Multilevel evidence on how policymakers may reduce avoidable deaths due to COVID-19: the case of Brazil

Rafael De Freitas Souza, Luiz Paulo Fávero, Michel Ferreira Cardia Haddad and Hamilton Luiz Corrêa

International Journal of Mathematics in Operational Research, 2022, vol. 21, issue 3, 321-337

Abstract: We propose a hierarchical linear method to investigate the effectiveness of social distancing measures. By considering the COVID-19 data as a two-level structure, we are able to demonstrate a significant reduction of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases as a direct consequence of lockdown measures adopted by some states in Brazil. The multilevel modelling is the most appropriate method for the case of Brazil due to the fact that political battles between federal and State government leaders have led to the adoption of lockdown measures with distinct levels of flexibility adopted by each of its 27 states. During the outbreak of such a novel and highly contagious disease, decisions made by policymakers either prevent or increase the number of avoidable deaths. Thus, our results are also potentially useful to convince policymakers to adopt reasonable policy measures to shorten the COVID-19 pandemic in the biggest Latin American country.

Keywords: COVID-19; emerging countries; lockdown; multilevel modelling; SARS-CoV-2. (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=122218 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijmore:v:21:y:2022:i:3:p:321-337

Access Statistics for this article

More articles in International Journal of Mathematics in Operational Research from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().