Evidence map›Paper›PMID 20346187›Full record

ArticleBMC public health2010

Analysis of the effectiveness of interventions used during the 2009 A/H1N1 influenza pandemic.

Nilimesh Halder, Joel K Kelso, George J Milne

Abstract read
In one paragraph

Article in BMC public health, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 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

44 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Reflecting on prediction strategies for epidemics: Preparedness and public health response.Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology · 2021
    Review
  7. Viral Pandemics of the Last Four Decades: Pathophysiology, Health Impacts and Perspectives.International journal of environmental research and public health · 2020
    Review
  8. Article
  9. Article
  10. People's perception and cost-effectiveness of home confinement during an influenza pandemic: evidence from the French case.The European journal of health economics : HEPAC : health economics in prevention and care · 2018
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. The new pandemic influenza A/(H1N1)pdm09 virus: is it really "new"?Journal of preventive medicine and hygiene · 2016
    Article
  16. Article
  17. Article
  18. Article
  19. Observational
  20. Risk-based input-output analysis of influenza epidemic consequences on interdependent workforce sectors.Risk analysis : an official publication of the Society for Risk Analysis · 2013
    Article
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

3 authors.

Nilimesh HalderSchool of Computer Science and Software Engineering, University of Western Australia, Perth, Australia.
Joel K Kelso
George J Milne

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFollowing the emergence of the A/H1N1 2009 influenza pandemic, public health interventions were activated to lessen its potential impact. Computer modelling and simulation can be used to determine the potential effectiveness of the social distancing and antiviral drug therapy interventions that were used at the early stages of the pandemic, providing guidance to public health policy makers as to intervention strategies in future pandemics involving a highly pathogenic influenza strain.

methodsAn individual-based model of a real community with a population of approximately 30,000 was used to determine the impact of alternative interventions strategies, including those used in the initial stages of the 2009 pandemic. Different interventions, namely school closure and antiviral strategies, were simulated in isolation and in combination to form different plausible scenarios. We simulated epidemics with reproduction numbers R0 of 1.5, which aligns with estimates in the range 1.4-1.6 determined from the initial outbreak in Mexico.

resultsSchool closure of 1 week was determined to have minimal effect on reducing overall illness attack rate. Antiviral drug treatment of 50% of symptomatic cases reduced the attack rate by 6.5%, from an unmitigated rate of 32.5% to 26%. Treatment of diagnosed individuals combined with additional household prophylaxis reduced the final attack rate to 19%. Further extension of prophylaxis to close contacts (in schools and workplaces) further reduced the overall attack rate to 13% and reduced the peak daily illness rate from 120 to 22 per 10,000 individuals. We determined the size of antiviral stockpile required; the ratio of the required number of antiviral courses to population was 13% for the treatment-only strategy, 25% for treatment and household prophylaxis and 40% for treatment, household and extended prophylaxis. Additional simulations suggest that coupling school closure with the antiviral strategies further reduces epidemic impact.

conclusionsThese results suggest that the aggressive use of antiviral drugs together with extended school closure may substantially slow the rate of influenza epidemic development. These strategies are more rigorous than those actually used during the early stages of the relatively mild 2009 pandemic, and are appropriate for future pandemics that have high morbidity and mortality rates.

Indexed as

Influenza A Virus, H5N1 SubtypeAdultAntiviral AgentsChildCommunity Health PlanningContact TracingDisease ProgressionFemaleHumansInfluenza, HumanMaleMexicoPandemicsPost-Exposure ProphylaxisPublic PolicyQuarantineAntiviral Agents

Identifiers

PMID20346187
PMCPMC2853510

What OpenQuestion holds

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LicenceCC BY
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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.