Mathematical Models for Tuberculosis Disease Transmission in Southeast Asia: A Systematic Literature Review

Abstract

Research on tuberculosis (TB) continues to be a primary focus, given its status as a serious threat to global health, including in the Southeast Asia region. Enhancing understanding of the TB transmission model is imperative, with the main objectives of this study being (1) identifying developed models, (2) describing the study methodologies employed, and (3) identifying proposed interventions within these models. By applying for a Systematic Literature Review following the 2020 PRISMA guidelines, we successfully collected 872 articles from the Scopus database, specifically focusing on those studying TB spread through compartmental mathematical models. However, only 21 articles met the eligibility criteria for further analysis utilizing the meta-synthesis analysis method. Each article was then thoroughly analyzed to identify its characteristics and research context. Various interventions proposed in each model were evaluated, identified, and summarized to understand the potential for model development in future research. The entire content of the articles discusses the role of mathematics in analyzing TB models and transmission studies, with various interventions explained in detail. The results of the analysis indicate that the mathematical modelling of TB transmission can be enhanced by developing models with direct and indirect interventions for the human population. Various approaches in tuberculosis transmission dynamics, including compartmental models and spatial modelling techniques, are highlighted in this research. Evaluating the effectiveness of interventions and control measures implemented in the models also serves as a focal point to assess their impact on TB spread. This review contributes to synthesizing existing knowledge, identifying research gaps, and highlighting opportunities for future advancements in mathematical modelling for TB control strategies in the Southeast Asia region.