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Data-driven identification of communities with high levels of tuberculosis infection in the Democratic Republic of Congo.
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Document type | Article de périodique (Journal article) – Article de recherche |
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Access type | Accès libre |
Publication date | 2022 |
Language | Anglais |
Journal information | "Scientific reports" - Vol. 12, no.1, p. 3912 [1-10] (2022) |
Peer reviewed | yes |
Publisher | Nature Publishing Group ((United Kingdom) London) |
e-issn | 2045-2322 |
Publication status | Publié |
Affiliations |
UCL
- SSS/IREC/MBLG - Pôle de Microbiologie médicale UCL - SST/ICTM - Institute of Information and Communication Technologies, Electronics and Applied Mathematics |
MESH Subject | Democratic Republic of the Congo ; Humans ; Incidence ; Latent Tuberculosis ; Prospective Studies ; Tuberculosis |
Links |
Bibliographic reference | Faccin, Mauro ; Rusumba, Olivier ; Ushindi, Alfred ; Riziki, Mireille ; Habiragi, Tresor ; et. al. Data-driven identification of communities with high levels of tuberculosis infection in the Democratic Republic of Congo.. In: Scientific reports, Vol. 12, no.1, p. 3912 [1-10] (2022) |
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Permanent URL | http://hdl.handle.net/2078.1/277581 |