Analysis of predicted trends in drug-resistant tuberculosis incidence in Urumqi based on a dynamic model of resistance gene mutations

This study aims to predict the future incidence of tuberculosis in Urumqi using a dynamic model that incorporates pathogenic molecular characteristics. Sputum samples from tuberculosis patients in Urumqi were collected from 2017 to 2021. Following mycobacterium tuberculosis culture, strain identification, drug sensitivity tests and whole-genome sequencing, drug resistance genes mutations were analyzed. Additionally, tuberculosis incidence data from 2014 to 2023 were collected. A dynamic model incorporating pathogenic molecular characteristics was developed to predict tuberculosis incidence. Mutations in the isoniazid resistance gene KatG, ethambutol resistance gene embB, and the amikacin, kanamycin and capreomycin co-resistant genes rrs were observed at loci not listed in the second edition of the World Health Organization mutation catalog for Mycobacterium tuberculosis complex. Predictions generated by the dynamic model, which includes these unique mutation sites, indicate a slight decline in drug-resistant tuberculosis incidence in Urumqi in the future. This suggests that these specific mutations may influence future drug-resistant tuberculosis incidence in the region. Incorporating pathogen biological characteristics into dynamic models for predicting the incidence trends of infectious diseases is feasible. Moreover, specific mutation sites may play a role in shaping the future trajectory of drug-resistant tuberculosis incidence in Urumqi.

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Publication Details

Journal
Advances in Continuous and Discrete Models
Published
2026-01-15
DOI
https://doi.org/10.1186/s13662-025-04050-3
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
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article

Analysis of predicted trends in drug-resistant tuberculosis incidence in Urumqi based on a dynamic model of resistance gene mutations

Pengwei Lou, Yanggui Chen, Yaoqin Lu, Jiandong Yang et al.
Advances in Continuous and Discrete Models
Tuberculosis Research and Epidemiology
article

Analysis of predicted trends in drug-resistant tuberculosis incidence in Urumqi based on a dynamic model of resistance gene mutations

Pengwei Lou, Yanggui Chen, Yaoqin Lu, Jiandong Yang, Jiabo Xu
article en

Abstract

This study aims to predict the future incidence of tuberculosis in Urumqi using a dynamic model that incorporates pathogenic molecular characteristics. Sputum samples from tuberculosis patients in Urumqi were collected from 2017 to 2021. Following mycobacterium tuberculosis culture, strain identification, drug sensitivity tests and whole-genome sequencing, drug resistance genes mutations were analyzed. Additionally, tuberculosis incidence data from 2014 to 2023 were collected. A dynamic model incorporating pathogenic molecular characteristics was developed to predict tuberculosis incidence. Mutations in the isoniazid resistance gene KatG, ethambutol resistance gene embB, and the amikacin, kanamycin and capreomycin co-resistant genes rrs were observed at loci not listed in the second edition of the World Health Organization mutation catalog for Mycobacterium tuberculosis complex. Predictions generated by the dynamic model, which includes these unique mutation sites, indicate a slight decline in drug-resistant tuberculosis incidence in Urumqi in the future. This suggests that these specific mutations may influence future drug-resistant tuberculosis incidence in the region. Incorporating pathogen biological characteristics into dynamic models for predicting the incidence trends of infectious diseases is feasible. Moreover, specific mutation sites may play a role in shaping the future trajectory of drug-resistant tuberculosis incidence in Urumqi.

Advances in Continuous and Discrete ModelsVol. 2026(1)
Xinjiang Medical University (CN), Xinjiang Uygur Autonomous Region Disease Prevention and Control Center (CN), Xinjiang Institute of Engineering (CN)
Good health and well-being
Openalex Percentile: Top 85%
Tuberculosis Research and Epidemiology
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Analysis of predicted trends in drug-resistant tuberculosis incidence in Urumqi based on a dynamic model of resistance gene mutations — Pengwei Lou, Yanggui Chen, et al. · Advances in Continuous and Discrete Models (2026) | TGRS Research Map | TGRS