Understanding the distribution and dynamics of human pathogens is fundamental to control infectious diseases by guiding where and when to target resources. Until now, however, efforts to understand the dynamics of most pathogens have been conducted in isolation, focusing on one specific disease at a time. Over the past years, high throughput multiplexed serological assays have become available, allowing to simultaneously quantify antibody responses against 100s and even 1000s of antigens, from a single sample. These novel technologies offer unprecedented opportunities to (1) study the dynamics of multiple pathogens simultaneously, (2) characterize immune profiles of populations, and (3) evaluate hypotheses around immunological interactions within and between pathogen groups. Numerous methodological and computational challenges remain in terms of how to make meaningful epidemiological inferences from these new tools. We have been developing methods to analyze and estimate key transmission parameters from multiple sources of data, with a focus on serological assays. This proposal will expand these lines of work, developing tools and analytic methods necessary to translate the promise of high throughput serology into mechanistic insights about pathogen dynamics. We will leverage existing collaborations with researchers at the forefront of these technologies, as well as detailed population studies (including longitudinal birth cohorts and cross-sectional studies) that have collected and characterized serum samples to apply and evaluate these platforms in over 10 countries.
We aim to develop and validate a suite of robust computational and analytical pipelines with the goal of (1) reconstructing the longitudinal evolution of antibody repertoires in individuals within and across pathogen groups as a function of infection history, and (2) characterizing transmission histories and immune profiles of populations. In developing our analytical pipelines, we will perform extensive simulation studies to evaluate the performance of different models under multiple assumptions of how the data is generated. We will then perform data analysis and inference to reconstruct transmission histories, susceptibility profiles of populations to multiple pathogens, estimate attack rates, and characterize longitudinal evolution of antibody responses. This will be the most comprehensive assessment, and validation, of population and individual serological responses across pathogen groups, performed to date. Through these projects, we will also develop a suite of open-source software/tools to disseminate our methods and allow other researchers to analyze their data and gain insight into immune landscapes population risk profiles. This project will create tools that use high-throughput multiplexed serological data to answer fundamental questions on the dynamics and interactions of different pathogen groups and provide insights that can be used by policymakers to guide infectious disease control efforts.
Over the past years, high throughput multiplexed serological assays have become available, allowing to simultaneously quantify antibody responses against 100s and even 1000s of antigens, from a single sample. These novel technologies offer unprecedented opportunities to study the dynamics of multiple pathogens simultaneously reconstruct susceptibility profiles of populations and inform control interventions. The central theme of my research program is to develop robust and validated tools and analytic methods necessary to translate the promise of high throughput serology into mechanistic insights about pathogen dynamics.
