Examining socio-economic factors to understand the hospital case fatality rates of COVID-19 in the city of sao Paulo, Brazil

Author(s)

Lorenz, Camila ^[1] ; Moralejo Bermudi, Patricia Marques ^[1] ; de Aguiar, Breno Souza ^[2] ; Failla, Marcelo Antunes ^[3] ; Toporcov, Tatiana Natasha ^[1] ; Chiaravalloti-Neto, Francisco ^[1] ; Barrozo, Ligia Vizeu ^{[4, 5]}

Affiliation

^[1] Univ Sao Paulo, Dept Epidemiol, Fac Saude Publ, Sao Paulo, SP - Brazil

^[2] Secretaria Municipal Saude, Dept Epidemiol DE, Coordenacao Epidemiol & Informacao CEInfo, Sao Paulo, SP - Brazil

^[3] Secretaria Municipal Saude, Nucleo Geoproc & Informacoes Socioambientais GISA, Coordenacao Epidemiol & Informacao CEInfo, Sao Paulo, SP - Brazil

^[4] Univ Sao Paulo, Fac Filosofia Letras & Ciencias Humanas, Dept Geog, Sao Paulo, SP - Brazil

^[5] Univ Sao Paulo, Inst Estudos Avancados, Sao Paulo, SP - Brazil

• Document type: Journal article
• Source: Transactions of the Royal Society of Tropical Medicine and Hygiene; v. 115, n. 11, p. 1282-1287, NOV 2021.
• Web of Science Citations: 0

Abstract

Background: Understanding differences in hospital case fatality rates (HCFRs) of coronavirus disease 2019 (COVID-19) may help evaluate its severity and the capacity of the healthcare system to reduce mortality. Methods: We examined the variability in HCFRs of COVID-19 in relation to spatial inequalities in socio-economic factors, hospital health sector and patient medical condition across the city of Sao Paulo, Brazil. We obtained the standardized hospital case fatality ratio adjusted indirectly by age and sex, which is the ratio between the HCFR of a specific spatial unit and the HCFR for the entire study area. We modelled it using a generalized linear mixed model with spatial random effects in a Bayesian context. Results: We found that HCFRs were higher for men and for individuals >= 60 y of age. Our models identified per capita income as a significant factor that is negatively associated with the HCFRs of COVID-19, even after adjusting for age, sex and presence of risk factors. Conclusions: Spatial analyses of the implementation of these methods and of disparities in COVID-19 outcomes may help in the development of policies for at-risk populations in geographically defined areas. (AU)

• FAPESP's process: 17/10297-1 - Identification of risk areas for arboviruses using traps for adults of Aedes aegypti and Aedes albopictus and remote sensing images
• Grantee: Camila Lorenz
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• FAPESP's process: 20/12371-7 - Spatio-temporal patterns of Dengue cases and deaths, associated factors and identification of risk areas at two geographical scales: municipalities in Brazil and intra-urban areas of Campinas, State of São Paulo
• Grantee: Patricia Marques Moralejo Bermudi
• Support Opportunities: Scholarships in Brazil - Doctorate