Strengthening data collection for neglected tropical diseases: What data are needed for models to better inform tailored intervention programmes?

Locally tailored interventions for neglected tropical diseases (NTDs) are becoming increasingly important for ensuring that the World Health Organization (WHO) goals for control and elimination are reached. Mathematical models, such as those developed by the NTD Modelling Consortium, are able to off...

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Bibliographic Details
Published in:PLOS Neglected Tropical Diseases
Main Authors: Jaspreet Toor, Jonathan I D Hamley, Claudio Fronterre, María Soledad Castaño, Lloyd A C Chapman, Luc E Coffeng, Federica Giardina, Thomas M Lietman, Edwin Michael, Amy Pinsent, Epke A Le Rutte, T Déirdre Hollingsworth
Format: Article in Journal/Newspaper
Language:English
Published: Public Library of Science (PLoS) 2021
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Online Access:https://doi.org/10.1371/journal.pntd.0009351
https://doaj.org/article/75055111fbfe436383f7ce38a4420ecd
Description
Summary:Locally tailored interventions for neglected tropical diseases (NTDs) are becoming increasingly important for ensuring that the World Health Organization (WHO) goals for control and elimination are reached. Mathematical models, such as those developed by the NTD Modelling Consortium, are able to offer recommendations on interventions but remain constrained by the data currently available. Data collection for NTDs needs to be strengthened as better data are required to indirectly inform transmission in an area. Addressing specific data needs will improve our modelling recommendations, enabling more accurate tailoring of interventions and assessment of their progress. In this collection, we discuss the data needs for several NTDs, specifically gambiense human African trypanosomiasis, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminths (STH), trachoma, and visceral leishmaniasis. Similarities in the data needs for these NTDs highlight the potential for integration across these diseases and where possible, a wider spectrum of diseases.