In 2020, countries affected by the COVID-19 pandemic implemented various non-pharmaceutical interventions to contrast the spread of the virus and its impact on their healthcare systems and economies. Using Italian data at different geographic scales, we investigate the relationship between human mobility, which subsumes many facets of the population's response to the changing situation, and the spread of COVID-19. Leveraging mobile phone data from February through September 2020, we find a striking relationship between the decrease in mobility flows and the net reproduction number. We find that the time needed to switch off mobility and bring the net reproduction number below the critical threshold of 1 is about one week. Moreover, we observe a strong relationship between the number of days spent above such threshold before the lockdown-induced drop in mobility flows and the total number of infections per 100k inhabitants. Estimating the statistical effect of mobility flows on the net reproduction number over time, we document a 2-week lag positive association, strong in March and April, and weaker but still significant in June. Our study demonstrates the value of big mobility data to monitor the epidemic and inform control interventions during its unfolding.
翻译:2020年,受COVID-19大流行影响的国家实施了各种非药物性干预措施,以对比病毒的传播及其对保健系统和经济的影响。我们利用意大利不同地域范围的数据,调查人口流动与COVID-19大流行扩散之间的关系,这包括人口对不断变化的局势反应的许多方面。 利用2020年2月至9月的移动电话数据,我们发现流动流动量下降与净生殖数量之间有着惊人的关系。我们发现,关闭流动和将净生殖数降到1级临界阈值以下所需的时间大约为一周。此外,我们发现,在固定流动流动流量下降之前超过这一临界值的天数与每100公里居民感染总人数之间存在强烈的关系。我们估计流动流动流动对净生殖数量在统计上的影响,我们记录了两周的滞后积极联系,3月和4月是强劲的,6月是薄弱的,但仍然重要。我们的研究显示,大型流动数据对监测流行病的价值,并在疫情蔓延期间通报控制干预措施。