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Incorporating Herd Immunity Effects into Cohort Models of Vaccine Cost-Effectiveness

Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada

Andrea M. Anonychuk, MSc

Statistics and Epidemiology, GlaxoSmithKline Canada, Mississauga, Ontario, Canada, Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, Ontario, Canada

Thierry Van Effelterre, PhD

World-wide Bio Epidemiology, GlaxoSmithKline Biologicals, Rixensart, Belgium

Ba' Z. Pham, MSc

Department of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada

Maraki Fikre Merid, MSc

Department of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada

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.

Key Words: dynamic model • cohort model • universal vaccination • cost-effectiveness analysis • herd immunity • decision modeling.

This version was published on September 1, 2009

Medical Decision Making, Vol. 29, No. 5, 557-569 (2009)
DOI: 10.1177/0272989X09334419


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