Evidence map›Paper›PMID 21347316›Full record

ArticlePLoS computational biology2011

Mitigation strategies for pandemic influenza A: balancing conflicting policy objectives.

T Déirdre Hollingsworth, Don Klinkenberg, Hans Heesterbeek, Roy M Anderson

Abstract read
In one paragraph

Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

62 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Minimizing Societal Cost of Epidemics: Optimal Catastrophe Insurance Compensation Allocation.Risk analysis : an official publication of the Society for Risk Analysis · 2026
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  12. Timing of non-pharmaceutical interventions to mitigate COVID-19 transmission and their effects on mobility: a cross-country analysis.The European journal of health economics : HEPAC : health economics in prevention and care · 2022
    Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Dynamics of SARS-CoV-2 with waning immunity in the UK population.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  18. Epidemic interventions: insights from classic results.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  19. Review
  20. Article

2 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

T Déirdre HollingsworthMRC Centre for Outbreak Control and Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom. d.hollingsworth@imperial.ac.uk
Don Klinkenberg
Hans Heesterbeek
Roy M Anderson

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 R(0) 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.

Indexed as

Influenza A virusAntiviral AgentsComputational BiologyHealth PolicyHumansInfluenza, HumanInfluenza VaccinesMathematical ConceptsModels, BiologicalPandemicsPsychological DistanceTime FactorsAntiviral AgentsInfluenza Vaccines

Identifiers

PMID21347316
PMCPMC3037387

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.