Abstract
The World Health Organization recently launched its 2021-2030 roadmap, Ending the Neglect to Attain the Sustainable Development Goals , an updated call to arms to end the suffering caused by neglected tropical diseases. Modelling and quantitative analyses played a significant role in forming these latest goals. In this collection, we discuss the insights, the resulting recommendations and identified challenges of public health modelling for 13 of the target diseases: Chagas disease, dengue, gambiense human African trypanosomiasis (gHAT), lymphatic filariasis (LF), onchocerciasis, rabies, scabies, schistosomiasis, soil-transmitted helminthiases (STH), Taenia solium taeniasis/ cysticercosis, trachoma, visceral leishmaniasis (VL) and yaws. This piece reflects the three cross-cutting themes identified across the collection, regarding the contribution that modelling can make to timelines, programme design, drug development and clinical trials.
Highlights
Taenia solium taeniasis/ cysticercosis, trachoma, visceral leishmaniasis (VL) and yaws. This piece reflects the three cross-cutting themes identified across the collection, regarding the contribution that modelling can make to timelines, programme design, drug development and clinical trials
Whilst leading global health bodies like the World Health Organization (WHO) use modelling results to generate broad guidance at the international level, the truth is that this one-size-fits-all approach is unlikely to sufficiently describe intervention needs in every setting, such that local decision makers may be unsure why interventions – as advised by modelling – have not reached public health targets, when to stop MDA79, or why resurgence occurs
The increased use of mathematical and statistical modelling over the last decade has helped move the field of Neglected Tropical Disease (NTD) into a more quantitative space, providing the link between epidemiological concepts and observed reality
Summary
Taenia solium taeniasis/ cysticercosis, trachoma, visceral leishmaniasis (VL) and yaws. In addition to determining success or failure within the defined intervention time frames, modelling has provided insights into key factors of operational design like the treatment coverage necessary to reach goals in a given setting Where it may not be possible, models can be used to test the efficacy of separate and combined chemotherapeutic[37] and non-pharmaceutical interventions[23,45,46], including combined interventions that target multi-host systems for zoonotic NTDs14. Whilst leading global health bodies like the WHO use modelling results to generate broad guidance at the international level, the truth is that this one-size-fits-all approach is unlikely to sufficiently describe intervention needs in every setting, such that local decision makers may be unsure why interventions – as advised by modelling – have not reached public health targets, when to stop MDA79, or why resurgence occurs. It is imperative to balance the availability of tools at local scales with the expertise to use the models correctly
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