Critical events as drivers of infectious diseases : synthetic control analyses of elections and natural disasters

Abstract

This thesis examines how critical events — elections and natural disasters — affect the spread of respiratory diseases, focusing on COVID-19 and other infections. Using German district-level data and the Synthetic Control Method, three essays analyze (1) Bavaria's 2020 election, (2) regional elections outside pandemic periods, and (3) the 2021 flood in Western Germany. Results show that both elections and disasters can increase infection rates, depending on timing and context. The findings highlight the need for tailored mitigation strategies during essential events to protect public health while preserving societal functions.