Estimating the diagnostic performance of serological assays for emerging pathogens using a Bayesian approach: Myxoma virus in the Iberian hare (Lepus granatensis)

Abstract

Validated diagnostic tools are essential when conducting serological surveys. However, reliable tests are scarce and hard to attain for emerging pathogens due to the lack of reference tests or samples. Recently, a recombinant myxoma virus (MYXV), named ha-MYXV, raised alarm in the Iberian Peninsula for its impact on Iberian hare (Lepus granatensis) populations and its detection in wild (Oryctolagus cuniculus) and domestic rabbits. Here, we follow a Bayesian approach to evaluate two serological tools, an indirect ELISA (iELISA) and a competitive ELISA (cELISA), used to monitor this emerging pathogen in Iberian hare populations. We modelled serological data from 227 hares conveniently selected retrospectively for their apparent healthy status. First, we applied finite mixture models to adjust the cut-off thresholds of both tests, which improved the agreement between both tests (initial kappa = 0.42, after threshold adjustment = 0.78). Then, we employed Bayesian latent class models (BLCM) to estimate the assays’ specificity (Sp) and sensitivity (Se). The BLCM estimated median Sp of 94.0 % (95 % posterior probability interval (PPI): 85.9–99.4) and 96.1 % (PPI: 87.2–100.0), and Se of 77.7 % (PPI: 61.5–89.5) and 91.7 % (PPI: 78.1–99.9), for the iELISA and the cELISA, respectively. The true seroprevalence estimations show higher values in south-central Spain (ranging from 13.1 % to 70.4 %) and lower in the north (Navarra: 5.5 %). A Bayesian approach allowed to evaluate diagnostic tools for ha-MYXV, an emerging wildlife pathogen, in the absence of reference tests or samples. Future epidemiological studies of myxomatosis in Iberian hares should calculate true seroprevalence based on our estimations.