Skip to content Skip to navigation
University of Warwick
  • Study
  • |
  • Research
  • |
  • Business
  • |
  • Alumni
  • |
  • News
  • |
  • About

University of Warwick
Publications service & WRAP

Highlight your research

  • WRAP
    • Home
    • Search WRAP
    • Browse by Warwick Author
    • Browse WRAP by Year
    • Browse WRAP by Subject
    • Browse WRAP by Department
    • Browse WRAP by Funder
    • Browse Theses by Department
  • Publications Service
    • Home
    • Search Publications Service
    • Browse by Warwick Author
    • Browse Publications service by Year
    • Browse Publications service by Subject
    • Browse Publications service by Department
    • Browse Publications service by Funder
  • Help & Advice
University of Warwick

The Library

  • Login
  • Admin

Evidence synthesis and decision modelling to support complex decisions : stockpiling neuraminidase inhibitors for pandemic influenza usage

Tools
- Tools
+ Tools

Watson, Samuel I., Chen, Y-F.‏‎, Nguyen-Van-Tam, Jonathan S., Myles, Puja R., Venkatesan, Sudhir, Zambon, Maria, Uthman, Olalekan A., Chilton, Peter J. and Lilford, Richard (2016) Evidence synthesis and decision modelling to support complex decisions : stockpiling neuraminidase inhibitors for pandemic influenza usage. F1000Research, 5 . 2293. doi:10.12688/f1000research.9414.2

[img]
Preview
PDF
WRAP-evidence-synthesis-decision-modelling-support-complex-decisions-Watson-2017.pdf - Published Version - Requires a PDF viewer.
Available under License Creative Commons Attribution 4.0.

Download (1933Kb) | Preview
Official URL: https://doi.org/10.12688/f1000research.9414.2

Request Changes to record.

Abstract

Objectives: The stockpiling of neuraminidase inhibitor (NAI) antivirals as a defence against pandemic influenza is a significant public health policy decision that must be made despite a lack of conclusive evidence from randomised controlled trials regarding the effectiveness of NAIs on important clinical end points such as mortality. The objective of this study was to determine whether NAIs should be stockpiled for treatment of pandemic influenza on the basis of current evidence.

Methods: A decision model for stockpiling was designed. Data on previous pandemic influenza epidemiology was combined with data on the effectiveness of NAIs in reducing mortality obtained from a recent individual participant meta-analysis using observational data. Evidence synthesis techniques and a bias modelling method for observational data were used to incorporate the evidence into the model. The stockpiling decision was modelled for adults (≥16 years old) and the United Kingdom was used as an example. The main outcome was the expected net benefits of stockpiling in monetary terms. Health benefits were estimated from deaths averted through stockpiling.

Results: After adjusting for biases in the estimated effectiveness of NAIs, the expected net benefit of stockpiling in the baseline analysis was £444 million, assuming a willingness to pay of £20,000/QALY ($31,000/QALY). The decision would therefore be to stockpile NAIs. There was a greater probability that the stockpile would not be utilised than utilised. However, the rare but catastrophic losses from a severe pandemic justified the decision to stockpile.

Conclusions: Taking into account the available epidemiological data and evidence of effectiveness of NAIs in reducing mortality, including potential biases, a decision maker should stockpile anti-influenza medication in keeping with the postulated decision rule.

Item Type: Journal Article
Subjects: R Medicine > RA Public aspects of medicine
Divisions: Faculty of Medicine > Warwick Medical School > Health Sciences
Faculty of Medicine > Warwick Medical School > Health Sciences > Population, Evidence & Technologies (PET)
Faculty of Social Sciences > Warwick Business School
Faculty of Medicine > Warwick Medical School
Library of Congress Subject Headings (LCSH): Influenza -- Epidemiology, Epidemics, Antiviral agents, Decision making -- Mathematical models, Evidence-based medicine -- Statistical methods
Journal or Publication Title: F1000Research
Publisher: F1000 Research Ltd
ISSN: 2046-1402
Official Date: 12 September 2016
Dates:
DateEvent
16 March 2017Updated
12 September 2016Published
12 September 2016Accepted
Volume: 5
Article Number: 2293
DOI: 10.12688/f1000research.9414.2
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
Collaboration for Leadership in Applied Health Research and CareNational Institute for Health Researchhttp://dx.doi.org/10.13039/501100000272

Request changes or add full text files to a record

Repository staff actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics

twitter

Email us: wrap@warwick.ac.uk
Contact Details
About Us