|"(...) We model the evolution of the number of individuals that are reported to be sick with COVID-19 in
Germany. Our theoretical framework builds on a continuous time Markov chain with four states: healthy without
infection, sick, healthy after recovery or after infection but without symptoms and dead. Our quantitative
solution matches the number of sick individuals up to the most recent observation and ends with a share of sick
individuals following from infection rates and sickness probabilities. We employ this framework to study inter alia
the expected peak of the number of sick individuals in a scenario without public regulation of social contacts. We
also study the effects of public regulations. For all scenarios we report the expected end of the CoV-2 epidemic.
[Corona, COVID-19, SARS-CoV-2, spread of infection, Markov model, Germany, projection]