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1.
Afr Health Sci ; 22(1): 664-672, 2022 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-36032450

RESUMO

This paper presents voices from Africa on digital health in Africa. These voices were gleaned during interviews and an online, focus group session in May 2020, during which 30 experts across Africa, among others from the South, were asked about their experiences and observations on the conceptualisation of, and practices in, digital health in their respective communities and countries. Extensive input was provided, both orally and textually. The quotes gathered and presented in this paper indicate that there is a distinct need for the respectful co-development of digital health interventions in Africa. In addition, the quotes show how a one-size-fits-all solution approach does not exist, it is not a solution to Africa. Further, the community-focus, fit, and fragmentation of existing activities digital health interventions is questioned. The narratives provide a rich resource indicating capable and local agency and the need to address power-differences in international health development.


Assuntos
Formação de Conceito , África , Grupos Focais , Humanos , África do Sul
2.
Adv Genet (Hoboken) ; 2(2): e10050, 2021 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-34514430

RESUMO

The limited volume of COVID-19 data from Africa raises concerns for global genome research, which requires a diversity of genotypes for accurate disease prediction, including on the provenance of the new SARS-CoV-2 mutations. The Virus Outbreak Data Network (VODAN)-Africa studied the possibility of increasing the production of clinical data, finding concerns about data ownership, and the limited use of health data for quality treatment at point of care. To address this, VODAN Africa developed an architecture to record clinical health data and research data collected on the incidence of COVID-19, producing these as human- and machine-readable data objects in a distributed architecture of locally governed, linked, human- and machine-readable data. This architecture supports analytics at the point of care and-through data visiting, across facilities-for generic analytics. An algorithm was run across FAIR Data Points to visit the distributed data and produce aggregate findings. The FAIR data architecture is deployed in Uganda, Ethiopia, Liberia, Nigeria, Kenya, Somalia, Tanzania, Zimbabwe, and Tunisia.

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