Evidence map›Paper›PMID 36062624›Full record

ArticleInfluenza and other respiratory viruses2022

Characterization of influenza seasonality in China, 2010-2018: Implications for seasonal influenza vaccination timing.

Yilan Liao, Shan Xue, Yiran Xie, Yanping Zhang, Dayan Wang, Tong Zhao, Wei Du, Tao Chen, Hui Miao, Ying Qin and 4 more

Abstract read
In one paragraph

Article in Influenza and other respiratory viruses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–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

20 citing papers in PubMed.

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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

14 authors.

Yilan LiaoState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0001-7369-7353
Shan XueState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Yiran XieChinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Yanping ZhangDivision of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Dayan WangChinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Tong ZhaoState Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China.
Wei DuSchool of Public Health, Southeast University, Nanjing, China.
Tao ChenChinese National Influenza Center, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.
Hui MiaoCollege of Art and Science, Ohio State University, Columbus, Ohio, USA.
Ying QinDivision of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Jiandong ZhengDivision of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiaokun YangDivision of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Zhibin PengDivision of Infectious Diseases, Chinese Center for Disease Control and Prevention, Beijing, China.
Jianxing YuNational Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOptimizing the timing of influenza vaccination based on regional temporal seasonal influenza illness patterns may make seasonal influenza vaccination more effective in China.

methodsWe obtained provincial weekly influenza surveillance data for 30 of 31 provinces in mainland China from the Chinese Center for Disease Control and Prevention for the years 2010-2018. Influenza epidemiological regions were constructed by clustering analysis. For each region, we calculated onset date, end date, and duration of seasonal influenza epidemics by the modified mean threshold method. To help identify initial vaccination target populations, we acquired weekly influenza surveillance data for four age groups (0-4, 5-18, 19-59, and ≥60 years) in each region and in 171 cities of wide-ranging size. We used linear regression analyses to explore the association of epidemic onset dates by age group, city, and epidemiological region and provide evidence for initial target populations for seasonal influenza vaccination.

resultsWe determined that northern, mid, southwestern, southeast regions of mainland China have distinct seasonal influenza epidemic patterns. We found significant regional, temporal, and spatial heterogeneity of seasonal influenza epidemics. There were significant differences by age group and city size in the interval between epidemic onset in the city or age group and regional spread (epidemic lead time), with longer epidemic lead times for 5- to 18-year-old children and larger cities.

conclusionsKnowledge of influenza epidemic characteristics may help optimize local influenza vaccination timing and identify initial target groups for seasonal influenza vaccination in mainland China. Similar analyses may help inform seasonal influenza vaccination strategies in other regions and countries.

Indexed as

EpidemicsInfluenza, HumanAdolescentChildChild, PreschoolChinaCitiesHumansMiddle AgedSeasonsVaccinationChinainfluenzaseasonalityspatial heterogeneityvaccination

Identifiers

PMID36062624
PMCPMC9530570

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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.