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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Spatiotemporal-based clusters as a method for dengue surveillance

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Autor(es):
Canal, Mayara Romero [1] ; da Silva Ferreira, Elis Regina [1] ; Estofolete, Cassia Fernanda [2] ; Dias, Andreia Martiniano [1] ; Tukasan, Caroline [1] ; Bertoque, Ana Carolina [1] ; Muniz, Vitor Dantas [1] ; Nogueira, Mauricio Lacerda [2] ; da Silva, Natal Santos [3]
Número total de Autores: 9
Afiliação do(s) autor(es):
[1] Uniao Fac Grandes Lagos, Fac Med, Sao Jose Do Rio Preto, SP - Brazil
[2] Fac Med Sao Jose do Rio Preto, Lab Pesquisas Virol, Sao Paulo - Brazil
[3] Uniao Fac Grandes Lagos, Lab Modelagens Matemat & Estat Med, Sao Jose Do Rio Preto, SP - Brazil
Número total de Afiliações: 3
Tipo de documento: Artigo Científico
Fonte: Revista Panamericana de Salud Pública = Pan American Journal of Public Health; v. 41, 2017.
Citações Web of Science: 0
Resumo

Objectives. To develop and demonstrate the use of a new method for epidemiological surveillance of dengue. Methods. This was a retrospective cohort study using data from the Health Department of Sao Jose do Rio Preto (Sao Paulo, Brazil). The geographical coordinates were obtained using QGIS (TM) (Creative Commons Corporation, Mountain View, California, United States), based on patient addresses in the dengue notification system of the Government of Brazil. SaTScan (TM) (Martin Kulldorff, Boston, Massachusetts, United States) was then used to create a space-time scan analysis to find statistically significant clusters of dengue. These results were plotted and visualized using Google Earth (TM) mapping service (Google Incorporated, Mountain View, California, United States). Results. More clusters were detected when the maximum number of households per cluster was set to 10% (11 statistically significant clusters) rather than 50% (8 statistically significant clusters). The cluster radius varied from 0.18 - 2.04 km and the period of time varied from 6 days - 6 months. The infection rate was more than 0.5 cases/household. Conclusions. When using SaTScan for space-time analysis of dengue cases, the maximum number of households per cluster should be set to 10%. This methodology may be useful to optimizing dengue surveillance systems, especially in countries where resources are scarce and government programs have not had much success controlling the disease. (AU)

Processo FAPESP: 13/21719-3 - Estudo epidemiológico da dengue (sorotipos 1 a 4) em coorte prospectiva de São José do Rio Preto, São Paulo, Brasil, durante 2014 a 2018
Beneficiário:Maurício Lacerda Nogueira
Linha de fomento: Auxílio à Pesquisa - Temático