Ale Seun, Hunter Elizabeth, Kelleher John D
School of Computer Science, Technological University Dublin, Grangegorman Lower, Dublin, D07 H6K8, Dublin, Ireland.
School of Computer Science and Statistics, Trinity College Dublin, College Green, Dublin, D02 PN40, Dublin, Ireland.
BMC Infect Dis. 2024 Dec 18;24(1):1411. doi: 10.1186/s12879-024-10271-w.
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.
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.
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.
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.
历史上用于模拟传染病爆发的模型是基于方程的模型和统计模型。然而，这些模型没有考虑到影响常见血液传播病毒（BBV）传播的个人和社会因素，如人类免疫缺陷病毒（HIV）、丙型肝炎病毒（HCV）和乙型肝炎病毒（HBV）。基于主体的建模（ABM）是一种在公共卫生和流行病学中越来越受欢迎的替代建模方法。随着该领域的不断扩展，了解ABM的应用方式变得很重要。在此背景下，我们完成了一项关于BBV的ABM研究的范围综述。
纳入/排除标准是根据人群、概念和背景（PCC）的理念制定的。在检索研究BBV的ABM文献时，采用了系统评价和Meta分析的首选报告项目（PRISMA-ScR），这是范围综述的扩展。系统检索了三个数据库（Scopus、Pubmed和Embase）以获取文章。从所有数据库中检索到200篇文章，其中有10篇重复。去除重复项后，筛选出190篇论文以供纳入。在分析其余文章后，70篇在摘要筛选阶段被排除，32篇在全文判定阶段被排除。88篇被保留用于范围综述分析。为了分析这88篇论文的语料库，我们开发了一个五级分类法，首先根据疾病类型，然后是传播机制，接着是建模人群，再是地理位置，最后是模型结果对每篇论文进行分类。
该分析结果表明，BBV文献的ABM存在显著差距，特别是在影响BBV传播的社会和个人因素建模方面。
需要更全面的模型来解决不同人群、传播和干预机制下的各种结果。虽然ABM是研究BBV的有价值工具，但需要进一步研究以填补现有差距，并增进我们对影响BBV传播和控制的个人和社会因素的理解。这项研究可以让研究人员、建模人员、流行病学家和公共卫生从业者了解ABM研究领域，这些领域需要进一步探索以减轻全球BBV的负担。
