Spatiotemporal-based clusters as a method for dengue surveillance

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.