Plenary-02

Marisa Eisenberg

Associate Professor, Departments of Epidemiology, Complex Systems, & Mathematics

University of Michigan, Ann Arbor

Abstract:

Public health decision-making is complex and relies on multiple highly uncertain data sources. Data-driven methods and models are increasingly used to inform public health practice, as they can be used to help integrate these data to generate insights and help inform public health interventions. In this talk, we will explore some examples using models to integrate different data sources to understand spatiotemporal patterns of disease and inform intervention efforts in practice.