Evidence map›Paper›PMID 30630435›Full record

ArticleBMC infectious diseases2019

Influenza infections in Australia 2009-2015: is there a combined effect of age and sex on susceptibility to virus subtypes?

Kam Cheong Wong, Georgina M Luscombe, Catherine Hawke

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed, 1 pooled it
5.4field-weighted citation impact, top 4% of its field
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

37 citing papers in PubMed, 1 synthesis or guideline pooled it, 54 citations in OpenAlex.

  1. Pooled it
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  15. Sex-Differential and Non-specific Effects of Vaccines Over the Life Course.Current topics in microbiology and immunology · 2023
    Review
  16. Biological Sex and Pregnancy Affect Influenza Pathogenesis and Vaccination.Current topics in microbiology and immunology · 2023
    Article
  17. Article
  18. Article
  19. Sex Differences in Influenza: The Challenge Study Experience.The Journal of infectious diseases · 2022
    Article
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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 at 2 institutions in 1 country.

Kam Cheong WongBathurst Rural Clinical School, School of Medicine, Western Sydney University, Bathurst, NSW, Australia. K.Wong@westernsydney.edu.au.ORCID http://orcid.org/0000-0003-1898-7678
Georgina M LuscombeSchool of Rural Health, Faculty of Medicine and Health, University of Sydney, Orange, NSW, Australia.
Catherine HawkeSchool of Rural Health, Faculty of Medicine and Health, University of Sydney, Orange, NSW, Australia.
The University of Sydney · AUWestern Sydney University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundInfluenza is a global infectious disease with a large burden of illness and high healthcare costs. Those who experience greater burden of disease include younger and older people, and pregnant women. Although there are known age and sex susceptibilities, little is known about how the interaction of age and sex may affect a population's vulnerability to infection with different subtypes of influenza virus.

methodsLaboratory-confirmed cases of influenza notified between 1 January 2009 and 31 December 2015 obtained from the Australian Government National Notifiable Diseases Surveillance System Influenza Public Data Set were analysed by age, sex and virus subtype. Age standardised notification rates per 100,000 population were calculated separately for females and males and used to generate female-to-male ratios with 95% confidence intervals for influenza A and B, and for virus subtypes A(H1N1)pdm09 and A(H3N2).

results334,560 notifications for influenza A (all notifications), A(H1N1)pmd09, A(H3N2) and B subtypes from a total of 335,414 influenza notifications were analysed. Male notification rates were significantly higher for the 0 to 4 years old age group regardless of virus type or subtype; and higher for those aged 0 to 14 years and those 85 years and older for influenza types A and B and subtype A(H1N1)pdm09. Female notification rates were significantly higher for A(H1N1)pdm09 in those aged 15 to 54 years, for Type A and sub-type A(H3N2) in those aged 15 to 69 years, and for Influenza B in those aged 20 to 74 years.

conclusionsWe observed a female dominance in notification rates throughout the adult age groups, which could possibly be related to health seeking behaviours. However, differences in health seeking behaviours cannot explain the variations observed across virus subtypes in the particular age groups with higher female notifications. Depending on their age, females may be more susceptible to certain subtypes of influenza virus. These observations suggest that there is an interaction between age and sex on susceptibility to influenza infection which varies by the subtype of the virus. The inclusion of pregnancy and menopausal status in surveillance data may assist development of targeted public health approaches during the emergence of new subtypes of influenza virus. Targeted vaccination campaigns may need to take into consideration specific age and sex groups who have a greater susceptibility to influenza infection as well as those who experience a greater burden of illness.

Indexed as

AdolescentAdultAgedAged, 80 and overAge FactorsAustraliaChildChild, PreschoolDisease SusceptibilityFemaleHumansImmunization ProgramsInfantInfant, NewbornInfluenza A Virus, H1N1 SubtypeInfluenza A Virus, H3N2 SubtypeAgeInfluenza surveillanceInfluenza virus subtypeInfluenza virus type AInfluenza virus type BSex

Identifiers

PMID30630435
PMCPMC6327581
OpenAlexW2919057312

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.