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

Author

Listed:
  • Rafael De Freitas Souza
  • Luiz Paulo Fávero
  • Michel Ferreira Cardia Haddad
  • Hamilton Luiz Corrêa

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.

Suggested Citation

  • Rafael De Freitas Souza & Luiz Paulo Fávero & Michel Ferreira Cardia Haddad & Hamilton Luiz Corrêa, 2022. "Multilevel evidence on how policymakers may reduce avoidable deaths due to COVID-19: the case of Brazil," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 21(3), pages 321-337.
    • Handle: RePEc:ids:ijmore:v:21:y:2022:i:3:p:321-337
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