Evidence map›Paper›PMID 23304674›Full record

ArticleIranian journal of public health2012

Is a Mass Prevention and Control Program for Pandemic (H1N1) 2009 Good Value for Money? Evidence from the Chinese Experience.

Biyan Wang, Jinliang Xie, Pengqian Fang

Abstract read
In one paragraph

Article in Iranian journal of public health, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 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

6 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Costs and benefits of interventions aimed at major infectious disease threats: lessons from the literature.The European journal of health economics : HEPAC : health economics in prevention and care · 2020
    Review
  5. Article
  6. Influenza vaccination in oncology patients.Current infectious disease reports · 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.

Biyan WangSchool of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China ; Faculty of Humanity and Social Sciences, Guangxi University of Chinese Medicine, Nanning 530001, China.
Jinliang Xie
Pengqian Fang

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn order to provide guidance on the efficient allocation of health resources when handling public health emergencies in the future, the study evaluated the H1N1 influenza prevention and control program in Hubei Province of China using cost-benefit analysis.

methodsThe costs measured the resources consumed and other expenses incurred in the prevention and control of H1N1. The assumed benefits include resource consumption and economic losses which could be avoided by the measures for the prevention and control of H1N1. The benefit was evaluated by counterfactual thinking, which estimates the resource consumption and economic losses could be happened without any measures for the prevention and control, which have been avoided after measures were taken to prevent and control H1N1 in Hubei Province, these constitutes the benefit of this project.

resultsThe total costs of this program were 38.81 million U.S. dollars, while the total benefit was assessed as 203.71 million U.S. dollars. The net benefit was 164.9 million U.S. dollars with a cost-effectiveness ratio of 1:5.25.

conclusionsThe joint prevention and control strategy introduced by Hubei for H1N1 influenza is cost-effective.

Indexed as

Cost-benefitH1N1 influenzaPrevention and control

Identifiers

PMID23304674
PMCPMC3521884

What OpenQuestion holds

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Registered trials

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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.