Evidence map›Paper›PMID 40594174›Full record

ArticleScientific reports2025

HPV transmission and optimal control of cervical cancer in China.

Huarong Ren, Rui Xu, Juan Zhang

Abstract read
In one paragraph

Article in Scientific reports, 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.

  1. Article
  2. Article
  3. 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

3 authors.

Huarong RenComplex Systems Research Center, Shanxi University, Taiyuan, 030006, Shanxi, People's Republic of China.
Rui Xu *Complex Systems Research Center, Shanxi University, Taiyuan, 030006, Shanxi, People's Republic of China. xurui@sxu.edu.cn.
Juan Zhang *Complex Systems Research Center, Shanxi University, Taiyuan, 030006, Shanxi, People's Republic of China. zhangjuan1020@sxu.edu.cn.

Funding

National Natural Science Foundation of China 12271317National Natural Science Foundation of China 12371493
6 · The paper itself

Abstract

Cervical cancer (CC), the fourth most common female malignancy globally, is predominantly caused by persistent infection with high-risk human papillomavirus (HPV) strains. China faces a particularly severe burden, exhibiting both the world's second-highest CC prevalence and an alarming epidemiological trend characterized by steadily increasing incidence rates and younger age of onset. In response to the WHO's global elimination strategy, China launched the Action Plan for Accelerated Elimination of Cervical Cancer (2023-2030). Aligned with national prevention and control objectives, considering two key interventions, that is widespread HPV vaccination and systematic CC screening, this study develops a novel two-sex, age-structured transmission model to characterize HPV transmission dynamics and CC progression, and implementation of intervention strategies. Through mathematical modeling analysis and simulation, we quantify age- and sex-specific risk profiles, predict long-term epidemiological trends. Using optimal control theory, we propose a supply-constrained vaccine allocation strategy for maximal population protection and a cost-effective screening implementation plan, which will provide evidence-based recommendations to support China's national CC elimination goals.

Indexed as

PapillomaviridaePapillomavirus InfectionsUterine Cervical NeoplasmsAdolescentAdultAgedChinaEarly Detection of CancerFemaleHumansIncidenceMiddle AgedModels, TheoreticalPapillomavirus VaccinesPrevalenceYoung AdultPapillomavirus VaccinesAge structureCervical cancerDynamical modelHuman papillomavirusOptimum control strategySensitivity analysis

Identifiers

PMID40594174
PMCPMC12218410

What OpenQuestion holds

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LicenceCC BY
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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.