Published in:
Open Access 01-12-2012 | Research article
Analyzing the spatial and temporal distribution of human brucellosis in Azerbaijan (1995 - 2009) using spatial and spatio-temporal statistics
Published in: BMC Infectious Diseases | Issue 1/2012
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Background
Human brucellosis represents a significant burden to public and veterinary health globally, including the republic of Azerbaijan. The purpose of this study was to examine and describe the spatial and temporal aspects of the epidemiology of human brucellosis in Azerbaijan from 1995 to 2009.
Methods
A Geographic information system (GIS) was used to identify potential changes in the spatial and temporal distribution of human brucellosis in Azerbaijan during the study period. Epidemiological information on the age, gender, date, and location of incident cases were obtained from disease registries housed at the Republican Anti-Plague station in Baku. Cumulative incidences per 100,000 populations were calculated at the district level for three, 5-year periods. Spatial and temporal cluster analyses were performed using the Local Moran’s I and the Ederer-Myer-Mantel (EMM) test.
Results
A total of 7,983 cases of human brucellosis were reported during the 15-year study period. Statistically significant spatial clusters were identified in each of three, five year time periods with cumulative incidence rates ranging from 101.1 (95% CI: 82.8, 124.3) to 203.0 (95% CI; 176.4, 234.8). Spatial clustering was predominant in the west early in the study during period 1 and then in the east during periods 2 and 3. The EMM test identified a greater number of statistically significant temporal clusters in period 1 (1995 to 1999).
Conclusion
These results suggest that human brucellosis persisted annually in Azerbaijan across the study period. The current situation necessitates the development of appropriate surveillance aimed at improving control and mitigation strategies in order to help alleviate the current burden of disease on the population. Areas of concern identified as clusters by the spatial-temporal statistical analyses can provide a starting point for implementing targeted intervention efforts.