Background. Cohort models are often used in cost-effectiveness analysis (CEA) of vaccination. However, because they cannot capture herd immunity effects, cohort models underestimate the reduction in incidence caused by vaccination. Dynamic models capture herd immunity effects but are often not adopted in vaccine CEA. Objective. The objective was to develop a pseudo-dynamic approximation that can be incorporated into an existing cohort model to capture herd immunity effects. Methods. The authors approximated changing force of infection due to universal vaccination for a pediatric infectious disease. The projected lifetime cases in a cohort were compared under 1) a cohort model, 2) a cohort model with pseudo-dynamic approximation, and 3) an age-structured susceptible-exposed-infectious-recovered compartmental (dynamic) model. The authors extended the methodology to sexually transmitted infections. Results. For average to high values of vaccine coverage (P > 60%) and small to average values of the basic reproduction number (R 0 < 10), which describes school-based vaccination programs for many common infections, the pseudo-dynamic approximation significantly improved projected lifetime cases and was close to projections of the full dynamic model. For large values of R0 (R0 > 15), projected lifetime cases were similar under the dynamic model and the cohort model, both with and without pseudo-dynamic approximation. The approximation captures changes in the mean age at infection in the 1st vaccinated cohort. Conclusions. This methodology allows for preliminary assessment of herd immunity effects on CEA of universal vaccination for pediatric infectious diseases. The method requires simple adjustments to an existing cohort model and less data than a full dynamic model.
Fully dynamic approximation of LIS in polylogarithmic time
