  Early detection and isolation of COVID-19 patients are essential for
successful implementation of mitigation strategies and eventually curbing the
disease spread. With a limited number of daily COVID-19 tests performed in
every country, simulating the COVID-19 spread along with the potential effect
of each mitigation strategy currently remains one of the most effective ways in
managing the healthcare system and guiding policy-makers. We introduce
COVIDHunter, a flexible and accurate COVID-19 outbreak simulation model that
evaluates the current mitigation measures that are applied to a region,
predicts COVID-19 statistics (the daily number of cases, hospitalizations, and
deaths), and provides suggestions on what strength the upcoming mitigation
measure should be. The key idea of COVIDHunter is to quantify the spread of
COVID-19 in a geographical region by simulating the average number of new
infections caused by an infected person considering the effect of external
factors, such as environmental conditions (e.g., climate, temperature,
humidity), different variants of concern, vaccination rate, and mitigation
measures. Using Switzerland as a case study, COVIDHunter estimates that we are
experiencing a deadly new wave that will peak on 26 January 2022, which is very
similar in numbers to the wave we had in February 2020. The policy-makers have
only one choice that is to increase the strength of the currently applied
mitigation measures for 30 days. Unlike existing models, the COVIDHunter model
accurately monitors and predicts the daily number of cases, hospitalizations,
and deaths due to COVID-19. Our model is flexible to configure and simple to
modify for modeling different scenarios under different environmental
conditions and mitigation measures. We release the source code of the
COVIDHunter implementation at https://github.com/CMU-SAFARI/COVIDHunter.
