Data-driven malaria prevalence prediction in large densely populated urban holoendemic sub-Saharan West Africa

Over 200 million malaria cases globally lead to half-million deaths annually. The development of malaria prevalence prediction systems to support malaria care pathways has been hindered by lack of data, a tendency towards universal “monolithic” models (one-size-fits-all-regions) and a focus on long...

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Detalhes bibliográficos
Publicado no:Sci Rep
Main Authors: Brown, Biobele J., Manescu, Petru, Przybylski, Alexander A., Caccioli, Fabio, Oyinloye, Gbeminiyi, Elmi, Muna, Shaw, Michael J., Pawar, Vijay, Claveau, Remy, Shawe-Taylor, John, Srinivasan, Mandayam A., Afolabi, Nathaniel K., Rees, Geraint, Orimadegun, Adebola E., Ajetunmobi, Wasiu A., Akinkunmi, Francis, Kowobari, Olayinka, Osinusi, Kikelomo, Akinbami, Felix O., Omokhodion, Samuel, Shokunbi, Wuraola A., Lagunju, Ikeoluwa, Sodeinde, Olugbemiro, Fernandez-Reyes, Delmiro
Formato: Artigo
Idioma:Inglês
Publicado em: Nature Publishing Group UK 2020
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Article
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC7522256/
https://ncbi.nlm.nih.gov/pubmed/32985514
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-72575-6
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