Evidence map›Paper›PMID 25215608›Full record

ArticlePloS one2014

Seasonal patterns in human A (H5N1) virus infection: analysis of global cases.

Maya B Mathur, Rita B Patel, Michael Gould, Timothy M Uyeki, Jay Bhattacharya, Yang Xiao, Yoshi Gillaspie, Charlotte Chae, Nayer Khazeni

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

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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

9 authors.

Maya B MathurQuantitative Sciences Unit, Stanford University Department of Medicine, Stanford, California, United States of America.
Rita B PatelDivision of Pulmonary and Critical Care Medicine, Stanford University Medical Center, Stanford, California, United States of America.
Michael GouldKaiser Permanente Southern California, Pasadena, California, United States of America.
Timothy M UyekiInfluenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America.
Jay BhattacharyaCenter for Health Policy and Center for Primary Care and Outcomes Research, Stanford University, Stanford, California, United States of America.
Yang XiaoDepartment of Languages, Literatures, and Cultures, University of South Carolina, Columbia, South Carolina, United States of America.
Yoshi GillaspieDivision of Pulmonary and Critical Care Medicine, Stanford University Medical Center, Stanford, California, United States of America.
Charlotte ChaeDivision of Pulmonary and Critical Care Medicine, Stanford University Medical Center, Stanford, California, United States of America.
Nayer KhazeniDivision of Pulmonary and Critical Care Medicine, Stanford University Medical Center, Stanford, California, United States of America; Center for Health Policy and Center for Primary Care and Outcomes Research, Stanford University, Stanford, California, United States of America.

Funding

CORE--PROGRAM DEVELOPMENTP30AG017253 · NIA · STANFORD UNIVERSITY · PI BHATTACHARYA, JAY · 1999 to 2019
$5.8M
Comparative Effectiveness of Mitigation Strategies for Pandemic InfluenzaK08HS019816 · AHRQ · STANFORD UNIVERSITY · PI KHAZENI, NAYER · 2012 to 2016
$683k
AHRQ HHS 1K08 HS019816AHRQ HHS K08 HS019816NIA NIH HHS P30 AG017253
6 · The paper itself

Abstract

backgroundHuman cases of highly pathogenic avian influenza (HPAI) A (H5N1) have high mortality. Despite abundant data on seasonal patterns in influenza epidemics, it is unknown whether similar patterns exist for human HPAI H5N1 cases worldwide. Such knowledge could help decrease avian-to-human transmission through increased prevention and control activities during peak periods.

methodsWe performed a systematic search of published human HPAI H5N1 cases to date, collecting month, year, country, season, hemisphere, and climate data. We used negative binomial regression to predict changes in case incidence as a function of season. To investigate hemisphere as a potential moderator, we used AIC and the likelihood-ratio test to compare the season-only model to nested models including a main effect or interaction with hemisphere. Finally, we visually assessed replication of seasonal patterns across climate groups based on the Köppen-Geiger climate classification.

findingsWe identified 617 human cases (611 with complete seasonal data) occurring in 15 countries in Southeast Asia, Africa, and the Middle East. Case occurrence was much higher in winter (n = 285, p = 0.03) than summer (n = 64), and the winter peak occurred across diverse climate groups. There was no significant interaction between hemisphere and season.

interpretationAcross diverse climates, HPAI H5N1 virus infection in humans increases significantly in winter. This is consistent with increased poultry outbreaks and HPAI H5N1 virus transmission during cold and dry conditions. Prioritizing prevention and control activities among poultry and focusing public health messaging to reduce poultry exposures during winter months may help to reduce zoonotic transmission of HPAI H5N1 virus in resource-limited settings.

Indexed as

InternationalitySeasonsClimateGeographyHumansIncidenceInfluenza A Virus, H5N1 SubtypeInfluenza, HumanRegression Analysis

Identifiers

PMID25215608
PMCPMC4162536

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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.