Interdisciplinary approaches are merited when attempting to understand the complex and idiosyncratic processes driving the spillover of pathogens from wildlife and vector species to human populations. Public health data are often available for zoonotic pathogens but can lead to erroneous conclusions if the data have been spatially or temporally aggregated. As an illustration, we use human Lyme disease incidence data as a case study to examine correlations between mammalian biodiversity, fried chicken restaurants and obesity rates on human disease incidence. We demonstrate that Lyme disease incidence is negatively correlated with mammalian biodiversity, the abundance of fried chicken restaurants and obesity rates. We argue, however, that these correlations are spurious, representing both an ‘ecologic fallacy’ and Simpson’s paradox, and are generated by the use of aggregated data. We argue that correlations based on aggregated data across large spatial scales must be rigorously examined before being invoked as proof of disease ecology theory or as a rationale for public health policy.

中文翻译：

---

生态谬误和综合数据：以炸鸡餐馆，肥胖症和莱姆病为例。

当试图了解导致病原体从野生生物和媒介物种向人类扩散的复杂而特异的过程时，应采用跨学科方法。公共卫生数据通常可用于人畜共患病病原体，但如果数据已在空间或时间上进行汇总，则可能导致错误的结论。作为说明，我们以人类莱姆病发病率数据为例，研究了哺乳动物生物多样性，炸鸡店和肥胖率与人类疾病发病率之间的相关性。我们证明，莱姆病的发病率与哺乳动物的生物多样性，炸鸡店的数量和肥胖率呈负相关。但是，我们认为这些关联是虚假的，既代表“生态谬误”，又代表辛普森悖论，并且是通过使用汇总数据生成的。我们认为，在被引用为疾病生态理论的证明或公共卫生政策的依据之前，必须严格检查基于大空间尺度上汇总数据的相关性。