Spatio-temporal distribution of dengue occurrences in Três Corações, Minas Gerais, using point processes
DOI:
https://doi.org/10.5433/1679-0367.2020v41n2Suplp377Keywords:
Epidemiology, Aedes aegypti, Statistical methods, Rainfall.Abstract
Objective: detect the presence of space-time clusters of dengue cases in Três Corações, Minas Gerais, Brazil, using information on the location and time of each occurrence and the historical series of rainfall in the study period. Methods: the Kernel method was used to estimate the intensity of the cases, while the space-time K-function and the scan method were used to detect the pattern and identify clusters, respectively. Results: from the 2,818 observed cases, it was found that most of these occurred in the end of rainy periods. The presence of clusters of cases was also detected, mainly, in the central region of the city. One reason for the formation of clusters may be due to the higher population density of the affected regions. Conclusion: the results show that individuals who live in densely populated regions are more likely to get dengue. The statistical methods used allowed to characterize the spatio-temporal distribution of dengue cases and, they can also be used to analyze other endemic or pandemic diseases, which can contribute to policies to prevent and combat the proliferation of these diseases.Downloads
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References
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Cabral JA, Freitas MV. Distribuição espacial e determinantes socioeconômicos e demográficos da dengue nos municípios brasileiros. Rev Bras Estud Reg Urbanos. 2012;6(1):81-95.
Climate-data.org. Clima Três Corações [Internet]. 2020 [citado 2020 maio 6]. Disponível em: https://pt.climate-data.org/america-do-sul/brasil/minas-gerais/tres-coracoes-25070.
Dias LB, Almeida SC, Haes TM, Mota LM, Roriz-Filho JS. Dengue: transmissão, aspectos clínicos, diagnóstico e tratamento. Medicina (Ribeirão Preto). 2010;43(2):143-52.
Diggle PJ, Chetwynd AG, Haggkivist R, Morris SE. Second order analysis of space-time clustering. Stat Methods Med Res. 1995;4(2):124-36.
Diggle PJ. Statistical analysis of spatial and spatio-temporal point patterns. 3rd ed. Boca Raton: CRC Press; 2013.
Ferreira LM. Mapeamento dos casos de dengue na cidade de Lavras-MG, no período de 2007-2010 [dissertação]. Lavras: Universidade Federal de Lavras; 2012.
Gabriel E, Rowlingson B, Diggle PJ. stpp: an R package for plotting, simulating and analyzing spatio-temporal point patterns. J Stat Soft. 2013;53(2):1-29.
Google INC. Google Earth [software]. Versão 7.1.5.1557. 2017. Disponível em: https://www.google.com.br/intl/pt-BR/earth/.
Higa Y. Dengue vectors and their spatial distribution. Trop Med Health [Internet]. 2011 [cited 2020 May 8];39:17-27. Available from: https://www.jstage.jst.go.jp/article/tmh/39/4SUPPLEMENT/39_2011-S04/_pdf/-char/en.
Instituto Brasileiro de Geografia e Estatística. Três Corações [Internet]. 2020 [citado 2020 jan 15]. Disponível em: https://cidades.ibge.gov.br/brasil/mg/tres-coracoes.
Instituto Oswaldo Cruz. Aedes e dengue: vetor e doença [Internet]. 2016 [citado 2016 nov 14]. Disponível em: http://www.ioc.fiocruz.br/dengue/textos/aedesvetoredoenca.html.
Kulldorff M, Heffernan R, Hartman J, Assunção R, Mostashari F. A space-time permutation scan statistic for disease outbreak detection. PLoS Med. 2005;2(3).
Kulldorff M, Information Management Services Inc. SaTScanTM [software]. Version 9. 1.1. 2013.
Loecher M, Ropkins K. RgoogleMaps and loa: unleashing R graphics power on map tiles. J Stat Soft. 2015;63(4):1-18.
Machiner F, Rodrigues DJ, Andrade EA. Distribuição de dengue no norte de Mato Grosso, Brasil, 2001-2005. Cad Saúde Colet. 2009;17(3):627-40.
Malik A, Yasar A, Tabinda AB, Zaheer IE, Malik K, Batool A, et al. Assessing spatio-temporal trend of vector breeding and dengue fever incidence in association with meteorological conditions. Environ Monit Assess. 2017;189(4).
Mendonça FA, Souza AV, Dutra DA. Saúde pública, urbanização e dengue no Brasil. Soc Nat. 2009;21(3):257-69.
Ministério da Saúde (BR). Guia de vigilância em saúde: volume 2 [Internet]. 2017 [citado 2020 maio 8]. Disponível em: https://bvsms.saude.gov.br/bvs/publicacoes/guia_vigilancia_saude_volume_2.pdf.
Ministério da Saúde (BR). Guia de vigilância epidemiológica [Internet]. 2005 [citado 2020 maio 5]. Disponível em: http://bvsms.saude.gov.br/bvs/publicacoes/Guia_Vig_Epid_novo2.pdf.
Ministério da Saúde (BR). SINAN: Sistema de Informação de Agravos de Notificação [Internet]. 2020 [citado 2020 mar 12]. Disponível em: http://portalsinan.saude.gov.br/.
Neiva HS, Cardoso C. Clima e dengue: uma ajuda para compreender a epidemia na cidade do Rio de Janeiro. Rev Pol Publ [Internet]. 2018 [citado 2020 maio 8]; 22:1135-50. Disponível em: http://www.redalyc.org/articulo.oa?id=321158844058.
Pebesma EJ, Bivand RS. Classes and methods for spatial data: the sp Package [Internet]. 2005 [cited 2020 May 6]. Available from: https://cran.r-project.org/web/packages/sp/vignettes/intro_sp.pdf.
Prefeitura Municipal de Três Corações. Estatísticas [Internet]. 2020 [citado 2020 maio 6]. Disponível em: https://www.trescoracoes.mg.gov.br/index.php/2014-12-30-11-10-09/5190-estatisticas.
R Core Team. R: a language and environment for statistical computing. Vienna: The R Foundation for Statistical Computing; 2017.
Schabenberger O, Gotway CA. Statistical methods for spatial data analysis. Boca Raton: CRC Press; 2017.
Silva FG, Magalhães SCM. Correlação entre fatores climáticos, socioambientais e a dengue na microrregião Montes Claros/MG. Caminhos de Geografia. 2017;18(61): 231-44.
Silva JS, Mariano ZF, Scopel I. A influência do clima urbano na proliferação do mosquito Aedes aegypti em Jataí (GO), na perspectiva da Geografia Médica. Hygeia. 2007;3(5).
Simone TS, Nogueira RMR, Araújo ESM. Dengue virus surveillance: the co-circulation of DENV-1, DENV-2 and DENV-3 in the state of Rio de Janeiro, Brazil. Trans R Soc Trop Med Hyg. 2004;98:553-62.
Toan DTT, Hu W, Quang TP, Hoat LN, Wright P, Martens P. Hot spot detection and spatio-temporal dispersion of dengue fever in Hanoi, Vietnam. Glob Health Action. 2013;6(1).
Valle D, Bellinato DF, Viana-Medeiros PF, Lima JBP, Martins Junior ADJ. Resistance to temephos and deltamethrin in Aedes aegypti from Brazil between 1985 and 2017. Mem Inst Oswaldo Cruz. 2019;114.
Viana DV, Ignotti E. A ocorrência da dengue e variações meteorológicas no Brasil: revisão sistemática. Rev Bras Epidemiol. 2013;16(2):240-56.
Warkentien T, Pavlicek R. Dengue fever: historical perspective and the global response. J Infect Dis Epidemiol [Internet]. 2016 [cited 2020 May 8];2(2). Available from: https://clinmedjournals.org/articles/jide/journal-of-infectious-diseases-and-epidemiology-jide-2-015.pdf.
World Health Organization. Dengue guidelines for diagnosis, treatment, prevention and control. Geneva: WHO; 2009.
World Health Organization. Frequently asked questions on dengue [Internet]. 2016 [cited 2016 Nov 14]. Available from: http://www.wpro.who.int/mediacentre/releases/2010/20100916_ FAQs/en/.
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Published
2020-11-21
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Abreu RF de, Ferreira RA, Scalon JD. Spatio-temporal distribution of dengue occurrences in Três Corações, Minas Gerais, using point processes. Semin. Cienc. Biol. Saude [Internet]. 2020 Nov. 21 [cited 2024 Nov. 21];41(2Supl):377-88. Available from: https://ojs.uel.br/revistas/uel/index.php/seminabio/article/view/39558
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