Estimation of optimal antiviral stockpile for a novel influenza pandemic

Abstract

Background: A stockpile of antiviral drugs is important for mitigating a novel influenza pandemic. Recently, intervention strategies against such a pandemic have improved significantly, affecting the required size and composition of the stockpile. Our goal is to estimate the optimal ratio of conventional to newer antiviral drugs.

Method: We estimated epidemic parameters from daily-case data about H1N1pdm09 in the Republic of Korea, and used a deterministic ordinary differential equation model and stochastic simulation to predict the number of patients in a future pandemic. We considered an antiviral stockpile containing neuraminidase inhibitors (NAI) and a new drug, cap-dependent endonuclease inhibitor (CENI), seeking the optimum ratio of the two drugs under different epidemiological and economic assumptions.

Results: With an effective reproductive number of 1.36, the expected cumulative cases did not exceed 30 % of the population in all vaccination scenarios. If the non-pharmaceutical intervention strategy is intensified and the effective reproductive number is decreased to 1.29, a 20 % antiviral stockpile of the population is sufficient. Assuming that CENI is prescribed for 10 % of patients, the expected total number of cases is decreased from 30 % to approximately 25 % of the population. If the cost of CENI is triple that of NAI, no expenditures beyond the current budget are necessary; if it is quintuple, expenditures increase by 17 %.

Conclusion: Stockpiling CENI reduces the number of patients by reducing the infectious period. However, the government needs to consider the cost-effective stockpile ratio of such new drugs. This will depend not only on the cost of the drugs, but on factors difficult to anticipate, such as the transmissibility of the virus, the time needed for vaccine development, and (especially) the emergence of resistance. If this information can be estimated, our model can be used to obtain the optimum.