Generalizing the spatial relative risk function

W T P Sarojinie Fernando; Martin L Hazelton

doi:10.1016/j.sste.2013.12.002

Generalizing the spatial relative risk function

Spat Spatiotemporal Epidemiol. 2014 Apr:8:1-10. doi: 10.1016/j.sste.2013.12.002. Epub 2014 Jan 7.

Authors

W T P Sarojinie Fernando¹, Martin L Hazelton²

Affiliations

¹ Institute of Fundamental Sciences, Massey University, New Zealand.
² Institute of Fundamental Sciences, Massey University, New Zealand; Infectious Disease Research Centre, Massey University, New Zealand. Electronic address: m.hazelton@massey.ac.nz.

PMID: 24606990
DOI: 10.1016/j.sste.2013.12.002

Abstract

The spatial relative risk function is defined as the ratio of densities describing respectively the spatial distribution of cases and controls. It has proven to be an effective tool for visualizing spatial variation in risk in many epidemiological applications over the past 20 years. We discuss the generalization of this function to spatio-temporal case-control data, and also to situations where there are covariates available that may affect the spatial patterns of disease. We examine estimation of the generalized relative risk functions using kernel smoothing, including asymptotic theory and data-driven bandwidth selection. We also consider construction of tolerance contours. Our methods are illustrated on spatio-temporal data describing the 2001 outbreak of foot-and-mouth disease in the United Kingdom, with farm size as a covariate.

Keywords: Bandwidth selection; Covariate; Density ratio; Foot and mouth disease; Kernel density estimation; Spatio-temporal.

MeSH terms

Animals
Case-Control Studies
Disease Outbreaks / prevention & control*
Disease Outbreaks / statistics & numerical data
Foot-and-Mouth Disease / epidemiology*
Humans
Models, Theoretical
Multivariate Analysis
Public Health Surveillance
Risk Assessment / methods*
Spatio-Temporal Analysis*
Topography, Medical / methods
United Kingdom / epidemiology