Journal article
Strengthening data collection for neglected tropical diseases: what data are needed for models to better inform tailored intervention programmes?
- Abstract:
- 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 839.3KB, Terms of use)
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- Publisher copy:
- 10.1371/journal.pntd.0009351
Authors
- Publisher:
- Public Library of Science
- Journal:
- PLoS Neglected Tropical Diseases More from this journal
- Volume:
- 15
- Issue:
- 5
- Article number:
- e0009351
- Place of publication:
- United States
- Publication date:
- 2021-05-13
- DOI:
- EISSN:
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1935-2735
- ISSN:
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1935-2727
- Pmid:
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33983937
- Language:
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English
- Keywords:
- Pubs id:
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1176825
- Local pid:
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pubs:1176825
- Deposit date:
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2021-10-06
- ARK identifier:
Terms of use
- Copyright holder:
- Toor et al.
- Copyright date:
- 2021
- Rights statement:
- ©2021 Toor et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
- Licence:
- CC Attribution (CC BY)
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