A Collaborative Approach to the Analysis of the COVID-19 Response in Africa
This addresses the problem of limited machine learning competencies and infrastructure in Africa for pandemic response, but it appears incremental as it builds on existing collaborative methods.
The paper tackled the challenge of applying machine learning to COVID-19 in Africa by proposing a cross-border collaborative capacity building approach, resulting in a demonstration of its application to discover answers to COVID-19 questions.
The COVID-19 crisis has emphasized the need for scientific methods such as machine learning to speed up the discovery of solutions to the pandemic. Harnessing machine learning techniques requires quality data, skilled personnel and advanced compute infrastructure. In Africa, however, machine learning competencies and compute infrastructures are limited. This paper demonstrates a cross-border collaborative capacity building approach to the application of machine learning techniques in discovering answers to COVID-19 questions.