Country-specific optimization of testing rates and unlock measures can help to contain COVID19 infection

In response to the COVID19 outbreak many countries have implemented lockdown to ensure social distancing. However, long lockdowns globally affected the livelihood of millions of people resulting in subsequent unlocks that started a second wave of infection in multiple countries. Unlocking of the economies critically imposes extra burden on testing and quarantine of the infected people to keep the reproduction number ( R 0 ) <1. This, as we demonstrate, requires optimizing a cost-benefit trade-off between testing rate and unlock extent. We delineate a strategy to optimize the trade-off by utilizing a data-trained epidemic model and coupling it with a stochastic agent based model to implement contact tracing. In a country specific manner, we quantitatively demonstrate how combination of unlock and testing can maintain R 0 <1.