Crowdsourced surveillance for neglected tropical diseases, Nigeria
Our surveillance method outperformed traditional surveillance, showing its promise for enhancing neglected tropical disease surveillance. The method's ability to detect emerging conditions and support post-elimination surveillance reinforces its value.
Authors
- David Chinaecherem Innocent (ORCID: https://orcid.org/0000-0002-2463-2681)
- Joshua Chisom Ogboeze
- Chidera Chisom Obasi (ORCID: https://orcid.org/0000-0002-0208-2295)
- Uchechukwu Madukaku Chukwuocha (ORCID: https://orcid.org/0000-0002-4986-6847)
- Obiageli J. Nebe (ORCID: https://orcid.org/0000-0002-5032-4236)
- S.O. Sam-Wobo (ORCID: https://orcid.org/0000-0003-0185-9012)
- Ayoola Oluwaseun Bosede (ORCID: https://orcid.org/0000-0002-6670-6087)
- Akajiaku C. Chukwuocha (ORCID: https://orcid.org/0000-0001-9381-0771)
- Christopher Sule Oyamienlen
- Ikechukwu Nosike Simplicius Dozie
- C.N. Ukaga
- B. E. B. Nwoke
Institutions
- Federal University of Technology Owerri (NG)
- Imo State University (NG)
- Federal University of Agriculture, Abeokuta (NG)
- Federal Ministry of Health (NG)
- Kingsley House (US)
Publication Details
- Journal
- Bulletin of the World Health Organization
- Published
- 2025-12-01
- DOI
- https://doi.org/10.2471/blt.24.292448
- Citations
- 1
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 1.35
Funders
- Bill and Melinda Gates Foundation
- Bundesministerium für Gesundheit