Agent based modelling of blood borne viruses: a scoping review.

Autor: Ale S; School of Computer Science, Technological University Dublin, Grangegorman Lower, Dublin, D07 H6K8, Dublin, Ireland. seun.ale@tudublin.ie., Hunter E; School of Computer Science, Technological University Dublin, Grangegorman Lower, Dublin, D07 H6K8, Dublin, Ireland., Kelleher JD; School of Computer Science and Statistics, Trinity College Dublin, College Green, Dublin, D02 PN40, Dublin, Ireland.
Jazyk: angličtina
Zdroj: BMC infectious diseases [BMC Infect Dis] 2024 Dec 18; Vol. 24 (1), pp. 1411. Date of Electronic Publication: 2024 Dec 18.
DOI: 10.1186/s12879-024-10271-w
Abstrakt: Background: The models that historically have been used to model infectious disease outbreaks are equation-based and statistical models. However, these models do not capture the impact of individual and social factors that affect the spread of common blood-borne viruses (BBVs) such as human immunodeficiency virus (HIV), hepatitis C virus (HCV), and hepatitis B virus (HBV). Agent-based modelling (ABM) is an alternative modelling approach that is gaining popularity in public health and epidemiology. As the field expands, it is important to understand how ABMs have been applied. In this context, we completed a scoping review of research that has been done on the ABM of BBVs.
Method: The inclusion/exclusion criteria were drafted using the idea of Population, Concept, and Context (PCC). The Preferred Reporting Item for Systematic Reviews and Meta-Analysis, an extension to scoping review (PRISMA-ScR), was employed in retrieving ABM literature that studied BBVs. Three databases (Scopus, Pubmed, and Embase) were systematically searched for article retrieval. 200 articles were retrieved from all the databases, with 10 duplicates. After removing the duplicates, 190 papers were screened for inclusion. After analysing the remaining articles, 70 were excluded during the abstract screening phase, and 32 were excluded during the full-text decision. Eighty-eight were retained for the scoping review analysis. To analyse this corpus of 88 papers, we developed a five-level taxonomy that categorised each paper based first on disease type, then transmission mechanism, then modelled population, then geographic location and finally, model outcome.
Results: The result of this analysis show significant gaps in the ABM of BBV literature, particularly in the modeling of social and individual factors influencing BBV transmission.
Conclusion: There is a need for more comprehensive models that address various outcomes across different populations, transmission and intervention mechanisms. Although ABMs are a valuable tool for studying BBVs, further research is needed to address existing gaps and improve our understanding of individual and social factors that influence the spread and control of BBVs. This research can inform researchers, modellers, epidemiologists, and public health practitioners of the ABM research areas that need to be explored to reduce the burden of BBVs globally.
Competing Interests: Declarations. Ethics approval and consent to participate: Ethics approval was not required for this research. Consent to participate was not required. Competing interests: The authors declare no competing interests.
(© 2024. The Author(s).)
Databáze: MEDLINE
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