Detecção de agrupamentos espaço-temporais de ocorrências de dengue utilizando processos pontuais

Detalhes bibliográficos
Ano de defesa: 2017
Autor(a) principal: Abreu, Rodrigo Ferreira de
Orientador(a): Não Informado pela instituição
Banca de defesa: Não Informado pela instituição
Tipo de documento: Dissertação
Tipo de acesso: Acesso aberto
Idioma: por
Instituição de defesa: Universidade Federal de Lavras
Programa de Pós-Graduação em Estatística e Experimentação Agropecuária
UFLA
brasil
Departamento de Ciências Exatas
Programa de Pós-Graduação: Não Informado pela instituição
Departamento: Não Informado pela instituição
País: Não Informado pela instituição
Palavras-chave em Português:
Link de acesso: http://repositorio.ufla.br/jspui/handle/1/12354
Resumo: Dengue is one of the most infectious diseases affecting the world's population, where around 50 million people get the disease every year and, approximately, 2.5 billion people are in risky areas. Brazil is one of the countries where the population is most prone to be infected with dengue. Understanding the spatial and temporal behavior of dengue cases is one of the most important aspects for the decision making of public health managers. Thus, the aim of this work was to present and evaluate several statistical methods that can be used to detect the presence of space-time clusters in dengue cases. The following methods are presented for the detection of global spatiotemporal clustering: Knox test, Mantel test, Jacquez test, homogeneous K function and non-homogeneous K function. The Scan statistic was also used to detect clusters at specific times and locations. The performance of the methods was evaluated from the application of them in data of occurrences of dengue in the city of Três Corações - MG, during the period from 01/01/2010 to 12/31/2015. The Knox, Mantel and Jacques tests indicated the presence of spatio-temporal clusters in dengue occurrences in the study region. From the analyzes using the homogeneous and non-homogeneous K functions, it was possible to verify that the patterns of clustering of dengue occurrences are results of first order effects (intensity) and not of second order effects (spatio-temporal dependence). The analysis with scan statistic allowed the identification of six significant local spatio-temporal clusters in the city of Três Corações. The results show that each method has its peculiarities and, therefore, should not be used individually for the detection of space-time clusters of dengue cases. It is recommended to use the combined methods for a more precise description of the spatio-temporal clustering of dengue cases.