Ferreira Cláudia P, Marcondes Diego, Melo Mariana P, Oliva Sérgio M, Peixoto Cláudia M, Peixoto Pedro S
Institute of Biosciences, São Paulo State University (UNESP), Botucatu 18618-689, Brazil.
Department of Applied Mathematics, Institute of Mathematics and Statistics, University of São Paulo, São Paulo 05508-090, Brazil.
Patterns (N Y). 2021 Oct 8;2(10):100349. doi: 10.1016/j.patter.2021.100349. Epub 2021 Sep 15.
In response to the coronavirus pandemic, governments implemented social distancing, attempting to block the virus spread within territories. While it is well accepted that social isolation plays a role in epidemic control, the precise connections between mobility data indicators and epidemic dynamics are still a challenge. In this work, we investigate the dependency between a social isolation index and epidemiological metrics for several Brazilian cities. Classic statistical methods are employed to support the findings. As a first, initially surprising, result, we illustrate how there seems to be no apparent functional relationship between social isolation data and later effects on disease incidence. However, further investigations identified two regimes of successful employment of social isolation: as a preventive measure or as a remedy, albeit remedy measures require greater social isolation and bring higher burden to health systems. Additionally, we exhibit cases of successful strategies involving lockdowns and an indicator-based mobility restriction plan.
为应对新冠疫情，各国政府实施了社交距离措施，试图阻止病毒在各地区内传播。虽然人们普遍认为社会隔离在疫情防控中发挥着作用，但移动数据指标与疫情动态之间的精确联系仍是一个挑战。在这项工作中，我们研究了巴西几个城市的社会隔离指数与流行病学指标之间的相关性。采用经典统计方法来支持研究结果。作为第一个起初令人惊讶的结果，我们说明了社会隔离数据与对疾病发病率的后续影响之间似乎没有明显的函数关系。然而，进一步调查发现了成功实施社会隔离的两种模式：作为预防措施或作为补救措施，尽管补救措施需要更大程度的社会隔离并给卫生系统带来更高负担。此外，我们展示了涉及封锁和基于指标的流动限制计划的成功策略案例。
