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Background: Dengue and chikungunya are mosquito-borne viral diseases that are of public health importance throughout the tropical and subtropical regions of the world. Seasonal variations in transmission of these viruses have been suggested owing to the ecology of their mosquito vectors. However, little is known about the epidemiology of the diseases Tanzania. To address this gap, seasonal community-based cross-sectional surveys were undertaken to identify potential clusters of transmission in Hai district in northern Tanzania. Methods: Epidemiological and entomological data from two cross-sectional surveys were used to examine the spatial pattern of dengue and chikungunya transmission. Six villages namely, Boma Ng’ombe, Magadini, Rundugai, Nshara and Kware were involved in the study. Serological measures of dengue and chikungunya virus infections were derived using enzyme-linked immunosorbent assays, and all participants were geo-referenced to the household level using a global positioning system. Potential clusters of individual exposed to dengue and chikungunya virus , as well as clusters of Aedes mosquitoes in the wet and dry seasons were detected using SaTScan. All significant clusters (with p≤0.05) were mapped using ArcGIS. Results: A large, widely dispersed cluster of chikungunya exposed individuals was detected spanning Rundugai and parts of Magadini villages (RR = 2.58,  p= 0.01), while no significant clustering was observed in the dry season. Spatial clusters of Aedes aegypti were detected in Rundugai in both the wet and dry seasons (RR = 2.56, p< 0.001 and RR = 2.24, p=0.05, respectively). In the dry season a small cluster was also detected in Kware (RR = 2.25, p=0.05). No significant clusters of dengue were detected in both seasons. Conclusion: Clusters of chikungunya-exposed individuals and Aedes mosquitoes indicate on-going transmission of chikungunya virus in Hai district of northern Tanzania.

Mapping clusters of chikungunya and dengue transmission in northern Tanzania using disease exposure and vector data