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Municipios in the Time of Covid-19 in Brazil: Socioeconomic Vulnerabilities, Transmission Factors and Public Policies.

ABSTRACT: This paper aims at identifying the Covid-19 infection and mortality risk factors in Brazil during the pandemic's first wave. Three groups of variables are considered: socioeconomic and health vulnerabilities, factors related to the virus transmission channels (mobility and density) and the effects of the policy responses. The analysis at the level of all 5,570 municipalities, drawing on a matching of different statistical and administrative databases, returns three main results. First, structurally vulnerable populations are hardest hit-non-white, poor, in poor health, favela residents and informal workers-showing the impact of socioeconomic inequalities. Second, we highlight some policy repercussions. The Auxilio Emergencial (emergency cash transfer) has had a mitigating effect in communities with relatively more informal workers. Finally, Covid-19 has hit hardest in municipalities that are more pro-Bolsonaro. The president's rhetoric and attitudes may have prompted his supporters to adopt more risky behaviour, suffer the consequences and infect others.

Supplementary information

The online version contains supplementary material available at 10.1057/s41287-021-00487-w.

SUBMITTER: Razafindrakoto M

PROVIDER: S-EPMC8582239 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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<i>Municípios</i> in the Time of Covid-19 in Brazil: Socioeconomic Vulnerabilities, Transmission Factors and Public Policies.

Razafindrakoto Mireille M Roubaud François F Saboia João J Castilho Marta Reis MR Pero Valeria V

The European journal of development research 20211111 6

This paper aims at identifying the Covid-19 infection and mortality risk factors in Brazil during the pandemic's first wave. Three groups of variables are considered: socioeconomic and health vulnerabilities, factors related to the virus transmission channels (mobility and density) and the effects of the policy responses. The analysis at the level of all 5,570 municipalities, drawing on a matching of different statistical and administrative databases, returns three main results. First, structura ...[more]

PMID: 34785867

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