https://socictopen.socict.org/files/original/e1798530b2cee9d6f800d3876f9b012c.pdf ff3cc100c1368267208c88ea33d518a8 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Spatio-temporal and stochastic modelling of severe acute respiratory syndrome Creator An entity primarily responsible for making the resource Poh-Chin Lai, Kim-Hung Kwong, Ho Ting Wong Description An account of the resource This study describes the development of a spatio-temporal disease model based on the episodes of severe acute respiratory syndrome (SARS) that took place in Hong Kong in 2003. In contrast to conventional, deterministic modelling approaches, the model described here is predominantly spatial. It incorporates stochastic processing of environmental and social variables that interact in space and time to affect the patterns of disease transmission in a community. The model was validated through a comparative assessment between actual and modelled distribution of diseased locations. Our study shows that the inclusion of location-specific characteristics satisfactorily replicates the spatial dynamics of an infectious disease. The Pearson’s correlation coefficients for five trials based on 3-day aggregation of disease counts for 1-3, 4-6 and 7-9 day forecasts were 0.57- 0.95, 0.54-0.86 and 0.57-0.82, respectively, while the correlation based on 5-day aggregation for the 1-5 day forecast was 0.55- 0.94 and 0.58-0.81 for the 6-10 day forecast. The significant and strong relationship between actual results and forecast is encouraging for the potential development of an early warning system for detecting this type of disease outbreaks. Date A point or period of time associated with an event in the lifecycle of the resource 2013 Subject The topic of the resource infectious disease epidemiology, spatial modelling, estimating disease spread, SARS, Geographical information system, early warning system, Hong Kong Identifier An unambiguous reference to the resource within a given context DOI: 10.4081/gh.2013.65 Source A related resource from which the described resource is derived Geospatial Health Publisher An entity responsible for making the resource available PAGEPress Publications Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Geography (General) Language A language of the resource EN