Research Article Disparities in Spatial Prevalence of Feline Retroviruses due to Data Aggregation: A Case of the Modifiable Areal Unit Problem Bimal K. Chhetri, 1 Olaf Berke, 1,2,3 David L. Pearl, 1 and Dorothee Bienzle 4 1 Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada N1G 2W1 2 Department of Mathematics and Statistics, University of Guelph, Guelph, ON, Canada N1G 2W1 3 Institute of Biometry, Epidemiology and Information Processing, University of Veterinary Medicine Hannover (Foundation), 30173 Hannover, Germany 4 Department of Pathobiology, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada N1G 2W1 Correspondence should be addressed to Bimal K. Chhetri; bchhetri@uoguelph.ca Received 2 October 2013; Accepted 9 January 2014; Published 20 February 2014 Academic Editor: Daniel A. Feeney Copyright © 2014 Bimal K. Chhetri et al. his is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. he knowledge of the spatial distribution feline immunodeiciency virus and feline leukemia virus infections, which are untreatable, can inform on their risk factors and high-risk areas to enhance control. However, when spatial analysis involves aggregated spatial data, results may be inluenced by the spatial scale of aggregation, an efect known as the modiiable areal unit problem (MAUP). In this study, area level risk factors for both infections in 28,914 cats tested with ELISA were investigated by multivariable spatial Poisson regression models along with MAUP efect on spatial clustering and cluster detection (for postal codes, counties, and states) by Moran’s  test and spatial scan test, respectively. he study results indicate that the signiicance and magnitude of the association of risk factors with both infections varied with aggregation scale. Further more, Moran’s  test only identiied spatial clustering at postal code and county levels of aggregation. Similarly, the spatial scan test indicated that the number, size, and location of clusters varied over aggregation scales. In conclusion, the association between infection and area was inluenced by the choice of spatial scale and indicates the importance of study design and data analysis with respect to speciic research questions. 1. Introduction Infections with feline immunodeiciency virus (FIV) and feline leukemia virus (FeLV) have been reported from a number of countries and are important conditions in cats [1]. he most common mode of transmission of these immunosuppressive retroviruses is through bite wounds. FeLV infection is also commonly acquired via the oronasal route through mutual grooming, nursing, or sharing of dishes [2]. he known risk factors for acquiring these infections are male sex, adulthood, and exposure to outdoors, whereas being neutered and indoor lifestyle are known protective factors [3]. Recent studies estimate a seroprevalence of 2.3% (FeLV) and 2.5% (FIV) in the United States (US) [4] and 3.4% (FeLV) and 4.3% (FIV) in Canada [1]. Despite decades of discovery, clinical management of cats infected with FIV and FeLV is still challenging without the existence of an efective therapeutic intervention [3]. herefore, better ways to control the infections and pro- phylactic management is the mainstay of disease prevention strategy for these infections. A number of previous studies have suggested that the prevalence of retroviral infections in domestic cat populations varies by regions and maybe attributed to variable population density, reproductive status, age, gender, and housing conditions [5–11]. For the US and Canada, spatial variation in FIV and FeLV seroprevalence has been reported in previous studies that generated data for this research [1, 4]. Here we attempt to extend the indings by applying spatial statistical methods to illustrate geographic variation in the distribution of FIV and FeLV infections and assess the relationship with group-level risk factors. Spatial epidemiological methods are commonly used to identify, describe, and quantify spatial patterns in the distribution of health events. Spatial patterns commonly of Hindawi Publishing Corporation Journal of Veterinary Medicine Volume 2014, Article ID 424138, 11 pages http://dx.doi.org/10.1155/2014/424138