Spatial patterns of black fly (Simulium damnosum s.l.) dispersal in Ghana and Benin and their implications for onchocerciasis surveillance

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Background Entomological surveillance for onchocerciasis is closely linked to riverine environments where black fly vectors breed. Relying solely on this xenomonitoring method may underestimate exposure risk in communities further away, as black flies can disperse over hundreds of kilometres. As endemic countries aim for elimination, understanding spatial heterogeneities in entomological indices is crucial. Methods We therefore conducted spatially explicit entomological surveys around two historical breeding sites: Bétérou in Benin and Asubende in Ghana, during the 2023 and 2024 wet seasons. Using a radial sampling design, 40 settlements within 25 km around each site were selected. black flies were collected via Human Landing Catches at both breeding sites and settlements, and one Esperanza Window Trap at each settlement. Black flies were identified morphologically; biting rates were calculated relative to sampling effort; parity assessed by dissection; and parasite presence determined through O-150 PCR pool-screening and dissection. Generalised Additive Models described trends in entomological indices over distance. Results A total of 76,050 black flies was collected over 656 sampling days, primarily in Bétérou. In Bétérou, black fly counts and biting rates generally declined with increasing distance from the breeding site, though notable spatial variation was observed. Positive O-150 PCR pools were found at 31 of 41 sites, with infective flies detected up to 19 km from the breeding site. Bétérou exceeded the WHO infectivity prevalence threshold for interrupted transmission in 2023 (0.11%) and 2024 (0.08%). Parous rates remained relatively constant across distance. In Asubende, similar trends were observed, but low catches limited trend analysis, and no infective flies were detected via PCR. Conclusions These findings demonstrate that black fly dispersal and infectivity capable of sustaining transmission extend beyond breeding sites and first-line villages. This underscores the importance of broader, spatially extensive vector sampling to better evaluate transmission patterns and inform elimination efforts. To gain deeper understanding of the underlying spatial dynamics beyond descriptive trend analysis, comprehensive spatial–temporal modelling is required.