Mobility- and behavior-based early-warning system after the first wave of COVID-19

This project aims to develop a mobility- and behavior-based early-warning system after the first wave of COVID-19 in the Netherlands. In the current phase of the outbreak in Europe, local lockdowns have become part of the containment policies in several countries, including Spain and Germany and are discussed in the Netherlands (RTL Nieuws, 14-07-2020). We will investigate whether, how and under what conditions these measures could be effective and feasible. - We use the information on syndrome and behavior surveillance and mobility, already available to us. - We enable regional decision-making by creating decision support tools in the form of dashboards, complementary to those by the Ministry of Health, and investigate the policy response. - While testing implies inevitable delays, our approach enables quick action because we can observe high-risk behavior almost instantaneously, and we predict the progression of the disease spread. HYPOTHESIS Information on mobility with real-time information on symptoms and risky behavior, combined in a mathematical model, can enable an effective regional early-warning system and decision support tools for policy response in containment of COVID-19 after the first wave. The consortium has expertise in mathematical models for spreading processes (TU/e), epidemiology (UU, LUMC), behavioral sciences (LUMC), data analytics (Mezuro, Ilionx),and governance (UT). We use the mobility information available at Mezuro and the syndrome and behaviour surveillance data from the COVID Radar app by the LUMC. The project consists of three work packages (WPs): WP 1 optimizes the COVID Radar app and integrates its data with the Mezuro mobility data. WP2 develops mathematical epidemiological models that quantify and predict the spread of Covid-19 in the Netherlands. WP 3 delivers an early-warning decision support system in the form of dashboards and investigates the policy response.