51
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A flexibly shaped spatial scan statistic for detecting clusters

      research-article
      1 , , 1
      International Journal of Health Geographics
      BioMed Central

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          The spatial scan statistic proposed by Kulldorff has been applied to a wide variety of epidemiological studies for cluster detection. This scan statistic, however, uses a circular window to define the potential cluster areas and thus has difficulty in correctly detecting actual noncircular clusters. A recent proposal by Duczmal and Assunção for detecting noncircular clusters is shown to detect a cluster of very irregular shape that is much larger than the true cluster in our experiences.

          Methods

          We propose a flexibly shaped spatial scan statistic that can detect irregular shaped clusters within relatively small neighborhoods of each region. The performance of the proposed spatial scan statistic is compared to that of Kulldorff's circular spatial scan statistic with Monte Carlo simulation by considering several circular and noncircular hot-spot cluster models. For comparison, we also propose a new bivariate power distribution classified by the number of regions detected as the most likely cluster and the number of hot-spot regions included in the most likely cluster.

          Results

          The circular spatial scan statistics shows a high level of accuracy in detecting circular clusters exactly. The proposed spatial scan statistic is shown to have good usual powers plus the ability to detect the noncircular hot-spot clusters more accurately than the circular one.

          Conclusion

          The proposed spatial scan statistic is shown to work well for small to moderate cluster size, up to say 30. For larger cluster sizes, the method is not practically feasible and a more efficient algorithm is needed.

          Related collections

          Most cited references20

          • Record: found
          • Abstract: not found
          • Article: not found

          A spatial scan statistic

            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Modified Randomization Tests for Nonparametric Hypotheses

              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              The Detection of Clusters in Rare Diseases

                Bookmark

                Author and article information

                Journal
                Int J Health Geogr
                International Journal of Health Geographics
                BioMed Central (London )
                1476-072X
                2005
                18 May 2005
                : 4
                : 11
                Affiliations
                [1 ]Department of Technology Assessment and Biostatistics, National Institute of Public Health, 3–6 Minami 2 chome Wako, Saitama 351-0197 Japan
                Article
                1476-072X-4-11
                10.1186/1476-072X-4-11
                1173134
                15904524
                d9f09d70-d1c6-49d0-a7cb-c566d4f5d295
                Copyright © 2005 Tango and Takahashi; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 14 April 2005
                : 18 May 2005
                Categories
                Methodology

                Public health
                Public health

                Comments

                Comment on this article