Spatio-Temporal Analysis of Suicide-Related Emergency Calls

Miriam Marco, Antonio López-Quílez, David Conesa, Enrique Gracia and Marisol Lila
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Miriam Marco: Department of Social Psychology, University of Valencia, Avda. Blasco Ibáñez, 21, 46010 Valencia, Spain
Antonio López-Quílez: Department of Statistics and Operations Research, University of Valencia, Dr. Moliner, 50, 46100 Burjassot, Spain
David Conesa: Department of Statistics and Operations Research, University of Valencia, Dr. Moliner, 50, 46100 Burjassot, Spain
Enrique Gracia: Department of Social Psychology, University of Valencia, Avda. Blasco Ibáñez, 21, 46010 Valencia, Spain
Marisol Lila: Department of Social Psychology, University of Valencia, Avda. Blasco Ibáñez, 21, 46010 Valencia, Spain

IJERPH, 2017, vol. 14, issue 7, 1-13

Abstract: Considerable effort has been devoted to incorporate temporal trends in disease mapping. In this line, this work describes the importance of including the effect of the seasonality in a particular setting related with suicides. In particular, the number of suicide-related emergency calls is modeled by means of an autoregressive approach to spatio-temporal disease mapping that allows for incorporating the possible interaction between both temporal and spatial effects. Results show the importance of including seasonality effect, as there are differences between the number of suicide-related emergency calls between the four seasons of each year.

Keywords: bayesian modeling; disease mapping; police calls-for-service; seasonality; social epidemiology (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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