Design of a FAIR digital data health infrastructure in Africa for COVID-19 reporting and research

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.Computer Systems, Imagery and Medi

Mobile health data collection at primary health care in Ethiopia: a feasible challenge

OBJECTIVES: Feasibility assessment of mobile health (mHealth) data collection at primary health care in Ethiopia. STUDY DESIGN AND SETTING: A total of 14 health workers were recruited from 12 primary health care facilities to use smartphones, installed with customized data collection application and electronic maternal health care forms for assessing pregnant women's health for 6 months. Qualitative approaches comprising in-depth interviews and field notes were used to document the users' perception and experience in using the application and forms. RESULTS: All health workers had never had previous exposure to smartphones and electronic forms, but they got used to them easily. Over 6 months, all health workers completed a total of 952 patient records using the forms on smartphones. Health workers' acceptability and demand for the application and forms were high. In introducing the application, nontechnical challenges were more difficult to solve than technical challenges. CONCLUSION: Introducing an mHealth application at primary health care for routine collection of health data relevant to maternal health at a small scale was feasible. Nonetheless, implementing a system of assigning unique and consistent patient identifier, standardization of health services, and improving mobile network coverage would be prerequisites for scaled-up usage of such an application