非线性时空模型的分析模拟方法：Covid-19 传染的空间显著性

IF 2.1 2区数学 Q3 GEOSCIENCES, MULTIDISCIPLINARY

Spatial Statistics Pub Date : 2024-06-13 DOI:10.1016/j.spasta.2024.100844

Michael Beenstock , Yoel Cohen , Daniel Felsenstein

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引用次数: 0

摘要

有向图理论中的 "出度 "用于衡量个别地点在通过传染病时空网络传播 Covid-19 发病率时的显著性，以及它们在疫苗接种推广的时空扩散中的显著性。在一个空间计量经济学模型中，发病率与疫苗接种推广情况成反比变化，而疫苗接种推广情况与发病率直接变化，该模型用于计算发病率的动态自动淘汰度和疫苗接种对发病率影响的动态交叉淘汰度。前者确定传染热点，后者确定疫苗接种推广对降低全国发病率特别有效的地点。这些跨度是通过分析而不是数字模拟计算出来的。

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Analytical simulation methodology for nonlinear spatiotemporal models: Spatial salience in Covid-19 contagion

‘Outdegree’ from directed graph theory is used to measure the salience of individual locations in the transmission of Covid-19 morbidity through the spatiotemporal network of contagion and their salience in the spatiotemporal diffusion of vaccination rollout. A spatial econometric model in which morbidity varies inversely with vaccination rollout, and vaccination rollout varies directly with morbidity is used to calculate dynamic auto-outdegrees for morbidity and dynamic cross-outdegrees for the effect of vaccination on morbidity. The former identifies hot spots of contagion, and the latter identifies locations in which vaccination rollout is particularly effective in reducing national morbidity. These outdegrees are calculated analytically rather than simulated numerically.

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来源期刊

Spatial Statistics GEOSCIENCES, MULTIDISCIPLINARY-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

CiteScore

4.00

自引率

21.70%

发文量

审稿时长

55 days

期刊介绍： Spatial Statistics publishes articles on the theory and application of spatial and spatio-temporal statistics. It favours manuscripts that present theory generated by new applications, or in which new theory is applied to an important practical case. A purely theoretical study will only rarely be accepted. Pure case studies without methodological development are not acceptable for publication. Spatial statistics concerns the quantitative analysis of spatial and spatio-temporal data, including their statistical dependencies, accuracy and uncertainties. Methodology for spatial statistics is typically found in probability theory, stochastic modelling and mathematical statistics as well as in information science. Spatial statistics is used in mapping, assessing spatial data quality, sampling design optimisation, modelling of dependence structures, and drawing of valid inference from a limited set of spatio-temporal data.