Evidence map›Paper›PMID 33045428›Full record

ArticleInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases2021

Epidemiological Characteristics and Factors Associated with Critical Time Intervals of COVID-19 in Eighteen Provinces, China: A Retrospective Study.

Feng Zhou, Chong You, Xiaoyu Zhang, Kaihuan Qian, Yan Hou, Yanhui Gao, Xiao-Hua Zhou

Open access · goldAbstract read
In one paragraph

Article in International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 40% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Imported COVID-19 cases: A hot topic with a lack of a clear definition.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2021
    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

7 authors at 3 institutions in 2 countries.

Feng ZhouDepartment of Biostatistics, School of Public Health, Peking University, Beijing, China.
Chong YouBeijing International Center for Mathematical Research, Peking University, Beijing, China.
Xiaoyu ZhangSchool of Medicine, Macau University of Science and Technology, Macau, China.
Kaihuan QianDepartment of Biostatistics, School of Public Health, Peking University, Beijing, China.
Yan HouDepartment of Biostatistics, School of Public Health, Peking University, Beijing, China.
Yanhui GaoDepartment of Epidemiology and Medical statistics, School of Public Health, Guangdong Pharmaceutical University, Guangzhou, China.
Xiao-Hua ZhouDepartment of Biostatistics, School of Public Health, Peking University, Beijing, China; Beijing International Center for Mathematical Research, Peking University, Beijing, China; School of Mathematical Sciences, Peking University, Beijing, China. Electronic address: azhou@math.pku.edu.cn.
Peking University · CNGuangdong Pharmaceutical University · CNMacau University of Science and Technology · MO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs COVID-19 ravages continuously around the world, more information on the epidemiological characteristics and factors associated with time interval between critical events is needed to contain the pandemic and to assess the effectiveness of interventions.

methodsIndividual information on confirmed cases from January 21 to March 2 was collected from provincial or municipal health commissions. We identified the difference between imported and local cases in the epidemiological characteristics. Two models were established to estimate the factors associated with time interval from symptom onset to hospitalization (TOH) and length of hospital stay (LOS) respectively.

resultsAmong 7,042 cases, 3392 (48.17%) were local cases and 3304 (46.92%) were imported cases. Since the first intervention was adopted in Hubei on January 23, the daily reported imported cases reached a peak on January 28 and gradually decreased since then. Imported cases were on average younger (41 vs. 48), and had more male (58.66% vs. 47.53%) compared to local cases. Furthermore, imported cases had more contacts with other confirmed cases (2.80 ± 2.33 vs. 2.17 ± 2.10), which were mainly within family members (2.26 ± 2.18 vs. 1.57 ± 2.06). The TOH and LOS were 2.67 ± 3.69 and 18.96 ± 7.63 days respectively, and a longer TOH was observed in elderly living in the provincial capital cities that were higher migration intensity with Hubei.

conclusionsMeasures to restrict traffic can effectively reduce imported spread. However, household transmission is still not controlled, particularly for the infection of imported cases to elderly women. It is still essential to surveil and educate patients about the early admission or isolation.

Indexed as

SARS-CoV-2AdolescentAdultAgedAged, 80 and overChinaCOVID-19FemaleHospitalizationHumansLength of StayMaleMiddle AgedRetrospective StudiesTime FactorsYoung AdultCOVID-19EpidemiologyHousehold Transmission.Imported CasesTime Interval

Identifiers

PMID33045428
PMCPMC7545161
OpenAlexW3092496095

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.