Because we did not use a probability sampling design for sample collection, we estimated the prevalence of convenience samples (hereafter "prevalence") of each targeted infectious agent and the 95% confidence interval (CI) [31]. As leopard cats are endangered and our sample size was limited, we did not conclude that one of the targeted infectious agents was absent in the population of leopard cats if all of the individual samples tested negative.

The samples from live-trapped (LT) and FD leopard cats were pooled to identify possible spatial or temporal clusters of target pathogens using SaTScan v9 [32] with the Bernoulli model [33]. The analysis was used to determine whether positive cases were randomly distributed over space and time. Detection of a significant cluster of positive cases would help to identify the possible influencing factors, which would be critical for implementing disease management and prevention programs. Cluster determination was performed by gradually scanning a window across time and/or space and comparing the numbers of observed and expected cases [34]. Multiple window sizes were used during scanning. Significant spatial and temporal clusters were reevaluated using Monte Carlo replications under the null hypothesis to ensure adequate power for defining clusters [34]. The maximum-likelihood approach was used to determine the clusters, and a p-value was determined for each cluster [34].

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