Evidence map›Paper›PMID 35331730›Full record

ArticleJournal of theoretical biology2022

The non-pharmaceutical interventions may affect the advantage in transmission of mutated variants during epidemics: A conceptual model for COVID-19.

Shi Zhao, Kai Wang, Marc K C Chong, Salihu S Musa, Mu He, Lefei Han, Daihai He, Maggie H Wang

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of theoretical biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Trial
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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

8 authors at 1 institution in 1 country.

Shi ZhaoJC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China; CUHK Shenzhen Research Institute, Shenzhen, China. Electronic address: zhaoshi.cmsa@gmail.com.
Kai WangDepartment of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, China.
Marc K C ChongJC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China; CUHK Shenzhen Research Institute, Shenzhen, China. Electronic address: marc@cuhk.edu.hk.
Salihu S MusaDepartment of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China; Department of Mathematics, Kano University of Science and Technology, Wudil, Nigeria. Electronic address: salihu-sabiu.musa@connect.polyu.hk.
Mu HeDepartment of Foundational Mathematics, Xi'an Jiaotong-Liverpool University, Suzhou, China. Electronic address: mu.he@xjtlu.edu.cn.
Lefei HanSchool of Global Health, Chinese Center for Tropical Diseases Research, Shanghai Jiao Tong University School of Medicine, Shanghai, China. Electronic address: lfhan@sjtu.edu.cn.
Daihai HeDepartment of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China. Electronic address: daihai.he@polyu.edu.hk.
Maggie H WangJC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China; CUHK Shenzhen Research Institute, Shenzhen, China. Electronic address: maggiew@cuhk.edu.hk.
Xinjiang Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As the COVID-19 pandemic continues, genetic mutations in SARS-CoV-2 emerge, and some of them are found more contagious than the previously identified strains, acting as the major mechanism for many large-scale epidemics. The transmission advantage of mutated variants is widely believed as an innate biological feature that is difficult to be altered by artificial factors. In this study, we explore how non-pharmaceutical interventions (NPI) may affect transmission advantage. A two-strain compartmental epidemic model is proposed and simulated to investigate the biological mechanism of the relationships among different NPIs, the changes in transmissibility of each strain and transmission advantage. Although the NPIs are effective in flattening the epidemic curve, we demonstrate that NPIs probably lead to a decline in transmission advantage, which is likely to occur if the NPIs become intensive. Our findings uncover the mechanistic relationship between NPIs and transmission advantage dynamically, and highlight the important role of NPIs not only in controlling the intensity of epidemics but also in slowing or even containing the growth of the proportion of variants.

Indexed as

COVID-19EpidemicsHumansModels, TheoreticalPandemicsSARS-CoV-2COVID-19Mathematical modellingNon-pharmaceutical interventionReproduction numberTransmission advantage

Identifiers

PMID35331730
PMCPMC8934756
OpenAlexW4220741665

What OpenQuestion holds

Textmetadata
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.