Optimal vaccine allocation for the early mitigation of pandemic influenza.

With new cases of avian influenza H5N1 (H5N1AV) arising frequently, the threat of a new influenza pandemic remains a challenge for public health. Several vaccines have been developed specifically targeting H5N1AV, but their production is limited and only a few million doses are readily available. Be...

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Autores principales:	Laura Matrajt, M Elizabeth Halloran, Ira M Longini
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2013
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/97902db92f7a48db9ffa594c3d0f8bf2
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spelling	oai:doaj.org-article:97902db92f7a48db9ffa594c3d0f8bf22021-11-18T05:52:20ZOptimal vaccine allocation for the early mitigation of pandemic influenza.1553-734X1553-735810.1371/journal.pcbi.1002964https://doaj.org/article/97902db92f7a48db9ffa594c3d0f8bf22013-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23555207/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358With new cases of avian influenza H5N1 (H5N1AV) arising frequently, the threat of a new influenza pandemic remains a challenge for public health. Several vaccines have been developed specifically targeting H5N1AV, but their production is limited and only a few million doses are readily available. Because there is an important time lag between the emergence of new pandemic strain and the development and distribution of a vaccine, shortage of vaccine is very likely at the beginning of a pandemic. We coupled a mathematical model with a genetic algorithm to optimally and dynamically distribute vaccine in a network of cities, connected by the airline transportation network. By minimizing the illness attack rate (i.e., the percentage of people in the population who become infected and ill), we focus on optimizing vaccine allocation in a network of 16 cities in Southeast Asia when only a few million doses are available. In our base case, we assume the vaccine is well-matched and vaccination occurs 5 to 10 days after the beginning of the epidemic. The effectiveness of all the vaccination strategies drops off as the timing is delayed or the vaccine is less well-matched. Under the best assumptions, optimal vaccination strategies substantially reduced the illness attack rate, with a maximal reduction in the attack rate of 85%. Furthermore, our results suggest that cooperative strategies where the resources are optimally distributed among the cities perform much better than the strategies where the vaccine is equally distributed among the network, yielding an illness attack rate 17% lower. We show that it is possible to significantly mitigate a more global epidemic with limited quantities of vaccine, provided that the vaccination campaign is extremely fast and it occurs within the first weeks of transmission.Laura MatrajtM Elizabeth HalloranIra M LonginiPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 9, Iss 3, p e1002964 (2013)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Laura Matrajt M Elizabeth Halloran Ira M Longini Optimal vaccine allocation for the early mitigation of pandemic influenza.
description	With new cases of avian influenza H5N1 (H5N1AV) arising frequently, the threat of a new influenza pandemic remains a challenge for public health. Several vaccines have been developed specifically targeting H5N1AV, but their production is limited and only a few million doses are readily available. Because there is an important time lag between the emergence of new pandemic strain and the development and distribution of a vaccine, shortage of vaccine is very likely at the beginning of a pandemic. We coupled a mathematical model with a genetic algorithm to optimally and dynamically distribute vaccine in a network of cities, connected by the airline transportation network. By minimizing the illness attack rate (i.e., the percentage of people in the population who become infected and ill), we focus on optimizing vaccine allocation in a network of 16 cities in Southeast Asia when only a few million doses are available. In our base case, we assume the vaccine is well-matched and vaccination occurs 5 to 10 days after the beginning of the epidemic. The effectiveness of all the vaccination strategies drops off as the timing is delayed or the vaccine is less well-matched. Under the best assumptions, optimal vaccination strategies substantially reduced the illness attack rate, with a maximal reduction in the attack rate of 85%. Furthermore, our results suggest that cooperative strategies where the resources are optimally distributed among the cities perform much better than the strategies where the vaccine is equally distributed among the network, yielding an illness attack rate 17% lower. We show that it is possible to significantly mitigate a more global epidemic with limited quantities of vaccine, provided that the vaccination campaign is extremely fast and it occurs within the first weeks of transmission.
format	article
author	Laura Matrajt M Elizabeth Halloran Ira M Longini
author_facet	Laura Matrajt M Elizabeth Halloran Ira M Longini
author_sort	Laura Matrajt
title	Optimal vaccine allocation for the early mitigation of pandemic influenza.
title_short	Optimal vaccine allocation for the early mitigation of pandemic influenza.
title_full	Optimal vaccine allocation for the early mitigation of pandemic influenza.
title_fullStr	Optimal vaccine allocation for the early mitigation of pandemic influenza.
title_full_unstemmed	Optimal vaccine allocation for the early mitigation of pandemic influenza.
title_sort	optimal vaccine allocation for the early mitigation of pandemic influenza.
publisher	Public Library of Science (PLoS)
publishDate	2013
url	https://doaj.org/article/97902db92f7a48db9ffa594c3d0f8bf2
work_keys_str_mv	AT lauramatrajt optimalvaccineallocationfortheearlymitigationofpandemicinfluenza AT melizabethhalloran optimalvaccineallocationfortheearlymitigationofpandemicinfluenza AT iramlongini optimalvaccineallocationfortheearlymitigationofpandemicinfluenza
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Optimal vaccine allocation for the early mitigation of pandemic influenza.

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