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Model-based testing for space–time interaction using point processes: An application to psychiatric hospital admissions in an urban area


Meyer, Sebastian; Warnke, Ingeborg; Rössler, Wulf; Held, Leonhard (2016). Model-based testing for space–time interaction using point processes: An application to psychiatric hospital admissions in an urban area. Spatial and Spatio-temporal Epidemiology, 17(5):15-25.

Abstract

Spatio-temporal interaction is inherent to cases of infectious diseases and occurrences of earthquakes, whereas the spread of other events, such as cancer or crime, is less evident. Statistical significance tests of space–time clustering usually assess the correlation between the spatial and temporal (transformed) distances of the events. Although appealing through simplicity, these classical tests do not adjust for the underlying population nor can they account for a distance decay of interaction. We propose to use the framework of an endemic–epidemic point process model to jointly estimate a background event rate explained by seasonal and areal characteristics, as well as a superposed epidemic component representing the hypothesis of interest. We illustrate this new model-based test for space–time interaction by analysing psychiatric inpatient admissions in Zurich, Switzerland (2007–2012). Several socio-economic factors were found to be associated with the admission rate, but there was no evidence of general clustering of the cases.

Abstract

Spatio-temporal interaction is inherent to cases of infectious diseases and occurrences of earthquakes, whereas the spread of other events, such as cancer or crime, is less evident. Statistical significance tests of space–time clustering usually assess the correlation between the spatial and temporal (transformed) distances of the events. Although appealing through simplicity, these classical tests do not adjust for the underlying population nor can they account for a distance decay of interaction. We propose to use the framework of an endemic–epidemic point process model to jointly estimate a background event rate explained by seasonal and areal characteristics, as well as a superposed epidemic component representing the hypothesis of interest. We illustrate this new model-based test for space–time interaction by analysing psychiatric inpatient admissions in Zurich, Switzerland (2007–2012). Several socio-economic factors were found to be associated with the admission rate, but there was no evidence of general clustering of the cases.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Uncontrolled Keywords:Spatio-temporal point process; Knox test; Mantel test; Space–time K-function; Global test of clustering; Psychiatric inpatient admissions
Language:English
Date:May 2016
Deposited On:25 May 2016 17:53
Last Modified:26 May 2016 08:13
Publisher:Elsevier
ISSN:1877-5845
Publisher DOI:https://doi.org/10.1016/j.sste.2016.03.002
Official URL:http://arxiv.org/abs/1512.09052

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