Systems Epidemiological analysis of the COVID-19 PANdemic accounting for host-virus interaction and human behavior

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The spreading of infectious diseases is a multi-scale and dynamic process which depends on pathogen virulence, host immune responses, and human behavior (e.g. adherence to social distancing). The interplay of these scales is purely understood, and inter-individual variability (biomedical and socio-economical) often disregarded. We will study (1) inter-individual variability of host-virus interaction to SARS-CoV-2 infection and (2) decision making processes of healthy and infected individuals (and their household members) in different economic and social interactions to determine factors relevant for virus transmission versus containment. The project will establish a systems epidemiological approach considering biomedical and (micro-)economic aspects. The Munich-KoCo19 cohort study framework will provide state-of-the-art virologic, immunologic/serologic, host genetic, and clinical characterization data for up to 6000 individuals alongside information about behavior and socio-economic profiles. This comprehensive dataset will be analyzed using statistical and machine learning approaches. Furthermore, we will develop integrative epidemiological-economical models accounting for inter-individual variability, their influence on decision making (e.g. whether individuals stay-at-home or go-to-work depending on incomes, savings or other pre-existing conditions), and ultimately the dynamics of the SARS-CoV-2 epidemic. The integration of the scales will provide novel insights and methods which can be transferred to other infections and future epidemics.