Michael Beenstock , Yoel Cohen , Daniel Felsenstein
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引用次数: 0
Abstract
‘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.
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.
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