预测阿富汗到2032年的结核病流行：一个数学模型分析

IF 3.5 Q1 Social Sciences

Journal of Biosafety and Biosecurity Pub Date : 2026-03-01 Epub Date: 2025-12-24 DOI:10.1016/j.jobb.2025.12.003

Abdul Raqib Muslimyar , Mohammad Farooq Hakimi , Dost Mohammad Faizi , Muhammad Haroon Stanikzai , Naqibullah Wardak

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引用次数: 0

摘要

准确的疾病预测可以为公共卫生政策提供信息。然而，包括阿富汗在内的许多国家尚未从这次演习中吸取教训。本研究旨在预测阿富汗到2032年的结核病（TB）患病率，并使用数学模型估计繁殖数R0。方法采用易感感染（SI）非线性流行模型对阿富汗结核病流行进行预测。模型参数是根据阿富汗公共卫生部在2013年至2022年期间收集的数据估计的。还对SI模型的拟合优度进行了评估。结果SI模型预测到2032年阿富汗结核病患病率将上升至0.214058。此外，我们使用2013年至2022年期间收集的结核病报告数据对模型进行了参数化，并估计基本复制数约为3.39。该研究表明，SI模型预测了未来几年阿富汗结核病患病率的非线性增长。因此，该模型可以帮助卫生政策制定者优化资源分配并指导该国未来的结核病治疗公共卫生战略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Forecasting tuberculosis prevalence in Afghanistan until 2032: a mathematical modelling analysis

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Forecasting tuberculosis prevalence in Afghanistan until 2032: a mathematical modelling analysis

Background

Accurate disease forecasting can inform public health policies. Nonetheless, many countries, including Afghanistan, have yet to learn from this exercise.

Objectives

This study aimed to forecast tuberculosis (TB) prevalence in Afghanistan until 2032 and to estimate the reproduction number

R_{0}

using a mathematical model.

Methods

We utilised the susceptible–infected (SI) nonlinear epidemic model to forecast the prevalence of TB in Afghanistan. The model parameters were estimated from the data collected by the Afghan Ministry of Public Health between 2013 and 2022. The goodness-of-fit of the SI model was also assessed.

Results

The SI model predicted that the prevalence of TB in Afghanistan would increase to 0.214058 by 2032. In addition, we parameterised the model using the TB notification data collected between 2013 and 2022 and estimated the basic reproduction number at approximately 3.39.

Conclusion

The study indicates that the SI model predicts a nonlinear increase in TB prevalence in Afghanistan in the years ahead. Therefore, this model can help inform health policymakers in optimising resource allocation and guiding future public health strategies for TB care in the country.

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