Les hommes ont oublié cette vérité. Mais tu ne dois pas l'oublier, dit le renard. Tu deviens responsable pour toujours de ce que tu as apprivoisé.
Le Petit Prince, chap. 21

Monday, 11 May 2015

Epidemiology of FeLV and FIV in USA and Canada

Chhetri, B. (2015). Spatial and temporal epidemiology of feline immunodeficiency virus and feline leukemia virus infections in the United States and Canada (Doctoral dissertation, The University of Guelph).

This thesis investigates the geographical and temporal variations in feline immunodeficiency virus (FIV) and feline leukemia virus (FeLV) infections, and the importance of known risk factors for these infections relative to each other in the United States and Canada. In addition, the effect of the modifiable areal unit problem (MAUP) on commonly used spatial analysis methods was assessed.
Choropleth mapping and spatial scan testing revealed that compared to FIV, FeLV infection was predominant in western regions, and FIV infection was predominant in eastern regions of the US. A multilevel case-case study design for comparison of FIV and FeLV infections indicated that cats that were adult, male, healthy, or outdoor cats were more likely to be seropositive for FIV compared to FeLV when compared to juvenile, female, sick or cats kept exclusively indoors. Neuter status and testing at clinic or shelter did not differ significantly between the two infections. Time series analysis did not reveal an increasing or decreasing trend in FIV or FeLV seropositivity among cats tested at the Animal Health Laboratory (AHL) from 1999-2012. Further, the FIV vaccine introduction did not have a significant effect on changing seroprevalence for FIV. It was evident from this study that commonly used spatial epidemiological methods (Moran's I, the spatial scan test and spatial Poisson regression modeling) are sensitive to the choice of the spatial aggregation scale (state, county, postal code levels) for analysis, (i.e., are affected by the MAUP). The MAUP effect was expressed as differences in strength and significance of clustering, differences in size and number of clusters detected, and differences in significance and magnitude of associations between FIV or FeLV infections and predictor variables as the level of aggregation changed.

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