Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.
Inter-model comparison of the landscape determinants of vector-borne disease: implications for epidemiological and entomological risk modeling.
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DOI：
10.1371/journal.pone.0103163
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发表时间：
2014
期刊：
影响因子：
3.7
通讯作者：
Remais JV
中科院分区：
文献类型：
--
作者：
Lorenz A;Dhingra R;Chang HH;Bisanzio D;Liu Y;Remais JV
外推景观回归模型用于评估病媒传播疾病的风险和其他应用需要深思熟虑的基本模型选择问题的评价。为了研究这种选择的影响，进行了分析，探讨在何种程度上不同的景观模型同意在其流行病学和昆虫学的风险预测时，外推到新的地区。六个文献绘制的景观模型之间的协议进行了检查，通过比较预测的县级分布的莱姆病或肩突硬蜱载体使用斯皮尔曼排名相关性。AUC分析和多项式逻辑回归被用来评估这些外推景观模型预测观测到的国家数据的能力。三个模型的基础上的措施，植被，栖息地斑块特征，草本土地覆盖出现了有效的预测所观察到的疾病和病媒分布。包含这三个模型的集成模型比单个模型提高了精度和预测能力。定性模型特征的先验评估有效地识别了随后在定量分析中作为更好的预测因子出现的模型。提供了定量模型比较的方法和用于外推的候选模型的定性评估的核对表;这两种工具的目的都是为了改善模型制作者与有兴趣将其应用于新领域和研究问题的人之间的合作。
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.
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