OBJECTIVES

Meningococcal disease is contagious and rare in the United States but results in severe consequences. Over 35 cases occurred on college campuses in the last five years. Two new vaccines became available in 2015 that target serogroup B (MenB), the serogroup most commonly affecting adolescents. We assessed cost-effectiveness of mandatory vaccination for college students relative to no preemptive vaccination.

METHODS

We constructed a decision analytic model to compare costs and outcomes in two cohorts of 1,400 entering college students over a 4-year time horizon (typical enrollment interval) with and without preemptive vaccination. Base case probability of contracting MenB was reported 2016 incidence among college students age 16-24 (0.23 per 100,000). Vaccine characteristics reflected a composite of both marketed vaccines obtained from package inserts and literature. Modeled course of treatment, clinical events, and response to outbreaks were sourced from published reports. Costs and benefits reflected a health system perspective (university health service) and were discounted at 3%. Sensitivity analysis further accounted for uncertainty in probabilities, costs, and disutility weights.

RESULTS

Using our base case estimates and a 4-year time horizon, we calculated the expected discounted cost of prevention and treatment to be $466,000 in the MenB vaccination group and $6,159 vaccinating only after an outbreak. The expected number of MenB cases was 0.007 versus 0.013, respectively. Incremental cost per MenB case avoided (ICER) was $79.3 million. With sensitivity analysis, increasing the MenB incidence by a factor of 10 reduced the ICER to $7.0 million. Reducing the vaccine cost by 50% decreased ICER to $28.0 million. All conclusions were upheld under the complete range of sensitivity analysis.

CONCLUSIONS

Mandatory vaccination with the MenB vaccine does not appear to be cost-effective from a health system perspective. The greatest driver of its unsuitability appears to be the extremely low chance of infection in existing disease surveillance data.