Prevention and treatment approaches to public health: what can we learn from simulations?

A longstanding question in public health relates to the most effective allocation of resources to reduce the population burden of disease. The debate often centers on the relative contribution that primary prevention of the causes of disease, versus medical care services to treat disease sequelae, make to population health. We will use simulation approaches to answer this question from the perspective of different types of diseases. Topics include: (1) identifying the disease prevalence threshold at which treatment becomes more cost-effective than prevention, as applied to the case of malaria; (2) strategies to adapt prevention and treatment antiviral-based strategies to an epidemic’s phase to maximize reductions in HIV incidence; (3) optimum combinations of prevention and treatment packages to reduce the prevalence of psychiatric disorders in urban areas; and (4) the use of genetic prediction for personalized medicine.

We hope this set of presentations can serve as a starting point for discussion on the types of policy-relevant questions we need to answer in epidemiology, the advantages and limitations of the simulation approach to identify policy solutions, and the new directions we should pursue in the use of epidemiology to inform public health policy.