Modelling a discrete spatial response using generalized linear mixed models: application to Lyme disease vectors

@article{Das2002ModellingAD,
  title={Modelling a discrete spatial response using generalized linear mixed models: application to Lyme disease vectors},
  author={Abhik Das and Subhash R. Lele and Gregory E. Glass and Timothy Shields and Jonathan Patz},
  journal={International Journal of Geographical Information Science},
  year={2002},
  volume={16},
  pages={151-166}
}
Predicting disease risk by identifying environmental factors responsible for the geographical distribution of disease vectors can help target control strategies and optimize preventive measures. In this study we present a hierarchical approach to model the distribution of Lyme disease ticks as a function of environmental factors. We use the Poisson framework natural for count data while allowing for spatial correlations. To help identify environmental factors that best explain tick abundance… CONTINUE READING

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