A comparison of least squares regression and geographically weighted regression modeling of West Nile virus risk based on environmental parameters.

ABSTRACT:

Background

The primary aim of the study reported here was to determine the effectiveness of utilizing local spatial variations in environmental data to uncover the statistical relationships between West Nile Virus (WNV) risk and environmental factors. Because least squares regression methods do not account for spatial autocorrelation and non-stationarity of the type of spatial data analyzed for studies that explore the relationship between WNV and environmental determinants, we hypothesized that a geographically weighted regression model would help us better understand how environmental factors are related to WNV risk patterns without the confounding effects of spatial non-stationarity.

Methods

We examined commonly mapped environmental factors using both ordinary least squar

SUBMITTER: Kala AK 

PROVIDER: S-EPMC5372833 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature