Agent-based modelling of Mycobacterium tuberculosis transmission: A systematic review

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Abstract

Abstract Background: Traditional epidemiological models simplify many aspects of Mycobacterium tuberculosis transmission to capture observed tuberculosis (TB) epidemic dynamics, leading to interest in more advanced methodologies,such as agent-based modelling (ABM), that can more flexibly represent the underlying complexity. We synthesised evidence on the application of ABMs in TB transmission modelling to identify trends, methodological approaches, and directions for future research. Methods: Following PRISMA and Cochrane guidelines, we searched electronic databases and supplemented this approach by searching reference lists of included studies. Eligible studies were screened against the inclusion criteria. Results: We identified 26 eligible studies that employed ABMs to model M.tb transmission and evaluate interventions. Study characteristics differed in relation to their population, setting, time horizon, software, and computational expense. Conclusions: ABMs are a versatile approach for representing complex disease dynamics, particularly in cases such as TB, where heterogeneous mixing and household transmission are often overlooked by traditional models. However, their advanced capabilities come with challenges, including those arising from their stochastic nature, such as parameter tuning and high computational expense. To improve transparency and reproducibility, open-source code sharing and standardised reporting are recommended to enhance ABM reliability in studying epidemiologically complex diseases such as TB. PROSPERO Registration: CRD42022380580.