Evidence map›Paper›PMID 41772501›Full record

ArticleBMC public health2026

The hidden burden: a regional study revealing the substantial burden and distinct epidemiology of asymptomatic pulmonary tuberculosis in Southern China.

Huiying Feng, Hongdi Liang, Huali Xu, Shanshan Huang, Jianwei Li, Wenpei Wen, Yuhui Chen, Fangjing Zhou

Abstract read
In one paragraph

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

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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

8 authors.

Huiying FengCenter for Tuberculosis Control of Guangdong Province, No.485 of West Huangpu AVE, Tianhe District, Guangzhou, 510630, China.
Hongdi LiangCenter for Tuberculosis Control of Guangdong Province, No.485 of West Huangpu AVE, Tianhe District, Guangzhou, 510630, China.
Huali XuCenter for Tuberculosis Control of Guangdong Province, No.485 of West Huangpu AVE, Tianhe District, Guangzhou, 510630, China.
Shanshan HuangCenter for Tuberculosis Control of Guangdong Province, No.485 of West Huangpu AVE, Tianhe District, Guangzhou, 510630, China.
Jianwei LiCenter for Tuberculosis Control of Guangdong Province, No.485 of West Huangpu AVE, Tianhe District, Guangzhou, 510630, China.
Wenpei WenCenter for Tuberculosis Control of Guangdong Province, No.485 of West Huangpu AVE, Tianhe District, Guangzhou, 510630, China.
Yuhui ChenCenter for Tuberculosis Control of Guangdong Province, No.485 of West Huangpu AVE, Tianhe District, Guangzhou, 510630, China.
Fangjing ZhouCenter for Tuberculosis Control of Guangdong Province, No.485 of West Huangpu AVE, Tianhe District, Guangzhou, 510630, China. zhoufangjing1224@126.com.

Funding

Guangdong Provincial Clinical Research Center for Tuberculosis 2020B1111170014
6 · The paper itself

Abstract

backgroundThe clinical spectrum of pulmonary tuberculosis (PTB) ranges from symptomatic to asymptomatic disease, yet the burden and epidemiology of asymptomatic PTB remain poorly characterized. This study aims to elucidate the prevalence, detection methods, and associated features of asymptomatic PTB in southern China through a large-scale comparative analysis.

methodsWe conducted a regional cross-sectional study using data from China’s Tuberculosis Information Management System (2022–2024). A total of 102,274 PTB patients were classified as symptomatic or asymptomatic according to World Health Organization criteria. Descriptive statistics and χ² tests were used to compare demographics, case detection pathways. A multivariable logistic regression model was performed to examine the factors independently associated with asymptomatic presentation.

resultsAmong all cases, 34.0% (n = 34,741) were asymptomatic. This proportion was consistently higher in the developed Pearl River Delta region than in non-PRD regions. Asymptomatic rates were elevated among younger age groups (15–25 years: 44.5%), migrant populations (39.0%), and high-risk groups (38.3%). Although passive case finding accounted for 97.9% of all cases, active case finding identified a markedly higher proportion of asymptomatic PTB (82.4%). Multivariable analysis revealed that the influence of key factors, such as previous TB history (aOR, 1.75, 95%CI,1.64–1.87) and co-morbidities (aOR, 1.74, 95%CI,1.64–1.84) on symptomatic presentation was significantly modified by regional economic development.

conclusionThis study reveals a substantial, under-ascertained reservoir of asymptomatic PTB in China, which is systematically missed by passive detection strategies. The higher yield of ACF and the identified demographic and regional disparities highlight the urgent need for a strategic shift towards proactive, targeted, and contextually adapted screening interventions to interrupt transmission effectively.

Indexed as

Cost of IllnessTuberculosis, PulmonaryAdolescentAdultAgedChildChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedPrevalenceRisk FactorsYoung AdultAsymptomatic pulmonary tuberculosisRisk factorsSurveillance

Identifiers

PMID41772501
PMCPMC13059173

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