Evidence map›Paper›PMID 37147332›Full record

ArticleScientific reports2023

Modelling the reopen strategy from dynamic zero-COVID in China considering the sequela and reinfection.

Sijin Wu, Zhejun Huang, Susan Grant-Muller, Dongfeng Gu, Lili Yang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.6field-weighted citation impact, top 11% 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

3 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
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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

5 authors at 2 institutions in 2 countries.

Sijin WuDepartment of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, 518055, China.
Zhejun HuangDepartment of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, 518055, China.
Susan Grant-MullerInstitute for Transport Studies, University of Leeds, Leeds, LS2 9JT, UK.
Dongfeng GuSchool of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, 518055, China.
Lili YangDepartment of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, 518055, China. yangll@sustech.edu.cn.
Southern University of Science and Technology · CNUniversity of Leeds · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the dynamic zero-COVID policy has effectively controlled virus spread in China, China has to face challenges in balancing social-economic burdens, vaccine protection, and the management of long COVID symptoms. This study proposed a fine-grained agent-based model to simulate various strategies for transitioning from a dynamic zero-COVID policy with a case study in Shenzhen. The results indicate that a gradual transition, maintaining some restrictions, can mitigate infection outbreaks. However, the severity and duration of epidemics vary based on the strictness of the measures. In contrast, a more direct transition to reopening may lead to rapid herd immunity but necessitate preparedness for potential sequelae and reinfections. Policymakers should assess healthcare capacity for severe cases and potential long-COVID symptoms and determine the most suitable approach tailored to local conditions.

Indexed as

COVID-19ChinaHumansPost-Acute COVID-19 SyndromeReinfectionSARS-CoV-2

Identifiers

PMID37147332
PMCPMC10161982
OpenAlexW4372294512

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.