Human mobility and poverty as key drivers of COVID-19 transmission and control
AbstractBackgroundApplying heavy nationwide restrictions is a powerful method to curtail COVID-19 transmission but poses a significant humanitarian and economic crisis. Thus, it is essential to improve our understanding of COVID-19 transmission and develop more focused and effective strategies. As human mobility drives transmission, data from cell phone devices can be utilized to achieve these goals.MethodsWe analyzed aggregated and anonymized mobility data from the cell-phone devices of>3 million users between February 1, 2020, to May 16, 2020 – in which several movement restrictions were applied and lifted in Israel. We integrated these mobility patterns into age-, risk- and region-structured transmission model. Calibrated to coronavirus incidence in 250 regions covering Israel, we evaluated the efficacy and effectiveness in decreasing mortality of applying localized and temporal lockdowns (stay-at-home order).ResultsPoorer regions exhibited lower and slower compliance with the restrictions. Our transmission model further indicated that individuals from poverty areas were associated with high transmission rates. Model projections suggested that, counterintuitively, school closure has an adverse effect and increases COVID-19 mortality in the long run, while interventions focusing on the elderly are the most efficient. We also found that applying localized and temporal lockdowns during regional outbreaks reduce mortality compared to nationwide lockdowns. These trends were consistent across vast ranges of epidemiological parameters, possible seasonal forcing, and even when we assumed that vaccination would be commercially available in 1-3 years.ConclusionsMore resources should be devoted to helping impoverished regions. Utilizing cellphone data despite being anonymized and aggregated can help policymakers worldwide identify hotspots and apply designated strategies against future COVID-19 outbreaks.