| dc.description.abstract | The emergence of the COVID-19 global pandemic presents serious health and livelihood threats to people in low- and middle-income countries (LMICs) all over the world. There is an urgent need for accurate, real-time data for health policy and planning to combat the threats. In many countries there are methodological gaps in data integration and a lack of information and research capacity to make informed decisions to guide public health policy. The absence of data also makes it difficult to identify vulnerable populations and provide appropriate information to protect and improve people's health. Moreover, obtaining information can be especially difficult under the restrictions of pandemic lockdowns.
Current innovations in AI and data science can support the collection and analysis of real-time, accurate data from multiple data sources. This project proposes to develop the key elements of a coordinated pan-African COVID-19 data ecosystem with a robust suite of data standards, technologies, and data integration methods that leverage AI and data science for analysis and oversight. It will focus on data from Kenya and Malawi because both countries adopted different strategies to combat the COVID-19 pandemic. The goal is to scale the dissemination of information to enhance decision-making and guide the development and implementation of strategies to reduce morbidity and mortality from COVID-19.
The project is developing a network of stakeholders to exchange information, experiences, and knowledge that will support data acquisition, management, governance, and reporting; a data tracking system; a common data model; and a comprehensive data hub for COVID-19 data to demonstrate how COVID-19 is affecting transmission dynamics, its impact on health, education, work, transport, and effective interventions. It will also enhance the methodological capacity of data analysts and develop communication strategies for the public, policymakers, and decision-makers. | |
