Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review
Abstract Background Traditional epidemiological models tend to oversimplify the transmission dynamics of Mycobacterium tuberculosis (M.tb) to replicate observed tuberculosis (TB) epidemic patterns. This has led to growing interest in advanced methodologies like agent-based modelling (ABM), which can...
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| Format: | Article |
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BMC
2024-12-01
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| Series: | BMC Infectious Diseases |
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| Online Access: | https://doi.org/10.1186/s12879-024-10245-y |
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| author | Viet Long Bui Angus E. Hughes Romain Ragonnet Michael T. Meehan Alec Henderson Emma S. McBryde James M. Trauer |
| author_facet | Viet Long Bui Angus E. Hughes Romain Ragonnet Michael T. Meehan Alec Henderson Emma S. McBryde James M. Trauer |
| author_sort | Viet Long Bui |
| collection | DOAJ |
| description | Abstract Background Traditional epidemiological models tend to oversimplify the transmission dynamics of Mycobacterium tuberculosis (M.tb) to replicate observed tuberculosis (TB) epidemic patterns. This has led to growing interest in advanced methodologies like agent-based modelling (ABM), which can more accurately represent the complex heterogeneity of TB transmission. Objectives To better understand the use of agent-based models (ABMs) in this context, we conducted a systematic review with two main objectives: (1) to examine how ABMs have been employed to model the intricate heterogeneity of M.tb transmission, and (2) to identify the challenges and opportunities associated with implementing ABMs for M.tb. Search methods We conducted a systematic search following PRISMA guidelines across four databases (MEDLINE, EMBASE, Global Health, and Scopus), limiting our review to peer-reviewed articles published in English up to December 2022. Data were extracted by two investigators using a standardized extraction tool. Prospero registration: CRD42022380580. Selection criteria Our review included peer-reviewed articles in English that implement agent-based, individual-based, or microsimulation models of M.tb transmission. Models focusing solely on in-vitro or within-host dynamics were excluded. Data extraction targeted the methodological, epidemiological, and computational characteristics of ABMs used for TB transmission. A risk of bias assessment was not conducted as the review synthesized modelling studies without pooling epidemiological data. Results Our search initially identified 5,077 studies, from which we ultimately included 26 in our final review after exclusions. These studies varied in population settings, time horizons, and model complexity. While many incorporated population heterogeneity and household structures, some lacked essential features like spatial structures or economic evaluations. Only eight studies provided publicly accessible code, highlighting the need for improved transparency. Authors’ conclusions ABMs are a versatile approach for representing complex disease dynamics, particularly in cases like TB, where they address heterogeneous mixing and household transmission 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 like TB. |
| format | Article |
| id | doaj-art-1f19ab1fbb774cbc9b8608f28ac3ec79 |
| institution | OA Journals |
| issn | 1471-2334 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Infectious Diseases |
| spelling | doaj-art-1f19ab1fbb774cbc9b8608f28ac3ec792025-08-20T02:20:41ZengBMCBMC Infectious Diseases1471-23342024-12-0124111110.1186/s12879-024-10245-yAgent-based modelling of Mycobacterium tuberculosis transmission: a systematic reviewViet Long Bui0Angus E. Hughes1Romain Ragonnet2Michael T. Meehan3Alec Henderson4Emma S. McBryde5James M. Trauer6School of Public Health and Preventive Medicine, Monash UniversitySchool of Public Health and Preventive Medicine, Monash UniversitySchool of Public Health and Preventive Medicine, Monash UniversityAustralian Institute of Tropical Health and Medicine, James Cook UniversityAustralian Institute of Tropical Health and Medicine, James Cook UniversityAustralian Institute of Tropical Health and Medicine, James Cook UniversitySchool of Public Health and Preventive Medicine, Monash UniversityAbstract Background Traditional epidemiological models tend to oversimplify the transmission dynamics of Mycobacterium tuberculosis (M.tb) to replicate observed tuberculosis (TB) epidemic patterns. This has led to growing interest in advanced methodologies like agent-based modelling (ABM), which can more accurately represent the complex heterogeneity of TB transmission. Objectives To better understand the use of agent-based models (ABMs) in this context, we conducted a systematic review with two main objectives: (1) to examine how ABMs have been employed to model the intricate heterogeneity of M.tb transmission, and (2) to identify the challenges and opportunities associated with implementing ABMs for M.tb. Search methods We conducted a systematic search following PRISMA guidelines across four databases (MEDLINE, EMBASE, Global Health, and Scopus), limiting our review to peer-reviewed articles published in English up to December 2022. Data were extracted by two investigators using a standardized extraction tool. Prospero registration: CRD42022380580. Selection criteria Our review included peer-reviewed articles in English that implement agent-based, individual-based, or microsimulation models of M.tb transmission. Models focusing solely on in-vitro or within-host dynamics were excluded. Data extraction targeted the methodological, epidemiological, and computational characteristics of ABMs used for TB transmission. A risk of bias assessment was not conducted as the review synthesized modelling studies without pooling epidemiological data. Results Our search initially identified 5,077 studies, from which we ultimately included 26 in our final review after exclusions. These studies varied in population settings, time horizons, and model complexity. While many incorporated population heterogeneity and household structures, some lacked essential features like spatial structures or economic evaluations. Only eight studies provided publicly accessible code, highlighting the need for improved transparency. Authors’ conclusions ABMs are a versatile approach for representing complex disease dynamics, particularly in cases like TB, where they address heterogeneous mixing and household transmission 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 like TB.https://doi.org/10.1186/s12879-024-10245-yAgent-based modellingTuberculosisMycobacterium tuberculosisTransmission |
| spellingShingle | Viet Long Bui Angus E. Hughes Romain Ragonnet Michael T. Meehan Alec Henderson Emma S. McBryde James M. Trauer Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review BMC Infectious Diseases Agent-based modelling Tuberculosis Mycobacterium tuberculosis Transmission |
| title | Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review |
| title_full | Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review |
| title_fullStr | Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review |
| title_full_unstemmed | Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review |
| title_short | Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review |
| title_sort | agent based modelling of mycobacterium tuberculosis transmission a systematic review |
| topic | Agent-based modelling Tuberculosis Mycobacterium tuberculosis Transmission |
| url | https://doi.org/10.1186/s12879-024-10245-y |
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