| Full text | |
| Author(s): |
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]
Total Authors: 9
|
| Affiliation: | [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
Total Affiliations: 3
|
| Document type: | Journal article |
| Source: | Revista Panamericana de Salud Pública = Pan American Journal of Public Health; v. 41, 2017. |
| Web of Science Citations: | 0 |
| Abstract | |
ABSTRACT 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 São José do Rio Preto (São Paulo, Brazil). The geographical coordinates were obtained using QGIS™ (Creative Commons Corporation, Mountain View, California, United States), based on patient addresses in the dengue notification system of the Government of Brazil. SaTScan™ (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™ 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) | |
| FAPESP's process: | 13/21719-3 - Epidemiological study of dengue (serotypes1-4) in a cohort of São José do Rio Preto, São Paulo, Brazil, during 2014-2018 |
| Grantee: | Maurício Lacerda Nogueira |
| Support Opportunities: | Research Projects - Thematic Grants |