Papers & Publications
How AI and data can change the fight against Malaria in Kenya
Author: Dr. Lisette Schutte, Solution Lead Epidemic Preparedness, PharmAccess, How AI and data can change the fight against Malaria in Kenya, PharmAccess, Nov 4, 2025
Artificial Intelligence to Connect Private Sector Malaria Diagnosis and Case Reporting in Kisumu County, Kenya
Naomy Onyuka, Lisette Schutte, Nathalie Houben, Alloys K’oloo, Felix Bahati, Lilyana Dayo, Tobias F. Rinke de Wit, Artificial Intelligence to Connect Private Sector Malaria Diagnosis and Case Reporting in Kisumu County, Kenya. AI In Health Africa Conference, Nov 5, 2025
Assessing accuracy and performance: of recording mRDT results, result stability over time, and AI RDT reading, a collection of publications from a 4-country study in Africa
Publication collection for a 4-country operational research study in Benin, Nigeria, Uganda, andCote d'Ivoire. View full collection , BMC, Sprinter Nature November 2025
Highlighted paper: Lindblade, K.A., Mpimbaza, A., Ngufor, C. et al. Assessing the accuracy of the recording and reporting of malaria rapid diagnostic test results in four African countries: methods and key results. Malar J24, 206 (2025). https://doi.org/10.1186/s12936-025-05459-7
Malaria RDT (mRDT) interpretation accuracy by frontline health workers compared to AI in Kano state, Nigeria
Frade S, Cooper S, Smedinghoff S, Hattery D, Ruan Y, Isabelli P, Ravi N, McLaughlin M, Metz, L, Finette B, Malaria RDT (mRDT) interpretation accuracy by frontline health workers compared to AI in Kano state, Nigeria. BMC Digit Health 3, 50 (2025). https://doi.org/10.1186/s44247-025-00190-4
Artificial intelligence (AI)-driven rapid diagnostic test interpretation in a Connected Diagnostics (ConnDx) system for dynamic malaria surveillance
Bahati, F., Owuor, K., Milimo, E., Onyuka, N., K’Oloo, A., Koyuncu, C., Gomez, P., Maricich, N., Frade, S., Smedinghoff, S., Schutte, L., Houben, N., Owino, W., Dayoo, L., Ganda, G., Kariuki, S., Reboud, J., Cooper, J., de Wit, T. Artificial intelligence (AI)-driven rapid diagnostic test interpretation in a Connected Diagnostics (ConnDx) system for dynamic malaria surveillance. BMC Digit Health 3, 62 (2025). https://doi.org/10.1186/s44247-025-00197-x
Task Specific Computer Vision Versus Large Multi-Modal Models for Diagnostic Test Interpretation – A Benchmarking Study [version 1]
Mendonca R, Smedinghoff S, Li B, Gupta K, Ruan Y, Morris S, Isabelli P, Hattery D, Ratevosian J, Mateen B. Task Specific Computer Vision Versus Large Multi-Modal Models for Diagnostic Test Interpretation – A Benchmarking Study[version 1]. VeriXiv 2025, 2:272
(pre-print)
Online delivery of oral HIV pre- and post-exposure prophylaxis: findings from the ePrEP Kenya pilot
Kiptinness, C., Naik, P., Kareithi, T., Thuo, N., Okello, P., Culquichicon, C., Rafferty, M., Abdulrashid, S., Jomo, E., Nyamasyo, N., Wood, T., Mendonca, R., Malen, R.C., Dettinger, J.C., Pintye, J., Mwangi, J., Stergachis, A., Onentia, J., Curran, K., Mugambi, M.L., Were, D., Ngure, K., Sharma, M., Ortblad, K.F. and (2025), Online delivery of oral HIV pre- and post-exposure prophylaxis: findings from the ePrEP Kenya pilot. J Int AIDS Soc., 28: e26468. https://doi.org/10.1002/jia2.26468
Reimagining HIV prevention with artificial intelligence
Jirair Ratevosian, Michael Reid, Zhao Ni, Rouella Mendonca, Robyn Eakle , Cheryl Johnson, Izukanji Sikazwe, Meshack Ndirangu, Solange Baptiste, Linda-Gail Bekker, “Reimagining HIV prevention with artificial intelligence”, 11 June, 2025, The Lancet HIV, Volume 0, Issue 0
Assessing the accuracy of the recording and reporting of malaria rapid diagnostic test results in four African countries: Methods and key results
Kim A. Lindblade, Arthur Mpimbaza2, Corine Ngufor, William Yavo, Sunday Atobatele, Ese Akpiroroh, Abibatou Konate-Toure, Idelphonse Ahogni, Nelson Ssewante, Bosco Agaba, Augustin Kpemasse, Jacques Agnon, Onyebuchi Okoro, Godwin Ntadom, Antoine Tanoh, Cyriaque Affoukou, Jimmy Opigo, Shawna Cooper, John J. Aponte, Kevin Griffith, Radina Soebiyanto, Michael Humes, “Assessing the accuracy of the recording and reporting of malaria rapid diagnostic test results in four African countries: Methods and key results”. Malar J 24, 206 (2025). https://doi.org/10.1186/s12936-025-05459-7
Reform and Renewal: Five Recommendations for PEPFAR
Authors: Ratevosian J, Dow D, Ogbuoji O, Okeke L, Yamey G, Beyrer C; Reviewer: Morris S, "Reform and Renewal: Five Recommendations for PEPFAR" Duke Global Health Institute, Policy Brief, Feb 2025
Generative AI for Health in Low & Middle Income Countries
Hunt I, Parkhouse J, Rich L, Jin K, Imam M, Kim J, Posada M, Lopez M, Ugolnik Z, Soule S, Linos E, "Generative AI for Health in Low & Middle Income Countries" Center for Digital Health, Stanford, April 2025
Announcing the Lancet Global Health Commission on artificial intelligence (AI) and HIV: leveraging AI for equitable and sustainable impact
Reid M, Otieno B, van Heerden A, Sikazwe I, Baptiste S, Mendonca R, Tasi G, Sundaram M, "Announcing the Lancet Global Health Commission on artificial intelligence (AI) and HIV: leveraging AI for equitable and sustainable impact" The Lancet Global Health, Volume 13, Issue 4, e611 - e612
HealthPulse AI: Enhancing Diagnostic Trust and Accessibility in Under-Resourced Settings through AI [version 1]
Frade S, Rech D, Mendonca R, Cooper S, Morris S, Lee H, Gupta K, Sihan Li B, Ruan Y, Hattery D, Marucheck M, Isabelli P, "HealthPulse AI: Enhancing Diagnostic Trust and Accessibility in Under-Resourced Settings through AI" [version 1]. VeriXiv 2025, 2:54
(preprint)
Pilot Results: Elephant Health Nigeria, AI-powered malaria case management
Author: Jonathan Dola-Timothy, Elephant Nigeria, July 2024, Elephant Partners with Audere to increase testing rates for malaria, full Case Study here