Evidence map›Paper›PMID 34836947›Full record

ArticleNature communications2021

Changes in notifiable infectious disease incidence in China during the COVID-19 pandemic.

Meng-Jie Geng, Hai-Yang Zhang, Lin-Jie Yu, Chen-Long Lv, Tao Wang, Tian-Le Che, Qiang Xu, Bao-Gui Jiang, Jin-Jin Chen, Simon I Hay and 6 more

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 94 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
94citing papers in PubMed, 1 pooled it
11.5field-weighted citation impact, top 1% of its field
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

94 citing papers in PubMed, 1 synthesis or guideline pooled it, 161 citations in OpenAlex.

  1. Pooled it
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  5. Observational
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  17. Elevated risk of infectious diseases in adulthood after prenatal or early postnatal exposure to the Great Chinese Famine.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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34 more citing papers are in PubMed but not listed here.

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

16 authors at 5 institutions in 3 countries.

Meng-Jie Geng *Division of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
Hai-Yang Zhang *State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China.
Lin-Jie Yu *State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China.
Chen-Long LvState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China.
Tao WangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China.
Tian-Le CheState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China.
Qiang XuState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China.
Bao-Gui JiangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China.
Jin-Jin ChenState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China.
Simon I HayDepartment of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0002-0611-7272
Zhong-Jie LiDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.
George F GaoDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China.ORCID 0000-0002-3869-615X
Li-Ping WangDivision of Infectious Disease, Key Laboratory of Surveillance and Early-warning on Infectious Disease, Chinese Center for Disease Control and Prevention, Beijing, China. wanglp@chinacdc.cn.
Yang YangDepartment of Biostatistics, College of Public Health and Health Professions, and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA. yangyang@ufl.edu.ORCID 0000-0003-0428-5480
Li-Qun FangState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China. fang_lq@163.com.ORCID 0000-0002-4981-1483
Wei LiuState Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China. liuwei@bmi.ac.cn.ORCID 0000-0002-9302-8170
Institute of Microbiology · CNChinese Center For Disease Control and Prevention · CNInstitute of Microbiology · BYUniversity of Florida Health · USUniversity of Washington · US

Funding

Mathematical and Statistical Methods for the Control of Global Infectious Disease ThreatsR56AI148284 · NIAID · UNIVERSITY OF FLORIDA · PI HALLORAN, M ELIZABETH, LONGINI, IRA M · 2020 to 2020
$802k
NIAID NIH HHS R56 AI148284
6 · The paper itself

Abstract

Nationwide nonpharmaceutical interventions (NPIs) have been effective at mitigating the spread of the novel coronavirus disease (COVID-19), but their broad impact on other diseases remains under-investigated. Here we report an ecological analysis comparing the incidence of 31 major notifiable infectious diseases in China in 2020 to the average level during 2014-2019, controlling for temporal phases defined by NPI intensity levels. Respiratory diseases and gastrointestinal or enteroviral diseases declined more than sexually transmitted or bloodborne diseases and vector-borne or zoonotic diseases. Early pandemic phases with more stringent NPIs were associated with greater reductions in disease incidence. Non-respiratory diseases, such as hand, foot and mouth disease, rebounded substantially towards the end of the year 2020 as the NPIs were relaxed. Statistical modeling analyses confirm that strong NPIs were associated with a broad mitigation effect on communicable diseases, but resurgence of non-respiratory diseases should be expected when the NPIs, especially restrictions of human movement and gathering, become less stringent.

Indexed as

ChinaCommunicable Disease ControlCommunicable DiseasesCOVID-19Disease NotificationHumansIncidenceModels, StatisticalSARS-CoV-2

Identifiers

PMID34836947
PMCPMC8626444
OpenAlexW3216330277

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.