Detecting Leishmania in dogs: A hierarchical-modeling approach to investigate the performance of parasitological and qPCR-based diagnostic procedures.

We provide statistical estimates of key performance parameters for five diagnostic procedures used to detect Leishmania in dogs. Low clinical sensitivies likely reflect the absence of Leishmania parasites/DNA in perhaps ~50-70% of samples drawn from infected dogs. Although qPCR performance was similar across sample types, non-invasive eye-swabs were overall less likely to contain amplifiable DNA. Finally, modeling was instrumental to discovering (and formally accounting for) possible qPCR-plate contamination; even with stringent negative/blank-control scoring, ~4-5% of positive qPCRs were most likely false-positives. This work shows, in sum, how hierarchical site-occupancy models can sharpen our understanding of the problem of diagnosing host infections with hard-to-detect pathogens including Leishmania.