Spatial correlation of covid-19 with intensive care unit beds in Paraná
DOI:
https://doi.org/10.11606/s1518-8787.2022056003868Keywords:
COVID-19, complications, Intensive Care Units, supply & distribution, Spatial Analysis, Health Services Needs and Demand, Ecological StudiesAbstract
OBJECTIVE To analyze the spatial correlation between confirmed cases of covid-19 and the intensive care unit beds exclusive to the disease in municipalities of Paraná. METHODS This is an epidemiological study of ecological type which used data from the Epidemiological Report provided by the Department of Health of Paraná on the confirmed cases of covid-19 from March 12, 2020, to January 18, 2021. The number of intensive care beds exclusive to covid-19 in each municipality of Paraná was obtained by the Cadastro Nacional de Estabelecimentos de Saúde (CNES - National Registry of Health Establishments), provided online by the Departamento de Informática do Sistema Único de Saúde (Datasus - Informatics Department of the Brazilian Unified Health System). The Bivariate Moran’s Index (local and global) was used to analyze the intensive care bed variable and spatial correlation, with a 5% significance level. LISA Map was used to identify critical and transition areas. RESULTS In the analyzed period, we found 499,777 confirmed cases of covid-19 and 1,029 intensive care beds exclusive to the disease in Paraná. We identified a positive spatial autocorrelation between the confirmed cases of covid-19 (0.404–p ≤ 0.001) and intensive care beds exclusive to the disease (0.085–p ≤ 0.001) and disparities between the regions of Paraná. CONCLUSION Spatial analysis indicated that confirmed cases of covid-19 are related to the distribution of intensive care beds exclusive to the disease in Paraná, allowing us to find priority areas of care in the state regarding the dissemination and control of the disease.
References
Frater JL, Zini G, d’Onofrio G, Rogers HJ. COVID-19 and the clinical hematology laboratory. Int J Lab Hematol. 2020;42 Suppl 1:11-8. https://doi.org/10.1111/ijlh.13229
World Health Organization. Middle East respiratory syndrome coronavirus (MERS-Cov). Geneva (CH): WHO; 2016 [citado 26 abr 2021]. Disponível em: https://www.who.int/emergencies/mers-cov/en/
Centers for Disease Control and Prevention, National Center for Immunization and Respiratory Diseases, Division of Viral Diseases. Severe Acute Respiratory Syndrome (SARS). Atanta, GA: CDC; 2005 [citado 26 abr 2021]. Disponível em: https://www.cdc.gov/sars/about/faq.html
World Health Organization. Laboratory testing for coronavirus disease 2019 (COVID-19) in suspected human cases: interim guidance. Geneva (CH): WHO; 2020. Disponível em: https://www.who.int/publications-detail/laboratory-testing-for-2019-novel-coronavirus-in-suspected-human-cases-20200117
Yang WZ. [Thoughts of the COVID-19 outbreak phases changed from emergency response to the combination of emergent response and regular prevention and control activities]. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(6):806-8. Chinese. https://doi.org/10.3760/cma.j.cn112338-20200404-00516
World Health Organization. WHO Coronavirus Disease (COVID-19) Dashboard. Geneva (CH): WHO; 2021 [citado 26 abr 2021]. Disponível em: https://covid19.who.int/
Rothan HA, Byrareddy SN. The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak. J Autoimmun. 2020;109:e102433. https://doi.org/10.1016/j.jaut.2020.102433
Zhang G, Hu C, Luo L, Fang F, Chen Y, Li J, et al. Clinical features and short-term outcomes of 221 patients with COVID-19 in Wuhan, China. J Clin Virol. 2020;127:104364. https://doi.org/10.1016/j.jcv.2020.104364
World Health Organization. WHO Coronavirus Disease (COVID-19) Dashboard: Brazil situation. Geneva (CH): WHO; 2021 [citado 26 abr 2021]. Disponível em: https://covid19.who.int/region/amro/country/br
Secretaria da Saúde do Estado do Paraná. Coronavírus (COVID-19): panorama Covid 19. Inf Epidemiol. 24 abr 2021 [citado 26 abr 2021]. Disponível em: https://www.saude.pr.gov.br/sites/default/arquivos_restritos/files/documento/2021-04/informe_epidemiologico_26_04_2021.pdf
Instituto Brasileiro de Geografia e Estatística. Cidades. Paraná: Panorama. Rio de Janeiro; IBGE; 2020 [citado 13 jan 2021]. Disponível em: https://cidades.ibge.gov.br/brasil/pr/panorama
Secretaria da Saúde do Estado do Paraná. Regionais de Saúde. Curitiba, PR; 2021 [citado 13 jan 2021]. Disponível em: http://www.saude.pr.gov.br/Pagina/Regionais-de-Saude
Secretaria da Saúde do Estado do Paraná. Coronavírus (COVID-19). Inf Epidemiol. 18 jan 2021 [citado 18 jan 2021]. Disponível em: https://www.saude.pr.gov.br/sites/default/arquivos_restritos/files/documento/2021-01/informe_epidemiologico_18_01_2021.pdf
Ministério da Saúde (BR), Departamento de Informática do Sistema Único de Saúde (DATASUS). CNES - recursos físicos - hospitalar - leitos complementares – Brasil. Brasília, DF; 2021 [citado 18 jan 2021]. Disponível em: http://tabnet.datasus.gov.br/cgi/tabcgi.exe?cnes/cnv/leiutibr.def
Melo JAVB. Policentralidade e mobilidade na Região Metropolitana do Rio de Janeiro. Bitácora Urbano Territorial. 2019;29(3):11-20. https://doi.org/10.15446/bitacora.v29n3.62420
Moran PAP. Notes on continuous stochastic phenomena. Biometrika. 1950;37(1-2):17-23. https://doi.org/10.1093/biomet/37.1-2.17
Anselin L, Smimov O. Visualizing multivariate spatial correlation with dynamically linked Windows. In: Anselin L, Rey S. editors. New tools for spatial data analysis: proceedings of the Specialist Meeting. Santa Barbara, CA: Center for Spatially Integrated Social Science (CSISS), University of California; 2002 [citado 18 jan 2021]. p. 1-20. Disponível em: https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.201.2665&rep=rep1&type=pdf
Pedrosa NL, Albuquerque NLS. Análise espacial dos casos de COVID-19 e leitos de terapia intensiva no estado do Ceará, Brasil. Cienc Saude Colet. 2020;25 Suppl 1:2461-8. https://doi.org/10.1590/1413-81232020256.1.10952020
Gomes GGC, Bisco NCB, Paulo MF, Fabrin SCV, Fioco EM, Verri ED, et al. Perfil epidemiológico da Nova Doença Infecciosa do Coronavírus - COVID-19 (Sars-Cov-2) no mundo: estudo descritivo, janeiro-junho de 2020. Braz J Health Rev. 2020;3(4):7993-8007. https://doi.org/10.34119/bjhrv3n4-064
Garcia LP, Duarte E. Intervenções não farmacológicas para o enfrentamento à epidemia da COVID-19 no Brasil. Epidemiol Serv Saude. 2020;29(2):e2020222. https://doi.org/10.5123/s1679-49742020000200009
Ministério da Saúde (BR), Secretaria de Vigilância em Saúde. Doença pelo Coronavírus COVID-19. Bol Epidemiol: 2021[citado 18 jan 2021];(52 Nº Espec):1-85. Disponível em: http://saude.gov.br/images/pdf/2020/July/01/Boletim-epidemiologico-COVID-20-3.pdf
Lopes LFD, Faria RM, Lima MP, Kirchhof RS, Almeida DM, Moura GL. Descrição do perfil epidemiológico da Covid-19 na Região Sul do Brasil. Hygeia. 2020;16;188-98. https://doi.org/10.14393/Hygeia16054772
Crokidakis N. Modeling of the evolution of COVID-19 in Brazil: results from a Susceptible-Infectious-Quarantined-Recovered (SIQR) model. Int J Mod Phys C. 2020 [citado 16 jan 2021];31(10):2050135. Disponível em: https://arxiv.org/pdf/2003.12150.pdf
RankBR. Coronavírus a pandemia no Brasil [Internet]. Brasília; 2021 [citado 2021 abr 2021]. Disponível em: https://www.rankbr.com.br/
CDC COVID-19 Response Team. Geographic differences in COVID-19 cases, deaths, and incidence - United States, February 12-April 7, 2020. MMWR Morb Mortal Wkly Rep. 2020;69(15):465-71. https://doi.org/10.15585/mmwr. mm6915e4
Kuchler T, Russel D, Stroebel J. The geographic spread of COVID-19 correlates with structure of social networks as measured by Facebook. Cambridge, MA: National Bureau of Economic Research; 2020. (NBER Working Papers; nº 26990). https://doi.org/10.3386/w26990
Zheng R, Xu Y, Wang W, Ning G, Bi Y. Spatial transmission of COVID-19 via public and private transportation in China. Travel Med Infect Dis. 2020;34:101626. https://doi.org/10.1016/j.tmaid.2020.101626
Nascimento E, Tombini LHT, Ripplinger F. Espacialização da Covid-19 no Sul do Brasil: a interiorização da doença e o caso da mesorregião grande fronteira do Mercosul. Finisterra. 2020;55(115):27-35. https://doi.org/10.18055/Finis20367
Chen ZL, Zhang Q, Lu Y, Guo ZM, Zhang X, Zhang WJ, et al. Distribution of the COVID-19 epidemic and correlation with population emigration from Wuhan, China. Chin Med J (Engl). 2020;133(9):1044-50. https://doi.orrg/10.1097/CM9.0000000000000782
Moreira RS. COVID-19: unidades de terapia intensiva, ventiladores mecânicos e perfis latentes de mortalidade associados à letalidade no Brasil. Cad Saude Publica. 2020;36(5):e00080020. https://doi.org/10.1590/0102-311X00080020
Noronha KVMS, Guedes GR, Turra CM, Andrade MV, Botega L, Nogueira D, et al. Pandemia por COVID-19 no Brasil: análise da demanda e da oferta de leitos hospitalares e equipamentos de ventilação assistida segundo diferentes cenários. Cad Saude Publica. 2020;36(6):e00115320. https://doi.org/10.1590/0102-311X00115320
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Eduardo Rocha Covre, Natan David Pereira, Natan Nascimento de Oliveira, Patrícia Bossolani Charlo, Magda Lúcia Félix de Oliveira, Rosana Rosseto de Oliveira, Lígia Carreira, Luiz Augusto Facchini, João Ricardo Nickenig Vissoci, Maria Aparecida Salci
This work is licensed under a Creative Commons Attribution 4.0 International License.
