Computational Science Research

  • Modeling methodology

    Mathematical models are invaluable for exploring the dynamics of infectious diseases, health delivery systems, intervention strategies, and other public health concerns. With technological advancements and the progression of AI, models are more accessible than ever before. However, it can be difficult to balance model selection, performance, and usability. IDM’s modeling methodology teams are working to…

  • Using phylogenetic summary statistics for epidemiological inference

    Since the coining of the term phylodynamics, the use of phylogenies to understand infectious disease dynamics has steadily increased. As methods for phylodynamics and genomic epidemiology have proliferated and grown more computationally expensive, the epidemiological information they extract has also evolved to better complement what can be learned through traditional epidemiological data. However, for genomic…

  • Sciris: Simplifying scientific software in Python

    Sciris aims to streamline the development of scientific software by making it easier to perform common tasks. Sciris provides classes and functions that simplify access to frequently used low-level functionality in the core libraries of the scientific Python ecosystem (such as numpy for math and matplotlib for plotting), as well as in libraries of broader…

  • Insights into population behavior during the COVID-19 pandemic from cell phone mobility data and manifold learning

    Understanding the complex interplay between human behavior, disease transmission and non-pharmaceutical interventions during the COVID-19 pandemic could provide valuable insights with which to focus future public health efforts. Cell phone mobility data offer a modern measurement instrument to investigate human mobility and behavior at an unprecedented scale. We investigate aggregated and anonymized mobility data, which…

  • Augmented state feedback for improving observability of linear systems with nonlinear measurements

    This paper is concerned with the design of an augmented state feedback controller for finite-dimensional linear systems with nonlinear observation dynamics. Most of the theoretical results in the area of (optimal) feedback design are based on the assumption that the state is available for measurement. In this paper, we focus on finding a feedback control…

  • Estimating spatiotemporally varying malaria reproduction numbers in a near elimination setting

    In 2016 the World Health Organization identified 21 countries that could eliminate malaria by 2020. Monitoring progress towards this goal requires tracking ongoing transmission. Here we develop methods that estimate individual reproduction numbers and their variation through time and space. Individual reproduction numbers, Rc, describe the state of transmission at a point in time and…

  • Linear Model Regression on Time-series Data: Non-asymptotic Error Bounds and Applications

    Data-driven methods for modeling dynamic systems have recently received considerable attention as they provide a mechanism for control synthesis directly from the observed time-series data. In the absence of prior assumptions on how the time-series had been generated, regression on the system model has been particularly popular. In the linear case, the resulting least squares…

  • Data-Driven Method for Efficient Characterization of Rare Event Probabilities in Biochemical Systems

    As mathematical models and computational tools become more sophisticated and powerful to accurately depict system dynamics, numerical methods that were previously considered computationally impractical started being utilized for large-scale simulations. Methods that characterize a rare event in biochemical systems are part of such phenomenon, as many of them are computationally expensive and require high-performance computing.…

  • Mathematical models of SIR disease spread with combined non-sexual and sexual transmission routes

    The emergence of Zika and Ebola demonstrates the importance of understanding the role of sexual transmission in the spread of diseases with a primarily non-sexual transmission route. In this paper, we develop low-dimensional models for how an SIR disease will spread if it transmits through a sexual contact network and some other transmission mechanism, such…

  • Adaptive communication networks with privacy guarantees

    Utilizing the concept of observability, in conjunction with tools from graph theory and optimization, this paper develops an algorithm for network synthesis with privacy guarantees. In particular, we propose an algorithm for the selection of optimal weights for the communication graph in order to maximize the privacy of nodes in the network, from a control…