Evidence map›Paper›PMID 33271800›Full record

ArticleVaccines2020

Influenza Vaccination and Non-Pharmaceutical Measure Effectiveness for Preventing Influenza Outbreaks in Schools: A Surveillance-Based Evaluation in Beijing.

Ying Sun, Peng Yang, Quanyi Wang, Li Zhang, Wei Duan, Yang Pan, Shuangsheng Wu, Huaqing Wang

Abstract read
In one paragraph

Article in Vaccines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

8 authors.

Ying SunDepartment of National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing 100050, China.
Peng YangOffice of Beijing Center for Global Health, Beijing Center for Diseases Prevention and Control (CDC), Beijing 100013, China.
Quanyi WangInstitute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China.
Li ZhangInstitute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China.
Wei DuanInstitute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China.
Yang PanInstitute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China.ORCID 0000-0002-1994-6029
Shuangsheng WuInstitute for Infectious Diseases and Endemic Diseases Prevention and Control, Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China.
Huaqing WangDepartment of National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing 100050, China.

Funding

Beijing Center for Disease Prevention and Control, Beijing Research Center for Preventive Medicine 2019-BJYJ-03Beijing Science and Technology Planning Project Z201100005420010National Key R&D Program of China 2017YFC1309304
6 · The paper itself

Abstract

Although schools are known to play a major role in the spread of influenza virus, few studies have evaluated the effectiveness of vaccination and non-pharmaceutical measures for preventing influenza outbreaks in schools. We investigated all febrile illness outbreaks in primary and secondary schools in Beijing reported between August 2018 and July 2019. We obtained epidemiological information on febrile illness outbreaks and oral pharyngeal swabs from students in the outbreaks to test for influenza virus. We surveyed schools that did not report febrile illness outbreaks. We developed multi-level models to identify and evaluate factors associated with serious influenza outbreaks and explored the association of vaccine coverage and outbreaks using multi-stage regression models. We identified a total of 748 febrile illness outbreaks involving 8176 students in Beijing; 462 outbreaks were caused by influenza virus. Adjusted regression modeling showed that large class size (odds ratio (OR) = 2.38) and the number of days from identification of the first case to initiation of an intervention (OR = 1.17) were statistically significant and positively associated with serious outbreaks, and that high vaccination coverage (relative risk (RR) = 0.50) was statistically significant and negatively associated with outbreaks. Multi-stage regression modeling showed that RR decreased fastest when vaccination coverage was 45% to 51%. We conclude that high influenza vaccination coverage can prevent influenza outbreaks in schools and that rapid identification of febrile children and early initiation of non-pharmaceutical measures can reduce outbreak size.

Indexed as

febrile outbreakinfluenza vaccinationmulti-level modelmulti-stage regressionnon-pharmaceutical measure

Identifiers

PMID33271800
PMCPMC7712374

What OpenQuestion holds

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LicenceCC BY
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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.