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

ABSTRACT:

Background

Domestic dogs are primary reservoir hosts of Leishmania infantum, the agent of visceral leishmaniasis. Detecting dog infections is central to epidemiological inference, disease prevention, and veterinary practice. Error-free diagnostic procedures, however, are lacking, and the performance of those available is difficult to measure in the absence of fail-safe "reference standards". Here, we illustrate how a hierarchical-modeling approach can be used to formally account for false-negative and false-positive results when investigating the process of Leishmania detection in dogs.

Methods/findings

We studied 294 field-sampled dogs of unknown infection status from a Leishmania-endemic region. We ran 350 parasitological tests (bone-marrow microscopy and culture) and 1,01

SUBMITTER: Vital T 

PROVIDER: S-EPMC9803295 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature