tetano
Editor, Senior Moderator
Trans R Soc Trop Med Hyg
. 2021 Sep 22;trab144.
doi: 10.1093/trstmh/trab144. Online ahead of print.
Examining socio-economic factors to understand the hospital case fatality rates of COVID-19 in the city of São Paulo, Brazil
Camila Lorenz[SUP] 1 [/SUP], Patricia Marques Moralejo Bermudi[SUP] 1 [/SUP], Breno Souza de Aguiar[SUP] 2 [/SUP], Marcelo Antunes Failla[SUP] 3 [/SUP], Tatiana Natasha Toporcov[SUP] 1 [/SUP], Francisco Chiaravalloti-Neto[SUP] 1 [/SUP], Ligia Vizeu Barrozo[SUP] 4 [/SUP]
Affiliations
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 São 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.
Keywords: Bayesian spatial analysis; comorbidities; coronavirus; modelling.
. 2021 Sep 22;trab144.
doi: 10.1093/trstmh/trab144. Online ahead of print.
Examining socio-economic factors to understand the hospital case fatality rates of COVID-19 in the city of São Paulo, Brazil
Camila Lorenz[SUP] 1 [/SUP], Patricia Marques Moralejo Bermudi[SUP] 1 [/SUP], Breno Souza de Aguiar[SUP] 2 [/SUP], Marcelo Antunes Failla[SUP] 3 [/SUP], Tatiana Natasha Toporcov[SUP] 1 [/SUP], Francisco Chiaravalloti-Neto[SUP] 1 [/SUP], Ligia Vizeu Barrozo[SUP] 4 [/SUP]
Affiliations
- PMID: 34551109
- DOI: 10.1093/trstmh/trab144
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 São 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.
Keywords: Bayesian spatial analysis; comorbidities; coronavirus; modelling.