From survey and routine surveillance data, through to satellite imagery and cell phone data records, there is a vast, and growing, amount of data which could benefit health programs. In industry, the application of machine learning and AI is becoming an indispensable tool to extract useful information from data. However, most global health programs don’t have similar access to the resources and expertise required to implement these kinds of solutions. As such, opportunities to use data to improve the performance of health programs are missed.
We believe that the provision of algorithms-as-a-service (AaaS) offers an opportunity to address this gap. Such an approach removes barriers to entry, allowing disease programs with limited expertise in data science to apply algorithms to their data and gain otherwise unobtainable insights.
For a further discussion of the technical and institutional considerations related to the development of AaaS for global health, see our article here (coming!).