title: Choice of Antiviral Allocation Scheme for Pandemic Influenza Depends on Strain Transmissibility, Delivery Delay and Stockpile Size.
abstract: 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.
authors: School of Mathematical Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia.|School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC, 3010, Australia.
authors: Michael
authors: M
authors: Lydeamore
authors: School of Mathematical Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia.|ARC Centre of Excellence for Mathematical and Statistical Frontiers, Parkville, VIC, Australia.
authors: Nigel
authors: N
authors: Bean
authors: School of Mathematical Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia.
authors: Andrew J
authors: AJ
authors: Black
authors: School of Mathematical Sciences, The University of Adelaide, Adelaide, SA, 5005, Australia. joshua.ross@adelaide.edu.au.
authors: Joshua V
authors: JV
authors: Ross
mesh_terms: D000998:Antiviral Agents / Q000008:administration & dosage* / Q000600:supply & distribution*; D006801:Humans; D007251:Influenza, Human / Q000188:drug therapy* / Q000453:epidemiology* / Q000635:transmission; D055641:Mathematical Concepts; D008954:Models, Biological; D058873:Pandemics / Q000706:statistics & numerical data; D013269:Stochastic Processes; D062205:Strategic Stockpile
chemical_list: D000998:Antiviral Agents
keywords: Antivirals; Epidemic; Household model; Pandemic influenza