| |  | Ozonoff, Al | Effect of spatial resolution on cluster detection: a simulation study read moreAbstract: Sorry no abstract available for this article | 2007 |
| | | Stroud, Phillip | Spatial Dynamics of Pandemic Influenza in a Massive Artificial Society read moreAbstract: EpiSimS is a massive simulation of the movements, activities, and social interactions of individuals in realistic synthetic populations, and of the dynamics of contagious disease spread on the resulting social contact network. This paper describes the assumptions and methodology in the EpiSimS model. It also describes and presents a simulation of the spatial dynamics of pandemic influenza in an artificial society constructed to match the demographics of southern California. As an example of the utility of the massive simulation approach, we demonstrate a strong correlation between local demographic characteristics and pandemic severity, which gives rise to previously unanticipated spatial pandemic hotspots. In particular, the average household size in a census tract is strongly correlated with the clinical attack rate computed by the simulation. Public heath agencies with responsibility for communities having relatively high population per household should expect to be more severely hit by a pandemic. | 2007 |
| | | Heuer, Jan T. | Towards a Spatial Search Engine Using Geotags read moreAbstract: We introduce the idea of a spatial search engine based on geotags. Geotags are keywords linked to a concrete position. User generated geotags are available from Web 2.0 portals like Flickr1 or Google Maps2. We collected a sample dataset of about 300.000 geotags. In the following we explain a prototype implementation of a search engine and describe how to compute the spatial relevance of a tag. The last section gives an outlook about our research goals in this area and discusses the challenges and possible benefits of integrating semantic information. | 2007 |
| | | Demattei, Christophe | Arbitrarily shaped multiple spatial cluster detection for case event data read moreAbstract: An original method is proposed for spatial cluster detection of case event data. A selection order and the distance from the nearest neighbour are attributed to each point, once pre-selected points have been taken into account. This distance is weighted by the expected distance under the uniform distribution hypothesis. Potential clusters are located by modelling the multiple structural change of the distances on the selection order and the best model (containing one or several potential clusters) is selected using the double maximum test. Finally a p-value is obtained for each potential cluster. With this method multiple clusters of any shape can be detected. | 2007 |
| | | Viboud, C. | Synchrony, Waves, and Spatial Hierarchies in the Spread of Influenza read moreAbstract: Sorry no abstract available for this article | 2006 |
| | | Kardos, Julian | Expressing attribute uncertainty in spatial data using blinking regions read moreAbstract: This paper defines a new method of attribute uncertainty representation, the blinking region. It specifically communicates uncertainty in values associated with choropleth map regions. In this way, error and attribute (census) data can be made to alternate in the user’s view, communicating both datasets. The blinking region uncertainty visualization was tested via a web-based survey. Results show that it outperforms most current visualisation of attribute uncertainty techniques (e.g. image sharpness) in terms of visual appeal, speed of comprehension and overall effectiveness. Theoretically, regions that have the most attribute error could flicker at the fastest rate, with speed of blinking being proportional to the error. | 2006 |
| | | Neill, Daniel B. | Rapid detection of significant spatial clusters read moreAbstract: Sorry no abstract available for this article | 2004 |
| | | Grenfell, B. T. | Travelling waves and spatial hierarchies in measles epidemics read moreAbstract: Sorry no abstract available for this article | 2001 |
| | | Koperski, K. | Data mining methods for the analysis of large geographic databases read moreAbstract: this paper, a number of methods based on knowledge discovery techniques for large databases are presented. This methods may overcome some of the weaknesses of statistical analysis. Our study is focused on efficient method for mining strong spatial association rules in geographic information databases. A spatial association rule is a rule indicating certain association relationship among a set of spatial and possibly some non-spatial predicates. For example, a rule 80% of gas stations in rural... | 1996 |
| | | Besag, Julian | The detection of clusters in rare diseases read moreAbstract: Sorry no abstract available for this article | 1991 |
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