Modelling the effectiveness of intervention strategies to control COVID-19 outbreaks and estimating healthcare demand in Germany

Abstract

Objectives: An outbreak of the novel coronavirus in December 2019 caused a worldwide pandemic. This disease also impacts European countries, including Germany. Without effective medicines or vaccines, non-pharmaceutical interventions are the best strategy to reduce the number of cases. Study design: A deterministic model was simulated to evaluate the number of infectious and healthcare demand. Method: Using an age-structured SEIR model for the COVID-19 transmission, we project the COVID-19–associated demand for hospital and ICU beds within Germany. We estimated the effectiveness of different control measures, including active case-finding and quarantining of asymptomatic persons, self-isolation of people who had contact with an infectious person, and physical distancing, as well as a combination of these control measures. Results: We found that contact tracing could reduce the peak of ICU beds as well as mass testing. The time delay between diagnosis and self-isolation influences the control measures. Physical distancing to limit the contact rate would delay the peak of the outbreak, which results in the demand for ICU beds being below the capacity during the early outbreak. Conclusions: Our study analyzed several scenarios in order to provide policymakers that face the pandemic of COVID-19 with insights into the different measures available. We highlight that the individuals who have had contact with a virus-positive person must be quarantined as soon as possible to reduce contact with possible infectious cases and to reduce transmission. Keeping physical distance and having fewer contacts should be implemented to prevent overwhelming ICU demand.