Evidence map›Paper›PMID 40479011›Full record

ArticleFundamental research2023

Dynamic and classifier-based model SARS-CoV-2 Omicron spillover risk assessment in China.

Hongjie Wei, Jia Rui, Yunkang Zhao, Huimin Qu, Jing Wang, Guzainuer Abudurusuli, Qiuping Chen, Zeyu Zhao, Wentao Song, Yao Wang and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Fundamental research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Hongjie WeiState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.
Jia RuiState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.
Yunkang ZhaoState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.
Huimin QuState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.
Jing WangState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.
Guzainuer AbudurusuliState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.
Qiuping ChenState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.
Zeyu ZhaoState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.
Wentao SongState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.
Yao WangState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.
Roger FrutosCIRAD, Intertryp, Montpellier, France.
Tianmu ChenState Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen 361000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) continues to have a huge impact on health care and economic systems around the world. The first question to ponder is to understand the flow of COVID-19 in the spatial and temporal dimensions. We collected 7 Omicron clusters outbreaks in China since the outbreak of COVID-19 as of August 2022, selected outbreak cases from different Provinces and cities, and collected variable indicators that affect spillover outcomes, such as distance, migration index, PHSM index, daily reported cases number and so on. First, variables influencing spillover outcome events were assessed and analyzed retrospectively by constructing an infectious disease dynamics model and a classifier model, and secondly, the association between explanatory variables and spillover outcome events was constructed by fitting a logistics function. This study incorporates 7 influencing factors and classifies the spillover risk level into 3 levels. If different outbreak sites could be classified into different levels of spillover, it may reduce the pressure of epidemic prevention in some cities due to the lack of a uniform standard, which might be more conducive to achieving the goal of "dynamic zero".

Indexed as

a classifier modeldynamics modelinfluencing factorsSARS-CoV-2 Omicronspatial spillover risk

Identifiers

PMID40479011
PMCPMC10164289

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.