English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Lyme disease is an infectious disease that is caused by a bacterium calledBorrelia burgdorferi sensu stricto. In the United States, Lyme disease is oneof the most common infectious diseases. The major endemic areas of the diseaseare New England, Mid-Atlantic, East-North Central, South Atlantic, and WestNorth-Central. Virginia is on the front-line of the disease's diffusion fromthe northeast to the south. One of the research objectives for the infectiousdisease community is to identify environmental and economic variables that areassociated with the emergence of Lyme disease. In this paper, we use a spatialPoisson regression model to link the spatial disease counts and environmentaland economic variables, and develop a spatial variable selection procedure toeffectively identify important factors by using an adaptive elastic netpenalty. The proposed methods can automatically select important covariates,while adjusting for possible spatial correlations of disease counts. Theperformance of the proposed method is studied and compared with existingmethods via a comprehensive simulation study. We apply the developed variableselection methods to the Virginia Lyme disease data and identify importantvariables that are new to the literature. Supplementary materials for thispaper are available online.

Spatial Variable Selection and An Application to Virginia Lyme Disease Emergence