02431nas a2200193   4500000000100000008004100001260003700042100001500079700001400094700001600108700001300124700001200137245009500149856010300244300001300347490000700360520185600367022001402223       2025                            d  bPublic Library of Science (PLoS)1 aStapley JN1 aHamley JI1 aBasáñez M1 aWalker M1 aDavis E00aModelling transmission thresholds and hypoendemic stability for onchocerciasis elimination  uhttps://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1013026&type=printable  ae10130260 v213 a<p>The World Health Organization (WHO) has proposed elimination of onchocerciasis transmission (EOT) in a third of endemic countries by 2030. This requires country-wide verification of EOT. Prior to the shift from morbidity control to EOT, interventions in Africa were mostly targeted at moderate- to high-transmission settings, where morbidity was most severe. Consequently, there remain numerous low transmission (hypoendemic) settings which have hitherto not received mass drug administration (MDA) with ivermectin. The WHO has prioritised the delineation of hypoendemic settings to ascertain treatment needs. However, the stability of transmission at such low levels remains poorly understood. We use the stochastic EPIONCHO-IBM transmission model to characterise the stability of transmission dynamics in hypoendemic settings and identify a range of threshold biting rates (TBRs, the annual vector biting rates below which transmission cannot be sustained). We show how TBRs are dependent on population size, inter-individual exposure heterogeneity and simulation time. In contrast with deterministic expectations, there is no fixed TBR; instead, transmission can persist between 70 and 300 bites/person/year. Using survivorship models on data generated from model simulations, we find that multiple vector biting rates can sustain hypoendemic prevalence for several decades. These findings challenge the assumption that hypoendemic foci would naturally fade out following treatment in nearby higher-endemicity regions. Our modelling suggests that, to achieve EOT, treatment should be extended to all areas where endogenous infection is identified, emphasising the need for improved diagnostic tools suitable for detecting low-prevalence infection and for strategies that allow safe treatment of communities where MDA would not be suitable.</p>
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