Modeling tuberculosis transmission dynamics in Kazakhstan using SARIMA and SIR models
Aigerim Kalizhanova1, Sauran Yerdessov2, Yesbolat Sakko3
1Department of Mathematics, School of Sciences and Humanities, Nazarbayev University, Astana, 010000, Kazakhstan.
Scientific Reports
|October 22, 2024
Summary
This study modeled tuberculosis (TB) transmission in Kazakhstan using statistical and mathematical approaches. Findings indicate a declining TB incidence and a receding epidemic, supporting targeted control strategies.
Area of Science:
- Epidemiology
- Mathematical Modeling
- Public Health
Background:
- Tuberculosis (TB) presents a persistent global health challenge, with Kazakhstan experiencing significant difficulties in its control.
- Understanding TB transmission dynamics is crucial for effective public health interventions.
Purpose of the Study:
- To develop and compare statistical (SARIMA) and deterministic (SIR) models for analyzing TB transmission in Kazakhstan.
- To assess TB incidence trends and epidemic dynamics in Kazakhstan from 2014 to 2019.
Main Methods:
- Retrospective quantitative analysis of TB data from Kazakhstan's Unified National Electronic Health System (2014-2019).
- Development and comparison of Seasonal Autoregressive Integrated Moving Average (SARIMA) and Susceptible-Infected-Recovered (SIR) models.
- Evaluation of model predictive accuracy and calculation of the basic reproduction number (R0).
Main Results:
- SARIMA models effectively captured seasonal TB incidence variations, with one model showing superior predictive accuracy.
- Both SARIMA and SIR models indicated a declining trend in TB incidence.
- The SIR model yielded a basic reproduction number below 1, suggesting a receding epidemic.
Conclusions:
- Statistical and mathematical models provide valuable insights into TB transmission dynamics and epidemic trends in Kazakhstan.
- The findings support the effectiveness of current TB control strategies and inform future public health planning.
- This study lays the groundwork for more in-depth research on TB epidemiology and control in the region.
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