Evidence map›Paper›PMID 25940354›Full record

ArticleClinical infectious diseases : an official publication of the Infectious Diseases Society of America2015

Differences in the Epidemiology of Human Cases of Avian Influenza A(H7N9) and A(H5N1) Viruses Infection.

Ying Qin, Peter W Horby, Tim K Tsang, Enfu Chen, Lidong Gao, Jianming Ou, Tran Hien Nguyen, Tran Nhu Duong, Viktor Gasimov, Luzhao Feng and 15 more

Abstract readComparative Study
In one paragraph

Article in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 5 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

56 citing papers in PubMed, 5 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Trial
  7. Trial
  8. Article
  9. Article
  10. Article
  11. Article
  12. Immune history shapes human antibody responses to H5N1 influenza viruses.medRxiv : the preprint server for health sciences · 2024
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  19. Review
  20. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

25 authors.

Ying QinDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Peter W HorbyOxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, Oxford University, United Kingdom Singapore Infectious Disease Initiative.
Tim K TsangWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
Enfu ChenZhejiang Provincial Center for Disease Control and Prevention, Hangzhou.
Lidong GaoHunan Provincial Center for Disease Control and Prevention, Changsha.
Jianming OuFujian Provincial Center for Disease Control and Prevention, Fuzhou, China.
Tran Hien NguyenNational Institute of Hygiene and Epidemiology, Hanoi, Vietnam.
Tran Nhu DuongNational Institute of Hygiene and Epidemiology, Hanoi, Vietnam.
Viktor GasimovMinistry of Health of Azerbaijan, Baku.
Luzhao FengDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Peng WuWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
Hui JiangDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiang RenDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Zhibin PengDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Sa LiDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Ming LiDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Jiandong ZhengDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Shelan LiuZhejiang Provincial Center for Disease Control and Prevention, Hangzhou.
Shixiong HuHunan Provincial Center for Disease Control and Prevention, Changsha.
Rongtao HongFujian Provincial Center for Disease Control and Prevention, Fuzhou, China.
Jeremy J FarrarOxford University Clinical Research Unit, Wellcome Trust Major Overseas Programme, Ho Chi Minh City, Vietnam Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, Oxford University, United Kingdom Singapore Infectious Disease Initiative ISARIC, Centre for Tropical Medicine, University of Oxford, Churchill Hospital, United Kingdom.
Gabriel M LeungWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
George F GaoCAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences Office of Director-General, Chinese Center for Disease Control and Prevention, Beijing, China.
Benjamin J CowlingWHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region.
Hongjie YuDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

Understanding and controlling antibiotic resistanceU54GM088558 · NIGMS · HARVARD SCHOOL OF PUBLIC HEALTH · PI BUCKEE, CAROLINE O'FLAHERTY · 2009 to 2018
$26.4M
Virology &ImmunologyU19AI051915 · NIAID · NATIONAL CENTER FOR AIDS/STD CONTROL AND PREVENTION · PI SHAO, YIMING · 2002 to 2009
$21.6M
NIAID NIH HHS U19 AI051915NIAID NIH HHS U19 AI51915NIGMS NIH HHS U54 GM088558Wellcome TrustWellcome Trust 089276/B/09/ZWellcome Trust 089276/Z/09/Z
6 · The paper itself

Abstract

backgroundThe pandemic potential of avian influenza viruses A(H5N1) and A(H7N9) remains an unresolved but critically important question.

methodsWe compared the characteristics of sporadic and clustered cases of human H5N1 and H7N9 infection, estimated the relative risk of infection in blood-related contacts, and the reproduction number (R).

resultsWe assembled and analyzed data on 720 H5N1 cases and 460 H7N9 cases up to 2 November 2014. The severity and average age of sporadic/index cases of H7N9 was greater than secondary cases (71% requiring intensive care unit admission vs 33%, P = .007; median age 59 years vs 31, P < .001). We observed no significant differences in the age and severity between sporadic/index and secondary H5N1 cases. The upper limit of the 95% confidence interval (CI) for R was 0.12 for H5N1 and 0.27 for H7N9. A higher proportion of H5N1 infections occurred in clusters (20%) compared to H7N9 (8%). The relative risk of infection in blood-related contacts of cases compared to unrelated contacts was 8.96 for H5N1 (95% CI, 1.30, 61.86) and 0.80 for H7N9 (95% CI, .32, 1.97).

conclusionsThe results are consistent with an ascertainment bias towards severe and older cases for sporadic H7N9 but not for H5N1. The lack of evidence for ascertainment bias in sporadic H5N1 cases, the more pronounced clustering of cases, and the higher risk of infection in blood-related contacts, support the hypothesis that susceptibility to H5N1 may be limited and familial. This analysis suggests the potential pandemic risk may be greater for H7N9 than H5N1.

Indexed as

AdolescentAdultAgedAged, 80 and overAge FactorsAnimalsBasic Reproduction NumberChildChild, PreschoolFamily HealthFemaleHumansInfantInfluenza A Virus, H5N1 SubtypeInfluenza A Virus, H7N9 SubtypeInfluenza, Humanclinical epidemiologyclusterinfluenza A(H5N1)influenza A(H7N9)

Identifiers

PMID25940354
PMCPMC4542598

What OpenQuestion holds

Textmetadata
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.