Analyzing the cost-effectiveness of Lyme disease risk reduction approaches

Abstract

Lyme disease (LD) is endemic in many regions of the Northeastern United States. Given the elusive nature of the disease, a systematic approach to identify efficient interventions would be useful for policymakers in addressing LD. We used Markov modeling to investigate the efficiency of interventions. These interventions range from awareness-based to behavioral-based strategies. Targeting animal reservoirs of LD using fungal spray or bait boxes did not prove to be an effective intervention. Results of awareness-based interventions, including distribution of signage, fliers, and presentations, implementable in different geographical scales, suggest that policymakers should focus on these interventions, as they are both cost-effective and have the highest impact on lowering LD risk. Populations may lose focus of LD warnings over time, thus quick succession of these interventions is vital. Our modeling results identify the awareness-based intervention as the most cost-effective strategy to lower the number of LD cases. These results can aid in the establishment of effective LD risk reduction policy at various scales of implementation.

Keywords: Health policy analysis; Markov modeling; Risk assessment; Simulation.