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Spatial Scan for Disease Mapping on a Mobile Population
| Content Provider | CiteSeerX |
|---|---|
| Author | Lan, Liang Malbasa, Vuk Vucetic, Slobodan |
| Abstract | In disease mapping, the spatial scan statistic is used to detect spatial regions where population is exposed to a significantly higher disease risk than expected. In this important application, the current residence is typical-ly used to define the location of individuals from the population. Considering the mobility of humans at vari-ous temporal and spatial scales, using only information about the current residence may be an insufficiently in-formative proxy because it ignores a multitude of expo-sures that may occur away from home, or which had oc-curred at previous residences. In this paper, we propose a spatial scan statistic that is appropriate for disease mapping on mobile populations. We formulate a com-putationally efficient algorithm that uses the proposed s-tatistic to find significant high-risk regions from mobile population’s disease status data. The algorithm is appli-cable on large populations and over dense spatial grids. The experimental results demonstrate that the proposed algorithm is computationally efficient and outperforms the traditional disease clustering approaches at discov-ering high-risk regions in mobile populations. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Mobile Population Disease Mapping Spatial Scan Current Residence Spatial Scan Statistic Previous Residence Com-putationally Efficient Algorithm Traditional Disease Dense Spatial Grid Discov-ering High-risk Region Disease Risk Spatial Region Large Population Significant High-risk Region In-formative Proxy Experimental Result Spatial Scale Important Application Disease Status Data |
| Content Type | Text |
