Seasonal dynamic model for projecting tuberculosis epidemiological trends in Kyrgyzstan☆
6 affiliations
- 1Department of Scientific Research Management, I.K. Akhunbaev Kyrgyz State Medical Academy, Bishkek, Kyrgyzstan
- 2School of Public Health, Xinjiang Medical University, Urumqi, China
- 3Department of Strategic Development and International Cooperation, National Tuberculosis Program, Bishkek, Kyrgyzstan
- 4National Center for Tuberculosis, Ministry of Health, Bishkek, Kyrgyzstan
- 5College of Information Engineering, Xinjiang Institute of Engineering, Urumqi, China
- 6College of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, China
Abstract
Tuberculosis (TB) remains a major public health burden in Kyrgyzstan; however, the seasonal transmission dynamics of TB in the country have not been quantitatively characterized. This study aimed to develop a seasonal dynamic model to simulate TB transmission, estimate the basic reproduction number R ₀, assess transmission intensity, and inform evidence-based prevention and control strategies. Using monthly reported new TB cases from the national TB surveillance and registration system in Kyrgyzstan from 2022 to 2025, we constructed a seasonal SEIR model incorporating periodic transmission and reactivation rates. Model parameters were estimated using a Bayesian Markov chain Monte Carlo (MCMC) method. R ₀ was calculated using two methods: the periodic time-varying method and the annual average transmission rate method. Local sensitivity analysis was performed to evaluate the impact of the baseline transmission parameter a s and the baseline reactivation parameter a e on TB transmission dynamics. The model adequately captured the seasonal fluctuations and overall downward trend in new TB cases, achieving a mean absolute percentage error (MAPE) of 8.66% and a root mean square percentage error (RMSPE) of 9.95%. The estimated periodic R ₀ was 0.8842 (95% credible interval [CrI]: 0.8811-0.8873), which remained below the threshold of unity. Assuming no change in current prevention and control measures, projections suggest a gradual decline in monthly new TB cases, with the annual number of new cases declining to approximately 2902 by 2126. These results indicate that TB transmission has not been fully interrupted and that elimination is unlikely to be achieved within the projection period. Sensitivity analysis revealed that both a s and a e substantially affected the number of new TB cases and R ₀, and that modest changes in these parameters could drive R ₀ above the threshold of unity. The seasonal SEIR model provided a good fit to the monthly number of new TB cases in Kyrgyzstan. Although the estimated R ₀ is below the threshold of unity, indicating a declining epidemic trend, the rate of decline remains relatively slow, highlighting the need to sustain and strengthen prevention and control measures.
Related
- Spondylodiscitis in a tuberculosis-endemic setting in Somalia: epidemiological, clinical, radiological, and outcome findings from a retrospective study
- Epidemiological Modeling of Seasonal Influenza Through Periodic Mean-Reverting Stochastic Processes
- Seasonal variations of Triatoma dimidiata demography and Trypanosoma cruzi transmission within its multi-host community in the Yucatan Peninsula, Mexico: Insights from an integrative SIR eco-epidemiological modelling
- Epidemiological Study of Utilization of National Tuberculosis Elimination Programme Services among Key TB Patients accessing Public Sector Facilities in Central Gujarat: A Cross-Sectional Study
- Altitude and child development: A cross‐sectional comparative study of children in urbanized low‐altitude and rural high‐altitude settings in Kyrgyzstan
BibTeX
@article{altynai2026seasonal,
title = {{Seasonal dynamic model for projecting tuberculosis epidemiological trends in Kyrgyzstan☆}},
author = {Baitelieva Altynai and Pengwei Lou and Kalmambetova Gulmira and Daniil Shauer and Jiabo Xu and Kai Wang},
journal = {Infectious Disease Modelling},
year = {2026},
month = oct,
doi = {10.1016/j.idm.2026.10.003},
url = {https://europepmc.org/article/PMC/PMC13717878},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Seasonal dynamic model for projecting tuberculosis epidemiological trends in Kyrgyzstan☆
AU - Baitelieva Altynai
AU - Pengwei Lou
AU - Kalmambetova Gulmira
AU - Daniil Shauer
AU - Jiabo Xu
AU - Kai Wang
PY - 2026
DA - 2026/10/13
JO - Infectious Disease Modelling
DO - 10.1016/j.idm.2026.10.003
UR - https://europepmc.org/article/PMC/PMC13717878
AB - Tuberculosis (TB) remains a major public health burden in Kyrgyzstan; however, the seasonal transmission dynamics of TB in the country have not been quantitatively characterized. This study aimed to develop a seasonal dynamic model to simulate TB transmission, estimate the basic reproduction number R ₀, assess transmission intensity, and inform evidence-based prevention and control strategies. Using monthly reported new TB cases from the national TB surveillance and registration system in Kyrgyzstan from 2022 to 2025, we constructed a seasonal SEIR model incorporating periodic transmission and reactivation rates. Model parameters were estimated using a Bayesian Markov chain Monte Carlo (MCMC) method. R ₀ was calculated using two methods: the periodic time-varying method and the annual average transmission rate method. Local sensitivity analysis was performed to evaluate the impact of the baseline transmission parameter a s and the baseline reactivation parameter a e on TB transmission dynamics. The model adequately captured the seasonal fluctuations and overall downward trend in new TB cases, achieving a mean absolute percentage error (MAPE) of 8.66% and a root mean square percentage error (RMSPE) of 9.95%. The estimated periodic R ₀ was 0.8842 (95% credible interval [CrI]: 0.8811-0.8873), which remained below the threshold of unity. Assuming no change in current prevention and control measures, projections suggest a gradual decline in monthly new TB cases, with the annual number of new cases declining to approximately 2902 by 2126. These results indicate that TB transmission has not been fully interrupted and that elimination is unlikely to be achieved within the projection period. Sensitivity analysis revealed that both a s and a e substantially affected the number of new TB cases and R ₀, and that modest changes in these parameters could drive R ₀ above the threshold of unity. The seasonal SEIR model provided a good fit to the monthly number of new TB cases in Kyrgyzstan. Although the estimated R ₀ is below the threshold of unity, indicating a declining epidemic trend, the rate of decline remains relatively slow, highlighting the need to sustain and strengthen prevention and control measures.
SN - 2468-2152
SN - 2468-0427
ER -