  Motivation: 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 COVID19 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 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) and mitigation
measures.
  Results: Using Switzerland as a case study, COVIDHunter estimates that the
policy-makers need to keep the current mitigation measures for at least 30 days
to prevent demand from quickly exceeding existing hospital capacity. Relaxing
the mitigation measures by 50% for 30 days increases both the daily capacity
need for hospital beds and daily number of deaths exponentially by an average
of 23.8x, who may occupy ICU beds and ventilators for a period of time. 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.
  Availability: https://github.com/CMU-SAFARI/COVIDHunter
