Title |
Socioeconomic determinants of geographic disparities in campylobacteriosis risk: a comparison of global and local modeling approaches
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Published in |
International Journal of Health Geographics, October 2012
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DOI | 10.1186/1476-072x-11-45 |
Pubmed ID | |
Authors |
Jennifer Weisent, Barton Rohrbach, John R Dunn, Agricola Odoi |
Abstract |
Socioeconomic factors play a complex role in determining the risk of campylobacteriosis. Understanding the spatial interplay between these factors and disease risk can guide disease control programs. Historically, Poisson and negative binomial models have been used to investigate determinants of geographic disparities in risk. Spatial regression models, which allow modeling of spatial effects, have been used to improve these modeling efforts. Geographically weighted regression (GWR) takes this a step further by estimating local regression coefficients, thereby allowing estimations of associations that vary in space. These recent approaches increase our understanding of how geography influences the associations between determinants and disease. Therefore the objectives of this study were to: (i) identify socioeconomic determinants of the geographic disparities of campylobacteriosis risk (ii) investigate if regression coefficients for the associations between socioeconomic factors and campylobacteriosis risk demonstrate spatial variability and (iii) compare the performance of four modeling approaches: negative binomial, spatial lag, global and local Poisson GWR. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Czechia | 1 | 1% |
Canada | 1 | 1% |
Unknown | 81 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 16 | 19% |
Researcher | 16 | 19% |
Student > Doctoral Student | 11 | 13% |
Student > Master | 8 | 10% |
Student > Bachelor | 4 | 5% |
Other | 14 | 17% |
Unknown | 14 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 15 | 18% |
Social Sciences | 10 | 12% |
Agricultural and Biological Sciences | 7 | 8% |
Environmental Science | 5 | 6% |
Computer Science | 4 | 5% |
Other | 21 | 25% |
Unknown | 21 | 25% |