVID-19 in the United States. Most recently, he has been co-leading IDM's COVID-19 response, with a focus on analytics and modeling to inform COVID-19 control strategy in collaboration with the Washington State Department of Health and Governor's office.
PUBLICATIONS (8)
The polio environmental surveillance (ES) system has been an incredible tool for advancing polio eradication efforts because of its ability to highlight the spatial and temporal extent of poliovirus circulation. While ES often outperforms, or is more sensitive than AFP surveillance, the sensitivity of the ES system has not been well characterized. Fundamental uncertainty of ES site sensitivity…
The oral polio vaccine (OPV) contains live-attenuated polioviruses that induce immunity by causing low virulence infections in vaccine recipients and their close contacts. Widespread immunization with OPV has reduced the annual global burden of paralytic poliomyelitis by a factor of 10,000 or more and has driven wild poliovirus (WPV) to the brink of eradication. However, in instances that have…
The globally synchronized removal of the attenuated Sabin type 2 strain from the oral polio vaccine (OPV) in April 2016 marked a major change in polio vaccination policy. This change will provide a significant reduction in the burden of vaccine-associated paralytic polio (VAPP), but may increase the risk of circulating vaccine-derived…
Background Wild type 2 poliovirus was last observed in 1999. The Sabin-strain oral polio vaccine type 2 (OPV2) was critical to eradication, but it is known to revert to a neurovirulent phenotype, causing vaccine-associated paralytic poliomyelitis. OPV2 is also transmissible and can establish…
Background Trivalent oral polio vaccine (tOPV) was replaced worldwide from April, 2016, by bivalent types 1 and 3 oral polio vaccine (bOPV) and one dose of inactivated polio vaccine (IPV) where available. The risk of transmission of type 2 poliovirus or Sabin 2 virus on re-introduction or resurgence of type 2 poliovirus after…
To assess the dynamics of genetic reversion of live poliovirus vaccine in humans, we studied molecular evolution in Sabin-like poliovirus isolates from Nigerian acute flaccid paralysis cases obtained from routine surveillance. We employed a novel modeling approach to infer substitution and recombination rates from whole-genome sequences and information about poliovirus…
Wild poliovirus type 3 (WPV3) has not been seen anywhere since the last case of WPV3-associated paralysis in Nigeria in November 2012. At the time of writing, the most recent case of wild poliovirus type 1 (WPV1) in Nigeria occurred in July 2014, and WPV1 has not been seen in Africa since a case in Somalia in August 2014. No cases associated with circulating vaccine-…
Background: Phylogeography improves our understanding of spatial epidemiology. However, application to practical problems requires choices among computational tools to balance statistical rigor, computational complexity, sensitivity to sampling strategy and interpretability. Methods: We introduce a fast, heuristic algorithm to…
Mike Famulare
Principal Research Scientist
BIOGRAPHY
Stewart Chang has a Ph.D. in Bioinformatics from the University of Michigan, where he researched the mathematical modeling of host response to tuberculosis (TB) bacterium. He also has a Bachelor of Arts degree in Biochemistry, as well as Latin, from Rice University. Stewart has over ten years of experience with a variety of computational modeling and analysis techniques, including post-doctoral work at the University of British Columbia (UBC) as well as at the University of Washington, Seattle (UW), where he investigated the mathematical modeling of HIV infection at UBC, and did genomic analysis of influenza-infected and HIV-infected cells at the UW. Stewart also has a strong community focus. Before turning to research, he joined Teach for America and taught math in rural south Louisiana, where he worked with under-resourced communities. As a member of IDM’s research team, Stewart is currently developing and parameterizing the IDM model of HIV infection, and is working on the IDM model of TB infection.
PUBLICATIONS (5)
Background Gold mines represent a potential hotspot for Mycobacterium tuberculosis (Mtb) transmission and may be exacerbating the tuberculosis (TB) epidemic in South Africa. However, the presence of multiple factors complicates estimation of the mining contribution to the TB…
Background The post-2015 End TB Strategy sets global targets of reducing tuberculosis incidence by 50% and mortality by 75% by 2025. We aimed to assess resource requirements and cost-effectiveness of strategies to achieve these targets in China, India, and South Africa. Methods We examined…
Background The post-2015 End TB Strategy proposes targets of 50% reduction in tuberculosis incidence and 75% reduction in mortality from tuberculosis by 2025. We aimed to assess whether these targets are feasible in three high-burden countries with contrasting epidemiology and previous programmatic achievements…
To assess the dynamics of genetic reversion of live poliovirus vaccine in humans, we studied molecular evolution in Sabin-like poliovirus isolates from Nigerian acute flaccid paralysis cases obtained from routine surveillance. We employed a novel modeling approach to infer substitution and recombination rates from whole-genome sequences and information about poliovirus…
Background: New WHO guidelines recommend initiation of antiretroviral therapy for HIV-positive adults with CD4 counts of 500 cells per μL or less, a higher threshold than was previously recommended. Country decision makers have to decide whether to further expand eligibility for antiretroviral therapy accordingly. We aimed to assess the…
Stewart Chang
Sr. Research Scientist
BIOGRAPHY
Daniel Bridenbecker has a Bachelor of Science (B.S.) from Lewis and Clark College in Portland, Oregon, and majored in both Math and Physics. Additionally, Daniel completed Master of Science course work in Mathematics at Georgia State University. Prior to working at IDM, Daniel was the Software Engineering Manager at Cloud Cap Technology that developed fully autonomous autopilots and pan/tilt/zoom camera systems for small unmanned air vehicles. Daniel came to Cloud Cap after his partner and he sold their custom software development company, Solution Engineering, Inc., to the Goodrich Corporation. At Solution Engineering, Daniel worked on numerous projects ranging from precision measurement to decision support software. Daniel also brings over 10 years of experience developing air-to-air combat simulations for Lockheed Martin. This experience includes pilot decision logic, integrated avionics system, and numerous data analysis tools. As a member of the IDM software team, Daniel’s primary focus is on developing EMOD software.
PUBLICATIONS (4)
Background The rapid scale-up of antiretroviral therapy (ART) towards the UNAIDS 90-90-90 goals over the last decade has sparked considerable debate as to whether universal test and treat can end the HIV-1 epidemic in sub-Saharan Africa. We aimed to develop a network transmission model, calibrated to capture age-specific and sex-specific gaps in the scale-up of ART, to estimate the…
Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness.…
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Background reactive case detection is best poised to push a region to elimination. This study uses mathematical modelling to assess how baseline transmission intensity and local interconnectedness affect the impact of reactive activities in the context of other possible intervention packages. Methods…
Dan Bridenbecker
Sr. Software Engineer
BIOGRAPHY
DC Sutliffe has a Bachelor of Art (B.A.) in Graphic Design with an emphasis in Computer Science from the University of the Pacific, as well as completing Master of Science coursework in Computer Information Systems. DC has more than 10 years of System Engineering experience including progressive responsibility and expertise in Quality Assurance Analysis, Configuration Management, and AT&T Core Network Architecture, Test Automation as well as Project Management within the Software Testing Field. Prior to joining IDM, she worked for the Turkish Government on the Istanbul Seismic Mitigation and Emergency Preparedness(ISMEP) in combination with Nippon Telegraph and Telephone East Corporation (NTT East) supporting the implementation of EDX SignalPro that aided in the testing of calculations and statistical analysis of base Radio Frequency (RF) simulations. DC has worked for larger corporations, freelanced for small start-ups, as well as volunteered for humanitarian, political and environmental organizations. As a member of the IDM software team, DC’s current work focuses on supporting and testing the IDM Large Data Project.
DC Sutliffe
IT Systems Engineer
BIOGRAPHY
Dennis Harding has over twenty years in software and engineering expertise, with a Bachelor of Science degree in Electrical Engineering from San Jose State University as well as two years of graduate work in Computer Science from Santa Clara University. Dennis’ past work has included microwave communications as well as computer science, and he has two patents to his credit, as well as five more patents still pending for his work. Dennis is a member of the IEEE, a SCRUM master, and is experienced with Agile development. Dennis’ IDM work is focused on large data, and he leads IDM’s development efforts related to Large Data, including the generation of, management of, and storage issues related to extremely large data sets, such as those required for accurate simulation modeling.
PROJECTS (1)
Contagion Cube
The Contagion Cube project uses a wearable cube with a Bluetooth radio and LED display to simulate disease transmission in a live setting. IDM visitors wear the cube as they interact with others and watch as the LEDs light up to indicate a susceptible state, exposure events, and an infectious state. This provides a more tangible way for people to understand transmission dynamics and disease…
BIOGRAPHY
Jeff Steinkraus has a Master of Science degree in Computer Science and Engineering from the University of Michigan, as well as dual Bachelor of Science degrees in Computer Science and Honors Mathematics from the University of Michigan. Jeff’s master’s research focused on artificial intelligence (AI) and machine learning (ML). As a member of the IDM software team, Jeff has worked in a variety of areas, including input tools, disease model features and performance, and currently works on developing and enhancing an open, flexible infrastructure to support disease modeling.
PUBLICATIONS (1)
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
PROJECTS (1)
COMPS
Computational Modeling Platform Service (COMPS) is a web-based user interface that facilitates research by providing access to high-performance computing environments. The dashboard allows you to monitor simulations that are running or queued and manage cluster resources using a job-priority system. You can…
Jeff Steinkraus
Sr. Software Engineer
BIOGRAPHY
Ned McHugh has a Bachelor of Arts (B.A.) degree in Computer Science from Lehigh University, Bethlehem, PA., and over 25 years of experience in software development. Prior to working at IDM, Ned worked at Microsoft on Windows Azure, Windows Essential Business Server, and MSDN. He was on the software development team at Chase Bank that rewrote the consumer credit card web site infrastructure for scalability and reliability for millions of users. Ned also worked at Reuters and launched multiple stock brokerage web sites for buying and selling stocks online. As a member of the IDM software team, Ned is developing and enhancing the computing infrastructure for disease modeling.
PROJECTS (1)
COMPS
Computational Modeling Platform Service (COMPS) is a web-based user interface that facilitates research by providing access to high-performance computing environments. The dashboard allows you to monitor simulations that are running or queued and manage cluster resources using a job-priority system. You can…
BIOGRAPHY
In the olden days, Peter Sylwester went from studying Photography at the Rhode Island School of Design, straight-away to manipulating digital imagery on computers that were as big as a house. Then, as the computers got smaller and the images got bigger, Peter retouched and assembled digital imagery for big and fancy advertising agencies in Boston and San Francisco. As the internet came along, Peter surfed that wave as an animator of elaborate interfaces and developer of online games. In the subsequent years of the so-called Web 2.0, Peter joined Eddie Bauer to help engineer an integration of fashion and ecommerce, and then years later, at the advent of the smartphone revolution, worked as a technologist and design thinker for T-Mobile in their advanced innovations laboratory, the Creation Center. All the while, Peter has taught certification courses in multimedia development, design, and introductory programming at Portland State University and Bellevue Community College. At IDM, Peter designs and engineers interfaces intended to facilitate human interaction with complex workflows on high-performance computing technologies.
PROJECTS (1)
COMPS
Computational Modeling Platform Service (COMPS) is a web-based user interface that facilitates research by providing access to high-performance computing environments. The dashboard allows you to monitor simulations that are running or queued and manage cluster resources using a job-priority system. You can…
BIOGRAPHY
Tony Ting has a Bachelor of Engineering (B.E.) with Honors in Computer Science from the Hong Kong University of Science and Technology. His final year project focused on handwriting recognition in form documents. Tony started his career in software at HSBC Bank where he developed risk management software for the electronic cash project MONDEX, and developed misc front-end components of the HSBC internet banking site. He then worked for Microsoft on SQL Server developing internal tools for both programmability features and engineering support systems, as well as the development of a services verification framework in SQL Azure. Prior to working at IDM, Tony helped build a large scale peer-to-peer cloud storage network for a startup company. As a member of the IDM software team, Tony is currently leading the development of various verification tools and processes for the computing infrastructure for disease modeling. He also create tools to scientifically validate the demographics, migration and climate data used by the EMOD software.
PUBLICATIONS (1)
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Tony Ting
Software Development Engineer in Test
BIOGRAPHY
Matt has over 15 years of technical experience with startup companies throughout the Puget Sound area, as well as Microsoft where he was both a System Analyst for the Bing software development and quality assurance labs and servers, and an IT Operations Engineer supporting Active Directory (ADFS). Additionally, Matt has an AA from Skagit Valley College and course work from Western Washington University where he focused on a degree in Education before changing to technology. As a member of the software team, Matt is the Systems Administrator and deploys, administers, and updates IDM’s large-scale computing systems, including the high-performance computing cluster, and their related infrastructure services.
Matt Hughes
IT Systems Engineer
BIOGRAPHY
John Sheppard is a member of the IDM software development team and brings over 16 years of experience in software development and engineering excellence. He has worked in biodiversity informatics, bioinformatics, and data analytics, as well as search technology and large scale distributed systems. John is also the co-author of multiple patents related to search and data analytics technologies. With a long history in the field as well as wide interests that span most of computer science, he has been involved in various open source projects, including projects for rules engines, peer mesh networks, and language runtimes. Within IDM, John leads the development efforts focused on creating the operational infrastructure for IDM’s modeling solvers.
PROJECTS (1)
COMPS
Computational Modeling Platform Service (COMPS) is a web-based user interface that facilitates research by providing access to high-performance computing environments. The dashboard allows you to monitor simulations that are running or queued and manage cluster resources using a job-priority system. You can…
BIOGRAPHY
Jillian Gauld has a Master of Science in Population and Public Health from the University of British Columbia, along with a Bachelor of Science (Honours) in Biology from Queen’s University. She received funding from the Canadian Institutes of Health Research for her master’s thesis, which focused on the development of contact networks in the hospital setting, and modeling the transmission of respiratory pathogens between healthcare workers. Prior to joining IDM, Jillian was an environmental health scientist at the BC Centre for Disease Control in Vancouver, Canada. As a member of the IDM research team, Jillian is working on transmission network development and epidemiology, to inform vaccination policies and control strategies for enteric and respiratory diseases.
PUBLICATIONS (2)
Since the prequalification of the Typhoid conjugate vaccine (TCV) by the WHO and subsequent position paper published in 2018, strategies for roll-out of the vaccine have been under discussion [1]. The 2018 position paper recommends the introduction of TCV to be…
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Jillian Gauld
Research Scientist
BIOGRAPHY
Dejan Lukacevic has a Bachelor of Science in Computer Science from the School of Electrical Engineering, University of Belgrade, Serbia. He is an experienced Software Engineer with a strong background in relational databases, SQL, software tools and automation. Dejan is passionate about data, coding and quality. Prior to joining IDM, Dejan worked at Microsoft for 8 years, most recently on testing Windows Error Reporting (WER), large-scale processing harnesses, and testing relational databases. Prior to Microsoft he worked in the NGO sector, leading the development of microfinance and project monitoring systems for community development projects. As a member of the IDM software team, Dejan is focusing on supporting research by developing scalable software tools, analyzing spatial, climate and demographics data, and managing PostgreSQL databases and Azure data processing pipelines.
PUBLICATIONS (1)
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Dejan Lukacevic
Software Engineer
BIOGRAPHY
André Lin has a PhD in Medical Sciences from the Radboud University Medical Centre, Netherlands, along with a Master’s degree and a PhD in Applied Biology from the University of Ouagadougou. He was also awarded a graduate scholarship in Biology Engineering from the University of Sciences and Technology in Algiers where his interest lay in the biological and anti-bacterial properties of a cobalt-60’s sterile irradiated amniotic membrane tissue. As a doctoral candidate, André Lin used sensitive molecular tools and first quantified the full extent of the human reservoir for gametocytes. Prior to joining IDM, André Lin was Principal Investigator of epidemiological and clinical studies at CNRFP, Ouagadougou. His work contributed novel and highly relevant findings about malaria low-density infections and immunity to accurately understand the composition and dynamics of the infectious reservoir to facilitate current and future malaria control and elimination efforts. He also acted as temporary advisor for WHO. As part of the research team at IDM, André works to identify and organize input data in order to refine and apply models to conduct sensitivity analyses as well as explore trade-offs among multiple interventions. His concentration is optimizing disease eradication plans for time, cost, and robustness and developing novel diagnostic techniques in support of elimination and eradication of malaria.
PUBLICATIONS (11)
Background Malaria incidence has plateaued in Sub-Saharan Africa despite Seasonal Malaria Chemoprevention’s (SMC) introduction. Community health workers (CHW) use a door-to-door delivery strategy to treat children with SMC drugs, but for SMC to be as effective as in clinical trials, coverage must be high over successive seasons.…
Background Absolute numbers of COVID-19 cases and deaths reported to date in the sub-Saharan Africa (SSA) region have been significantly lower than those across the Americas, Asia, and Europe. As a result, there has been limited information about the demographic and clinical characteristics of deceased cases in the region, as well as the impacts of different case management…
Malaria infections occurring below the limit of detection of standard diagnostics are common in all endemic settings. However, key questions remain surrounding their contribution to sustaining transmission and whether they need to be detected and targeted to achieve malaria elimination. In this study we analyse a range of malaria datasets to quantify the density, detectability, course of…
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
As Africa-wide malaria prevalence declines, an understanding of human movement patterns is essential to inform how best to target interventions. We fitted movement models to trip data from surveys conducted at 3–5 sites throughout each of Mali, Burkina Faso, Zambia and Tanzania. Two models were compared in terms of…
Malaria transmission remains high in Sub-Saharan Africa despite large-scale implementation of malaria control interventions. A comprehensive understanding of the transmissibility of infections to mosquitoes may guide the design of more effective transmission reducing strategies. The impact of P. falciparum sexual stage immunity on the infectious reservoir for malaria has never been…
Background Infection with Plasmodium can elicit antibodies that inhibit parasite survival in the mosquito, when they are ingested in an infectious blood meal. Here, we determine the transmission-reducing activity (TRA) of naturally acquired antibodies from 648 malaria-exposed individuals using lab-based…
Background As malaria prevalence declines in many parts of the world due to widescale control efforts and as drug-resistant parasites begin to emerge, a quantitative understanding of human movement is becoming increasingly relevant to malaria control. However, despite its importance, significant knowledge gaps remain regarding human movement,…
Mass-screen-and-treat and targeted mass-drug-administration strategies are being considered as a means to interrupt transmission of Plasmodium falciparum malaria. However, the effectiveness of such strategies will depend on the extent to which current and future diagnostics are able to detect those individuals who are infectious to mosquitoes. We estimate the…
Background Plasmodium falciparum gametocytes are essential for malaria transmission. Malaria control measures that aim at reducing transmission require an accurate characterization of the human infectious reservoir. Methods We longitudinally determined human infectiousness to mosquitoes and P…
Background Elimination of malaria can only be achieved through removal of all vectors or complete depletion of the infectious reservoir in humans. Mechanistic models can be built to synthesize diverse observations from the field collected under a variety of conditions and subsequently used to query the infectious…
PROJECTS (2)
easyVA web portal for clinicians
Understanding the patterns and underlying causes of disease mortality remains an urgent question, to which IDM and BMGF have been dedicating more attention and effort. easyVA is a user-friendly web-based interface that will allow physicians to easily visualize questions and answers from verbal autopsies and enter the cause of death. easyVA will also enable an algorithm-based application for…
Shape-shifting Plasmodium parasitemiae: a novel approach for modeling malaria infection and immunity
Targeted interventions used to interrupt malaria transmission in an endemic population depend on an accurate description of the parasite burden: who is at risk for infection, who is infectious, and what is the appropriate response given data from both active and passive surveillance measures. Sampling of parasite densities in malaria-endemic settings gives limited information on the infection…
Andre Lin Ouedraogo
Research Scientist
BIOGRAPHY
Bryan Ressler is a Senior Software Developer at IDM. He holds a BS of Information & Computer Science from UC Irvine. For the last 27 years, he has worked in application software development, embedded systems, user interface design, mobile applications and research incubations. A few of the projects he has worked on include system software at Apple, graphics applications at Adobe Systems, startup companies in the MPEG, e-learning, medical and content distribution fields, photo manipulation applications at Microsoft (including PhotoSynth and MS Research’s ICE photo-stitching application), and research incubation projects at eBay Research Labs. Bryan is also an electronic artist, musician, and member of the Maker movement. At IDM, he is concentrating on creating and fine-tuning the upcoming COMPS user interface.
PROJECTS (1)
COMPS
Computational Modeling Platform Service (COMPS) is a web-based user interface that facilitates research by providing access to high-performance computing environments. The dashboard allows you to monitor simulations that are running or queued and manage cluster resources using a job-priority system. You can…
BIOGRAPHY
Ben Althouse is a member of the epidemiology team at IDM where he explores pneumococcal pneumonia vaccines, the transmission dynamics of respiratory pathogens, and the role of complex human contact structures on disease transmission. He was an Omidyar Fellow at the Santa Fe Institute, holds a PhD in Epidemiology and a Master of Science in Biostatistics from the Johns Hopkins Bloomberg School of Public Health where he was awarded an NSF Graduate Research Fellowship, and holds Bachelor of Science degrees in Mathematics and Biochemistry from the University of Washington. His previous work has included mathematical modeling of sylvatic dengue virus transmission in nonhuman primates in Senegal, examining the role of antimicrobial use on the evolution of drug resistance, using Twitter as a model system of co-infection dynamics, and using novel data sources (such as Google searches, Twitter, and Wikipedia article views) for population-level surveillance of infectious and chronic diseases. Ben is an Affiliate Faculty member in the Department of Biology at New Mexico State University, Las Cruces, and an Affiliate Assistant Professor at the Information School at UW.
PUBLICATIONS (6)
Background Absolute numbers of COVID-19 cases and deaths reported to date in the sub-Saharan Africa (SSA) region have been significantly lower than those across the Americas, Asia, and Europe. As a result, there has been limited information about the demographic and clinical characteristics of deceased cases in the region, as well as the impacts of different case management…
Background The west African Ebola epidemic (2014–15) necessitated behaviour change in settings with prevalent and pre-existing unmet needs as well as extensive mechanisms for local community action. We aimed to assess spatial and temporal trends in community-reported needs and associations with behaviour change, community engagement, and the overall…
Identifying the transmission sources and reservoirs of Streptococcus pneumoniae (SP) is a long-standing question for pneumococcal epidemiology, transmission dynamics, and vaccine policy. Here we use serotype to identify SP transmission and examine acquisitions (in the same household, local community, and county, or of unidentified origin…
Importance Current acellular pertussis vaccines may not protect against transmission of Bordetella pertussis. Objective To assess whether a priming dose of whole-cell pertussis (wP) vaccine is cost-effective at reducing pertussis infection in infants. Design, Setting, and…
Novel data streams (NDS), such as web search data or social media updates, hold promise for enhancing the capabilities of public health surveillance. In this paper, we outline a conceptual framework for integrating NDS into current public health surveillance. Our approach focuses on two key questions: What are the opportunities for using NDS and what are the minimal tests of validity and…
Background The recent increase in whooping cough incidence (primarily caused by Bordetella pertussis) presents a challenge to both public health practitioners and scientists trying to understand the mechanisms behind its resurgence. Three main hypotheses have been proposed to explain the…
Ben Althouse
Principal Research Scientist
BIOGRAPHY
Steve Kroiss has a Ph.D. in Biology from Washington University in St. Louis and a B.S. in Biology from the University of Wisconsin Madison. For his postdoctoral work at the University of Washington in Seattle, he studied the effects of climate change on the geographic range boundaries and population dynamics of forests on Mt. Rainier. For his dissertation, he studied the effectiveness of different land management strategies for restoring rare plant populations in the Ozark Mountains and on the California coastline. He also worked at the Chicago Botanic Garden and consulted for Point Reyes National Seashore, helping to monitor and manage rare plant species. As an Education Research Fellow at the Center for Integration of Research, Teaching and Learning, he helped develop evidence-based teaching methods for improving students’ understanding of primary research articles. As a Teaching Associate at UW Seattle, he helped formulate several courses in ecology and statistical modeling. Additionally, he led a volunteer teaching team in the Young Scientist Program, a science outreach program for public school students. Steve has joined the Polio team as a research scientist to support polio eradication efforts by creating and improving statistical risk models, mapping disease spread, and analyzing vaccination campaign data.
PUBLICATIONS (3)
The polio environmental surveillance (ES) system has been an incredible tool for advancing polio eradication efforts because of its ability to highlight the spatial and temporal extent of poliovirus circulation. While ES often outperforms, or is more sensitive than AFP surveillance, the sensitivity of the ES system has not been well characterized. Fundamental uncertainty of ES site sensitivity…
Background Pakistan is one of only three countries where poliovirus circulation remains endemic. For the Pakistan Polio Eradication Program, identifying high risk districts is essential to target interventions and allocate limited resources. Methods Using a hierarchical Bayesian framework we developed…
The globally synchronized removal of the attenuated Sabin type 2 strain from the oral polio vaccine (OPV) in April 2016 marked a major change in polio vaccination policy. This change will provide a significant reduction in the burden of vaccine-associated paralytic polio (VAPP), but may increase the risk of circulating vaccine-derived…
Steve Kroiss
Sr. Research Scientist
BIOGRAPHY
Adam Akullian is a Research Scientist at IDM and an Affiliate Associate Professor in the Department of Global Health at the University of Washington. Adam has a Ph.D. in Epidemiology from the University of Washington and an Sc.B. in Environmental Science from Brown University. He is a recipient of a National Science Foundation (NSF) Graduate Research Fellowship. As a doctoral candidate, Adam studied the spatial epidemiology of emerging enteric diseases and the geography of HIV in sub-Saharan Africa. As a member of the IDM’s research team, Adam is dedicated to understanding what it will take to end the HIV epidemic, considering heterogeneous risk of acquisition and transmission across populations, and uses mathematical modeling and spatial epidemiology in his work.
PUBLICATIONS (15)
Background The number of people on antiretroviral therapy (ART) requiring treatment monitoring in low-resource settings is rapidly increasing. Point-of-care (POC) testing for ART monitoring might alleviate burden on centralised laboratories and improve clinical outcomes, but its cost-effectiveness is unknown. Methods We used cost and effectiveness data from the…
Introduction Over one hundred implementation studies of HIV pre‐exposure prophylaxis (PrEP) are completed, underway or planned. We synthesized evidence from these studies to inform mathematical modelling of the prevention cascade for oral and long‐acting PrEP in the setting of western Kenya, one of the world’s most…
Background The rapid scale-up of antiretroviral therapy (ART) towards the UNAIDS 90-90-90 goals over the last decade has sparked considerable debate as to whether universal test and treat can end the HIV-1 epidemic in sub-Saharan Africa. We aimed to develop a network transmission model, calibrated to capture age-specific and sex-specific gaps in the scale-up of ART, to estimate the…
Over the past decade, there has been a massive scale-up of primary and secondary prevention services to reduce the population-wide incidence of HIV. However, the impact of these services on HIV incidence has not been demonstrated using a prospectively followed, population-based cohort from South Africa—the country with the world’s highest rate of new infections. To quantify HIV incidence…
Mobility in sub-Saharan Africa links geographically-separate HIV epidemics, intensifies transmission by enabling higher-risk sexual behavior, and disrupts care. This population-based observational cohort study measured complex dimensions of mobility in rural Uganda and Kenya. Survey data were collected every 6 months beginning in 2016 from a random sample of 2308 adults in 12 communities…
Background Despite policies for universal HIV testing and treatment (UTT) regardless of CD4 count, there are still 1.8 million new HIV infections and 1 million AIDS-related deaths annually. The UNAIDS 90-90-90 goals target suppression of HIV viral load in 73% of all HIV-infected people worldwide by 2030. However, achieving these targets may not lead to expected reductions in HIV…
Background Large geographical variations in the intensity of the HIV epidemic in sub-Saharan Africa call for geographically targeted resource allocation where burdens are greatest. However, data available for mapping the geographic variability of HIV prevalence and detecting HIV ‘hotspots’ is scarce, and population-based surveillance data are not…
Introduction There are significant knowledge gaps concerning complex forms of mobility emergent in sub‐Saharan Africa, their relationship to sexual behaviours, HIV transmission, and how sex modifies these associations. This study, within an ongoing test‐and‐treat trial (SEARCH, NCT01864603), sought to measure effects of…
Western Kenya suffers a highly endemic and also very heterogeneous epidemic of human immunodeficiency virus (HIV). Although female sex workers (FSW) and their male clients are known to be at high risk for HIV, HIV prevalence across regions in Western Kenya is not strongly correlated with the fraction of women engaged in commercial sex. An agent-based network model of HIV transmission,…
Non-typhoidal Salmonella (NTS) is a leading cause of bloodstream infections in Africa, but the various contributions of host susceptibility versus unique pathogen virulence factors are unclear. We used data from a population-based surveillance platform (population ~25,000) between 2007–2014 and NTS genome-sequencing to compare host and pathogen-specific factors between individuals…
Though a wide body of observational and model-based evidence underscores the promise of Universal Test and Treat (UTT) to reduce population-level HIV incidence in high-burden areas of Sub-Saharan Africa (SSA), the only cluster- randomized trial of UTT completed to date, ANRS 12249, did not show a significant reduction in incidence. More UTT…
Under the premise that in a resource-constrained environment such as Sub-Saharan Africa it is not possible to do everything, to everyone, everywhere, detailed geographical knowledge about the HIV epidemic becomes essential to tailor programmatic responses to specific local needs. However, the design and evaluation of national HIV…
Objective To quantify the contribution of specific sexual partner age groups to the risk of HIV acquisition in men and women in hyperendemic region of South Africa. Design We conducted a population-based cohort study among women (15–49 years of age) and men (15–55 years of age) between…
Voluntary Medical Male Circumcision (VMMC) for human immunodeficiency virus (HIV) prevention has scaled up rapidly among young men in western Kenya since 2008. Whether the program has successfully reached uncircumcised men evenly across the region is largely unknown…
Introduction The availability of specialized HIV services is limited in rural areas of sub-Saharan Africa where the need is the greatest. Where HIV services are available, people living with HIV (PLHIV) must overcome large geographic, economic and social barriers to access healthcare. The objective of this study was to understand the…
VIDEOS (2)
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Senior Research Manager Caitlin Bever, PhD, discusses the challenges of preventing and treating malaria and how modeling plays a role in determining which interventions would be the most effective for a particular country.
Senior Research Manager Caitlin Bever, PhD, discusses the challenges of preventing and treating malaria and how modeling plays a role in determining which interventions would be the most effective for a particular country.
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Modeling Eradication: what will it take to 'treat our way out' of the Hiv epidemic
Modeling Eradication: what will it take to 'treat our way out' of the Hiv epidemic?
Adam Akullian
Research Scientist
BIOGRAPHY
Svetlana Titova holds a Bachelor of Science in Applied Mathematics from the University of California, Santa Barbara, and a Certificate of C# Programming from the UC, San Diego Extension. For five years, she tested firmware and software for sonar technology with Teledyne RD Instruments, whose clients included USGS and DARPA. She also tested the Forza Motorsport video game at Turn 10 Studios for three years. Svetlana brings her skills back to the field of science as she joins IDM to test UI components that are currently under development.
PUBLICATIONS (1)
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
PROJECTS (1)
Contagion Cube
The Contagion Cube project uses a wearable cube with a Bluetooth radio and LED display to simulate disease transmission in a live setting. IDM visitors wear the cube as they interact with others and watch as the LEDs light up to indicate a susceptible state, exposure events, and an infectious state. This provides a more tangible way for people to understand transmission dynamics and disease…
Svetlana Titova
Software Test Engineer
BIOGRAPHY
Dennis Chao holds a PhD from the University of New Mexico and a BSE from Princeton University. Prior to IDM, Dennis was a Staff Scientist in the Vaccine and Infectious Disease Division at the Fred Hutchinson Cancer Research Center. He developed models of infectious disease transmission for influenza, cholera, and dengue in order to better understand the epidemiology of these pathogens and to predict the effectiveness of potential intervention strategies. His prior projects included research on threats from bioterrorism and emerging infectious diseases as well as modeling the effects of mass cholera vaccinations in Haiti and Africa. Dennis joins IDM’s Epidemiology team as a research scientist to continue his work with enteric diseases and modeling.
PUBLICATIONS (6)
Traditional clinical prediction models focus on parameters of the individual patient. For infectious diseases, sources external to the patient, including characteristics of prior patients and seasonal factors, may improve predictive performance. We describe the development of a predictive model that integrates multiple sources of data in a principled statistical framework using a post-test…
Background Most of the world’s sickle cell disease (SCD) burden is in Africa, where it is a major contributor to child morbidity and mortality. Despite the low cost of many preventive SCD interventions, insufficient resources have been allocated, and progress in alleviating the SCD burden has lagged behind other public-health efforts in Africa. The…
Background Pediatric diarrhea can be caused by a wide variety of pathogens, from bacteria to viruses to protozoa. Pathogen prevalence is often described as seasonal, peaking annually and associated with specific weather conditions. Although many studies have described the seasonality of diarrheal disease, these studies have occurred predominantly in temperate regions. In tropical and…
Background: Pediatric diarrhea can be caused by a wide variety of pathogens, from bacteria to viruses to protozoa. Pathogen prevalence is often described as seasonal, peaking annually and associated with specific weather conditions. Although many studies have described the seasonality of diarrheal disease, these studies have occurred predominantly in temperate regions. In tropical and resource…
Background Oral cholera vaccine (OCV) is a feasible tool to prevent or mitigate cholera outbreaks. A better understanding of the vaccine’s efficacy among different age groups and how rapidly its protection wanes could help guide vaccination policy.…
Dengue vaccines will soon provide a new tool for reducing dengue disease, but the effectiveness of widespread vaccination campaigns has not yet been determined. We developed an agent-based dengue model representing movement of and transmission dynamics among people and mosquitoes in Yucatán, Mexico, and simulated various vaccine scenarios to evaluate effectiveness under…
PROJECTS (1)
Contagion Cube
The Contagion Cube project uses a wearable cube with a Bluetooth radio and LED display to simulate disease transmission in a live setting. IDM visitors wear the cube as they interact with others and watch as the LEDs light up to indicate a susceptible state, exposure events, and an infectious state. This provides a more tangible way for people to understand transmission dynamics and disease…
Dennis Chao
Sr. Research Scientist
BIOGRAPHY
Cory is a member of the System Administration and Application Support team, with over 20 years of experience designing and supporting IT infrastructure systems for startup and global companies, including High-Performance Compute Clusters that have been on the Top500 list. His focus at IDM is to provide stable, efficient systems operating in our world class data center and in the cloud. Cory has a Bachelor of Science degree in Electrical Engineering from North Dakota State University.
Cory Kitzan
IT Systems Engineer
BIOGRAPHY
Zhaowei has a PhD in Mathematics and MS in Computer Science from the University of Florida. He has over 18 years of experience working as a computer software developer. Zhaowei has experience with Web Search Tools, ASPX applications, Windows applications, and Python applications. As part of IDM’s team Zhaowei will be working on IDM’s DTK-Tools.
Zhaowei Du
Software Engineer
BIOGRAPHY
Ashlee Mehaddi is a Project Manager at IDM. Ashlee has her Bachelor's degree in Writing Studies from the University of Washington, Tacoma as well as a Technical Writing certificate from the University of Washington, Seattle. Ashlee has over ten years of experience managing and coordinating projects for a small business owner. In her role at IDM Ashlee helps coordinate and drive web content and development, is involved in planning and organizing IDM's annual Symposium as well as many other projects related to IDM's mission.
Ashlee Mehaddi
Project Manager
BIOGRAPHY
Ye has a Master of Engineering in Mechanical Engineering from Virginia Tech, and a Bachelor of Engineering (with honors) in Mechanical and Electronic Engineering from Zhejiang University, China. Ye has four years of experience working as a Senior Software Engineer in test at MicroStrategy where her primary focus was MicroStrategy Intelligent server and web server testing. Ye also has experience with mobile and web UI testing. Ye’s testing experience includes software functional testing, stability test, and performance testing/tuning. As a member of IDM’s team her primary focus will be the COMPS RESTful service.
PUBLICATIONS (1)
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Ye Chen
Sr. Software Development Engineer
BIOGRAPHY
Jen Schripsema has an MS in User Centered Design and Engineering from the University of Washington and BA in Biology from the Colorado College. She has experience working as the solo writer at a fast-paced startup and implementing documentation systems that allow for greater collaboration with researchers and engineers. Jen has written and edited content for Windows Embedded about how to build operating systems for embedded devices and led projects to design documentation landing pages, informational posters, and other illustrations. Jen has written science news articles for a variety of publications, including a project on the importance of interdisciplinary research teams. Additionally, she wrote news articles for patients with chronic health conditions. As a senior technical writer for IDM, Jen contributes to software documentation and teaching tools.
PROJECTS (1)
Contagion Cube
The Contagion Cube project uses a wearable cube with a Bluetooth radio and LED display to simulate disease transmission in a live setting. IDM visitors wear the cube as they interact with others and watch as the LEDs light up to indicate a susceptible state, exposure events, and an infectious state. This provides a more tangible way for people to understand transmission dynamics and disease…
BIOGRAPHY
Qinghua has a MS in Public Administration from Illinois Institute of Technology and BS in Science Engineering from Queen Mary, University of London. Qinghua has experience with web applications such as a prosecution system that recorded hunting violations, citation information and fine amount. As part of IDM’s team Qinghua will be designing and querying large data for climate, demographic and transportation as inputs for IDM’s modeling software as well as conducting data reduction and analysis of simulations reports, and designing and implementing usability testing for enhanced user experience.
PROJECTS (1)
easyVA web portal for clinicians
Understanding the patterns and underlying causes of disease mortality remains an urgent question, to which IDM and BMGF have been dedicating more attention and effort. easyVA is a user-friendly web-based interface that will allow physicians to easily visualize questions and answers from verbal autopsies and enter the cause of death. easyVA will also enable an algorithm-based application for…
BIOGRAPHY
Mandy Izzo is a Senior Science Writer for the Institute for Disease Modeling, where she develops scientific content for the global health community. She earned a BA in Integrative Biology from the University of California, Berkeley; an MS in Biology from California State University, Northridge; and a PhD in Ecology and Evolutionary Biology from the University of Michigan. Her training was furthered during post-doctoral positions at the University of California, Davis, first in the Department of Entomology and Nematology, and then in the Department of Fish, Wildlife, and Conservation Biology. She has over 11 years of field and lab experience in the biological sciences that include the design, oversight, execution, and analysis of projects. Trained as an Evolutionary Ecologist with specialization in the Behavioral Ecology of insects, Mandy’s work on insects has spanned topics such as the evolution of cricket song in the presence of an acoustically-orienting parasitic fly; the evolution of signals mediating inter- and intra-sexual selection in paper wasps; how multi-modal signals interact to mediate social interactions among dominance hierarchies in social insects; and how social interactions maintain honesty in communication. In addition to her work on insects, she has forayed into other taxa as well, examining the functionality of zebra stripes and studying the social, hormonal, and genetic basis of aggressive behavior of female tree swallows. Mandy is passionate about science communication, and aims to help make science more accessible between fields as well as to the general public. Her enjoyment of engaging others in science is manifest in her numerous publications and award-winning presentations. She holds a long-standing interest in public health and epidemiology, and is extremely excited for the opportunity to participate in the scientific process with a group that strives towards increasing transparency in science.
PUBLICATIONS (1)
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
PROJECTS (1)
Contagion Cube
The Contagion Cube project uses a wearable cube with a Bluetooth radio and LED display to simulate disease transmission in a live setting. IDM visitors wear the cube as they interact with others and watch as the LEDs light up to indicate a susceptible state, exposure events, and an infectious state. This provides a more tangible way for people to understand transmission dynamics and disease…
Mandy Izzo
Sr. Science Writer
BIOGRAPHY
Amelia Bertozzi-Villa earned her MPH from the University of Washington and Bachelor’s degree in Biology with honors and a minor in math from New York University. Prior to coming to IDM, Amelia worked as a Post-Bachelor Fellow at the Institute for Health Metrics and Evaluation, where she focused primarily on small-area estimation of mortality at the county level in the US. Amelia's research focuses on malaria transmission in Southeast Asia and the integration of empirical and dynamical disease modeling frameworks. Her other affiliations are with the University of Washington's iSchool and Oxford University's Malaria Atlas Project.
PUBLICATIONS (1)
Background Mass drug administration (MDA) is a control and elimination tool for treating infectious diseases. For malaria, it is widely accepted that conducting MDA during the dry season results in the best outcomes. However, seasonal movement of populations into and out of MDA target areas is common in many places and…
Amelia Bertozzi-Villa
Research Scientist
BIOGRAPHY
Kurt Frey has a doctorate in Chemical Engineering from the Massachusetts Institute of Technology (MIT), as well as a Master of Science in Chemical Engineering Practice from MIT, and a Bachelor of Science in Chemical Engineering from the Ohio State University. Kurt has worked for a variety of research groups, and was most recently at Argonne National Laboratory, supporting efforts on environmental processes for nuclear waste, both in recycling and disposal.
PUBLICATIONS (2)
Background Measles causes significant childhood morbidity in Nigeria. Routine immunization (RI) coverage is around 40% country-wide, with very high levels of spatial heterogeneity (3–86%), with supplemental immunization activities (SIAs) at 2-year or 3-year intervals. We investigated cost savings and burden reduction that could be achieved by adjusting the inter-campaign…
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Kurt Frey
Senior Research Engineer

BIOGRAPHY
Prashanth Selvaraj has a Ph.D. in Mechanical Engineering from the University of California, Berkeley, and a Master's degree in Fluid Mechanics from Ecole Polytechnique, Paris, France. During his Ph.D., he studied the dynamics of epileptic seizures that form in the human cortex using a phsyiologically relevant mathematical model of cortical dynamics. Additionally, he proposed the use of optogenetics, which involves light sensitive ion channels expressed by certain cell types in the cortex, to inhibit the spread of seizures before they are fully formed using closed loop control methods. After his Ph.D., Prashanth worked as a postdoctoral researcher at the University of California, San Francisco, as part of the DARPA SUBNETS initiative. He investigated the underlying meso-scale networks in the brain that contribute to neuropsychiatric disorders like PTSD and depression, and worked on a closed loop method of electrical stimulation to disrupt the function of these networks alleviating symptoms of these disorders. As part of the research team at IDM, Prashanth works on calibrating mathematical models of disease spread and control to the dynamics of malaria in different regions around the world.
PUBLICATIONS (5)
Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness.…
Background Epidemiological surveys of malaria currently rely on microscopy, polymerase chain reaction assays (PCR) or rapid diagnostic test kits for Plasmodium infections (RDTs). This study investigated whether mid-infrared (MIR) spectroscopy coupled with supervised machine learning could constitute an alternative method for rapid malaria…
Background While bed nets and insecticide spraying have had significant impact on malaria burden in many endemic regions, outdoor vector feeding and insecticide resistance may ultimately limit their contribution to elimination and control campaigns. Complementary vector control methods such as endectocides or systemic insecticides, where humans or…
Background The propensity of different Anopheles mosquitoes to bite humans instead of other vertebrates influences their capacity to transmit pathogens to humans. Unfortunately, determining proportions of mosquitoes that have fed on humans, i.e. Human Blood Index (HBI), currently requires expensive and time-consuming laboratory procedures involving enzyme-linked…
Background Malaria transmission is both seasonal and heterogeneous, and mathematical models that seek to predict the effects of possible intervention strategies should accurately capture realistic seasonality of vector abundance, seasonal dynamics of within-host effects, and heterogeneity of exposure…
Prashanth Selvaraj
Sr. Research Scientist
BIOGRAPHY
David Kong has a bachelor of Science in Computer Science from Simon Fraser University in Canada. He has worked at HSBC in the 90's to develop one of the bank's first PC Banking software. He has done contract work at Microsoft working on products such as Microsoft Office Accounting, Windows Media Center and Connected System Framework. At Boeing, he worked at the DMS team for centralizing, categorizing and managing documents used in Boeing. Being joining IDM, he worked at a startup called Visible Technologies which help companies to collect, monitor analyze social media data using Data Big technologies. Within IDM, he works in the COMPS team as a software engineer focusing on UI development.
PROJECTS (1)
easyVA web portal for clinicians
Understanding the patterns and underlying causes of disease mortality remains an urgent question, to which IDM and BMGF have been dedicating more attention and effort. easyVA is a user-friendly web-based interface that will allow physicians to easily visualize questions and answers from verbal autopsies and enter the cause of death. easyVA will also enable an algorithm-based application for…
BIOGRAPHY
Having worked in the Administrative and Marketing fields for over 15 years, Donna Adams is truly passionate about people and enjoy helping others. With a Bachelor’s Degree in English from Seattle University and administrative experience from small tech start-ups to large organizations like Nintendo of America, she brings a can-do attitude that creates a workplace culture with a sense of collaboration and community. She actively volunteers her marketing and design skills to a local dance studio and opens up her home in Sammamish as a host family to foreign exchange students.
Donna Adams
Business Administrator
BIOGRAPHY
Jon Russell received his Ph.D. in Biochemistry from Harvard University and his B.S. in Molecular Biophysics and Biochemistry from Yale College. During his Ph.D, Jon studied the origins of noise in cell-fate decision making by the bacterium Bacillus subtilis. He was generously supported as a Hertz Fellow in the lab of Dr. Rich Losick. As an undergraduate, Jon characterized fungi isolated from tropical plant samples for their ability to degrade synthetic polymers. As part of the research team at IDM, Jon is interested in using bioinformatic and biometric datasets to model disease transmission among asymptomatic populations.
PUBLICATIONS (1)
Vector control has been a key component in the fight against malaria for decades, and chemical insecticides are critical to the success of vector control programs worldwide. However, increasing resistance to insecticides threatens to undermine these efforts. Understanding the evolution and propagation of resistance is thus imperative to mitigating loss of intervention effectiveness.…
PROJECTS (1)
Shape-shifting Plasmodium parasitemiae: a novel approach for modeling malaria infection and immunity
Targeted interventions used to interrupt malaria transmission in an endemic population depend on an accurate description of the parasite burden: who is at risk for infection, who is infectious, and what is the appropriate response given data from both active and passive surveillance measures. Sampling of parasite densities in malaria-endemic settings gives limited information on the infection…
Jon Russell
Research Scientist
BIOGRAPHY
Chris Jones earned a Bachelor of Arts in Mathematics from the University of Oregon before returning to study Chemistry and Computer Science. He was lured away by the software industry and has worked for over 10 years as a back-end and build/internal tools developer. Chris worked for several years in Microsoft's Developer Division on a high-level build and tools team tasked with maintaining build quality and improving the code validation and integration processes used across the org. containing over two thousand devs, while there he helped ship Visual Studio 2005 and 2008. He also spent time at Turn 10 Studios working on build tools and infrastructure during the production cycle for Forza 6. Currently he works to maintain and improve the continuous integration system, helping to ensure the modelling software is always in a near-shippable state and that QA/researchers have builds available for testing and use.
Christopher Jones
Build Test Engineer
BIOGRAPHY
Clinton Collins has a Bachelor of Computer Science from Bluefield State College. Clinton has ten years of experience working in Software Development working on a wide range of software projects including telecom billing platform, cloud billing services, and a medicaid reconciliation suite. At IDM Clinton will be working on Large Data software services including climate and demographics data. Outside of work, he enjoys hiking, live music, tinkering around with hardware and software, and travel.
Clinton Collins
Sr. Software Engineer
BIOGRAPHY
Thomas holds a Master’s (Dipl.-Ing.) degree in Information and Communication Engineering from the University of Duisburg-Essen in Germany. Thomas has about 10 years of experience in the field of R&D and software development. Before he started at the IDM he was a researcher at the University of Washington where he worked on vision based navigation for autonomous drones. Prior to coming to the US, he worked as a Software Engineer at Nikon Metrology in Leuven, Belgium, where he was in a team that made software for coordinate measurement machines. At Vanderlande in the Netherlands he started as embedded software engineer for high-availability and real-time systems, then changed to the development of graphical user interfaces which he later headed as lead engineer. His career started as software engineer for embedded systems at ebmpast in Landshut, Germany, with the development of an air mass flow controlled blower for gas fired boilers. Thomas joined the EMOD team a year ago and is very excited to work at IDM.
PUBLICATIONS (1)
Individual-based models provide modularity and structural flexibility necessary for modeling of infectious diseases at the within-host and population levels, but are challenging to implement. Levels of complexity can exceed the capacity and timescales for students and trainees in most academic institutions. Here we describe the process and advantages of a multi-disease framework approach…
Thomas Fischle
Software Engineer

BIOGRAPHY
Josh Suresh has a PhD in astrophysics from Harvard University, as well as dual BS degrees in mathematics and physics from MIT. His doctoral work involved using large-scale hydrodynamic simulations to study the formation and evolution of galaxies. Specifically, his thesis focused on how to leverage observations of the circumgalactic medium to inform and constrain theoretical models of key galaxy physics, e.g. feedback from supernovae and supermassive black holes. As part of the malaria team at IDM, Josh is focused on using epidemiological modeling to directly inform and support malaria elimination efforts in sub-Saharan Africa.
PUBLICATIONS (1)
Background While bed nets and insecticide spraying have had significant impact on malaria burden in many endemic regions, outdoor vector feeding and insecticide resistance may ultimately limit their contribution to elimination and control campaigns. Complementary vector control methods such as endectocides or systemic insecticides, where humans or…
Josh Suresh
Research Scientist
BIOGRAPHY
Clark Kirkman IV has a PhD in Atmospheric Sciences from the University of Washington where he studied high latitude climate and sea ice, ocean, and atmosphere interactions of the Southern Ocean. He previously obtained a MS in Computer Sciences at the University of Wisconsin – Madison and BA in Computer Science and Mathematics from Lewis & Clark College. Prior to joining IDM, Clark worked as a Software Engineer for Vaisala, where he supported and developed software and processes for assessing wind and solar energy sources. He focused on delivering flexible-yet-automated processes to the internal assessment production team to help them stay focused on the creative parts of their jobs and improve their productivity. He now applies his do-what-needs-to-be-done approach and passion for helping team members be more productive to IDM, where he directly supports researchers with their software needs, including the DTK tools.
Clark Kirkman
Research Software Engineer
BIOGRAPHY
Marita R. Zimmermann has a PhD in health economics and outcomes research from the University of Washington. She also holds a Master’s in Public Health from Brown University and a Bachelor of Science in chemical and biomedical engineering from Carnegie Mellon University. For her doctoral dissertation, she evaluated the feasibility and cost-effectiveness of an active surveillance pharmacovigilance program for HIV drugs in Namibia. She completed a post-doctoral fellowship with Institute for Clinical and Economic Review, in which she designed and implemented novel cost-effectiveness models for new and existing drugs within selected disease areas, such as multiple sclerosis, blindness, and atopic dermatitis. These models were designed to inform payer or other stakeholder decision making and to influence U.S. policy. Marita has completed many other cost-effectiveness, budget impact, and program evaluation models in both U.S. and global health settings in varying disease areas. Marita’s research uses econometric, epidemiologic, and modeling methods to evaluate and increase value in health. She has produced many peer-reviewed publications in journals such as Drug Safety, Journal of AIDS, Journal of the American Pharmacy Association, and American Journal of Public Health. As an economist in IDM's analysis and model usage center, Marita models the economic effects of infectious disease and vaccination, and assesses value of interventions. Her work aims to inform decision makers how to get the most bang for their healthcare buck.
PUBLICATIONS (1)
Background Measles causes significant childhood morbidity in Nigeria. Routine immunization (RI) coverage is around 40% country-wide, with very high levels of spatial heterogeneity (3–86%), with supplemental immunization activities (SIAs) at 2-year or 3-year intervals. We investigated cost savings and burden reduction that could be achieved by adjusting the inter-campaign…
Marita Zimmermann
Research Economist
BIOGRAPHY
Niket Thakkar received his PhD in Applied Mathematics from the University of Washington in March 2017. As a graduate student, he worked on a variety of nanoscale optics problems, using mathematical modeling and statistics in collaboration with experimentalists to guide the design of novel measurement techniques and nanotechnologies. His work has been published in journals such as Nature Photonics and ACS Nano, and he has received a number of awards including the National Science Foundation Graduate Research Fellowship, the Boeing Research Award, and the 2017 UW Graduate Medal. At IDM, Niket works with the analysis and model usage group, creating statistical and machine learning models in support of measles erradication efforts. Outside of research, Niket plays soccer, reads, bikes, and searches for good Mexican food.
Niket Thakkar
Sr. Research Scientist
BIOGRAPHY
Brittany Hagedorn is a financial analyst for the Institute for Disease Modeling. She collaborates with multiple disease teams to estimate the cost of proposed interventions and to assess their value in comparison to alternative strategies for disease control. Brittany is interested in questions around the value of information in helping policy makers design more cost-effective strategies, as well as the trade-offs between alternative intervention strategies under budgetary constraints. Prior to joining IDM, Brittany worked with North American healthcare delivery systems to optimize their workflows to improve safety and clinical outcomes while simultaneously reducing cost. She has also advised healthcare technology companies on product design and development. Brittany is an ASQ-certified Six Sigma Black Belt and holds a B.S. in Systems Engineering and Masters of Business Administration (MBA) from Washington University in St. Louis.
PUBLICATIONS (5)
Background Absolute numbers of COVID-19 cases and deaths reported to date in the sub-Saharan Africa (SSA) region have been significantly lower than those across the Americas, Asia, and Europe. As a result, there has been limited information about the demographic and clinical characteristics of deceased cases in the region, as well as the impacts of different case management…
Since the prequalification of the Typhoid conjugate vaccine (TCV) by the WHO and subsequent position paper published in 2018, strategies for roll-out of the vaccine have been under discussion [1]. The 2018 position paper recommends the introduction of TCV to be…
Background Measles causes significant childhood morbidity in Nigeria. Routine immunization (RI) coverage is around 40% country-wide, with very high levels of spatial heterogeneity (3–86%), with supplemental immunization activities (SIAs) at 2-year or 3-year intervals. We investigated cost savings and burden reduction that could be achieved by adjusting the inter-campaign…
Measles vaccination is a cost-effective way to prevent infection and reduce mortality and morbidity. However, in countries with fragile routine immunization infrastructure, coverage rates are still low and supplementary immunization campaigns (SIAs) are used to reach previously unvaccinated children. During campaigns, vaccine is generally administered to every child, regardless of their…
INTRODUCTION: The lack of specific policies on how many children must be present at a vaccinating location before a healthcare worker can open a measles-containing vaccine (MCV) - i.e. the vial-opening threshold - has led to inconsistent practices, which can have wide-ranging systems effects. METHODS: Using HERMES-generated simulation models of the routine…
Brittany Hagedorn
Research Scientist
BIOGRAPHY
Mary Fisher manages the Research Software Engineering Team at IDM responsible for development of workflow tools, web applications, data services, and specific requests to support research. Mary has a Bachelor of Arts in Biological Anthropology from the State University of New York at Albany. Mary has been working in IT for 17 years wearing many hats, including business systems analyst, project manager, quality assurance engineer, software engineer, database developer, and manager. Previously, she managed a team of 18 client integration engineers at Comcast Technology Solutions responsible for delivering video on demand solutions to large broadcast network companies. Prior to that, Mary managed the applications development team at Physicians Insurance responsible for managing their document imaging system, underwriting, claims and risk management handling system, and 7 websites with several integrations, including with continued medical education systems. Outside of work, Mary is an avid runner with Seattle Green Lake Running Group and DJ with local radio station, Hollow Earth Radio KHUHLP 104.9 FM.
PROJECTS (1)
COMPS
Computational Modeling Platform Service (COMPS) is a web-based user interface that facilitates research by providing access to high-performance computing environments. The dashboard allows you to monitor simulations that are running or queued and manage cluster resources using a job-priority system. You can…
BIOGRAPHY
Assaf Oron started his quantitative career in deterministic-dominated paradigms, earning a B.Sc. in physics followed by an M.Sc. in environmental science where he modeled water flow in a rock fracture. In between the two he taught elementary school kids how to catch bugs. After several years in industry, Assaf switched fields and continents, arriving from Israel to the University of Washington for Ph.D. studies in statistics. At UW Assaf helped start the local chapter of StatCom, a student-run service for pro-bono statistical consulting. Prior to joining IDM, Assaf worked at the UW MESA Air pollution study, and at Seattle Children's. Among other topics, he has contributed to methods for clinical trial design, spatiotemporal modeling, and analysis of high-dimensional data. At IDM Assaf focuses on general strategy development for interventions with high impact potential upon maternal, neonate and child health. He is humbled and excited at the opportunity to help improve so many lives.
PUBLICATIONS (7)
Objectives: To determine the feasibility of having caregivers assist in recognition of clinical deterioration in children hospitalized with febrile illness in a resource-limited setting. Design: Single-center, prospective, interventional pilot study. Setting: General pediatric wards at Kenyatta National Hospital, Nairobi, Kenya…
Sickle cell disease (SCD) is one of the most common blood disorders impacting planetary health. Over 300,000 newborns are diagnosed with SCD each year globally, with an increasing trend. The sickle cell disease ontology (SCDO) is the most comprehensive multidisciplinary SCD knowledge portal. The SCDO was collaboratively developed by the SCDO working group, which includes experts in SCD and…
Background Most of the world’s sickle cell disease (SCD) burden is in Africa, where it is a major contributor to child morbidity and mortality. Despite the low cost of many preventive SCD interventions, insufficient resources have been allocated, and progress in alleviating the SCD burden has lagged behind other public-health efforts in Africa. The…
Previous studies from low-resource countries have highlighted concerns surrounding non-specific effects of whole-cell pertussis vaccination, particularly in females. We sought to examine the effects of sex and birth weight on health services utilization following first exposure to whole-cell pertussis vaccine. Using a self-controlled case series design and by calculating relative incidence…
INTRODUCTION: The lack of specific policies on how many children must be present at a vaccinating location before a healthcare worker can open a measles-containing vaccine (MCV) - i.e. the vial-opening threshold - has led to inconsistent practices, which can have wide-ranging systems effects. METHODS: Using HERMES-generated simulation models of the routine…
Mass azithromycin distribution has been shown to reduce all-cause mortality in preschool children in sub-Saharan Africa. However, substantial heterogeneity in the apparent effect has been noted across geographic settings, suggesting a greater relative benefit in higher mortality settings. Here, we evaluated the relationship between the underlying mortality rate and the efficacy of azithromycin…
We examined whether baseline mortality risk, as a function of child age and site, modified the azithromycin mortality-reduction effect in the Macrolide Oraux pour Réduire les Décès avec un Oeil sur la Résistance (MORDOR) clinical trial. We used the Cox proportional hazards model with an interaction term. Three models were examined representing three sources for the baseline-risk covariate: two…
Assaf Oron
Research Manager
BIOGRAPHY
Albert Lee is a research scientist on the Data, Dynamics and Analytics Team, and he has a PhD in Physics from Harvard University. For his graduate work, he studied the physical properties of interstellar dust by mapping the three-dimensional variation in its temperature and by using large catalogs of stars to infer its color and composition. He has been a recipient of the National Science Foundation Graduate Research Fellowship as well as the Insight Data Fellowship. At IDM he is developing new genetic models and tools to better understand the transmission properties of diseases. Outside the office you'll likely find him scribbling away in a sketchpad or hunting for LPs.
Albert Lee
Research Scientist
BIOGRAPHY
Ross Carter has a Master of Science in Telecommunications from University of Colorado (Boulder) through the college of engineering and applied science. He also has a Bachelor of Arts degree in Spanish and minor in Portuguese from BYU. He has over twenty years of experience working at high tech companies, such as Microsoft and Amazon Web Services (AWS). He’s held many different roles: network analyst, course developer, technical program manager, programmer writer, and technical writer. He’s always enjoyed working on cutting edge technologies. Ross is excited to be working at IDM on the documentation team.
Ross Carter
Sr. Technical Writer
BIOGRAPHY
Wesley earned his PHD at Harvard University under Dr. Dyann Wirth, Dr. Daniel L Hartl, and Daniel E. Neafsey where he used computational biology and bioinformatic techniques to study malaria genomics. He is interested in studying infectious disease evolution with models combining traditional population genetics and epidemiology. At IDM, he works with Mike Famulare to create dynamic models aimed at exploring multiscale transmission and viral evolution.
PUBLICATIONS (2)
Background Unlike in most pathogens, multiple-strain (polygenomic) infections of P. falciparum are frequently composed of genetic siblings. These genetic siblings are the result of sexual reproduction and can coinfect the same host when cotransmitted by the same mosquito. The degree with which coinfecting strains are…
To study the effects of malaria-control interventions on parasite population genomics, we examined a set of 1,007 samples of the malaria parasite Plasmodium falciparum collected in Thiès, Senegal between 2006 and 2013. The parasite samples were genotyped using a molecular barcode of 24 SNPs. About 35% of the samples grouped into subsets with identical barcodes, varying…
Wesley Wong
Postdoctoral Research Scientist
BIOGRAPHY
Gregory is a Research Scientist in the Epidemiology Group at the Institute for Disease Modeling (IDM). Currently he is working on integrating genetic data into disease transmission modeling. Before coming to IDM he was a postdoc at the Yale School of Medicine where he predicted cancer risk from personal health data. He earned his Ph.D., in Physics, from the University of Illinois at Urbana-Champaign, where he worked on predicting optimal vaccine candidates based on fitness information derived from genetic data.
Gregory Hart
Research Scientist
BIOGRAPHY
Rafael C. Nunez is a Research Scientist on the epidemiology team at IDM. He brings more than 10 years of experience in data fusion, signal processing, machine learning, artificial intelligence, and high-performance computing. He received his Ph.D. in Electrical and Computer Engineering at the University of Miami, his M.Sc. in Electrical and Computer Engineering at the University of Delaware, and his B.Sc. in Electrical Engineering at Universidad Pontificia Bolivariana (Medellin, Colombia). His current research is focused on the development and application of machine learning algorithms for disease transmission models, with emphasis on prediction and model calibration.
Rafael Nunez
Research Scientist
BIOGRAPHY
Navideh Noori was a postdoctoral research associate at the Odum School of Ecology, University of Georgia, Athens, GA, for three years where she worked on developing mathematical and computational models of disease transmission, and application of statistical inference method and transmission models to infectious disease incidence data. Specifically she worked on two projects: 1) understanding the determinants of polio transmission and its large-scale epidemiology using a machine learning algorithm, 2) quantifying the consequences of measles-induced immune suppression for whooping cough epidemiology. She holds a PhD in Forest Hydrology from Auburn University, and a Master of Science in Civil Eng-Water Resource Eng from University of Tehran, Tehran, Iran. During her PhD, she focused on understanding the dynamics interplay between environmental variations and public health concern, namely flooding and infectious diseases (West Nile Virus), by applying a combination of hydrologic and hydraulic modeling, machine learning algorithms, field experiments, laboratory work, and statistical modeling. Navideh is a member of the epidemiology team at IDM where she works on developing an algorithm to identify high-risk pregnancies as well as continuing her work on transmission dynamics of infectious diseases using mathematical, statistical and machine learning models."
PUBLICATIONS (1)
Background Absolute numbers of COVID-19 cases and deaths reported to date in the sub-Saharan Africa (SSA) region have been significantly lower than those across the Americas, Asia, and Europe. As a result, there has been limited information about the demographic and clinical characteristics of deceased cases in the region, as well as the impacts of different case management…
Navideh Noori
Research Scientist
BIOGRAPHY
Monique Ambrose is Research Scientist on the malaria team at IDM. Prior to joining IDM, Monique was a NSF Graduate Research Fellow at the University of California, Los Angeles (UCLA). Her academic research focused on developing and fitting mechanistic models of zoonotic pathogens’ transmission dynamics. These models were used to answer applied questions, such as identifying epidemiological and behavioral shifts that contributed to an increase in human monkeypox incidence and assessing the expected effects of potential interventions in minimizing spillover of swine influenza into humans. Monique has a PhD in Biology from UCLA and a Bachelor’s degree in Biology from the University of California, Santa Barbara.
Monique Ambrose
Sr. Research Scientist
BIOGRAPHY
Roy holds a PhD from the Department of Global Health at the University of Washington. Prior to coming to IDM, Roy worked at the Institute for Health Metrics and Evaluation (IHME), first as a Data Analyst and later as a Researcher while completing his PhD. Roy has worked on a range of quantitative global health projects including: primary data collection from health facilities in four countries, quantifying cause-specific severity distributions of non-fatal health loss for the Global Burden of Disease project, subnational analysis of maternal and child health interventions in Nigeria, development of new methods for child mortality estimation, continent-scale geospatial analysis of child mortality, and spatial analysis of healthcare utilization in Zambia. At IDM, Roy works on modeling health service delivery.
Roy Burstein
Sr. Research Scientist
BIOGRAPHY
Katherine Rosenfeld works on building and analyzing epidemiological models in support of measles control and eradication. Her research focuses on how to effectively couple robust modeling and computation with passive and active intervention strategies. She earned a BS in Astronomy from Yale University and a PhD in Astronomy and Astrophysics from Harvard University.
Katherine Rosenfeld
Research Scientist
BIOGRAPHY
Mollie Van Gordon is a Research Scientist in the Data, Dynamics, and Analytics group at IDM. Mollie earned her Ph.D. at the University of California, Berkeley in the Geography department with a designated emphasis in Computational Science and Engineering. Her research spanned the fields of climate Dynamics, Land Cover Change, Remote Sensing, Machine Learning, Hydrology, and Complex Systems. As part of her graduate work, Mollie created a high-resolution land cover dataset for the West African Sahel based on satellite imaging, hand-classified maps, and machine learning techniques. This dataset, and the tool developed to create it, have since been deployed in West Africa for use as inputs into food security modeling, climate change adaptation planning, national resource management, and international reporting on forests, agriculture, and carbon stores. Her other graduate research, also based in West Africa, included spatial-temporal pattern recognition and analysis of precipitation trends, as well as systems analysis of small-scale watershed hydrology using information theory. Mollie's undergraduate degree from Barnard College of Columbia University includes training in astronomy, physics, women's studies, and international development studies. Her work experience includes women's and environmental advocacy at the United Nations; global water, sanitation, and hygiene development; and consulting for family planning and climate change adaptation efforts in the Sahel. Mollie's research interests include developing data-driven methods with wide-ranging applications; bringing data science methods to data-sparse environments; developing creative solutions to intractable problems; and determining how to ask the right questions.
PUBLICATIONS (1)
Background Absolute numbers of COVID-19 cases and deaths reported to date in the sub-Saharan Africa (SSA) region have been significantly lower than those across the Americas, Asia, and Europe. As a result, there has been limited information about the demographic and clinical characteristics of deceased cases in the region, as well as the impacts of different case management…
Mollie Van Gordon
Research Scientist
BIOGRAPHY
Jessica Ribado is a postdoctoral research scientist on the Data, Dynamics, and Analytics team. She is interested in integrating genomic data into disease transmission models. Prior to joining IDM, her doctoral research focused on understanding the effects of gut microbiome interventions in humans and mice. She used a variety of sequencing technologies (amplicon, shotgun whole genome, nanopore) to evaluate bacterial community differences between interventions and to complete genomes of novel organisms. Jessica earned her Ph.D. in Genetics at Stanford University and holds B.S. degrees in Statistics and Biological Science from Florida State University.
Jessica Ribado
Research Scientist
BIOGRAPHY
Cliff is a Senior Research Scientist on the Applied Math team, working on topics including optimization algorithm development, modeling of family planning interventions, and value-of-information analyses. He has a B.S. in neuroscience from the University of Queensland, a Ph.D. in theoretical physics from the University of Sydney, and a Diploma of Arts from the Sydney Conservatorium of Music. His postdoctoral work, as part of a DARPA project at the SUNY Downstate Medical Center, looked at how detailed computer simulations of a monkey brain could be used to make robotic arms to pick up balls. With funding from the Australian Research Council, he extended this work in his own lab at the University of Sydney, exploring the neural basis of computation. Simultaneously, he was a co-founder, director, and the head of software for the Optima Consortium for Decision Science, a nonprofit consultancy that has helped more than 50 countries plan health investment decisions using the Optima suite of tools. In addition to his work in neuroscience and public health, he has worked internationally as both a pianist and composer, with performances in Sydney, New York, London, and Lithuania.
Cliff Kerr
Sr. Research Scientist
BIOGRAPHY
Charles Eliot received a B.Sc. degree in Chemistry from MIT, then studied at Oxford University on a Rhodes Scholarship. Charles worked at Microsoft for almost 25 years in a variety of engineering management roles, including Head of Engineering Services for Skype. Charles leads IDM's Software Engineering organization, providing world-class software tools and services to support our contributions to eradicating infectious disease.
Charles Eliot
Deputy Director, Software
BIOGRAPHY
Lauren is a software developer at IDM. Since 2014, she has done nearly everything you can imagine in the software development life cycle: system architecture design, DevOps, database administration, middleware services, front-end development, project management, testing, and more. These days she is focused on translating researcher workflows into intuitive user interfaces. When not trying to optimize and automate everything under the sun, she is focusing on her creative writing or learning a new skill.
Lauren George
Software Engineer
BIOGRAPHY
Dan Goes has a Bachelor of Science (B.S.) from Colorado State University in Fort Collins, Colorado, and majored in Computer Science and Applied Computing Technology (Human Factors). Prior to working at IDM, Dan worked as an Avionics Software Engineer for Blue Origin, where he developed, tested, and integrated embedded software for the New Shepard launch vehicle and the BE-3 and BE-4 engines. Dan also previously worked at the Southwest Research Institute on embedded automotive security and space systems software. As a member of the IDM software team, Dan's primary focus is on developing EMOD software.
Dan Goes
Software Program Manager
BIOGRAPHY
Ali has a strong educational background in Systems Architecture including a Bachelor’s of Science Degree in Information Technology from the University of Maryland. Ali performed duties at various roles within the Information Technology industry throughout his professional career, including roles as a Systems Engineer for Department of Defense in Hawaii, A Systems Architect role for Lockheed Martin, and a Systems Engineer for Microsoft. With a handful of accompanying I.T. certificates, Ali also has an Associate Degree in Network Administration. As a member of the software team, Ali will be focusing on Automation and deployments of our Enterprise Linux solutions.
Ali Khalidy
IT Systems Engineer
BIOGRAPHY
Sharon Chen works the web services test team at IDM responsible for the test, validation and quality control of web service components and systems. Sharon has a Master of Engineering in Computer Science from Portland State University and Electric Engineer from Beijing JiaoTong University, China. Sharon earned Bachelor degree of Electric Engineer from Northern China Electric Power University, China. Sharon has been working in IT since 1998. Most of these years are quality assurance engineer and SDET, early few years were also software engineer. Previously, she worked at Cision with platform team responsible for testing large data collection and searching/indexing services. Prior to that, Sharon worked at few different software companies and testing from backend to front end to mobile device. Outside of work, Sharon likes to go to gym as much as possible.
Sharon Chen
Software Test Engineer
BIOGRAPHY
Meikang has a Master degree in Computer Science from the University of Houston, she started her career as a programmer in the oil and gas industry and grew interest in the fields of software test automation. She has worked as an SDET for five years in Microsoft SQL Server team and later on joined several startups focusing on building test infrastructure and continuous integration system. Her role in IDM focuses on the Data Services, she builds automation for testing the data pipeline and uses innovative ways to discover data issues.
Meikang Wu
Software Test Engineer
BIOGRAPHY
Dina Mistry is a Post Doctoral Research Scientist in the Epidemiology team at IDM. Dina has a Ph.D. in Physics and M.Sc. in Physics from Northeastern University. Dina also holds an Hon. B.Sc. in Astronomy, Physics, and Mathematics from the University of Toronto, Canada. Her doctoral research aimed at characterizing and modeling the social contact networks and mobility networks involved in the spread of airborne infectious diseases. Her research at IDM builds on this expertise by focusing on modeling human response to disease awareness and the impact this has on disease spreading using interdisciplinary approaches from Physics, Network Science, and Cognitive Psychology. Her interests include using digital signals of health information and communication (such as Google, Twitter, Reddit) to model disease awareness and response, as well as developing more general methods of network comparison and measurement.
Dina Mistry
Postdoctoral Research Scientist
BIOGRAPHY
Amanda Orcutt is an Administrative Assistant for IDM, having held a similar position at a Fortune 200 company in Manhattan, NYC. Amanda earned two Bachelor of Arts degrees in Women's and Gender Studies and Psychology from Pace University in NYC. After graduation, Amanda planned to spend the summer volunteering with an NGO in Uganda working with elementary school children at two schools. She was asked to extend her volunteer service, and spent the next year teaching health, hygiene and elementary classes. She also developed curriculums and teaching models, so that this teaching could continue with local teachers. Amanda has traveled back to Uganda several times to visit the 10 children she met there and is putting through school. Amanda grew up in North Bend, WA, and her passion for the Pacific Northwest keeps bringing her back! She loves almost every outdoor activity, and spends as much of her free time as possible hiking, camping, backpacking and skiing.
Amanda Orcutt
Administrative Assistant
BIOGRAPHY
Jason has a Bachelor's of Science Degree in Electrical Engineering from Washington State University with a minor in Mathematics and emphasis in Computer Science. Jason has served in many capacities in the IT field from service desk for the Federal Aviation Administration to systems architect at Microsft. In addition to his 11+ years in IT, he programmed LiDAR instruments at Pacific Northwest National Labs and was an accounting manager for Red Lion Hotels. He is excited to bring his broad experience to IDMod and eager to further expand his knowledge and skillset here.
Jason Ford
IT Systems Engineer
BIOGRAPHY
Kate worked for the Malaria Atlas Project (MAP) at the University of Oxford from 2010 to 2020, with whom she completed her DPhil in 2015. Kate obtained her BA in Secondary Education and Biology from Boston College in 2002. She spent six years teaching in the Chicago area where she received an MA in Teaching from Roosevelt University. In 2008, Kate transitioned to public health research through an MSc in the Control of Infectious Diseases at the London School of Hygiene and Tropical Medicine. Following field entomology work in the Kenyan highlands, Kate joined MAP. For her doctoral work, Kate focused on the spatial epidemiology and burden estimation of Plasmodium vivax malaria. As a postdoc and then the Director of Malaria Mapping for Elimination at MAP, Kate worked closely with the Clinton Health Access Initiative (CHAI) and other partners to provide technical support for control and elimination planning. Kate’s main interest is increasing the accessibility and utility of modelled outputs to malaria control programs.
Katherine Battle
Sr. Research Scientist
BIOGRAPHY
Natalia Corona is currently the Research Program Manager at the Institute for Disease Modeling, supporting research teams across Global Health and Global Development. Prior to joining IDM, Natalia worked as a senior quality engineer, project lead, and quality manager in the medical devices industry. She also volunteered with the Greater Austin chapter of Engineers Without Borders-USA as the Director of Projects, leading teams in developing water storage, distribution, and sanitation solutions in LMICs. Most recently, Natalia supported projects and initiatives at the IV Lab. Natalia holds a B.S. in Biomedical Engineering from the University of Texas at Austin.
Natalia Corona
Research Program Manager

BIOGRAPHY
Jamie Cohen is a Research Scientist at IDM. Jamie has a Ph.D. in Health Policy from Harvard University, with a concentration in Decision Sciences, and a Master of Science in Health Policy and Management from the Harvard T.H. Chan School of Public Health. As a doctoral candidate, Jamie developed a novel microsimulation model of HIV, HPV and cervical disease among women in South Africa. This model was used to evaluate cervical cancer screening and vaccination strategies in an HIV-endemic setting. As a member of the IDM research team, Jamie will use her background in mathematical modeling and applied health policy analysis to support the development, calibration, and application of IDM’s numerous disease models.
Jamie Cohen
Research Scientist

BIOGRAPHY
Shirley Leung has a Ph.D. in physical oceanography and an M.S. in environmental engineering from the University of Washington. Her PhD work focused on modeling how climate variability and change affect ocean ecosystems and the people dependent on them. She has also analyzed hydrologic model output at the United States Geological Survey and traffic patterns with the Washington State Transportation Center. As part of the malaria team at IDM, Shirley seeks to evaluate and refine models of mosquito gene drives for malaria elimination.
Shirley Leung
Postdoctoral Research Scientist

BIOGRAPHY
Greer Fowler has a Masters Degree in Health Administration from the University of Washington. She has a Bachelors Degree in Studio Art with an emphasis on painting and drawing from Whitman College. Greer has always enjoyed working to benefit the greater good. Prior to IDM she worked in healthcare with roles in program management, administration and process improvement. At IDM she supports project management and coordination for the Research team. In her spare time, Greer enjoys travel, art, and thrives on being active in the great outdoors.
Greer Fowler
Sr. Project Coordinator

BIOGRAPHY
Carrie Bennette is a senior research scientist at IDM and affiliate faculty in the CHOICE Institute at the University of Washington. Carrie has a masters in public health from Columbia University and a PhD in health economics from the University of Washington. Carrie spent a decade in academia studying strategies to accelerate clinical research and improve outcomes for cancer patients before being recruited to join Flatiron Health, a start up curating and analyzing electronic health records. Carrie spent 3 years at Flatiron, most recently as the scientific director of the machine learning team where she led efforts to derive meaning from millions of patients’ electronic health records using natural language processing techniques. At IDM, Carrie’s research is focused on statistical modeling and data analysis to support polio eradication efforts.
Carrie Bennette
Sr. Research Scientist

BIOGRAPHY
Josh Herbeck is a Senior Research Scientist at the Institute for Disease Modeling (IDM) in Seattle, WA. He is also an Assistant Professor in the Department of Global Health at the University of Washington. He has a BS in Biology from Tufts University, and a PhD from the University of California, Berkeley, where he focused on the molecular evolution of mitochondrial genes. At IDM, he uses mathematical modeling and phylogenetics to study infectious disease transmission and surveillance. Right now he is mostly focused on HIV evolution and epidemiology and is interested in the capacity of HIV to evolve in response to vaccines or broadly neutralizing antibodies, and in the use of phylogenetic data to understand patterns of transmission.
Joshua Herbeck
Sr. Research Scientist