Sawant Amit N, Stensrud Mats J
Chair of Biostatistics, Department of Mathematics, Ecole Polytechnique Federale de Lausanne, Switzerland.
Chair of Biostatistics, Department of Mathematics, Ecole Polytechnique Federale de Lausanne, Switzerland.
Epidemics. 2023 Oct 20;45:100722. doi: 10.1016/j.epidem.2023.100722.
During the COVID-19 pandemic, the effects of nationwide lockdowns on health outcomes have been widely studied in Western, developed countries. However, the effects of lockdowns in emerging and developing countries are largely unknown. We used data from India and Bangladesh to study the effect of nationwide restrictions on public movement in Bangladesh in April 2021 on health outcomes, specifically COVID-19 incidence and mortality. India and Bangladesh had nearly identical development of the COVID-19 Delta wave the weeks before the lockdown. We leveraged longitudinal data from the pre- and post-intervention period in both countries in a structural causal model, suggesting that the reported deaths in Bangladesh due to COVID-19 would have been ∼117% higher (95% PI: 72%-170%) in April 2021 had there been fewer restrictions. Further, we used population mobility data from Google to study behavioural changes in the two countries, supporting the hypothesis that the intervention had substantial effects on the mobility trends of the Bangladeshi population, which in turn reduced the number of COVID-19 deaths.
在新冠疫情期间，西方国家对全国性封锁措施对健康结果的影响进行了广泛研究。然而，新兴国家和发展中国家实施封锁的影响在很大程度上尚不清楚。我们利用印度和孟加拉国的数据，研究了2021年4月孟加拉国全国性限制公众流动措施对健康结果的影响，特别是新冠病毒感染率和死亡率。在封锁前的几周，印度和孟加拉国的新冠病毒德尔塔变异株疫情发展情况几乎相同。我们在一个结构因果模型中利用了两国干预前后的纵向数据，结果表明，如果限制措施较少，2021年4月孟加拉国因新冠病毒死亡的人数可能会高出约117%（95%预测区间：72%-170%）。此外，我们使用了谷歌的人口流动数据来研究两国的行为变化，支持了这一假设，即该干预措施对孟加拉国人口的流动趋势产生了重大影响，进而减少了新冠病毒死亡人数。
