Evidence map›Paper›PMID 35649394›Full record

ArticleJMIR public health and surveillance2022

Changes in Temporal Properties of Notifiable Infectious Disease Epidemics in China During the COVID-19 Pandemic: Population-Based Surveillance Study.

Xixi Zhao, Meijia Li, Naem Haihambo, Jianhua Jin, Yimeng Zeng, Jinyi Qiu, Mingrou Guo, Yuyao Zhu, Zhirui Li, Jiaxin Liu and 9 more

Open access · goldAbstract read
In one paragraph

Article in JMIR public health and surveillance, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

16 citing papers in PubMed, 28 citations in OpenAlex.

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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

19 authors at 11 institutions in 4 countries.

Xixi Zhao *The National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.ORCID 0000-0003-1745-8184
Meijia Li *Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, Brussel, Belgium.ORCID 0000-0001-8893-3697
Naem HaihamboFaculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, Brussel, Belgium.ORCID 0000-0002-1909-3919
Jianhua JinZhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.ORCID 0000-0002-3009-8745
Yimeng ZengState Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal Univeristy, Beijing, China.ORCID 0000-0003-4753-4328
Jinyi QiuSchool of Artificial Intelligence, Beijing Normal University, Beijing, China.ORCID 0000-0001-8675-3158
Mingrou GuoBrain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.ORCID 0000-0002-3942-0286
Yuyao ZhuCollege of Environmental Sciences and Engineering, Peking University, Beijing, China.ORCID 0000-0002-4443-886X
Zhirui LiBaoding First Central Hospital, Baoding, China.ORCID 0000-0002-9001-9332
Jiaxin LiuDepartment of Psychology, University of Washington, Seattle, Seattle, WA, United States.ORCID 0000-0003-0652-9100
Jiayi TengSchool of Psychology, Philosophy and Language Science, University of Edinburgh, Edinburgh, United Kingdom.ORCID 0000-0002-1320-2846
Sixiao LiSchool of Music, Faculty of Arts, University of Leeds, Leeds, United Kingdom.ORCID 0000-0001-8887-5028
Ya-Nan ZhaoInstitute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, Beijing, China.ORCID 0000-0002-7513-0569
Yanxiang CaoThe National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-2175-5846
Xuemei WangThe National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-6842-9888
Yaqiong LiThe National Clinical Research Center for Mental Disorders, Beijing Anding Hospital, Capital Medical University, Beijing, China.ORCID 0000-0002-1717-7625
Michel GaoWM Therapeutics Ltd, Beijing, China.ORCID 0000-0002-8647-7701
Xiaoyang FengInstitute of Mental Health, Peking University Sixth Hospital, Beijing, China.ORCID 0000-0003-1065-8597
Chuanliang HanBrain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.ORCID 0000-0002-5734-4790
Capital Medical University · CNBeijing Normal University · CNChinese Academy of Sciences · CNPeking University · CNVrije Universiteit Brussel · BEBaoding People's Hospital · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNSun Yat-sen University · CNUniversity of Edinburgh · GBUniversity of Leeds · GBUniversity of Washington · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCOVID-19 was first reported in 2019, and the Chinese government immediately carried out stringent and effective control measures in response to the epidemic.

objectiveNonpharmaceutical interventions (NPIs) may have impacted incidences of other infectious diseases as well. Potential explanations underlying this reduction, however, are not clear. Hence, in this study, we aim to study the influence of the COVID-19 prevention policies on other infectious diseases (mainly class B infectious diseases) in China.

methodsTime series data sets between 2017 and 2021 for 23 notifiable infectious diseases were extracted from public data sets from the National Health Commission of the People's Republic of China. Several indices (peak and trough amplitudes, infection selectivity, preferred time to outbreak, oscillatory strength) of each infectious disease were calculated before and after the COVID-19 outbreak.

resultsWe found that the prevention and control policies for COVID-19 had a strong, significant reduction effect on outbreaks of other infectious diseases. A clear event-related trough (ERT) was observed after the outbreak of COVID-19 under the strict control policies, and its decreasing amplitude is related to the infection selectivity and preferred outbreak time of the disease before COVID-19. We also calculated the oscillatory strength before and after the COVID-19 outbreak and found that it was significantly stronger before the COVID-19 outbreak and does not correlate with the trough amplitude.

conclusionsOur results directly demonstrate that prevention policies for COVID-19 have immediate additional benefits for controlling most class B infectious diseases, and several factors (infection selectivity, preferred outbreak time) may have contributed to the reduction in outbreaks. This study may guide the implementation of nonpharmaceutical interventions to control a wider range of infectious diseases.

Indexed as

Communicable DiseasesCOVID-19ChinaDisease OutbreaksHumansPandemicsclass B infectious diseaseCOVID-19epidemiologyevent-related troughhealth policyinfection selectivityoscillationpandemicprevention policypublic healthpublic health interventionsrisk preventionsurveillance

Identifiers

PMID35649394
PMCPMC9231598
OpenAlexW4282939334

What OpenQuestion holds

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LicenceCC BY
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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.