Effect of Physical Distancing on Covid-19 Incidence in Brazil: Does the Strictness of Mandatory Rules Matter?

Posted: 2021-09-11 19:00:00
Purpose: This study aims to examine the association between physical distancing measures and COVID-19 incidence among Brazilian states. Methods: We divided the methodology was divided into three steps. In the first step, we used nationwide GPS daily data to estimate country and state-level physical distancing and examined the association with COVID-19 incidence through a GAM model. Secondly, using PNAD COVID 19 data, a cluster analysis categorized the Brazilian states into different categories of physical distancing policies promoting adoption and political inclination of their governments. Finally, through a Poisson Regression Model, we examined the association of state physical distancing with variables related to the socio-economic situation, test coverage and early adoption of policies promoting physical distancing of each state. Results: Physical distancing effects on reduction of COVID-19 spread are heterogeneous among states. Estimation of (IRR) suggests that in a scenario of 100% of social isolation incidence of COVID-19 will have reached approximately only 2.6% of the magnitude compared to when there is no social isolation for Brazil (CI 95% 0.8 - 8.3). Only a 10% increase in SII in the country could have reflected in a 30.5% decrease of number of cases in 14 days. Adoption of physical distancing was associated with test coverage (IRR 0.976, CI 95% 0.973-0.979), Home Office (IRR 1.042, CI 95% 1.039 - 1.046), informal work proportion (IRR 0.961, CI 95% 0.958 - 0.965), political spectrum (IRR 0.961, CI 95% 0.958 - 0.965) and early moment of restrictive politics implementation (IRR 1.017, CI 95% 1.013 - 1.021). Conclusion: Physical distancing measures play a crucial role in mitigating the pandemic's spread. These analyses are crucial to support government decisions and improve the community's adherence to preventive measures. Keywords: Brazil; COVID-19; Incidence; Physical Distancing; Time-Series.

参考サイト PubMed: covid-19

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9月 28, 2020 バイオアソシエイツ


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