Evidence map›Paper›PMID 42205146›Full record

ArticleInfectious Disease Modelling2026

Spatial heterogeneity and tendency prediction of a community transmission model with HIV detection.

Jiaxin Liu, Fengying Wei, Zhen Jin, Jianfeng Xie

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Article in Infectious Disease Modelling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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4 authors.

Jiaxin LiuSchool 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.
Jianfeng XieFujian Provincial Center for Disease Control and Prevention, Fuzhou, 350012, Fujian, China.

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6 · The paper itself

Abstract

Background: World Health Organization recommends that the individuals with HIV infection take HIV detection as early as possible to avoid the potential transmission risk in the community, because HIV infection often exhibit no any symptoms and being neglected by the individuals at the acute phase. In China, a series of policies relating to HIV detection have been announced by the Chinese Center for Disease Control and Prevention for effectively controlling the HIV/AIDS infection scale. Methods: The next generation matrix method is governed to derive the basic reproduction number of SIDMA model with HIV detection in this study. The least squares method is used to perform the optimal fitting against the surveillance data of HIV/AIDS. The sensitivity index and partial rank correlation coefficients are used to investigate the impacts of key parameters on the HIV/AIDS incidence. The ARIMA model method is applied to predict the gender and age distributions of the Fujian HIV/AIDS epidemics. The Gini index method is for the spatial heterogeneity of all diagnosed cases. Results: The numerical simulation results show that the HIV/AIDS incidence depends on two significant parameters: detection rate and effective contact rate, and that basic reproduction number relies on effective contact rate. This study reveals that the long awareness delay extends the infection scale and prevalence risk of HIV/AIDS, and that the spatial heterogeneity of diagnosed cases in nine cities of Fujian Province is relatively uniform. The 2023-2030 tendency predictions with scenarios indicate that detection rate of SIDMA model is most critical for the prevalence of the Fujian HIV/AIDS epidemics. The gender and age predictions by ARIMA model indicate that females and 60 years old and over face the potential high HIV infection risks. Conclusions: The HIV detection rate is the most important contributor of SIDMA model for suppressing the HIV/AIDS incidence. The declining trend of basic reproduction number of SIDMA model in five phases indicates that HIV detection in Fujian Province have achieved remarkable achievements. The 2023-2030 tendency predictions of the Fujian HIV/AIDS epidemics provide the estimations with low-level incidence, meeting the control goal from the Chinese government. The four insights are recommended to the policy-makers and the local governments for fighting against the HIV/AIDS prevalence.

Indexed as

Basic reproduction numberHIV/AIDSHIV detectionSIDMA modelSpatial heterogeneityTendency prediction

Identifiers

PMID42205146
PMCPMC13202286

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