Infectious diseases remain among the greatest threats to human health. Novel epidemics occur with increasing frequency as ease of travel facilitates spread, and environmental changes alter underlying dynamics in unpredictable ways. At the same time, vaccines are increasingly controlling many major human pathogens. Yet, the potential of these advances can only be fully realized with a means to accurately measure and quantify the landscape of infectious diseases across many pathogens and scales, from the individual to the global population, and encompassing interactions and potential unintended consequences across related or unrelated pathogens. The overall objectives are to bridge novel developments in molecular biology and computational tools to fundamentally improve infectious disease surveillance and research. Aim 1 will build on a previously reported phage display system, and optimize it for infectious disease surveillance. PADERNS (Phage display for Antibody repertoire Detection and profiling via pathogen Epitope RecognitioN for infectious disease and public health Surveillance) will: enable serological surveillance for exposures to all human pathogens, including bacteria, parasites and mosquitos vectors, simultaneously, from accessible samples, i.e. saliva and dried blood spots; will discriminate exposures from closely related pathogens (i.e. Zika and Dengue) and estimate time since infection or vaccination. Importantly, it will be optimized for use in low resource settings and at a fraction of the cost of current technologies. Aim 2 will improve epidemic detection with development of Epi-TRACER (Epitope based TRacking of Anonymous samples via Comprehensive Epitope Recogntion). Epi-TRACER will use PADERNS repertoires from (1) to extract and construct epidemiologically powerful virtual longitudinal cohorts from cross-sectional sample sets that contain hidden serial samples (i.e. 80% of the US blood supply comes from repeat donors). Because Epi-TRACER runs on PADERNS data, it will simultaneously enable reconstruction of past, and early detection of current epidemics. Aim 3 will elucidate the life-histories of pathogen exposures across ages (pre-birth to elderly), time, genders and geographies to: quantify in unprecedented detail pathogen attack rates, heterologous effects of vaccines on off-target pathogens, and measure the longevity and waning of antibodies, including maternally derived antibodies, to improving vaccination and control strategies. These aims will be accomplished through a multi-disciplinary approach involving molecular biology and phage-display systems, robust longitudinal sample curation through collaborations, and, crucially, careful development of mathematical and statistical models to link the biology to individual and population level inference. Once complete, the tools, methods and data will be available to public health agencies and infectious disease researchers, opening the way to a step change in detection or control of existing and novel pathogens.