Inferring the regional distribution of Visceral Leishmaniasis incidence from data at different spatial scales

• Published in: Communications medicine 2024-11, Vol.4 (1), p.240-10, Article 240
• Main Authors: Nightingale, Emily S., Subramanian, Swaminathan, Schwarzer, Ashley R., Chapman, Lloyd A. C., Jambulingam, Purushothaman, Cameron, Mary M., Brady, Oliver J., Medley, Graham F., Lucas, Tim C. D.
• Format: Article
• Language: English
• Subjects: 692/699/255; 692/700/478/174; Medicine; Medicine & Public Health; Parasitic diseases; Polygons; Surveillance; Towns; Tropical diseases; Vegetation
• ISSN: 2730-664X; 2730-664X
• DOI: 10.1038/s43856-024-00659-9

Background As cases of visceral leishmaniasis (VL) in India dwindle, there is motivation to monitor elimination progress on a finer geographic scale than sub-district (block). Low-incidence projections across geographically- and demographically- heterogeneous communities are difficult to act upon, and equitable elimination cannot be achieved if local pockets of incidence are overlooked. However, maintaining consistent surveillance at this scale is resource-intensive and not sustainable in the long-term. Methods We analysed VL incidence across 45,000 villages in Bihar state, exploring spatial autocorrelation and associations with local environmental conditions in order to assess the feasibility of inference at this scale. We evaluated a statistical disaggregation approach to infer finer spatial variation from routinely-collected, block-level data, validating against observed village-level incidence. Results This disaggregation approach does not estimate village-level incidence more accurately than a baseline assumption of block-homogeneity. Spatial auto-correlation is evident on a block-level but weak between neighbouring villages within the same block, possibly suggesting that longer-range transmission (e.g., due to population movement) may be an important contributor to village-level heterogeneity. Conclusions Increasing the range of reactive interventions to neighbouring villages may not improve their efficacy in suppressing transmission, but maintaining surveillance and diagnostic capacity in areas distant from recently observed cases - particularly along routes of population movement from endemic regions - could reduce reintroduction risk in currently unaffected villages. The reactive, spatially-targeted approach to VL surveillance limits interpretability of data observed at the village level, and hence the feasibility of routinely drawing and validating inference at this scale. Plain Language Summary Near elimination, it is important to understand how the remaining cases of disease are distributed on a local level. However, surveillance data are more easily collated according to larger administrative units. We investigated whether village-level patterns of visceral leishmaniasis (VL) incidence could be inferred from administrative-level data using a statistical modelling approach. We found strong similarity in incidence between neighbouring administrative units but not between neighbouring villages, and model predictions did not correspond well to obs