Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/98185
Citations
Scopus Web of Science® Altmetric
?
?
Type: Journal article
Title: Choice of antiviral allocation scheme for pandemic influenza depends on strain transmissibility, delivery delay and stockpile size
Author: Lydeamore, M.
Bean, N.
Black, A.
Ross, J.
Citation: Bulletin of Mathematical Biology, 2016; 78(2):293-321
Publisher: Springer
Issue Date: 2016
ISSN: 0092-8240
1522-9602
Statement of
Responsibility: 
Michael Lydeamore, Nigel Bean, Andrew J. Black, Joshua V. Ross
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.
Keywords: Antivirals; Epidemic; Household model; Pandemic influenza
Rights: © Society for Mathematical Biology 2016
RMID: 0030042560
DOI: 10.1007/s11538-016-0144-6
Grant ID: http://purl.org/au-research/grants/arc/FT130100254
Appears in Collections:Mathematical Sciences publications

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.