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Objective <p>This study aims to predict the future incidence of tuberculosis in Urumqi using a dynamic model that incorporates pathogenic molecular characteristics.</p> Methods <p>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.</p> Results <p>Mutations in the isoniazid resistance gene <i>KatG</i>, ethambutol resistance gene <i>embB</i>, and the amikacin, kanamycin and capreomycin co-resistant genes <i>rrs</i> were observed at loci not listed in <i>the second edition of the World Health Organization mutation catalog for Mycobacterium tuberculosis complex</i>. 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.</p> Conclusion <p>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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月15日

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  • Pengwei Lou,
  • Jiandong Yang,
  • Yaoqin Lu,
  • Yanggui Chen,
  • Jiabo Xu

摘要

Objective

This study aims to predict the future incidence of tuberculosis in Urumqi using a dynamic model that incorporates pathogenic molecular characteristics.

Methods

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.

Results

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.

Conclusion

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.