Forecasting the Spread of SARS-CoV-2 is inherently Ambiguous given the Current State of Virus Research

Since the onset of the COVID-19 pandemic many researchers and health advisory institutions have focused on virus spread prediction through epidemiological models. Such models rely on virus- and disease characteristics of which most are uncertain or even unknown. This study addressed the validity of various assumptions using an epidemiological simulation model. We showed that multiple scenarios all lead to realistic numbers of deaths and ICU admissions, two observable and verifiable metrics, but gave different estimates for the number of infected and immune individuals. As these metrics are particularly important for policy makers, further research on virus and disease progression characteristics is essential. Until that time, epidemiological modeling studies cannot give conclusive results and should come with careful analysis of several scenarios on virus- and
disease characteristics.