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Although it is assumed that fecal shedding of feline leukemia virus (FeLV) constitutes a transmission potential, no study has been performed showing that feces of infected cats can be a source of infection. In this study, we investigated fecal viral shedding of FeLV and its role in viral pathogenesis with the goal to improve infection control. FeLV RNA and DNA levels were determined in rectal swabs of experimentally infected cats by real-time PCR, and the results were correlated with proviral and viral loads in whole blood and plasma, respectively, and plasma p27 levels. All antigenemic cats shed FeLV RNA and DNA in feces. To determine whether the viral RNA detected was infectious, virus isolation from feces was also performed. Infectious virus was isolated from feces of antigenemic cats, and these results perfectly correlated with the isolation of virus from plasma. Naïve cats exposed to these feces seroconverted, showing that infection through feces took place, but remained negative for the presence of FeLV provirus and p27 in blood, an outcome so far not described. Some of the organs collected after euthanasia were provirus positive at low copy numbers. From these results it is concluded that fecal shedding of FeLV plays a role in transmission, but it is probably of secondary importance in viral pathogenesis. Nevertheless, sharing of litter pans by susceptible and viremic cats could increase the environmental infectious pressure and appropriate measures should be taken to avoid unnecessary viral exposure.

The evaluation of newly developed diagnostic tests (tests) commonly involves the comparison of the test outcomes (pos/neg.) of a sample of animals to those of a reference test (gold standard) in order to derive sensitivity and specificity estimates. Often, however, new tests have to be evaluated against an imperfect reference test since a true gold standard test is either too expensive or too costly to apply. This results in bias in the test characteristic estimates. To solve this problem, latent class and Bayesian models can be used to estimate sensitivity and specificity when evaluating a diagnostic test in the absence of a gold standard. They require at least two imperfect reference tests applied to all individuals in the study. In our approach we used a two-test two-population scenario. Both the gold standard and these modelling approaches rely on various assumptions. When violated, biased results will be obtained. The analysis of field data from an Anaplasma marginale outbreak in cattle in Switzerland with four diagnostic procedures (detection of the agent, serology, PCR and hematocrit measurements) was used as a practical example to demonstrate and critically discuss the approaches taken. In this relatively small data set (n = 275) the estimates for the test characteristics obtained by the different methods were quite similar. Overall, the bias in the point estimates depended mainly on the chosen estimation approach. All tests showed a non-negligible correlation mainly in the test sensitivities. This emphasizes the importance of taking into account test dependence even if it seems not biologically plausible at first thought.