Evidence map›Paper›PMID 36192815›Full record

ArticleInfectious diseases of poverty2022

Assessing the mechanism of citywide test-trace-isolate Zero-COVID policy and exit strategy of COVID-19 pandemic.

Pei Yuan, Yi Tan, Liu Yang, Elena Aruffo, Nicholas H Ogden, Guojing Yang, Haixia Lu, Zhigui Lin, Weichuan Lin, Wenjun Ma and 5 more

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PubMed Full text at PMC Publisher
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Article in Infectious diseases of poverty, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

11 citing papers in PubMed.

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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

15 authors.

Pei Yuan *Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada.
Yi Tan *Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada.
Liu Yang *Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada.
Elena Aruffo *Laboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada.
Nicholas H OgdenCanadian Centre for Diseases Modeling (CCDM), York University, Toronto, Canada.
Guojing YangKey Laboratory of Tropical Translational Medicine of Ministry of Education and School of Tropical Medicine and Laboratory Medicine, The First Affiliated Hospital of Hainan Medical University, Hainan Medical University, Haikou, Hainan, China. guojingyang@hotmail.com.
Haixia LuSchool of Arts and Science, Suqian University, Suqian, Jiangsu, China.
Zhigui LinSchool of Mathematical Science, Yangzhou University, Yangzhou, Jiangsu, China.
Weichuan LinSchool of Mathematics and Statistics, Fujian Normal University, Fuzhou, Fujian, China.
Wenjun MaDepartment of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, Guangdong, China.
Meng FanSchool of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, China.
Kaifa WangSchool of Mathematics and Statistics, Southwest University, Chongqing, China.
Jianhe ShenSchool of Mathematics and Statistics, Fujian Normal University, Fuzhou, Fujian, China.
Tianmu ChenSchool of Public Health and State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Xiamen University, Xiamen, Fujian, China.
Huaiping ZhuLaboratory of Mathematical Parallel Systems (LAMPS), Department of Mathematics and Statistics, York University, 4700 Keele Street, Toronto, ON, M3J1P3, Canada. huaiping@yorku.ca.ORCID http://orcid.org/0000-0003-2718-595X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCountries that aimed for eliminating the cases of COVID-19 with test-trace-isolate policy are found to have lower infections, deaths, and better economic performance, compared with those that opted for other mitigation strategies. However, the continuous evolution of new strains has raised the question of whether COVID-19 eradication is still possible given the limited public health response capacity and fatigue of the epidemic. We aim to investigate the mechanism of the Zero-COVID policy on outbreak containment, and to explore the possibility of eradication of Omicron transmission using the citywide test-trace-isolate (CTTI) strategy.

methodsWe develop a compartmental model incorporating the CTTI Zero-COVID policy to understand how it contributes to the SARS-CoV-2 elimination. We employ our model to mimic the Delta outbreak in Fujian Province, China, from September 10 to October 9, 2021, and the Omicron outbreak in Jilin Province, China for the period from March 1 to April 1, 2022. Projections and sensitivity analyses were conducted using dynamical system and Latin Hypercube Sampling/ Partial Rank Correlation Coefficient (PRCC).

resultsCalibration results of the model estimate the Fujian Delta outbreak can end in 30 (95% confidence interval CI: 28-33) days, after 10 (95% CI: 9-11) rounds of citywide testing. The emerging Jilin Omicron outbreak may achieve zero COVID cases in 50 (95% CI: 41-57) days if supported with sufficient public health resources and population compliance, which shows the effectiveness of the CTTI Zero-COVID policy.

conclusionsThe CTTI policy shows the capacity for the eradication of the Delta outbreaks and also the Omicron outbreaks. Nonetheless, the implementation of radical CTTI is challenging, which requires routine monitoring for early detection, adequate testing capacity, efficient contact tracing, and high isolation compliance, which constrain its benefits in regions with limited resources. Moreover, these challenges become even more acute in the face of more contagious variants with a high proportion of asymptomatic cases. Hence, in regions where CTTI is not possible, personal protection, public health control measures, and vaccination are indispensable for mitigating and exiting the COVID-19 pandemic.

Indexed as

COVID-19Contact TracingHumansPandemicsPolicySARS-CoV-2Citywide testingCOVID-19Exit strategyTest-trace-isolateTransmission modelZero-COVID policy

Identifiers

PMID36192815
PMCPMC9529335

What Socratic 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 Socratic graph.