Evidence map›Paper›PMID 35346101›Full record

ArticleBMC infectious diseases2022

Comparison of 19 major infectious diseases during COVID-19 epidemic and previous years in Zhejiang, implications for prevention measures.

Haopeng Li, Feng Ling, Shiyu Zhang, Ying Liu, Chongjian Wang, Hualiang Lin, Jimin Sun, Yinglin Wu

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 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
3.4field-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

20 citing papers in PubMed, 34 citations in OpenAlex.

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  8. Impact of the COVID-19 pandemic on infectious diseases reporting.Journal of preventive medicine and hygiene · 2024
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  20. Hygiene Behavior and COVID-19 Pandemic: Opportunities of COVID-19-Imposed Changes in Hygiene Behavior.Inquiry : a journal of medical care organization, provision and financing
    Article
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 at 3 institutions in 1 country.

Haopeng Li *Department of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Feng Ling *Key Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Shiyu ZhangDepartment of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Ying LiuKey Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China.
Chongjian WangDepartment of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, China.
Hualiang LinDepartment of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Jimin SunKey Laboratory of Vaccine, Prevention and Control of Infectious Disease of Zhejiang Province, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, Zhejiang, China. jmsun@cdc.zj.cn.
Yinglin WuDepartment of Epidemiology, School of Public Health, Sun Yat-Sen University, Guangzhou, Guangdong, China. wuyl27@mail2.sysu.edu.cn.
Sun Yat-sen University · CNZhejiang Center for Disease Control and Prevention · CNZhengzhou University · CN

Funding

Bill and Melinda Gates Foundation INV-016826National Natural Science Foundation of China 82041021
6 · The paper itself

Abstract

backgroundThe global pandemic of coronavirus disease 2019 (COVID-19) has attracted great public health efforts across the world. Few studies, however, have described the potential impact of these measures on other important infectious diseases.

methodsThe incidence of 19 major infectious diseases in Zhejiang Province was collected from the National Notifiable Infectious Disease Surveillance System from January 2017 to October 2020. The entire epidemic control phase was divided into three stages. The government deployed the first level response from 24 January to 2 March (the most rigorous measures). When the outbreak of COVID-19 was under control, the response level changed to the second level from 3 to 23 March, and then the third level response was implemented after 24 March. We compared the epidemiological characteristics of 19 major infectious diseases during different periods of the COVID-19 epidemic and previous years.

resultsA total of 1,814,881 cases of 19 infectious diseases were reported in Zhejiang from January 2017 to October 2020, resulting in an incidence rate of 8088.30 cases per 1,000,000 person-years. After the non-pharmaceutical intervention, the incidence of 19 infectious diseases dropped by 70.84%, from 9436.32 cases per 1,000,000 person-years to 2751.51 cases per 1,000,000 person-years, with the large decrease in the first response period of influenza. However, we observed that the daily incidence of severe fever with thrombocytopenia syndrome (SFTS) and leptospirosis increased slightly (from 1.11 cases per 1,000,000 person-years to 1.82 cases per 1,000,000 person-years for SFTS and 0.30 cases per 1,000,000 person-years to 1.24 cases per 1,000,000 person-years for leptospirosis). There was no significant difference in the distribution of epidemiological characteristic of most infectious diseases before and during the implementation of COVID-19 control measures.

conclusionOur study summarizes the epidemiological characteristics of 19 infectious diseases and indicates that the rigorous control measures for COVID-19 are also effective for majority of infectious diseases.

Indexed as

Communicable DiseasesCOVID-19EpidemicsDisease OutbreaksHumansIncidenceCommunicable diseasesCOVID-19Prevention and control

Identifiers

PMID35346101
PMCPMC8958816
OpenAlexW4220870131

What OpenQuestion holds

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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.