COVID-19 in the municipality of Salvador: ecological study of the first months of the Pandemic
Autor(a) principal: | |
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Data de Publicação: | 2021 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/19783 |
Resumo: | Objective: to investigate the spatial distribution of confirmed cases and deaths of COVID-19 in the first four months of the Pandemic in the city of Salvador, from its health districts. Method: ecological study d with 34,691,000 confirmed cases and 1,589 deaths from COVID-19 in Salvador, Bahia, between March and June 2020. Data were analyzed in STATA 12.0 using descriptive and inferential statistics. Results: The mean number of confirmed cases was 109.2 cases/ ten thousand inhabitants. The districts of Barra/Rio Vermelho (143.8/ten thousand) and Centro Histórico (136.1/ten thousand) had an average of cases higher than the municipal average. There was an average of 5.4 deaths/ten thousand inhabitants, with the districts Liberdade (8.4/ten thousand) and Itapagipe (7.2/ten thousand) with averages higher than the municipal one. The districts of densities considered high (Botas, Itapagipe and Liberdade) represented 22.4% of the cases of diseases and 25.9% of the total deaths. The population and number of cases of H1N1 were significantly correlated with the number of cases of COVID-19 in the districts. There was an increasing trend in the number of cases, with average weekly growth of 27.17% (p-value < 0.001) and high in the period between March and June 2020. The health districts that had the highest growth in notifications were Barra- Rio Vermelho (30.3%), Cajazeiras (28.7%) and Pau da Lima (28.1%). Conclusions: the number of cases is higher in the regions with the highest circulation of people for economic and(or) tourist purposes, but lethality is higher in poorer regions of the municipality. The growing trend of cases requires attention to effective measures of social isolation. |
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COVID-19 in the municipality of Salvador: ecological study of the first months of the Pandemic COVID-19 en el municipio de Salvador: estudio ecológico de los primeros meses de la Pandemia COVID-19 no município de Salvador: estudo ecológico dos primeiros meses da Pandemia COVID-19EpidemiologyPublic health.COVID-19EpidemiologíaSalud pública.COVID-19EpidemiologiaSaúde pública.Objective: to investigate the spatial distribution of confirmed cases and deaths of COVID-19 in the first four months of the Pandemic in the city of Salvador, from its health districts. Method: ecological study d with 34,691,000 confirmed cases and 1,589 deaths from COVID-19 in Salvador, Bahia, between March and June 2020. Data were analyzed in STATA 12.0 using descriptive and inferential statistics. Results: The mean number of confirmed cases was 109.2 cases/ ten thousand inhabitants. The districts of Barra/Rio Vermelho (143.8/ten thousand) and Centro Histórico (136.1/ten thousand) had an average of cases higher than the municipal average. There was an average of 5.4 deaths/ten thousand inhabitants, with the districts Liberdade (8.4/ten thousand) and Itapagipe (7.2/ten thousand) with averages higher than the municipal one. The districts of densities considered high (Botas, Itapagipe and Liberdade) represented 22.4% of the cases of diseases and 25.9% of the total deaths. The population and number of cases of H1N1 were significantly correlated with the number of cases of COVID-19 in the districts. There was an increasing trend in the number of cases, with average weekly growth of 27.17% (p-value < 0.001) and high in the period between March and June 2020. The health districts that had the highest growth in notifications were Barra- Rio Vermelho (30.3%), Cajazeiras (28.7%) and Pau da Lima (28.1%). Conclusions: the number of cases is higher in the regions with the highest circulation of people for economic and(or) tourist purposes, but lethality is higher in poorer regions of the municipality. The growing trend of cases requires attention to effective measures of social isolation.Objetivo: investigar la distribución espacial de los casos confirmados y muertes por COVID-19 en los primeros cuatro meses de la Pandemia en la ciudad de Salvador, desde sus distritos sanitarios. Método: estudio ecológico d con 34.691.000 casos confirmados y 1.589 muertes por COVID-19 en Salvador, Bahía, entre marzo y junio de 2020. Los datos fueron analizados en STATA 12.0 por medio de estadística descriptiva e inferencial. Resultados: El número medio de casos confirmados fue de 109,2 casos por diez mil habitantes. Los distritos de Barra/Río Vermelho (143,8/diez mil) y Centro Histórico (136,1/diez mil) tuvieron un promedio de casos superior a la media municipal. Hubo un promedio de 5,4 muertes/diez mil habitantes, con los distritos Liberdade (8,4/diez mil) e Itapagipe (7,2/diez mil) con promedios superiores a los municipales. Los distritos de densidades consideradas altas (Botas, Itapagipe y Liberdade) representaron 22,4% de los casos y 25,9% del las muertes. La población y el número de casos de H1N1 se correlacionaron significativamente al número de casos de COVID-19 en los distritos. Hubo una tendencia creciente en el número de casos, con un crecimiento semanal promedio de 27.17% (valor p < 0.001) y alto en el período comprendido entre marzo y junio de 2020. Los distritos de salud que tuvieron mayor crecimiento en notificaciones fueron Barra- Rio Vermelho (30,3%), Cajazeiras (28,7%) y Pau da Lima (28,1%). Conclusiones: el número de casos es mayor en las regiones con mayor circulación de personas con fines económicos y turísticos, pero la letalidad es mayor en las regiones más pobres del municipio. La creciente tendencia de los casos exige que se preste atención a medidas eficaces de aislamiento social.Objetivo: investigar a distribuição espacial dos casos confirmados e óbitos da COVID-19 nos quatro primeiros meses da Pandemia no município de Salvador, a partir dos seus distritos sanitários. Método: estudo ecológico d com 34.691 mil casos confirmados e 1.589 mortes por COVID-19 em Salvador, Bahia, entre março e junho de 2020. Analisaram-se os dados no STATA 12.0 por meio de estatística descritiva e inferencial. Resultados: A média de casos confirmados foi de 109,2 casos/ dez mil habitantes. Os distritos de Barra/Rio Vermelho (143,8/dez mil) e Centro Histórico (136,1/dez mil) apresentaram média de casos superiores à média municipal. Houve média de 5,4 mortes/dez mil habitantes, ficando os distritos Liberdade (8,4/dez mil) e Itapagipe (7,2/dez mil) com médias superiores à municipal. Os distritos de densidades consideradas altas (Botas, Itapagipe e Liberdade) representaram 22,4% dos casos das doenças e 25,9% do total de mortes. A população e nº de casos de H1N1 correlacionaram-se significativamente ao número de casos de COVID-19 nos distritos. Observou-se tendência crescente do número de casos, com crescimento médio semanal de 27,17% (p-valor < 0,001) e alta no período entre março e junho de 2020. Os distritos sanitários que tiveram um maior crescimento de notificações foram Barra- Rio Vermelho (30,3%), Cajazeiras (28,7%) e Pau da Lima (28,1%). Conclusões: o número de casos é maior nas regiões de maior circulação de pessoas por fins econômicos e(ou) turísticos, porém a letalidade é maior em regiões mais pobres do município. A tendência crescente de casos requer atenção para medidas efetivas de isolamento social.Research, Society and Development2021-09-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/1978310.33448/rsd-v10i11.19783Research, Society and Development; Vol. 10 No. 11; e445101119783Research, Society and Development; Vol. 10 Núm. 11; e445101119783Research, Society and Development; v. 10 n. 11; e4451011197832525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/19783/17711Copyright (c) 2021 Rodolfo Macedo Cruz Pimenta; Rodrigo Marques da Silva; Gustavo Marques Porto Cardoso; Felipe Souza Dreger Nery; Victor Valentim Lassaval Farias; Wilton Nascimento Figueredo; Tássia Teles Santana de Macedohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessPimenta, Rodolfo Macedo Cruz Silva, Rodrigo Marques daCardoso, Gustavo Marques Porto Nery, Felipe Souza Dreger Farias, Victor Valentim Lassaval Figueredo, Wilton Nascimento Macedo, Tássia Teles Santana de 2021-10-23T19:01:11Zoai:ojs.pkp.sfu.ca:article/19783Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:39:36.708728Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
COVID-19 in the municipality of Salvador: ecological study of the first months of the Pandemic COVID-19 en el municipio de Salvador: estudio ecológico de los primeros meses de la Pandemia COVID-19 no município de Salvador: estudo ecológico dos primeiros meses da Pandemia |
title |
COVID-19 in the municipality of Salvador: ecological study of the first months of the Pandemic |
spellingShingle |
COVID-19 in the municipality of Salvador: ecological study of the first months of the Pandemic Pimenta, Rodolfo Macedo Cruz COVID-19 Epidemiology Public health. COVID-19 Epidemiología Salud pública. COVID-19 Epidemiologia Saúde pública. |
title_short |
COVID-19 in the municipality of Salvador: ecological study of the first months of the Pandemic |
title_full |
COVID-19 in the municipality of Salvador: ecological study of the first months of the Pandemic |
title_fullStr |
COVID-19 in the municipality of Salvador: ecological study of the first months of the Pandemic |
title_full_unstemmed |
COVID-19 in the municipality of Salvador: ecological study of the first months of the Pandemic |
title_sort |
COVID-19 in the municipality of Salvador: ecological study of the first months of the Pandemic |
author |
Pimenta, Rodolfo Macedo Cruz |
author_facet |
Pimenta, Rodolfo Macedo Cruz Silva, Rodrigo Marques da Cardoso, Gustavo Marques Porto Nery, Felipe Souza Dreger Farias, Victor Valentim Lassaval Figueredo, Wilton Nascimento Macedo, Tássia Teles Santana de |
author_role |
author |
author2 |
Silva, Rodrigo Marques da Cardoso, Gustavo Marques Porto Nery, Felipe Souza Dreger Farias, Victor Valentim Lassaval Figueredo, Wilton Nascimento Macedo, Tássia Teles Santana de |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Pimenta, Rodolfo Macedo Cruz Silva, Rodrigo Marques da Cardoso, Gustavo Marques Porto Nery, Felipe Souza Dreger Farias, Victor Valentim Lassaval Figueredo, Wilton Nascimento Macedo, Tássia Teles Santana de |
dc.subject.por.fl_str_mv |
COVID-19 Epidemiology Public health. COVID-19 Epidemiología Salud pública. COVID-19 Epidemiologia Saúde pública. |
topic |
COVID-19 Epidemiology Public health. COVID-19 Epidemiología Salud pública. COVID-19 Epidemiologia Saúde pública. |
description |
Objective: to investigate the spatial distribution of confirmed cases and deaths of COVID-19 in the first four months of the Pandemic in the city of Salvador, from its health districts. Method: ecological study d with 34,691,000 confirmed cases and 1,589 deaths from COVID-19 in Salvador, Bahia, between March and June 2020. Data were analyzed in STATA 12.0 using descriptive and inferential statistics. Results: The mean number of confirmed cases was 109.2 cases/ ten thousand inhabitants. The districts of Barra/Rio Vermelho (143.8/ten thousand) and Centro Histórico (136.1/ten thousand) had an average of cases higher than the municipal average. There was an average of 5.4 deaths/ten thousand inhabitants, with the districts Liberdade (8.4/ten thousand) and Itapagipe (7.2/ten thousand) with averages higher than the municipal one. The districts of densities considered high (Botas, Itapagipe and Liberdade) represented 22.4% of the cases of diseases and 25.9% of the total deaths. The population and number of cases of H1N1 were significantly correlated with the number of cases of COVID-19 in the districts. There was an increasing trend in the number of cases, with average weekly growth of 27.17% (p-value < 0.001) and high in the period between March and June 2020. The health districts that had the highest growth in notifications were Barra- Rio Vermelho (30.3%), Cajazeiras (28.7%) and Pau da Lima (28.1%). Conclusions: the number of cases is higher in the regions with the highest circulation of people for economic and(or) tourist purposes, but lethality is higher in poorer regions of the municipality. The growing trend of cases requires attention to effective measures of social isolation. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-09-06 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/19783 10.33448/rsd-v10i11.19783 |
url |
https://rsdjournal.org/index.php/rsd/article/view/19783 |
identifier_str_mv |
10.33448/rsd-v10i11.19783 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/19783/17711 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
https://creativecommons.org/licenses/by/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Research, Society and Development |
publisher.none.fl_str_mv |
Research, Society and Development |
dc.source.none.fl_str_mv |
Research, Society and Development; Vol. 10 No. 11; e445101119783 Research, Society and Development; Vol. 10 Núm. 11; e445101119783 Research, Society and Development; v. 10 n. 11; e445101119783 2525-3409 reponame:Research, Society and Development instname:Universidade Federal de Itajubá (UNIFEI) instacron:UNIFEI |
instname_str |
Universidade Federal de Itajubá (UNIFEI) |
instacron_str |
UNIFEI |
institution |
UNIFEI |
reponame_str |
Research, Society and Development |
collection |
Research, Society and Development |
repository.name.fl_str_mv |
Research, Society and Development - Universidade Federal de Itajubá (UNIFEI) |
repository.mail.fl_str_mv |
rsd.articles@gmail.com |
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1797052788510818304 |