Abstract
The statistical properties of disease incidence are reviewed and used to characterize spatial patterns of diseased entities (e.g. plants), satisfy assumptions of statistical analyses, and quantify change in incidence over time. Frequency of diseased plants can be represented by the binomial or, more commonly, the beta-binomial distribution. Spatial patterns of disease can be described by the aggregation parameter of the beta-binomial distribution, index of dispersion and related statistics, parameters of the binary form of the power law, as well as measures of spatial autocorrelation between sampling units. Disease incidence over time can be represented by continuous- and discrete-time nonlinear disease progress models, such as the logistic, and by autoregressive, integrated, moving average models. Ultimately, simultaneous spatio-temporal analyses can be performed to understand the dynamics of disease incidence in populations.
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