Impact of Program Scale and Indirect Effects on the Cost-Effectiveness of Vaccination Program

Medical Decision Making (MDM)
May–June 2012; 32 (3)

Original Articles
Impact of Program Scale and Indirect Effects on the Cost-Effectiveness of Vaccination Programs
Med Decis Making May–June 2012 32: 442-446, first published on April 3, 2012 doi:10.1177/0272989X12441397

Vaccination against infectious disease confers both a direct protective effect to the individual receiving the vaccine as well as an indirect “herd protection” effect by reducing the transmission to the rest of the community. In some cases, the indirect population-level benefits may even outweigh the direct individual-level effects of vaccination.1 This article is motivated by the concern that published cost-effectiveness evaluations of vaccination programs are often conducted in comparison to a nonvaccination scenario 2–8 and that failure to account for considerations of scale—notably, the vaccination coverage both prior to and after program implementation—can lead analysts to ignore the nonlinear effects of herd protection and may misrepresent the cost-effectiveness of program expansion.

We used a simple model of influenza transmission to show how coverage rates affect cost-effectiveness in the evaluation of vaccination programs when herd protection effects are considered. Specifically, we show how estimates of costs, health outcomes, and cost-effectiveness of the vaccination program change with different levels of vaccination coverage due to the herd protection effect.

Disease Transmission Model
A standard susceptible-infectious-recovered (SIR) differential equation model was used to capture influenza transmission dynamics (Figure 1 and Table 1)9 and to estimate the disease incidence at varying levels of vaccination coverage in a population of 100,000 homogeneous, randomly mixing individuals. Vaccination efficacy (ϵ) was assumed to be 70%.10 The basic reproduction number (R 0), the mean number of infectious cases from a single infection in a totally susceptible population, was assumed to be 1.5,11 producing an influenza attack rate of approximately 10% at 35% vaccination coverage, which mirrors the typical influenza season in the US.12 The contact rate was parameterized to generate the R 0 value, based on the relationship between the contact rate and basic reproduction number: R 0 × …