Hollingsworth, T. Déirdre, Klinkenberg, Don, Heesterbeek, Hans and Anderson, Roy M. (2011) Mitigation strategies for pandemic influenza A : balancing conflicting policy objectives. PLoS Computational Biology, Volume 7 (Number 2). Article no. e1001076. doi:10.1371/journal.pcbi.1001076 ISSN 1553-7358.

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Abstract

Mitigation of a severe influenza pandemic can be achieved using a range of interventions to reduce transmission. Interventions can reduce the impact of an outbreak and buy time until vaccines are developed, but they may have high social and economic costs. The non-linear effect on the epidemic dynamics means that suitable strategies crucially depend on the precise aim of the intervention. National pandemic influenza plans rarely contain clear statements of policy objectives or prioritization of potentially conflicting aims, such as minimizing mortality (depending on the severity of a pandemic) or peak prevalence or limiting the socio-economic burden of contact-reducing interventions. We use epidemiological models of influenza A to investigate how contact-reducing interventions and availability of antiviral drugs or pre-pandemic vaccines contribute to achieving particular policy objectives. Our analyses show that the ideal strategy depends on the aim of an intervention and that the achievement of one policy objective may preclude success with others, e.g., constraining peak demand for public health resources may lengthen the duration of the epidemic and hence its economic and social impact. Constraining total case numbers can be achieved by a range of strategies, whereas strategies which additionally constrain peak demand for services require a more sophisticated intervention. If, for example, there are multiple objectives which must be achieved prior to the availability of a pandemic vaccine (i.e., a time-limited intervention), our analysis shows that interventions should be implemented several weeks into the epidemic, not at the very start. This observation is shown to be robust across a range of constraints and for uncertainty in estimates of both R0 and the timing of vaccine availability. These analyses highlight the need for more precise statements of policy objectives and their assumed consequences when planning and implementing strategies to mitigate the impact of an influenza pandemic.

Item Type:	Journal Article
Subjects:	R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Divisions:	Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) Faculty of Science, Engineering and Medicine > Science > Mathematics
Library of Congress Subject Headings (LCSH):	Influenza A virus, Influenza viruses -- Research, Health planning, Communicable diseases -- Prevention, Health risk communication, Immunization
Journal or Publication Title:	PLoS Computational Biology
Publisher:	PLOS
ISSN:	1553-7358
Official Date:	2011
Dates:	Date Event 2011 Published
Volume:	Volume 7
Number:	Number 2
Page Range:	Article no. e1001076
DOI:	10.1371/journal.pcbi.1001076
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Date of first compliant deposit:	23 December 2015
Date of first compliant Open Access:	23 December 2015
Funder:	Sixth Framework Programme (European Commission) (FP6), Imperial College, London, Nederlandse Organisatie voor Wetenschappelijk Onderzoek [Netherlands Organisation for Scientific Research] (NWO)
Grant number:	SP22-CT-2004-511066 (FP6), 918.56.620 (NWO)

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