Volume 12, Number 3—March 2006
Perspective
Cost-effectiveness of West Nile Virus Vaccination
Armineh Zohrabian*
, Edward B. Hayes†, and Lyle R. Petersen†
, Edward B. Hayes†, and Lyle R. Petersen†Table 3
Sensitivity of the average cost-effectiveness ratio (ACER) for input variables
| Rank | Input variables | Regression coefficient† |
|---|---|---|
| 1 | Probability of symptomatic illness | 0.65 |
| 2 | Probability of infection | 0.51 |
| 3 | Vaccination cost | 0.50 |
| 4 | Probability of symptomatic illness after vaccination | –0.14 |
| 5 | Probability of neuroinvasive disease, given symptoms | 0.05 |
| 6 | Cost of lifelong disability | –0.03 |
| 7 | Probability of disability, given neuroinvasive disease | 0.03 |
| 8 | Cost of neuroinvasive disease | –0.02 |
| 9 | Cost of uncomplicated WNV febrile illness* | –0.01 |
| 10 | Cost of death (direct and indirect financial losses) | –0.01 |
| 11 | Probability of death, given neuroinvasive disease | 0.00 |
*WNV, West Nile virus.
†@Risk analysis software runs a regression where the dependent variable is the output variable, i.e., ACER, and the independent variables are the input variables presented as @Risk uniform distribution functions. Each iteration represents an observation for the regression. The coefficient calculated for each input variable measures the sensitivity of the output to that particular input distribution. For example, a coefficient of 0.65 indicates that a 1–standard deviation (SD) increase in probability of symptomatic illness increases the ACER by an SD of 0.65.
