Mathematical models simulating infectious diseases have become essential sources of evidence in support of policy decisions at all levels across the world. However, similar models describing non-communicable diseases (NCDs) lag severely behind, and their ability to become a critical component of the policy process has yet to be demonstrated.
We created Health-GPS, an innovative tool capable of forecasting the dynamic risks of acquiring NCDs to aid global policy development and implementation. Health-GPS is a microsimulation-based model able to describe NCD dynamics and capture the complex interactions between risk factors and disease.
Through reconciling a wide range of data, the model has the potential to accurately estimate the impact of piloted interventions across a given population. However, microsimulations remain underutilised tools by NCD decision makers.
To address this, Health-GPS was designed to be flexible, it can be used to test specific hypotheses; transparent, it was developed with a simple modular design allowing it to be easily expanded with new capabilities; efficient, it can run on multiple platforms and on high-performance environments; and finally, accessible, the model is open-source and a web-based user-interface is under development.
Our results illustrate the potential of Health-GPS, but more work is required to convince policy experts of the utility and accuracy of these models for supporting the decision-making process.