Evidence map›Paper›PMID 40797252›Full record

ArticleBMC public health2025

Impact of detection rate and preventive treatment of latent tuberculosis infection on the future burden of tuberculosis among students in shanghai: a predictive study using Markov modeling.

Xiao Xiao, Zhipeng Li, Jing Chen, Xin Shen

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Article in BMC public health, 2025. 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Xiao Xiao *Division of Tuberculosis and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, 1380 Zhongshan West Road, Shanghai, China.
Zhipeng Li *Division of Tuberculosis and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, 1380 Zhongshan West Road, Shanghai, China.
Jing ChenDivision of Tuberculosis and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, 1380 Zhongshan West Road, Shanghai, China. chenjing@scdc.sh.cn.
Xin ShenDivision of Tuberculosis and HIV/AIDS Prevention, Shanghai Municipal Center for Disease Control and Prevention, 1380 Zhongshan West Road, Shanghai, China. shenxin@scdc.sh.cn.

Funding

Key Young Talents Training Program for Shanghai Disease Control and Prevention 22QNGG04Shanghai Municipal Health Commission youth Project 20214Y0480Shanghai three-year (2023-2025) action plan to strengthen the public health system GWVI-11.1-05 and GWVI-11.2-YQ16
6 · The paper itself

Abstract

backgroundStudents represent a key demographic for tuberculosis (TB) control in China. This study utilizes a dynamic Markov model to forecast the epidemiological trends of active tuberculosis (ATB) among students in Shanghai through 2035 and evaluate the effectiveness of different control strategies.

methodsA Markov model incorporating six distinct states of TB transmission was utilized to simulate disease dynamics within a hypothetical cohort of 100,000 individuals. The model assessed the prevalence of latent tuberculosis infection (LTBI) and ATB, categorizing the cases based on whether they received the recommended treatment regimen.

resultsUnder the current measures without any additional interventions, the model projected a marginal decline in ATB prevalence. Specifically, ATB prevalence is predicted to decrease to 14.80 per 100,000 by 2035. With an increase in tuberculosis preventive treatment (TPT) coverage to 20%, 50%, or 80%, the reductions in ATB prevalence were modest. When the detection rate of LTBI was fixed at 12% and combined with TPT coverage levels of 20%, 50%, and 80%, the reductions in ATB prevalence were 17.01%, 36.56%, and 50.68% respectively. Increasing the detection rate of LTBI to 35% alongside TPT coverages of 20%, 50%, and 80% led to more pronounced declines in ATB prevalence, at 40.95%, 69.36%, and 80.46% respectively.

conclusionsUnder the current TB control measures, the prevalence of ATB among students would result in only marginal decline trajectories through 2035, falling substantially short of achieving the strategic goal of ending TB. Enhanced strategies that simultaneously increase detection rates and coverage of TPT are likely to significantly reduce ATB prevalence in this population.

Indexed as

Latent TuberculosisStudentsTuberculosisChinaFemaleForecastingHumansMaleMarkov ChainsPrevalenceYoung AdultLatent tuberculosis infectionMarkov modelTuberculosis prevalenceTuberculosis preventive treatment

Identifiers

PMID40797252
PMCPMC12341062

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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.