Mshani, I. H. et al. (2023) Key considerations, target product profiles, and research gaps in the application of infrared spectroscopy and artificial intelligence for malaria surveillance and diagnosis. Malaria Journal, 22(1), 346. (doi: 10.1186/s12936-023-04780-3) (PMID:37950315) (PMCID:PMC10638832)
![[img]](https://eprints.gla.ac.uk/style/images/fileicons/text.png) |
Text
311266.pdf - Published Version Available under License Creative Commons Attribution. 1MB |
Abstract
Studies on the applications of infrared (IR) spectroscopy and machine learning (ML) in public health have increased greatly in recent years. These technologies show enormous potential for measuring key parameters of malaria, a disease that still causes about 250 million cases and 620,000 deaths, annually. Multiple studies have demonstrated that the combination of IR spectroscopy and machine learning (ML) can yield accurate predictions of epidemiologically relevant parameters of malaria in both laboratory and field surveys. Proven applications now include determining the age, species, and blood-feeding histories of mosquito vectors as well as detecting malaria parasite infections in both humans and mosquitoes. As the World Health Organization encourages malaria-endemic countries to improve their surveillance-response strategies, it is crucial to consider whether IR and ML techniques are likely to meet the relevant feasibility and cost-effectiveness requirements—and how best they can be deployed. This paper reviews current applications of IR spectroscopy and ML approaches for investigating malaria indicators in both field surveys and laboratory settings, and identifies key research gaps relevant to these applications. Additionally, the article suggests initial target product profiles (TPPs) that should be considered when developing or testing these technologies for use in low-income settings.
| Item Type: | Articles |
|---|---|
| Additional Information: | Support was received from Bill and Melinda Gates Foundation (Grant number Grant No. OPP 1217647 to Ifakara Health Institute), Royal Society (Grant No ICA/R1/191238 to SAB University of Glasgow and Ifakara Health Institute), Rudolf Geigy Foundation through Swiss Tropical & Public Health Institute (to Ifakara Health Institute), Academy Medical Science Springboard Award (ref: SBF007\100094) to FB and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant agreement No. 832703, to KW). |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Baldini, Dr Francesco and Wynne, Professor Klaas and Ferguson, Professor Heather and Mshani, Mr Issa and Babayan, Dr Simon and Siria, Doreen Josen and Gonzalez Jimenez, Dr Mario and Mwanga, Emmanuel |
| Authors: | Mshani, I. H., Siria, D. J., Mwanga, E. P., Sow, B. B., Sanou, R., Opiyo, M., Sikulu-Lord, M. T., Ferguson, H. M., Diabate, A., Wynne, K., González-Jiménez, M., Baldini, F., Babayan, S. A., and Okumu, F. |
| College/School: | College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine College of Science and Engineering > School of Chemistry |
| Journal Name: | Malaria Journal |
| Publisher: | BioMed Central |
| ISSN: | 1475-2875 |
| ISSN (Online): | 1475-2875 |
| Published Online: | 10 November 2023 |
| Copyright Holders: | Copyright © The Author(s) 2023 |
| First Published: | First published in Malaria Journal 22(1):346 |
| Publisher Policy: | Reproduced under a Creative Commons license |
University Staff: Request a correction | Enlighten Editors: Update this record
Funder and Project Information
Funder and Project Information