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Abstract

River blindness is a parasitic disease caused by infection with the (very long-lived) filarial nematode Onchocerca volvulus. Onchocerciasis, is transmitted by (Simulium) blackflies and there is no known zoonotic reservoir of the human parasite. The name river blindness reflects that onchocerciasis can lead to irreversible blindness and vectors breed in fast flowing rivers and rapids. Onchocerciasis is distributed in Latin American countries (from Mexico to Brazil), in sub-Saharan Africa (from West to East) and Yemen. Most cases occur in Africa. Internationally-funded control programmes based on vector control (aerial application of larvicidal insecticides on vector breeding grounds in West African rivers) started in the early 1970’s, when there were no safe medications to treat human populations. In the late 1980’s, the broad-spectrum antiparasitic drug ivermectin (which was used in veterinary medicine) was approved for human treatment. Mass ivermectin administration campaigns started in earnest to complement or replace vector control. These campaigns were expanded to the remaining endemic countries in mid- to late 1990’s. Some evidence of onchocerciasis elimination by prolonged (annual or 6-monthly) ivermectin treatment alone emerged in a number of foci. As a result, the international control programmes shifted their focus from control of morbidity (eliminating blindness incidence) to elimination of transmission. The World Health Organization (WHO), supported by the London Declaration on Neglected Tropical Diseases (NTDs) in January 2012, launched a roadmap for the control and elimination of priority NTDs for the period 2012–2020. Recently, the WHO launched a consultation process to update this roadmap post-2020 with 2030 and beyond in the horizon. Transmission dynamics models of onchocerciasis have been used to aid control programmes since the late 1980’s. The first, stochastic ONCHOSIM model, was widely used. We have developed another model, EPIONCHO, starting with a deterministic version and generating an individual-based analogue, EPIONCHO-IBM. In this talk, I will describe how we came to develop and parameterise EPIONCHO using independent epidemiological, parasitological, entomological, and treatment datasets. I will discuss the impact of parametric and structural assumptions and how these influence transmission dynamics under long-term ivermectin treatment, as well as the reasons for the different probabilities of elimination that are predicted by ONCHOSIM and EPIONCHO/EPIONCHO-IBM. Finally, I will highlight areas of uncertainty inherent in crucial parasite population biology assumptions, identify data gaps, and discuss how we think some of these gaps could be narrowed by much needed field and laboratory studies blended with mathematical modelling and model fitting to longitudinal studies.