Bayesian latent class analysis to estimate the optimal cut-off for the MilA ELISA for the detection of Mycoplasma bovis antibodies in sera, accounting for repeated measures

Comparison of test performance of a conventional PCR and two field-friendly tests to detect Coxiella burnetii DNA in ticks using Bayesian latent class analysis

Introduction

Coxiella burnetii (C. burnetii)-infected livestock and wildlife have been epidemiologically linked to human Q fever outbreaks. Despite this growing zoonotic threat, knowledge of coxiellosis in wild animals remains limited, and studies to understand their epidemiologic role are needed. In C. burnetii-endemic areas, ticks have been reported to harbor and spread C. burnetii and may serve as indicators of risk of infection in wild animal habitats. Therefore, the aim of this study was to compare molecular techniques for detecting C. burnetii DNA in ticks.

Methods

In total, 169 ticks from wild animals and cattle in wildlife conservancies in northern Kenya were screened for C. burnetii DNA using a conventional PCR (cPCR) and two field-friendly techniques: Biomeme's C. burnetii qPCR Go-strips (Biomeme) and a new C. burnetii PCR high-resolution melt (PCR-HRM) analysis assay. Results were evaluated, in the absence of a gold standard test, using Bayesian latent class analysis (BLCA) to characterize the proportion of C. burnetii positive ticks and estimate sensitivity (Se) and specificity (Sp) of the three tests.

Results

The final BLCA model included main effects and estimated that PCR-HRM had the highest Se (86%; 95% credible interval: 56-99%), followed by the Biomeme (Se = 57%; 95% credible interval: 34-90%), with the estimated Se of the cPCR being the lowest (24%, 95% credible interval: 10-47%). Specificity estimates for all three assays ranged from 94 to 98%. Based on the model, an estimated 16% of ticks had C. burnetii DNA present.

Discussion

These results reflect the endemicity of C. burnetii in northern Kenya and show the promise of the PCR-HRM assay for C. burnetii surveillance in ticks. Further studies using ticks and wild animal samples will enhance understanding of the epidemiological role of ticks in Q fever.

Estimation of sensitivity and specificity of bulk tank milk PCR and 2 antibody ELISA tests for herd-level diagnosis of Mycoplasma bovis infection using Bayesian latent class analysis

Mycoplasmosis (due to infection with Mycoplasma bovis) is a serious disease of beef and dairy cattle that can adversely impact health, welfare and productivity (Maunsell et al. (2011)). Mycoplasmosis can lead to a range of often severe, clinical presentations. Mycoplasma bovis (M. bovis) infection can present either clinically or subclinically, with the potential for recrudescence of shedding in association with stressful periods. Infection can be maintained within herds because of intermittent shedding (Calcutt et al., 2018, Hazelton et al., 2018). M. bovis is recognized as poorly responsive to treatment which represents a major challenge for control in infected herds. Given this, particular focus is needed on biosecurity measures to prevent introduction into uninfected herds in the first place. A robust and reliable laboratory test for surveillance is important both for herd-level prevention and control. The objective of this study was to estimate the sensitivity and specificity of 3 diagnostic tests (one PCR and 2 ELISA tests) on bulk tank milk, for the herd-level detection of M. bovis using Bayesian latent class analysis. In autumn 2018, bulk tank milk samples from 11,807 herds, covering the majority of the main dairy regions in Ireland had been submitted to the Department of Agriculture testing laboratory for routine surveillance were made available. A stratified random sample approach was used to select a cohort of herds for testing from this larger sample set. A final study population of 728 herds had bulk tank milk samples analyzed using a Bio-X ELISA (ELISA 1), an IDvet ELISA (ELISA 2) and a PCR test. A Bayesian latent class analysis (BLCA) was conducted to estimate the sensitivity (Se) and specificity (Sp) of the 3 diagnostic tests applied to bulk tank milk (BTM) for the detection of the herd-level infection. An overall LCA was conducted on all herds within a single population (a 3-test, 1-population model). The herds were also split into 2 populations based on herd size (small herds had < 82 cattle) (a 3-test, 2-population model) and separately into 3 regions in Ireland (Leinster, Munster and Connacht/Ulster) (a 3-test, 3-population model). The latent variable of interest was the herd-level M. bovis infection status. In total, 363/728 (50%) were large herds, 7 (1.0%) were positive on PCR, 88 (12%) positive on ELISA 1, and 406 (56%) positive on ELISA 2. Based on the 2-population model, the sensitivity (95% Bayesian credible interval (BCI) was 0.03 (0.02, 0.05), 0.22 (0.18, 0.27), 0.94 (0.88, 0.98) for PCR, ELISA 1 and ELISA 2 respectively. The specificity (95% BCI) was 0.99 (0.99, 1.0), 0.97 (0.95, 0.99), and 0.92 (0.86, 0.97) for PCR, ELISA 1 and ELISA 2 respectively. The herd-level true prevalence was estimated at 0.43 (BCI 0.35, 0.5) for smaller herds. The true prevalence was estimated at 0.62 (BCI 0.55, 0.69) for larger herds. The true prevalence was estimated at 0.56 (BCI 0.49, 0.463) in the 1-population model. For the 3-population model, the sensitivity (95% BCI) was 0.03 (0.02, 0.05), 0.24 (0.18, 0.29), 0.95 (0.9, 0.98) for PCR, ELISA 1 and ELISA 2 respectively. The specificity (95% BCI) was 0.99 (0.99, 1.0), 0.98 (0.96, 0.99), and 0.88 (0.79, 0.95) for PCR, ELISA 1 and ELISA 2 respectively. The herd-level true prevalence (95% BCI) was estimated at 0.65 (0.56, 0.73), 0.38 (0.28, 0.46) and 0.53 (0.4, 0.65) for population 1, 2, 3 respectively. Across all 3 models, the range in true prevalence was 38% to 65% of Irish dairy herds infected with M. bovis. The operating characteristics vary substantially between tests. The IDvet ELISA had a relatively high Se (the highest Se of the 3 tests studied) but it was estimated at 0.95 at its highest in 3-test, 3-population model. This test may be an appropriate test for herd-level screening or prevalence estimation within the context of the endemically infected Irish dairy cattle population. Further work is required to optimize this test and its interpretation when applied at herd-level to offset concerns related to the lower than optimal test Sp.

Point-of-care potentials of lateral flow-based field screening for Mycoplasma bovis infections: a literature review

Point-of-care (POC) field screening for tools for Mycoplasma bovis (M. bovis) is still lacking due to the requirement for a simple, robust field-applicable test that does not entail specialized laboratory equipment. In accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines, this review identifies the methodologies that were retrieved based on our search strategy that have been reported for the diagnosis of m. bovis infection between 2014 and diagnostics. A search criterion was generated to curate 103 articles, which were reduced in number (to 46), following the screening guidelines of PRISMA. The 43 articles included in the study present 25 different assay methods. The assay methods were grouped as microbiological culture, serological assay, PCR-based assay, LAMP-based assay, NGS-based assay, or lateral flow assay. We, however, focus our discussion on the three lateral flow-based assays relative to others, highlighting the advantages they present above the other techniques and their potential applicability as a POC diagnostic test for M. bovis infections. We therefore call for further research on developing a lateral flow-based screening tool that could revolutionize the diagnosis of M. bovis infection.

A Bayesian finite mixture model approach to evaluate dichotomization method for correlated ELISA tests

In diagnostic accuracy studies, a commonly employed approach involves dichotomizing continuous data and subsequently analyzing them using a Bayesian latent class model (BLCM), often relying on binomial or multinomial distributions, rather than preserving their continuous nature. However, this procedure can inadvertently lead to less reliable outcomes due to the inherent loss of information when converting the original continuous measurements into binary values. Through comprehensive simulations, we demonstrated the limitations and disadvantages of dichotomizing continuous biomarkers from two correlated tests. Our findings highlighted notable disparities between the true values and the model estimates as a result of dichotomization. We discovered the crucial significance of selecting a reference test with high diagnostic accuracy in test evaluation in order to obtain reliable estimates of test accuracy and prevalences. Our study served as a call to action for veterinary researchers to exercise caution when utilizing dichotomization.

Diagnostic performance of Mycoplasmopsis bovis antibody ELISA tests on bulk tank milk from dairy herds

BACKGROUND

Testing of bulk tank milk (BTM) for Mycoplasmopsis bovis (previously Mycoplasma bovis) antibodies is increasingly popular. However the performance of some commercially available tests is unknown, and cutoff values possibly need to be adjusted in light of the purpose. Therefore, the aim of this study was to compare the diagnostic performance of three commercially available M. bovis antibody ELISAs on BTM, and to explore optimal cutoff values for screening purposes. A prospective diagnostic test accuracy study was performed on 156 BTM samples from Belgian and Swiss dairy farms using Bayesian Latent Class Analysis. Samples were initially classified using manufacturer cutoff values, followed by generated values.

RESULTS

Following the manufacturer's guidelines, sensitivity of 91.4%, 25.6%, 69.2%, and specificity of 67.2%, 96.8%, 85.8% were observed for ID-screen, Bio K432, and Bio K302, respectively. Optimization of cutoffs resulted in a sensitivity of 89.0%, 82.0%, and 85.5%, and a specificity of 83.4%, 75.1%, 77.2%, respectively.

CONCLUSIONS

The ID-screen showed the highest diagnostic performance after optimization of cutoff values, and could be useful for screening. Both Bio-X tests may be of value for diagnostic or confirmation purposes due to their high specificity.

Shrimp MultiPath™ multiplexed PCR white spot syndrome virus detection in penaeid shrimp

White spot syndrome virus (WSSV), which causes white spot disease, is one of the notoriously feared infectious agents in the shrimp industry, inflicting estimated production losses world-wide of up to US$1 billion annually. Cost-effective accessible surveillance testing and targeted diagnosis are key to alerting shrimp industries and authorities worldwide early about WSSV carrier status in targeted shrimp populations. Here we present key validation pathway metrics for the Shrimp MultiPathTM (SMP) WSSV assay as part of the multi-pathogen detection platform. With superior throughput, fast turn-around time, and extremely low cost per test, the SMP WSSV assay achieves a high level of analytical sensitivity (~2.9 copies), perfect analytical specificity (~100%), and good intra- and inter-run repeatability (coefficient of variation <5%). The diagnostic metrics were estimated using Bayesian latent class analysis on data from 3 experimental shrimp populations from Latin America with distinct WSSV prevalence and yielded a diagnostic sensitivity of 95% and diagnostic specificity of 99% for SMP WSSV, which was higher than these parameters for the TaqMan quantitative PCR (qPCR) assays currently recommended by the World Organisation for Animal Health and the Commonwealth Scientific and Industrial Research Organisation. This paper additionally presents compelling data for the use of synthetic double-stranded DNA analyte spiked into pathogen-naïve shrimp tissue homogenate as a means to substitute clinical samples for assay validation pathways targeting rare pathogens. SMP WSSV shows analytical and diagnostic metrics comparable to qPCR-based assays and demonstrates fit-for-purpose performance for detection of WSSV in clinically diseased and apparently healthy animals.