ABSTRACT
OBJECTIVE: To analyze the transmission dynamics of dengue, a public health problem in Brazil and the Metropolitan Region of Belo Horizonte (MRBH). METHODS: The spatiotemporal evolution of the occurrence of dengue in the municipality of Contagem, state of Minas Gerais, a region with high arbovirus transmission, was analyzed. Furthermore, epidemic and non-epidemic periods were analyzed, based on probable cases of dengue. This is an ecological study that used the Notifiable Diseases Information System (SINAN) national database. The analyses were carried out considering the period from epidemiological week (EW) 40 of 2011 to 39 of 2017. Spatial analysis tools (crude and smoothed incidence rate, directional distribution ellipse, global Moran index and local Moran index, and spatial scanning time with definition of epidemiological risk) were used. RESULTS: The 2012 to 2013 and 2015 to 2016 epidemic cycles presented high incidence rates. The disease was concentrated in more urbanized areas, with a small increase in cases throughout the municipality. Seven statistically significant local clusters and areas with a high rate of cases and accentuated transmission in epidemic cycles were observed throughout the municipality. Spatial autocorrelation of the incidence rate was observed in all periods. CONCLUSION: The results of the present study highlight a significant and heterogeneous increase in dengue notifications in Contagem over the years, revealing distinct spatial patterns during epidemic and non-epidemic periods. Geoprocessing analysis identified high-risk areas, a piece of knowledge that can optimize the allocation of resources in the prevention and treatment of the disease for that municipality.
Subject(s)
Dengue , Epidemics , Spatio-Temporal Analysis , Humans , Dengue/epidemiology , Dengue/transmission , Brazil/epidemiology , Incidence , Cities/epidemiology , Time Factors , Disease Notification/statistics & numerical dataABSTRACT
ABSTRACT Objective: To analyze the transmission dynamics of dengue, a public health problem in Brazil and the Metropolitan Region of Belo Horizonte (MRBH). Methods: The spatiotemporal evolution of the occurrence of dengue in the municipality of Contagem, state of Minas Gerais, a region with high arbovirus transmission, was analyzed. Furthermore, epidemic and non-epidemic periods were analyzed, based on probable cases of dengue. This is an ecological study that used the Notifiable Diseases Information System (SINAN) national database. The analyses were carried out considering the period from epidemiological week (EW) 40 of 2011 to 39 of 2017. Spatial analysis tools (crude and smoothed incidence rate, directional distribution ellipse, global Moran index and local Moran index, and spatial scanning time with definition of epidemiological risk) were used. Results: The 2012 to 2013 and 2015 to 2016 epidemic cycles presented high incidence rates. The disease was concentrated in more urbanized areas, with a small increase in cases throughout the municipality. Seven statistically significant local clusters and areas with a high rate of cases and accentuated transmission in epidemic cycles were observed throughout the municipality. Spatial autocorrelation of the incidence rate was observed in all periods. Conclusion: The results of the present study highlight a significant and heterogeneous increase in dengue notifications in Contagem over the years, revealing distinct spatial patterns during epidemic and non-epidemic periods. Geoprocessing analysis identified high-risk areas, a piece of knowledge that can optimize the allocation of resources in the prevention and treatment of the disease for that municipality.
RESUMO Objetivo: Analisar a dinâmica de transmissão da dengue, problema de saúde pública no Brasil e Região Metropolitana de Belo Horizonte (RMBH). Métodos: Foi analisada a evolução espaçotemporal da ocorrência de dengue no município de Contagem, estado de Minas Gerais, região de alta transmissão da arbovirose. Ainda, foram analisados períodos epidêmicos e não epidêmicos, com base em casos prováveis de dengue. Trata-se de um estudo ecológico que utilizou o banco de dados nacional do Sistema de Informação de Agravos de Notificação (SINAN). As análises foram realizadas considerando-se o período compreendido da semana epidemiológica 40 de 2011 a 39 de 2017. Ferramentas de análise espacial (taxa de incidência bruta e suavizada, elipse de distribuição direcional, índice de Moran global e índice de Moran local, e varredura espaçotemporal com definição do risco epidemiológico) foram utilizadas. Resultados: Os ciclos epidêmicos 2012 a 2013 e 2015 a 2016 apresentaram altas taxas de incidência. A doença concentrou-se em áreas mais urbanizadas, com pequena expansão de casos por todo o município. Foram observados sete aglomerados locais estatisticamente significativos e áreas com alta taxa de casos e transmissão acentuada em ciclos epidêmicos em todo o município. A autocorrelação espacial da taxa de incidência foi observada em todos os períodos. Conclusão: Os resultados do presente estudo destacam um aumento significativo e heterogêneo nas notificações de dengue em Contagem ao longo dos anos, revelando padrões espaciais distintos durante períodos epidêmicos e não epidêmicos. A análise de geoprocessamento identificou áreas de alto risco, conhecimento este que pode otimizar a alocação de recursos na prevenção e tratamento da doença para o referido município.
ABSTRACT
COVID-19 is an infectious disease caused by the recently discovered coronavirus SARS-Cov-2. The disease became pandemic affecting many countries globally, including Brazil. Considering the expansion process and particularities during the initial stages of the epidemic, we aimed to analyze the spatial and spatiotemporal patterns of COVID-19 occurrence and to identify priority risk areas in Minas Gerais State, Southeast Brazil. An ecological study was performed considering all data from human cases of COVID-19 confirmed from the epidemiological week (EW) 11 (March 08, 2020) to EW 26 (June 27, 2020). Crude and smoothed incidence rates were used to analyze the distribution of disease patterns based on global and local indicators of spatial association and space-time risk assessment. Positive spatial autocorrelation and spatial dependence were found. Our results suggest that the metropolitan region of the State capital Belo Horizonte (MRBH) and Vale do Rio Doce mesoregions, as major epidemic foci in the beginning of the expansion process, have had important influence on the dispersion of SARS-CoV-2 in Minas Gerais State. Triangulo Mineiro/Alto Paranaiba region presented the highest risk of infection. In addition, six statistically significant spatiotemporal clusters were identified in the State, three at high risk and three at low risk. Our findings contribute to a greater understanding of the space-time disease dynamic and discuss strategies for identification of priority areas for COVID-19 surveillance and control.
