Aggregation of macroparasites among hosts is nearly universal among parasite-host associations. Researchers testing hypotheses on origins of parasite aggregation and its importance to parasite and host population ecology have used different measures of aggregation that are not necessarily measuring the same thing, potentially clouding our understanding of underlying epidemiological processes. We highlight these differences in meanings by exploring properties and interrelationships of six common measures of parasite aggregation, and provide a “user’s guide” to inform researchers’ decisions regarding their application. We compared the mathematical expressions of the different measures of aggregation, and ran two series of simulations and analyses. The first simulations tested the effect of random removals of parasites on aggregation levels under different conditions, while the second explored interrelationships between the measures, as well as between other individual parasitological sample measures (i.e. mean abundance, prevalence) and aggregation. Results of simulations and analyses showed that the six measures of aggregation could be separated readily into three groups: the variance-to-mean ratio (VMR) together with mean crowding, patchiness with k of the negative binomial, and Poulin’s D with Hoover’s index. These three pairs of measures showed differing responses to random parasite removals and differing relations with mean abundance and/or prevalence, highlighting that metrics capture different variation in other sample measures and different attributes of aggregation. We used results of our simulations and analyses, and a literature review, to list the properties, advantages, and disadvantages of each aggregation metric. We provide a comprehensive exploration of what is assessed by each metric, as a guide to metric choice. We implore researchers to provide enough information such that aggregation measures from each group are reported or can be readily calculated. Such steps are needed to allow large-scale analyses of variation in degrees of aggregation within and among parasite-host associations, to uncover epidemiological processes shaping parasite distributions.

大型寄生虫在宿主之间的聚集在寄生虫-宿主协会中几乎是普遍存在的。研究人员测试了关于寄生虫聚集起源及其对寄生虫和宿主种群生态的重要性的假设，使用了不同的聚集测量方法，这些方法不一定测量相同的东西，可能会模糊我们对潜在流行病学过程的理解。我们通过探索寄生虫聚集的六种常见测量方法的特性和相互关系来强调这些含义上的差异，并提供“用户指南”来告知研究人员有关其应用的决策。我们比较了不同聚合度量的数学表达式，并进行了两个系列的模拟和分析。第一个模拟测试了不同条件下随机去除寄生虫对聚集水平的影响，而第二个模拟则探讨了这些措施之间以及其他单个寄生虫学样本测量（即平均丰度、流行率）和聚集之间的相互关系。模拟和分析的结果表明，六种聚合度量可以很容易地分为三组：方差与均值比 (VMR) 以及均值拥挤、负二项式k的斑块性以及 Poulin's D和 Hoover 指数。这三对测量结果显示出对随机寄生虫清除的不同响应以及与平均丰度和/或流行率的不同关系，突出显示指标捕获了其他样本测量中的不同变化和不同的聚合属性。我们使用模拟和分析的结果以及文献综述来列出每个聚合指标的属性、优点和缺点。我们对每个指标评估的内容进行了全面的探索，作为指标选择的指南。我们恳请研究人员提供足够的信息，以便报告或可以轻松计算每个组的聚合度量。需要采取这些步骤来大规模分析寄生虫-宿主协会内部和之间聚集程度的变化，以揭示影响寄生虫分布的流行病学过程。