Evaluating Social Distancing Measures and Their Association with the Covid-19 Pandemic in South America

Abstract

Social distancing is a powerful non-pharmaceutical intervention used as a way to slow the spread of the SARS-CoV-2 virus around the world since the end of 2019 in China. Taking that into account, this work aimed to identify variations on population mobility in South America during the pandemic (15 February to 27 October 2020). We used a data-driven approach to create a community mobility index from the Google Covid-19 Community Mobility and relate it to the Covid stringency index from Oxford Covid-19 Government Response Tracker (OxCGRT). Two hypotheses were established: countries which have adopted stricter social distancing measures have also a lower level of circulation (H1), and mobility is occurring randomly in space (H2). Considering a transient period, a low capacity of governments to respond to the pandemic with more stringent measures of social distancing was observed at the beginning of the crisis. In turn, considering a steady-state period, the results showed an inverse relationship between the Covid stringency index and the community mobility index for at least three countries (H1 rejected). Regarding the spatial analysis, global and local Moran indices revealed regional mobility patterns for Argentina, Brazil, and Chile (H1 rejected). In Brazil, the absence of coordinated policies between the federal government and states regarding social distancing may have played an important role for several and extensive clusters formation. On the other hand, the results for Argentina and Chile could be signals for the difficulties of governments in keeping their population under control, and for long periods, even under stricter decrees.

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Hierarchical Model of Multi-level Index to Assess Local Resilience Capability in COVID-19

“…It mainly focuses on policy making, rather than the implementation of policy. For example, indicators affecting policy execution (i.e., the public acceptance and the reaction of policies) are not taken into consideration in this tool [24][25][26][27].…”

The influencing factors of health–related quality of life of the general population of Iran during the COVID-19 Pandemic

“…In January 2022, the number of confirmed cases of COVID-19 was over 6,373,174, and the number of deaths from COVID-19 was more than 132,454 ( 2 ). Around the world, a variety of strong social distancing measures have been implemented to slow the growth rate of COVID-19 cases (e.g., in Wuhan and other Chinese cities ( 3 , 4 ), across European countries ( 5 ), French regions ( 6 ), or some U.S. states ( 7 , 8 ).…”