Taming the pandemic by doing the mundane

We propose a network-based multi-compartment emulator for the COVID-19 pandemic spread by accounting for various epidemiological factors, and different intervention options like lockdown, testing and vaccination. Our model allows migrations across a network of nodes representing different population centers or strata. The focus is on making optimal decisions which, by making a meaningful assessment of the costs due to deaths, lockdowns and the capacity of the healthcare system, minimize the economic impact of the pandemic. Our results suggest that a combination of high rate of testing and rapid vaccination is very effective in bringing the pandemic under control quickly and economically.