{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T21:50:08Z","timestamp":1778709008461,"version":"3.51.4"},"reference-count":39,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T00:00:00Z","timestamp":1762992000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>This study investigates the dynamics of the drug-resistant tuberculosis model through a fractional stochastic modeling framework. The model employs fractional-order derivatives to capture the memory effects in disease transmission, while Brownian motion is introduced to represent the random disturbances, thereby providing a more realistic description of the disease dynamics. First, a fractional deterministic model based on the Atangana-Baleanu-Caputo derivative was developed, and its optimal parameter values were obtained from the actual data from the case of drug-resistant tuberculosis in China. Second, the existence and uniqueness of the solution of the fractional stochastic model were proved, and its numerical solution was explored. Furthermore, the impacts of different interventions strategies on the control of drug-resistant tuberculosis in China were compared. The results demonstrate that the combined interventions exhibit superior efficacy compared to any single intervention. Numerical simulations of deterministic and fractional stochastic models verify the effects of memory and random effects on drug-resistant tuberculosis. It was found that as the noise level increases, the degree of random perturbation in the model solution also increases, and higher noise levels may lead to the early disappearance of drug-resistant tuberculosis.<\/jats:p>","DOI":"10.1371\/journal.pone.0335889","type":"journal-article","created":{"date-parts":[[2025,11,13]],"date-time":"2025-11-13T18:44:11Z","timestamp":1763059451000},"page":"e0335889","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Analysis of drug-resistant tuberculosis transmission dynamics in China using fractional stochastic model"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2620-336X","authenticated-orcid":true,"given":"Shaoping","family":"Jiang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2570-0756","authenticated-orcid":true,"given":"Hongyan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yudie","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2025,11,13]]},"reference":[{"key":"pone.0335889.ref001","unstructured":"World Health Organization. ea. type. 2023. https:\/\/www.who.int\/teams\/global-tuberculosis-programme\/tb-reports"},{"issue":"2","key":"pone.0335889.ref002","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/S1473-3099(19)30568-7","article-title":"Drug-resistant tuberculosis in eastern Europe and central Asia: a time-series analysis of routine surveillance data","volume":"20","author":"A Dadu","year":"2020","journal-title":"Lancet Infect Dis."},{"issue":"6","key":"pone.0335889.ref003","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.2105\/AJPH.52.6.1002","article-title":"The use of mathematical models in the study of the epidemiology of tuberculosis","volume":"52","author":"H Waaler","year":"1962","journal-title":"Am J Public Health Nations Health."},{"key":"pone.0335889.ref004","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.aej.2022.12.061","article-title":"Investigation of the effect of awareness and treatment on Tuberculosis infection via a novel epidemic model","volume":"68","author":"I Ullah","year":"2023","journal-title":"Alexandria Engineering Journal."},{"key":"pone.0335889.ref005","first-page":"362","article-title":"Dynamic model of tuberculosis considering multi-drug resistance and their applications","volume":"3","author":"Y Yu","year":"2018","journal-title":"Infect Dis Model."},{"key":"pone.0335889.ref006","doi-asserted-by":"crossref","first-page":"100131","DOI":"10.1016\/j.health.2022.100131","article-title":"Effective strategies towards eradicating the tuberculosis epidemic: an optimal control theory alternative","volume":"3","author":"TT Yusuf","year":"2023","journal-title":"Healthcare Analytics."},{"issue":"12","key":"pone.0335889.ref007","doi-asserted-by":"crossref","first-page":"1303","DOI":"10.4236\/am.2016.712115","article-title":"A mathematical model of tuberculosis with drug resistance effects","volume":"07","author":"M Ronoh","year":"2016","journal-title":"AM."},{"issue":"3","key":"pone.0335889.ref008","doi-asserted-by":"crossref","first-page":"467","DOI":"10.3934\/dcdss.2020026","article-title":"Models of fluid flowing in non-conventional media: new numerical analysis","volume":"13","author":"A Atangana","year":"2020","journal-title":"Discrete & Continuous Dynamical Systems - S."},{"key":"pone.0335889.ref009","doi-asserted-by":"crossref","unstructured":"Yavuz M, Akman M, Usta F, \u00d6zdemir N. 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