Geoffrey Rose's two principal approaches to public health intervention are (1) targeted strategies focusing on individuals at a personal increased risk of disease and (2) population-wide approaches focusing on the whole population. Beyond his discussion of the strengths and weaknesses of these approaches, there is no empiric work examining the conditions under which one of these approaches may be better than the other.Methods
This article uses mathematical simulations to model the benefits and costs of the two approaches, varying the cut points for treatment, effect magnitudes, and costs of the interventions. These techniques then were applied to the specific example of an intervention on blood pressure to reduce cardiovascular disease.Findings
In the general simulation (using an inverse logit risk curve), lower costs of intervention, treating people with risk factor values at or above where the slope on the risk curve is at its steepest (for targeted interventions), and interventions with larger effects on reducing the risk factor (for population-wide interventions) provided benefit/cost advantages. In the specific blood pressure intervention example, lower-cost population-wide interventions had better benefit/cost ratios, but some targeted treatments with lower cutoffs prevented more absolute cases of disease.Conclusions
These simulations empirically evaluate some of Rose's original arguments. They can be replicated for particular interventions being considered and may be useful in helping public health decision makers assess potential intervention strategies.