SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities

(2020) SARS-CoV-2 non-pharmaceutical interventions in Brazilian municipalities. DRYAD doi:10.5061/dryad.vdncjsxs2 [Dataset]

Abstract

Information on local NPI policies related to COVID-19 were collected through a phone-based survey conducted directly with mayors, with an option to receive a protected password to respond to the questionnaire online at a later time or to update previous answers. We focused on information that has a direct impact on the mobility of residents; that was associated with a specific date of implementation; and that, as policies, are of public domain but were not yet tabled together. We collected information on policies adapting a classification system that included: (1) adoption of cordon sanitaire, (2) prohibition of agglomeration, (3) closure of all but essential services, and (4) compulsory use of face covers, (5) reduction in public transportation offer and if so, what was the percentage of the reduction, and (6) if there was already any easing of the above distancing measures. For all questions there was a side column asking when the action was adopted, and that field was populated in the format DD/MM/YYYY. In order to collect these data, we started a collaboration with the Brazilian Confederation of Municipalities (CNM). This cooperation was established through a meeting followed by a written agreement signed by the first and last authors of this paper with CNM on April 9, 2020. The authors were allowed to describe, deposit and analyse the dataset. The public availability of these data also extends to other scholars the right to analyse the data. CNM has a call centre and as the largest municipal association in Brazil, they possess the email and telephone number of all Brazilian elected mayors. The capillarity of that organisation makes it an ideal partner for such large-scale data collection. The partnership was established because of the need to understand the impact of decentralized measures in Brazil and what decentralisation causes to the spread of infectious diseases. Upon the establishment of this collaboration, CNM designed further questions to the questionnaire that are of interest to their monitoring of municipalities, such as budgetary information possibly affected by the pandemic. In total, the questionnaire had 47 questions; our database has 5 columns related to the identification of the municipality and 13 of the 47 questions that were part of our collaboration to document NPI policy strategies. The 13 questions that form this dataset (6 thematic questions with respective 6 dates of implementation and 1 question pertaining to percentage) were discussed through coordinated orientation.,Brazil has one of the fastest-growing COVID-19 epidemics worldwide. Non-pharmaceutical interventions (NPIs) have been adopted on a municipal level, with asynchronous actions taken across 5,568 municipalities and the Federal District. This paper addresses this complexity reporting on a novel dataset with survey responses from 4,027 mayors, 72.3% of the total municipalities in the country. This dataset responds to the urgency to track and share findings on fragmented policies to tackle health crises like the COVID-19 pandemic. Quantifying NPIs can allow for understanding the effectiveness of interventions in reducing transmission. We offer temporal details for a range of measures aimed at generating social distancing as well as when local governments started to relax those measures.,Because not all municipal authorities answered to all questions, we suggest users to consider additional sources of information to document missing policy implementation using preferably official source of information such as local decrees. However, as decrees are not always available online, secondary sources such as media reports may need to be consulted. As the pandemic progresses and as Brazil is a highly affected country, we invite researchers to use the data to best understand the pandemic and support health policymakers in their efforts.

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Contributors

Contributor: Chieh-Hsi Wu

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