Evidence map›Paper›PMID 33176936›Full record

ArticleVaccine2020

Estimated influenza illnesses and hospitalizations averted by influenza vaccination among children aged 6-59 months in Suzhou, China, 2011/12 to 2015/16 influenza seasons.

Wanqing Zhang, Junmei Gao, Liling Chen, Jianmei Tian, Matthew Biggerstaff, Suizan Zhou, Sujian Situ, Yin Wang, Jun Zhang, Alexander J Millman and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Vaccine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

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4 · The record

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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

13 authors.

Wanqing ZhangDepartment of Epidemiology, School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Junmei GaoDepartment of Epidemiology, School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Liling ChenSuzhou Center for Disease Control and Prevention, Suzhou, China.
Jianmei TianSuzhou University Affiliated Children's Hospital, Suzhou, China.
Matthew BiggerstaffInfluenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Suizan ZhouInfluenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Sujian SituInfluenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Yin WangDepartment of Epidemiology, School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.
Jun ZhangSuzhou Center for Disease Control and Prevention, Suzhou, China.
Alexander J MillmanInfluenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Carolyn M GreeneInfluenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Tao ZhangDepartment of Epidemiology, School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China. Electronic address: tzhang@shmu.edu.cn.
Genming ZhaoDepartment of Epidemiology, School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China. Electronic address: gmzhao@shmu.edu.cn.

Funding

CGH CDC HHS U2G GH000018Intramural CDC HHS CC999999
6 · The paper itself

Abstract

backgroundThere are few estimates of vaccination-averted influenza-associated illnesses in China.

methodsWe used a mathematical model and Monte Carlo algorithm to estimate numbers and 95% confidence intervals (CI) of influenza-associated outcomes (hospitalization, illness, and medically-attended (MA) illness) averted by vaccination among children aged 6-59 months in Suzhou from October 2011-September 2016. Influenza illnesses included non-hospitalized MA influenza illnesses and non-MA influenza illnesses. The numbers of influenza-associated outcomes averted by vaccination were the difference between the expected burden if there were no vaccination given and the observed burden with vaccination. The model incorporated the disease burden estimated based on surveillance data from Suzhou University Affiliated Children's Hospital (SCH) and data from health utilization surveys conducted in the catchment area of SCH, age-specific estimates of influenza vaccination coverage in Suzhou from the Expanded Program on Immunization database, and influenza vaccine effectiveness estimates from previous publications. Averted influenza estimations were presented as absolute numbers and in terms of the prevented fraction (PF). A hypothetical scenario with 50% coverage (but identical vaccine effectiveness) over the study period was also modeled.

resultsIn ~250,000 children, influenza vaccination prevented an estimated 731 (CI: 549-960) influenza hospitalizations (PF: 6.2% of expected, CI: 5.8-6.6%) and 10,024 (7593-12,937) influenza illnesses (PF: 6.5%, 6.4-6.7%), of which 8342 (6338-10,768) were MA (PF: 6.6%, 6.4-6.7%) from 2011 to 2016. The PFs declined each year along with decreasing influenza vaccination coverage. If 50% of the study population had been vaccinated over time, the estimated numbers of averted cases during the study period would have been 4059 (3120-5762) influenza hospitalizations (PF: 27.2%, 26.4-27.9%) and 56,215 (42,925-78,849) influenza illnesses (PF: 28.5%, 28.3-28.7%), of which 46,596 (35,662-65,234) would be MA (PF: 28.5%, 28.3-28.7%).

conclusionInfluenza vaccination is estimated to have averted influenza-associated illness outcomes even with low coverage in children aged 6-59 months in Suzhou. Increasing influenza vaccination coverage in this population could further reduce illnesses and hospitalizations.

Indexed as

Influenza, HumanInfluenza VaccinesAdolescentAdultChildChinaHospitalizationHumansInfantMiddle AgedSeasonsVaccinationYoung AdultInfluenza VaccinesAverted outcomesChildrenHospitalizationInfluenza illnessInfluenza vaccinationMedically attended

Identifiers

PMID33176936
PMCPMC7728434

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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.