期刊名称：Journal of Artificial Societies and Social Simulation
印刷版ISSN：1460-7425
出版年度：2018
卷号：21
期号：4
页码：1-16
DOI：10.18564/jasss.3870
出版社：University of Surrey, Department of Sociology
摘要：Socioeconomic status can have an important eect on health. In this paper we: (i) propose using house price data as a publicly available proxy for socioeconomic status to examine neighbourhood socioeconomic status at a more fine grained resolution than is available in Irish Central Statistics Oice data; (ii) use a dissimilarity index to demonstrate and measure the existence of socioeconomic clustering at a neighbourhood level; (iii) demonstrate that using a standard ABM initialisation process based on CSO small area data results in ABMs systematically underestimating the socioeconomic clustering in Irish neighbourhoods; (iv) demonstrate that ABM models are better calibrated towards socioeconomic clustering a er a segregation models has been runfor a burn-in period a er initial model setup; and (v) that running a socioeconomic segregation model during the initiation of an ABM epidemiology model can have an eect on the outbreak patterns of the model. Our results support the use of segregation models as useful additions to the initiation process of ABM for epidemiology.
关键词：Agent-Based; Socioeconomic Status; Infectious Disease; Simulation; Model; Segregation Model
