Global health has become a multi-billion dollar industry whose product is a set of interventions aimed at decreasing the burden of disease in developing countries. The industry’s emphasis of the MDGs and SDGs on specific disease problems encourage a biomedical, disease-specific approach to tackling ill-health, despite the social-economic-political basis for their persistence.
In recent years, there has been a focus on the utilisation of evidence-based decision-making in global health. While an emphasis on the localisation of this approach is often part of the rhetoric, its realisation has been challenging in practice. The processes of decision-making at different localities are inherently heterogenous and the evidence needs of local practitioners are not well understood.
The LEAD Project addresses these issues with a synergistic approach to evidence development and utilisation between local public health practitioners and researchers at LSE and LSHTM. While there has been some work on knowledge translation for use in global health policy and practice, there is a surprising lack of information on what is actually useful from a practice standpoint, especially from the perspective of local actors. The LEAD Project aims to identify and respond to the needs of local actors by taking advantage of recent technological and computational advances, in particular the processing and identification capabilities of artificial intelligence for application in global health.
The main objectives are to:
- Understand the needs, limitations and challenges faced by local public health practitioners in terms of evidence for decision-making;
- Examine the ability to harness new technologies in computational power and artificial intelligence techniques to localise evidence for decision-making, directly in response and adapted to the needs of local public health practitioners.