Evidence map›Paper›PMID 28946870›Full record

ArticleBMC infectious diseases2017

Possible explanations for why some countries were harder hit by the pandemic influenza virus in 2009 - a global mortality impact modeling study.

Kathleen F Morales, John Paget, Peter Spreeuwenberg

Abstract read
In one paragraph

Article in BMC infectious diseases, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing 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

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

  1. Pooled it
  2. Impact of PMEnvironmental science and pollution research international · 2023
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  3. Statistical model for factors correlating with COVID-19 deaths.International journal of disaster risk reduction : IJDRR · 2022
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  4. Recent Insights into Particulate Matter (PMInternational journal of environmental research and public health · 2022
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  9. Ambient PMThe Science of the total environment · 2021
    Article
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  12. Article
  13. Particulate matter (PMEnvironmental pollution (Barking, Essex : 1987) · 2020
    Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Tuberculosis as a Risk Factor for 1918 Influenza Pandemic Outcomes.Tropical medicine and infectious disease · 2019
    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.

Kathleen F MoralesSage Analytica, Portland, Maine, USA.
John PagetNetherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands. j.paget@nivel.nl.ORCID 0000-0002-1503-2481
Peter SpreeuwenbergNetherlands Institute for Health Services Research (NIVEL), Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA global pandemic mortality study found prominent regional mortality variations in 2009 for Influenza A(H1N1)pdm09. Our study attempts to identify factors that explain why the pandemic mortality burden was high in some countries and low in others.

methodsAs a starting point, we identified possible risk factors worth investigating for Influenza A(H1N1)pdm09 mortality through a targeted literature search. We then used a modeling procedure (data simulations and regression models) to identify factors that could explain differences in respiratory mortality due to Influenza A(H1N1)pdm09. We ran sixteen models to produce robust results and draw conclusions. In order to assess the role of each factor in explaining differences in excess pandemic mortality, we calculated the reduction in between country variance, which can be viewed as an effect-size for each factor.

resultsThe literature search identified 124 publications and 48 possible risk factors, of which we were able to identify 27 factors with appropriate global datasets. The modelling procedure indicated that age structure (explaining 40% of the mean between country variance), latitude (8%), influenza A and B viruses circulating during the pandemic (3-8%), influenza A and B viruses circulating during the preceding influenza season (2-6%), air pollution (pm10; 4%) and the prevalence of other infections (HIV and TB) (4-6%) were factors that explained differences in mortality around the world. Healthcare expenditure, levels of obesity, the distribution of antivirals, and air travel did not explain global pandemic mortality differences.

conclusionsOur study found that countries with a large proportion of young persons had higher pandemic mortality rates in 2009. The co-circulation of influenza viruses during the pandemic and the circulation of influenza viruses during the preceding season were also associated with pandemic mortality rates. We found that real time assessments of 2009 pandemic mortality risk factors (e.g. obesity) probably led to a number of false positive findings.

Indexed as

Models, StatisticalAdultAir TravelAntiviral AgentsChildComorbidityHIV InfectionsHumansInfluenza A Virus, H1N1 SubtypeInfluenza, HumanObesityPandemicsPrevalenceRisk FactorsSeasonsAntiviral AgentsGlobalInfluenzaModellingMortalityPandemicRisk factors

Identifiers

PMID28946870
PMCPMC5613504

What OpenQuestion holds

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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.