Abstract
BackgroundAn improved understanding in transmission variation of kala-azar is fundamental to conduct surveillance and implementing disease prevention strategies. This study investigated the spatio-temporal patterns and hotspot detection for reporting kala-azar cases in Vaishali district based on spatial statistical analysis.MethodsEpidemiological data from the study area during 2007–2011 was used to examine the dynamic space-time pattern of kala-azar outbreaks, and all cases were geocoded at a village level. Spatial smoothing was applied to reduce random noise in the data. Inverse distance weighting (IDW) is used to interpolate and predict the pattern of VL cases distribution across the district. Moran’s I Index (Moran’s I) statistics was used to evaluate autocorrelation in kala-azar spatial distribution and test how villages were clustered or dispersed in space. Getis-Ord Gi*(d) was used to identify the hotspot and cold spot areas within the study site.ResultsMapping kala-azar cases or incidences reflects the spatial heterogeneity in the incidence rate of kala-azar affected villages in Vaishali district. Kala-azar incidence rate map showed most of the highest endemic villages were located in southern, eastern and northwestern part of the district; in the middle part of the district generally show the medium occurrence of VL. There was a significant positive spatial autocorrelation of kala-azar incidences for five consecutive years, with Moran’s I statistic ranging from 0.04-0.17 (P <0.01). The results revealed spatially clustered patterns with significant differences by village. The hotspots showed the spatial trend of kala-azar diffusion (P < 0.01).ConclusionsThe results pointed to the usefulness of spatial statistical approach to improve our understanding the spatio-temporal dynamics and control of kala-azar. The study also showed the north-western and southern part of Vaishali district is most likely endemic cluster region. To employ exact and geographically suitable risk-reduction programmes, apply of such spatial analysis tools should suit a vital constituent in epidemiology research and risk evaluation of kala-azar.
Highlights
Spatial analysis Mapping kala-azar cases or incidences reflects the spatial heterogeneity in the incidence rate of kala-azar affected villages in Vaishali district
The high and/or low visceral leishmaniais (VL) affected villages are not distributed uniformly in the study area, but they are strongly clustered in some particular parts across the district
This study reveals the spatial and temporal characteristics of kala-azar disease in Vaishali district of Bihar (India) using GIS tools and spatial statistical analysis, which allow for the quantification of the degree of clustering of VL infections
Summary
Fisher NI, Lewis T, Embleton BJJ: Statistical analysis of spherical data. An improved understanding in transmission variation of kala-azar is fundamental to conduct surveillance and implementing disease prevention strategies. This study investigated the spatio-temporal patterns and hotspot detection for reporting kala-azar cases in Vaishali district based on spatial statistical analysis. Kala-azar or visceral leishmaniais (VL) is one of the leading causes of morbidity and mortality in Bihar, India [1,2]. In the Indian subcontinent, passive surveillance system in 2007–2011 from the district only. The district accounted for >5 percent of total kalaazar cases reported from Bihar, and disease transmission in the district appeared the major focus fueling a sustained epidemic. The incidence of kala-azar shows high variability within the district
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