Heterogeneous interventions reduce the spread of COVID-19 in simulations on real mobility data

Abstract Major interventions have been introduced worldwide to slow down the spread of SARS-CoV-2 virus. Large scale lockdown human movements are effective in reducing spread, but they come at a cost significantly limited societal functions. We show that natural statistically diverse, and disease is influenced by small group active individuals gathering venues. find focused on these most mobile popular venues reduce both peak infection rate total infected population while retaining high social activity levels. These trends seen consistently simulations with real mobility data different scales, resolutions, modalities from multiple cities across world. The observation implies compared broad sweeping interventions, more heterogeneous strategies targeted based network effects provide better balance between pandemic control regular activities.