Evidence map›Paper›PMID 40303718›Full record

ArticleTransboundary and emerging diseases2023

International Importation Risk Estimation of SARS-CoV-2 Omicron Variant with Incomplete Mobility Data.

Yan Zhu, Yuan Bai, Mingda Xu, Lin Wang, Thomas K T Li, Zhanwei Du, Yuexuan Wang

Abstract read
In one paragraph

Article in Transboundary and emerging diseases, 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

7 authors.

Yan ZhuQICI Quantum Information and Computation Initiative, Department of Computer Science, The University of Hong Kong, Pokfulam Road, Hong Kong, China.ORCID https://orcid.org/0000-0002-4963-160X
Yuan BaiWHO Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, Hong Kong Special Administrative Region, The University of Hong Kong, Hong Kong, China.
Mingda XuLaboratory of Data Discovery for Health Limited, Hong Kong Science Park, Hong Kong Special Administrative Region, Hong Kong, China.ORCID https://orcid.org/0009-0002-7153-5953
Lin WangDepartment of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.
Thomas K T LiDepartment of Obstetrics and Gynecology, Queen Mary Hospital, The University of Hong Kong, Hong Kong, China.
Zhanwei DuWHO Collaborating Center for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, Hong Kong Special Administrative Region, The University of Hong Kong, Hong Kong, China.
Yuexuan WangAI Technology Lab, Department of Computer Science, The University of Hong Kong, Pokfulam Road, Hong Kong, China.ORCID https://orcid.org/0000-0002-8573-0867

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A novel Omicron subvariant named BQ.1 emerged in Nigeria in July 2022 and has since become a dominant strain, causing a significant number of repeated infections even in countries with high-vaccination rates. Due to the high flow of people between Western Africa and other non-African countries, there is a high risk of Omicron BQ.1 being introduced to other countries from Western Africa. In this context, we developed a model based on deep neural networks to estimate the probability that the Omicron BQ.1 introduced to other countries from Western Africa based on the incomplete population mobility data from Western Africa to other non-African countries. Our study found that the highest risk was in France and Spain during the study period, while the importation risk of other 13 non-African countries including Canada and the United States is also high. Our approach sheds light on how deep learning techniques can assist in the development of public health policies, and it has the potential to be extended to other types of viruses.

Indexed as

COVID-19SARS-CoV-2Africa, WesternHumansRisk AssessmentTravel

Identifiers

PMID40303718
PMCPMC12016809

What OpenQuestion holds

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Registered trials

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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.