Author: Wang, Jin-Feng; Christakos, George; Han, Wei-Guo; Meng, Bin
Title: Data-driven exploration of ‘spatial pattern-time process-driving forces’ associations of SARS epidemic in Beijing, China Document date: 2008_4_26
ID: 2nko37oo_56
Snippet: The present modelling approach is concerned mainly with statistical associations rather than causal laws. The latter are available primarily in cases in which the fundamental disease mechanisms (molecular biology, etc.) are well understood. In this sense, SARS modelling could benefit from future developments in basic scientific research in disease etiology and mathematical theories of epidemic propagation, as well as from sophisticated surveillan.....
Document: The present modelling approach is concerned mainly with statistical associations rather than causal laws. The latter are available primarily in cases in which the fundamental disease mechanisms (molecular biology, etc.) are well understood. In this sense, SARS modelling could benefit from future developments in basic scientific research in disease etiology and mathematical theories of epidemic propagation, as well as from sophisticated surveillance capabilities and metaanalysis. Furthermore, the present SARS modelling could be improved by considering epidemic variation and dependence in a composite space-time continuum under conditions of multi-sourced uncertainty. This may involve a combination of random field theories with temporal GIS techniques.
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