Choice of Antiviral Allocation Scheme for Pandemic Influenza Depends on Strain Transmissibility, Delivery Delay and Stockpile Size
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Recently, pandemic response has involved the use of antivirals. These antivirals are often allocated to households dynamically throughout the pandemic with the aim being to retard the spread of infection. A drawback of this is that there is a delay until infection is confirmed and antivirals are delivered. Here an alternative allocation scheme is considered, where antivirals are instead preallocated to households at the start of a pandemic, thus reducing this delay. To compare these two schemes, a deterministic approximation to a novel stochastic household model is derived, which allows efficient computation of key quantities such as the expected epidemic final size, expected early growth rate, expected peak size and expected peak time of the epidemic. It is found that the theoretical best choice of allocation scheme depends on strain transmissibility, the delay in delivering antivirals under a dynamic allocation scheme and the stockpile size. A broad summary is that for realistic stockpile sizes, a dynamic allocation scheme is superior with the important exception of the epidemic final size under a severe pandemic scenario. Our results, viewed in conjunction with the practical considerations of implementing a preallocation scheme, support a focus on attempting to reduce the delay in delivering antivirals under a dynamic allocation scheme during a future pandemic.
KeywordsAntivirals Epidemic Household model Pandemic influenza
We gratefully acknowledge the support of the ARC (FT130100254 and ACEMS) and NHMRC (PRISM\(^2\)) .
- Anderson RM, May RM (1991) Infectious diseases of humans: dynamics and control. Oxford University Press, OxfordGoogle Scholar
- Australian Bureau of Statistics (2011) NPRD number of persons usually resident in dwelling. Census 2011Google Scholar
- Ball F (1996) Threshold behaviour in stochastic epidemics among households. In: Heyde C, Prohorov Y, Pyke R, Rachev S (eds) Athens conference on applied probability and time series analysis, Lecture Notes in Statistics, vol 114, pp 253–266. Springer New York. doi: 10.1007/978-1-4612-0749-8
- Commonwealth of Australia (2009) Australian Health Management Plan for Pandemic InfluenzaGoogle Scholar
- Commonwealth of Australia (2011) Review of Australia’s health sector response to pandemic (H1N1) 2009: lessons identifiedGoogle Scholar
- Ghani A, Baguelin M, Griffin J, Flasche S, van Hoek AJ, Cauchemez S, Donnelly C, Robertson C, White M, Truscott J et al (2009) The early transmission dynamics of H1N1pdm influenza in the United Kingdom. PLoS Curr 1:RRN1130Google Scholar
- Jefferson T, Jones MA, Doshi P, Del Mar CB, Heneghan CJ, Hama R, Thompson MJ (2012) Neuraminidase inhibitors for preventing and treating influenza in healthy adults and children. Cochrane Database Syst Rev 1(1):18–35Google Scholar
- Pandemic Influenza Preparedness Team (2011) Department of Health: National Pandemic Flu Service: an evaluationGoogle Scholar
- Public Health England (2014) Pandemic influenza strategic frameworkGoogle Scholar
- Stiver G (2003) The treatment of influenza with antiviral drugs. Can Med Assoc J 168(1):49–57Google Scholar
- U.S. Department of Health and Human Services (2005) HHS pandemic influenza planGoogle Scholar