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

Accurate disease forecasting can inform public health policies. Nonetheless, many countries, including Afghanistan, have yet to learn from this exercise. This study aimed to forecast tuberculosis (TB) prevalence in Afghanistan until 2032 and to estimate the reproduction number R 0 using a mathematical model. 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. 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. 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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Publication Details

Journal
Journal of Biosafety and Biosecurity
Published
2025-12-25
DOI
https://doi.org/10.1016/j.jobb.2025.12.003
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Muhammad Haroon Stanikzai, Mohammad Farooq Hakimi, Abdul Raqib Muslimyar, Dost Mohammad Faizi et al.
Journal of Biosafety and Biosecurity
Tuberculosis Research and Epidemiology
article

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

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

Abstract

Accurate disease forecasting can inform public health policies. Nonetheless, many countries, including Afghanistan, have yet to learn from this exercise. This study aimed to forecast tuberculosis (TB) prevalence in Afghanistan until 2032 and to estimate the reproduction number R 0 using a mathematical model. 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. 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. 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.

Journal of Biosafety and BiosecurityVol. 8(1)
Kabul University (AF), Kandahar University (AF)
Openalex Percentile: Top 31%
Tuberculosis Research and Epidemiology
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Forecasting tuberculosis prevalence in Afghanistan until 2032: a mathematical modelling analysis — Muhammad Haroon Stanikzai, Mohammad Farooq Hakimi, et al. · Journal of Biosafety and Biosecurity (2025) | TGRS Research Map | TGRS