title: Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.
abstract: Extrapolating landscape regression models for use in assessing vector-borne disease risk and other applications requires thoughtful evaluation of fundamental model choice issues. To examine implications of such choices, an analysis was conducted to explore the extent to which disparate landscape models agree in their epidemiological and entomological risk predictions when extrapolated to new regions. Agreement between six literature-drawn landscape models was examined by comparing predicted county-level distributions of either Lyme disease or Ixodes scapularis vector using Spearman ranked correlation. AUC analyses and multinomial logistic regression were used to assess the ability of these extrapolated landscape models to predict observed national data. Three models based on measures of vegetation, habitat patch characteristics, and herbaceous landcover emerged as effective predictors of observed disease and vector distribution. An ensemble model containing these three models improved precision and predictive ability over individual models. A priori assessment of qualitative model characteristics effectively identified models that subsequently emerged as better predictors in quantitative analysis. Both a methodology for quantitative model comparison and a checklist for qualitative assessment of candidate models for extrapolation are provided; both tools aim to improve collaboration between those producing models and those interested in applying them to new areas and research questions.
authors: Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.
authors: Alyson
authors: A
authors: Lorenz
authors: Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.
authors: Radhika
authors: R
authors: Dhingra
authors: Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.
authors: Howard H
authors: HH
authors: Chang
authors: Department of Environmental Sciences, Emory University, Atlanta, Georgia, United States of America.
authors: Donal
authors: D
authors: Bisanzio
authors: Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.
authors: Yang
authors: Y
authors: Liu
authors: Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America; Program in Population Biology, Ecology and Evolution, Graduate Division of Biological and Biomedical Sciences, Emory University, Atlanta, Georgia, United States of America.
authors: Justin V
authors: JV
authors: Remais
mesh_terms: D000818:Animals; D003141:Communicable Diseases / Q000453:epidemiology* / Q000635:transmission*; D066264:Datasets as Topic; D004199:Disease Vectors; D006801:Humans; D018884:Ixodes; D008193:Lyme Disease / Q000635:transmission; D008962:Models, Theoretical; D016017:Odds Ratio; D015203:Reproducibility of Results; D012306:Risk; D014481:United States