Evidence map›Paper›PMID 39925973›Full record

ArticleInfectious Disease Modelling2025

HCV transmission model with protection awareness in an SEACTR community.

Liangwei Wang, Fengying Wei, Zhen Jin, Xuerong Mao, Shaojian Cai, Guangmin Chen, Kuicheng Zheng, Jianfeng Xie

Abstract read
In one paragraph

Article in Infectious Disease Modelling, 2025. 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.

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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.

Liangwei WangSchool of Mathematics and Statistics, Fuzhou University, Fuzhou, 350116, Fujian, China.
Fengying WeiSchool of Mathematics and Statistics, Fuzhou University, Fuzhou, 350116, Fujian, China.
Zhen JinComplex Models Research Center, Shanxi University, Taiyuan, 030006, Shanxi, China.
Xuerong MaoDepartment of Mathematics and Statistics, University of Strathclyde, Glasgow, G1 1XH, UK.
Shaojian CaiFujian Provincial Center for Disease Control and Prevention, Fuzhou, 350012, Fujian, China.
Guangmin ChenFujian Provincial Center for Disease Control and Prevention, Fuzhou, 350012, Fujian, China.
Kuicheng ZhengFujian Provincial Center for Disease Control and Prevention, Fuzhou, 350012, Fujian, China.
Jianfeng XieFujian Provincial Center for Disease Control and Prevention, Fuzhou, 350012, Fujian, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hepatitis C virus (HCV) is a bloodborne virus that causes both acute and chronic hepatitis with the severity from a mild illness to liver cirrhosis and cancer. As one of the major infectious diseases in China, the monthly surveillance data from the Fujian Provincial Center for Disease Control and Prevention shows the increasing tendency from 2004 to 2011, the stable tendency from 2012 to 2016, and the declining tendency from 2017 to 2022. The 2004-2022 HCV infection tendency of Fujian Province is affected by nation-wide main control measures of Chinese government, because no control measures for HCV are modified from 2020 to 2022 during the prevalence of COVID-19 in Fujian Province. Methods: The SEACTR (the susceptible, the exposed, the acutely infected, the chronically infected, the treated, the recovered) models with protection awareness are proposed. The next generation matrix method is used to compute basic reproduction number of toy model and dynamic analysis method is used to produce stochastic reproduction number of modified model. The least squares method and toy model are used to perform the optimal fitting against the monthly surveillance data. The positive preserving truncated Euler-Maruyama method is applied in modified model for the positivity of numerical simulations. Results: The optimal fitting is performed using the monthly surveillance data provided by the Fujian Provincial Center for Disease Control and Prevention from 2004 to 2022. The sensitivities of protection efficiency and conversion rate to basic reproduction number and stochastic reproduction number are analyzed. The reproduction numbers and HCV infection scale with measures (single-measure, double-measure, triple-measure, and none-measure) are compared using toy model and modified model. The impacts of protection efficiency and conversion rate on exposed population, acutely infected population, chronically infected population, and treated population are analyzed. The tendency predictions for infected population and treated population in Fujian Province from 2023 to 2035 are conducted. Conclusions: The HCV infection scale mainly depends on both protection efficiency and conversion rate, in which protection efficiency is the most important contributor. The reproduction numbers show the declining tendencies by phases, which indicate that the prevention and control of HCV in Fujian Province has achieved a remarkable achievement. The 2023-2035 tendency predictions of HCV infection scale in Fujian Province grow slowly due to approximately 19-109 monthly infections. The overall HCV growth tendency of Fujian Province is consistent with the nation-wide elimination objective.

Indexed as

HCVProtection awarenessSEACTR modelTransmission dynamics

Identifiers

PMID39925973
PMCPMC11803831

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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.