Evidence map›Paper›PMID 36632179›Full record

ArticleInfectious Disease Modelling2023

The mechanism shaping the logistic growth of mutation proportion in epidemics at population scale.

Shi Zhao, Inchi Hu, Jingzhi Lou, Marc K C Chong, Lirong Cao, Daihai He, Benny C Y Zee, Maggie H Wang

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

Article in Infectious Disease Modelling, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
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 3 institutions in 2 countries.

Shi ZhaoJC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China.
Inchi HuDepartment of Information Systems, Business Statistics and Operations Management, Hong Kong University of Science and Technology, Hong Kong, China.
Jingzhi LouJC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China.
Marc K C ChongJC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China.
Lirong CaoJC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China.
Daihai HeDepartment of Applied Mathematics, Hong Kong Polytechnic University, Hong Kong, China.
Benny C Y ZeeJC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China.
Maggie H WangJC School of Public Health and Primary Care, Chinese University of Hong Kong, Hong Kong, China.
Chinese University of Hong Kong · HKHong Kong Polytechnic University · HKHong Kong University of Science and Technology · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Virus evolution is a common process of pathogen adaption to host population and environment. Frequently, a small but important fraction of virus mutations are reported to contribute to higher risks of host infection, which is one of the major determinants of infectious diseases outbreaks at population scale. The key mutations contributing to transmission advantage of a genetic variant often grow and reach fixation rapidly. Based on classic epidemiology theories of disease transmission, we proposed a mechanistic explanation of the process that between-host transmission advantage may shape the observed logistic curve of the mutation proportion in population. The logistic growth of mutation is further generalized by incorporating time-varying selective pressure to account for impacts of external factors on pathogen adaptiveness. The proposed model is implemented in real-world data of COVID-19 to capture the emerging trends and changing dynamics of the B.1.1.7 strains of SARS-CoV-2 in England. The model characterizes and establishes the underlying theoretical mechanism that shapes the logistic growth of mutation in population.

Indexed as

COVID-19Logistic growthPopulation dynamicsSelective pressureTransmission advantage

Identifiers

PMID36632179
PMCPMC9811219
OpenAlexW4312221455

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.