Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review
Viet Long Bui1, Angus E Hughes2, Romain Ragonnet2
1School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia. viet.bui1@monash.edu.
Agent-based models (ABMs) offer a detailed approach to understanding tuberculosis (TB) transmission, capturing complex population dynamics often missed by traditional models. Improving transparency through shared code is key for future TB research.
Area of Science:
- Epidemiology
- Computational Biology
- Public Health Modeling
Background:
- Traditional epidemiological models oversimplify Mycobacterium tuberculosis (M.tb) transmission dynamics.
- Agent-based modeling (ABM) is increasingly recognized for its ability to represent complex TB transmission heterogeneity.
Conclusions:
- ABMs are versatile for complex disease dynamics like TB, addressing heterogeneous mixing and household transmission.
- Challenges include stochasticity, parameter tuning, and high computational costs.
- Recommendations include open-source code sharing and standardized reporting to improve ABM reliability and reproducibility for TB research.
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