Cost-effectiveness analysis of universal influenza vaccination: Application of the susceptible-infectious-complication-recovery model

Objectives Despite the fact that vaccination is an effective primary prevention strategy for the containment of influenza outbreaks, health policymakers have shown great concern over the enormous costs involved in universal immunization, particularly when resources are limited. Methods A two-arm cost-effectiveness analysis (CEA) was conducted that took into account the aspect of herd immunity. The analysis used a study cohort of 100 000 residents with a demographic make-up identical to that of the underlying population in Taipei County, Taiwan, during the epidemic influenza season of 2001–2002. The parameters embedded in the dynamic process of infection were estimated through the application of the newly proposed susceptible–infection–complication–recovery (SICR) model to the empirical data, in order to compute the number of deaths and complications averted due to universal vaccination compared to no vaccination. Incremental cost-effectiveness ratios (ICERs) and the cost-effectiveness acceptability curve (CEAC) given maximum amount of willingness-to-pay (WTP) were calculated to delineate the results of the two-arm CEA. Results The incremental costs involved in the vaccinated group as compared to the unvaccinated group were $1195 to reduce one additional complication and $805 to avert one additional death, allowing for herd immunity. The corresponding figures were higher for the results without considering herd immunity. Given the ceiling ratio of WTP equal to $10 000 (approximately two-thirds of GDP), the probability of the vaccination being cost-effective for averting death was 100% and for averting complications was 96.7%. Conclusions Universal vaccination against seasonal influenza was found to be very cost-effective, particularly when herd immunity is considered. The probability of being cost-effective was almost certain given the maximum amount of WTP within two-thirds of the GDP.