Spatiotemporal tools for emerging and endemic disease hotspots in small areas—an analysis of dengue and chikungunya in Barbados, 2013 - 2016

Objective: To detect potential hotspots of transmission of dengue and chikungunya in Barbados, and assess impact of input surveillance data and methodology on observed patterns of risk. Methods: Using two methods of cluster detection, Moran’s I and spatial scan statistics, we analyzed the geospatial and temporal distribution of disease cases and rates across Barbados for dengue fever in 2013-2016, and a 2014 chikungunya outbreak. Results: During years with high numbers of dengue cases, hotspots for cases were found with Moran’s I in south and central regions in 2013 and 2016, respectively. Using smoothed disease rates, clustering was detected every year for dengue. Hotspots were not detected via spatial scan statistics, but coldspots suggesting lower rates of disease activity were found in southwestern Barbados during high case years of dengue. Conclusions: Spatial analysis of surveillance data is useful in identifying outbreak hotspots, complementing existing early warning systems. We caution that these methods should be used in a manner appropriate to available data, and reflecting explicit public health goals—managing for overall case numbers, or targeting anomalous rates for further investigation.