基于贝叶斯时空变异性模型的空间疾病集群进化

IF 2.1 Q3 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH Spatial and Spatio-Temporal Epidemiology Pub Date : 2023-08-27 DOI:10.1016/j.sste.2023.100617
Frank Badu Osei
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引用次数: 0

摘要

本研究提出使用时空随机效应模型的超越后验概率来研究集群的时间动态。为每个区域指定的当地时间趋势在空间上进一步平滑。我们使用多元马尔可夫随机场来模拟共同的空间和空间变化的时间趋势,以纳入区域内的相关性。我们在完全贝叶斯框架内估计模型参数。进一步利用超越后验概率将共同空间趋势划分为热点、冷点和中性点。本地时间趋势分为上升趋势、下降趋势和稳定趋势。结果是一个3×3表,描述了集群内的时间趋势。作为示范,我们应用提出的方法来研究加纳肠道寄生虫感染的空间聚类演变。我们发现本文提出的方法适用并可扩展到其他或多种可能具有不同时空概念的热带病。
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Evolution of spatial disease clusters via a Bayesian space-time variability modelling

This study proposes to use exceedance posterior probabilities of a space-time random-effects model to study the temporal dynamics of clusters. The local time trends specified for each area is further smoothed over space. We modelled the common spatial and the space-varying temporal trend using a multivariate Markov Random field to incorporate within-area correlations. We estimate the model parameters within a fully Bayesian framework. The exceedance posterior probabilities are further used to classify the common spatial trend into hot-spots, cold-spots, and neutral-spots. The local time trends are classified into increasing, decreasing, and stable trends. The results is a 3×3 table depicting the time trends within clusters. As a demonstration, we apply the proposed methodology to study the evolution of spatial clustering of intestinal parasite infections in Ghana. We find the methodology presented in this paper applicable and extendable to other or multiple tropical diseases which may have different space-time conceptualizations.

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来源期刊
Spatial and Spatio-Temporal Epidemiology
Spatial and Spatio-Temporal Epidemiology PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
5.10
自引率
8.80%
发文量
63
期刊最新文献
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