Evidence map›Paper›PMID 39270985›Full record

ArticleVirologica Sinica2024

The spatiotemporal analysis of SARS-CoV-2 transmission in China since the termination of the dynamic zero-COVID policy.

Jiaying Li, Jingqi Yang, Xiao Ding, Hangyu Zhou, Na Han, Aiping Wu

Abstract read
In one paragraph

Article in Virologica Sinica, 2024. 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
–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

3 citing papers in PubMed.

  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

6 authors.

Jiaying LiState Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China.
Jingqi YangState Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China.
Xiao DingState Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China.
Hangyu ZhouState Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China.
Na HanState Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China.
Aiping WuState Key Laboratory of Common Mechanism Research for Major Diseases, Suzhou Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Suzhou 215123, China; Key Laboratory of Pathogen Infection Prevention and Control (Peking Union Medical College), Ministry of Education, Beijing 100730, China. Electronic address: wap@ism.cams.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

China's dynamic zero-COVID policy has effectively curbed the spread of SARS-CoV-2, while inadvertently creating immunity gaps within its population. Subsequent surges in COVID-19 cases linked to various SARS-CoV-2 lineages post-policy termination necessitate a thorough investigation into the epidemiological landscape. This study addresses this issue by analyzing a comprehensive dataset of 39,456 high-quality genomes collected nationwide over an 11-month period since policy termination. Through lineage assignment, phylogenetic analysis, pandemic pattern comparison, phylodynamic reconstruction, and recombination detection, we found that China's post-epidemic period could be divided into three stages, along with dynamic changes in dominant lineages. Geographical clustering of similar lineages implies the importance of cross-border cooperation among neighboring regions. Compared to the USA, UK, and Japan, China exhibits unique trajectories of lineage epidemics, characterized by initial lagging followed by subsequent advancement, indicating the potential influence of diverse prevention and control policies on lineage epidemic patterns. Hong Kong, Shanghai, and Hubei emerge as pivotal nodes in the nationwide spread, marking a shift in the transmission center from east to central regions of China. Although China hasn't experienced significant variant emergence, the detection and validation of the novel recombination event, XCN lineage, underscore the ongoing virus evolution. Overall, this study systematically analyzes the spatiotemporal transmission of SARS-CoV-2 virus in China since the termination of the dynamic zero-COVID policy, offering valuable insights for regional surveillance and evidence-based public health policymaking.

Indexed as

COVID-19PhylogenySARS-CoV-2Spatio-Temporal AnalysisChinaGenome, ViralHealth PolicyHumansRecombination, GeneticDynamic zero-COVID policyEpidemiologyPopulation immunityRecombinationSARS-CoV-2

Identifiers

PMID39270985
PMCPMC11738790

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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.