Evidence map›Paper›PMID 32631426›Full record

ArticleInfectious diseases of poverty2020

Transmission patterns of COVID-19 in the mainland of China and the efficacy of different control strategies: a data- and model-driven study.

Jian Zu, Miao-Lei Li, Zong-Fang Li, Ming-Wang Shen, Yan-Ni Xiao, Fan-Pu Ji

Open access · goldAbstract read
In one paragraph

Article in Infectious diseases of poverty, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 8% 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

30 citing papers in PubMed, 1 synthesis or guideline pooled it, 72 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

6 authors at 2 institutions in 1 country.

Jian ZuSchool of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China. jianzu@xjtu.edu.cn.
Miao-Lei LiSchool of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China.
Zong-Fang LiNational & Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710004, China.
Ming-Wang ShenSchool of Public Health, Health Science Center, Xi'an Jiaotong University, Xi'an, 710061, China.
Yan-Ni XiaoSchool of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an, 710049, China.
Fan-Pu JiNational & Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710004, China. jifanpu1979@163.com.ORCID http://orcid.org/0000-0002-1463-8035
Xi'an Jiaotong University · CNSecond Affiliated Hospital of Xi'an Jiaotong University · CN

Funding

Fundamental Research Funds for the Central Universities for COVID-19 xzy032020026Fundamental Research Funds for the Central Universities for COVID-19 xzy032020027Fundamental Research Funds for the Central Universities for COVID-19 xzy032020040,xzy012019107National Natural Science Foundation of China 11801435National Natural Science Foundation of China 11971375, 11571272, 11631012National Science and Technology Major Project of China 2018ZX10721202Natural Science Foundation of Shaanxi Province 2019JM-273Natural Science Foundation of Shaanxi Province 2019JQ-187Zhejiang University special scientific research fund for COVID-19 prevention and control 2020XGZX056
6 · The paper itself

Abstract

backgroundThe coronavirus disease 2019 (COVID-19) outbreak has seriously endangered the health and lives of Chinese people. In this study, we predicted the COVID-19 epidemic trend and estimated the efficacy of several intervention strategies in the mainland of China.

methodsAccording to the COVID-19 epidemic status, we constructed a compartmental model. Based on reported data from the National Health Commission of People's Republic of China during January 10-February 17, 2020, we estimated the model parameters. We then predicted the epidemic trend and transmission risk of COVID-19. Using a sensitivity analysis method, we estimated the efficacy of several intervention strategies.

resultsThe cumulative number of confirmed cases in the mainland of China will be 86 763 (95% CI: 86 067-87 460) on May 2, 2020. Up until March 15, 2020, the case fatality rate increased to 6.42% (95% CI: 6.16-6.68%). On February 23, 2020, the existing confirmed cases reached its peak, with 60 890 cases (95% CI: 60 350-61 431). On January 23, 2020, the effective reproduction number was 2.620 (95% CI: 2.567-2.676) and had dropped below 1.0 since February 5, 2020. Due to governmental intervention, the total number of confirmed cases was reduced by 99.85% on May 2, 2020. Had the isolation been relaxed from February 24, 2020, there might have been a second peak of infection. However, relaxing the isolation after March 16, 2020 greatly reduced the number of existing confirmed cases and deaths. The total number of confirmed cases and deaths would increase by 8.72 and 9.44%, respectively, due to a 1-day delayed diagnosis in non-isolated infected patients. Moreover, if the coverage of close contact tracing was increased to 100%, the cumulative number of confirmed cases would be decreased by 88.26% on May 2, 2020.

conclusionsThe quarantine measures adopted by the Chinese government since January 23, 2020 were necessary and effective. Postponing the relaxation of isolation, early diagnosis, patient isolation, broad close-contact tracing, and strict monitoring of infected persons could effectively control the COVID-19 epidemic. April 1, 2020 would be a reasonable date to lift quarantine in Hubei and Wuhan.

Indexed as

BetacoronavirusChinaCommunicable Disease ControlCoronavirus InfectionsCOVID-19Disease Transmission, InfectiousForecastingHumansModels, StatisticalNational Health ProgramsPandemicsPneumonia, ViralSARS-CoV-2COVID-19Effective reproduction numberIntervention strategyPrevalenceSARS-CoV-2Transmission dynamics

Identifiers

PMID32631426
PMCPMC7338105
OpenAlexW3040497931

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.