Instituto de Fısica, Universidade Federal da Bahia, Salvador, Bahia, Brazil.
Fundação Oswaldo Cruz, Porto Velho, Rondônia, Brazil.
Epidemics. 2021 Jun;35:100465. doi: 10.1016/j.epidem.2021.100465. Epub 2021 May 8.
COVID-19 is now identified in almost all countries in the world, with poorer regions being particularly more disadvantaged to efficiently mitigate the impacts of the pandemic. In the absence of efficient therapeutics or large-scale vaccination, control strategies are currently based on non-pharmaceutical interventions, comprising changes in population behavior and governmental interventions, among which the prohibition of mass gatherings, closure of non-essential establishments, quarantine and movement restrictions. In this work we analyzed the effects of 707 governmental interventions published up to May 22, 2020, and population adherence thereof, on the dynamics of COVID-19 cases across all 27 Brazilian states, with emphasis on state capitals and remaining inland cities. A generalized SEIR (Susceptible, Exposed, Infected and Removed) model with a time-varying transmission rate (TR), that considers transmission by asymptomatic individuals, is presented. We analyze the effect of both the extent of enforced measures across Brazilian states and population movement on the changes in the TR and effective reproduction number. The social mobility reduction index, a measure of population movement, together with the stringency index, adapted to incorporate the degree of restrictions imposed by governmental regulations, were used in conjunction to quantify and compare the effects of varying degrees of policy strictness across Brazilian states. Our results show that population adherence to social distance recommendations plays an important role for the effectiveness of interventions and represents a major challenge to the control of COVID-19 in low- and middle-income countries.
COVID-19 现已在世界上几乎所有国家得到确认,较贫困地区在有效减轻大流行影响方面处于明显劣势。在缺乏有效治疗方法或大规模疫苗接种的情况下,控制策略目前基于非药物干预措施,包括改变人口行为和政府干预措施,其中包括禁止群众集会、关闭非必要场所、隔离和限制流动。在这项工作中,我们分析了截至 2020 年 5 月 22 日发布的 707 项政府干预措施及其对所有 27 个巴西州 COVID-19 病例动态的影响,重点关注州首府和内陆剩余城市。提出了一个具有时变传播率(TR)的广义 SEIR(易感、暴露、感染和清除)模型,该模型考虑了无症状个体的传播。我们分析了巴西各州实施措施的程度和人口流动对 TR 和有效繁殖数变化的影响。社会流动性减少指数,即人口流动的衡量标准,以及严格指数,用于定量和比较巴西各州不同程度政策严格性的影响,该指数经过调整以纳入政府法规规定的限制程度。我们的结果表明,人口对社交距离建议的遵守对干预措施的有效性起着重要作用,并且是中低收入国家控制 COVID-19 的主要挑战。