Evidence map›Paper›PMID 34350810›Full record

Observational studyEmerging microbes & infections2021

Epidemiological and co-infection characteristics of common human coronaviruses in Shanghai, 2015-2020: a retrospective observational study.

Dechuan Kong, Yaxu Zheng, Linjie Hu, Jian Chen, Huanyu Wu, Zheng Teng, Yanqiu Zhou, Qi Qiu, Yihan Lu, Hao Pan

Open access · goldAbstract readHistorical ArticleObservational Study
In one paragraph

Observational study in Emerging microbes & infections, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

12 citing papers in PubMed, 22 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

10 authors at 2 institutions in 1 country.

Dechuan KongDepartment of Acute Communicable Diseases Control and Prevention, Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, People's Republic of China.
Yaxu ZhengDepartment of Acute Communicable Diseases Control and Prevention, Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, People's Republic of China.
Linjie HuDepartment of Epidemiology, Ministry of Education Key Laboratory of Public Health Safety, Fudan School of Public Health, Shanghai, People's Republic of China.
Jian ChenDepartment of Logistics Support, Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, People's Republic of China.
Huanyu WuShanghai Municipal Centre for Disease Control and Prevention, Shanghai, People's Republic of China.
Zheng TengInstitute of Pathogen Examination, Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, People's Republic of China.
Yanqiu ZhouInstitute of Pathogen Examination, Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, People's Republic of China.
Qi QiuDepartment of Acute Communicable Diseases Control and Prevention, Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, People's Republic of China.
Yihan LuDepartment of Epidemiology, Ministry of Education Key Laboratory of Public Health Safety, Fudan School of Public Health, Shanghai, People's Republic of China.ORCID https://orcid.org/0000-0003-4651-9433
Hao PanInstitute of Communicable Diseases Control and Prevention, Shanghai Municipal Centre for Disease Control and Prevention, Shanghai, People's Republic of China.
Shanghai Municipal Center For Disease Control Prevention · CNChildren's Hospital of Fudan University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease (COVID-19) pandemic is a major challenge worldwide. However, the epidemic potential of common human coronaviruses (HCoVs) remains unclear. This study aimed to determine the epidemiological and co-infection characteristics of common HCoVs in individuals with influenza-like illness (ILI) and severe acute respiratory infection (SARI). This retrospective, observational, multicentre study used data collected from patients admitted to nine sentinel hospitals with ILI and SARI from January 2015 through December 2020 in Shanghai, China. We prospectively tested patients for a total of 22 respiratory pathogens using multi-real-time polymerase chain reaction. Of the 4541 patients tested, 40.37% (1833/4541) tested positive for respiratory pathogens and 3.59% (163/4541) tested positive for common HCoVs. HCoV infection was more common in the non-endemic season for respiratory pathogens (odds ratio: 2.33, 95% confidence interval: 1.64-3.31). HCoV-OC43 (41.72%, 68/163) was the most common type of HCoV detected. The co-infection rate was 31.29% (51/163) among 163 HCoV-positive cases, with HCoV-229E (53.13%, 17/32), the HCoV type that was most frequently associated with co-infection. Respiratory pathogens responsible for co-infections with HCoVs included parainfluenza virus, rhinovirus/enterovirus, influenza A virus, and adenovirus. Furthermore, we identified one patient co-infected with HCoV-OC43 and HCoV-NL63/HKU1. The prevalence of common HCoVs remains low in ILI/SARI cases, in Shanghai. However, the seasonal pattern of HCoVs may be opposite to that of other respiratory pathogens. Moreover, HCoVs are likely to co-exist with specific respiratory pathogens. The potential role of co-infections with HCoVs and other pathogenic microorganisms in infection and pathogenesis of ILI and SARI warrants further study.

Indexed as

AlphacoronavirusSARS-CoV-2AdultAgedAged, 80 and overChinaCoinfectionCoronavirus InfectionsCOVID-19FemaleHistory, 21st CenturyHumansMaleMiddle AgedPrevalencePublic Health Surveillanceco-infectionHCoV-229EHCoV-OC43Human coronavirusrespiratory pathogenSARS-COV-2

Identifiers

PMID34350810
PMCPMC8381891
OpenAlexW3193197419

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.