Evidence map›Paper›PMID 32689711›Full record

ArticleInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases2020

The effectiveness of quarantine and isolation determine the trend of the COVID-19 epidemic in the final phase of the current outbreak in China.

Biao Tang, Fan Xia, Sanyi Tang, Nicola Luigi Bragazzi, Qian Li, Xiaodan Sun, Juhua Liang, Yanni Xiao, Jianhong Wu

Abstract readPublished Erratum
In one paragraph

Article in International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

22 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  11. A switching dynamic model based on phased COVID-19 data in Chongqing and its evaluation.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2022
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  20. Effects of masks on the transmission of infectious diseases.Advances in difference equations · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Biao TangThe Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China; Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, Ontario M3J 1P3, Canada.
Fan XiaThe Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China.
Sanyi TangSchool of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710119, People's Republic of China.
Nicola Luigi BragazziLaboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, Ontario M3J 1P3, Canada.
Qian LiLaboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, Ontario M3J 1P3, Canada; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China.
Xiaodan SunThe Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China; School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China.
Juhua LiangSchool of Mathematics and Information Science, Shaanxi Normal University, Xi'an 710119, People's Republic of China.
Yanni XiaoThe Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China; Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, Ontario M3J 1P3, Canada. Electronic address: yxiao@mail.xjtu.edu.cn.
Jianhong WuThe Interdisciplinary Research Center for Mathematics and Life Sciences, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China; Laboratory for Industrial and Applied Mathematics, Department of Mathematics and Statistics, York University, Toronto, Ontario M3J 1P3, Canada; Fields-CQAM Laboratory of Mathematics for Public Health, York University, Toronto, Ontario M3J 1P3, Canada. Electronic address: wujh@yorku.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesSince January 23, 2020, stringent measures for controlling the novel coronavirus epidemic have been gradually enforced and strengthened in mainland China. The detection and diagnosis have been improved, as well. However, the daily reported cases remaining at a high level make the epidemic trend prediction difficult.

methodsSince the traditional SEIR model does not evaluate the effectiveness of control strategies, a novel model in line with the current epidemic's process and control measures was proposed, utilizing multisource datasets including the cumulative number of reported, deceased, quarantined and suspected cases.

resultsResults show that the trend of the epidemic mainly depends on quarantined and suspected cases. The predicted cumulative numbers of quarantined and suspected cases nearly reached static states, and their inflection points have already been achieved, with the epidemic's peak coming soon. The estimated effective reproduction numbers using model-free and model-based methods are decreasing, as well as new infections, while newly reported cases are increasing. Most infected cases have been quarantined or put in the suspected class, which has been ignored in existing models.

conclusionsThe uncertainty analyses reveal that the epidemic is still uncertain, and it is important to continue enhancing the quarantine and isolation strategy and improving the detection rate in mainland China.

Indexed as

CoronavirusMathematical modelMultisource dataSEIR model

Identifiers

PMID32689711
PMCPMC7269954

What OpenQuestion holds

Textmetadata
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.