Leveraging Artificial Intelligence and Data Science Techniques in Harmonizing, Accessing and Analysing SARS-COV-2/COVID-19 Data in Rwanda (LAISDAR Project)
The SARS-COV-2/COVID-19 data has the potential to transform our disease understanding and advance science but also to understand outcomes which enable efficient preventive or treatment measure.
However, in Rwanda like in other countries this data is currently fragmented, incomplete and scattered across multiple institutions including hospitals, clinics and testing sites that have captured vast amounts of data on the disease.
Analysing those fragmented COVID-19, datasets brings poor evidence. Pooling all those datasets together in one single dataset is challenging as they have different data structure and data owner may fear break in data privacy. Therefore, we need an innovative approach to analysed all data together.