Modeling tuberculosis transmission dynamics in Kazakhstan using SARIMA and SIR models.

ABSTRACT: Tuberculosis (TB) is a highly contagious disease that remains a global concern affecting numerous countries. Kazakhstan has been facing considerable challenges in TB prevention and treatment for decades. This study aims to understand TB transmission dynamics by developing and comparing statistical and deterministic models: Seasonal Autoregressive Integrated Moving Average (SARIMA) and the basic Susceptible-Infected-Recovered (SIR). TB data from 2014 to 2019 were collected from the Unified National Electronic Health System (UNEHS) using retrospective quantitative analysis. SARIMA models were able to capture seasonal variations, with Model 2 exhibiting superior predictive accuracy. Both models showed declining TB incidence and revealed a notable predictive performance evaluated by statistica

SUBMITTER: Kalizhanova A 

PROVIDER: S-EPMC11496611 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature