A Bayesian approach to estimate the accuracy of in-house ELISA assay to measure rabies antibodies from compulsory vaccinated dogs and cattle

Abstract

Rabies is a vaccine-preventable disease that causes acute encephalitis in mammals, and it is still a significant public health problem in numerous countries. Infected dogs represent the main vectors involved in human rabies. Additionally, cattle rearing close to geographic areas where vampire bats are found presents an important connection with rural epidemiology. We applied two in-house enzyme-linked immunosorbent assay (ELISA) methodologies, considered alternatives to measure antibodies from vaccinated dogs and cattle, without employing the gold standard approach. The ELISA assays were performed on individual serum samples taken from domestic adult dogs and cows compulsory vaccinated against rabies (147 urban dogs and 64 cows; n = 211). The sandwich and liquid-phase competitive ELISA (scELISA and lpcELISA), considered in-house assays, were performed according to previous works. The only statistical methodology that allows this study is the Bayesian approach, developed to replace the conventional Hui-Walter paradigm. For conditional independent Bayesian model (one population, two tests and no gold standard) the prior information for sensitivity and specificity of each test, mode, prevalence and transformed (α, β) were submitted to Bayesian inference. The in-house lpcELISA revealed 16 - out of 261 serum samples - negative results, whereas in scELISA all results were positive. The Bayesian approach showed that prior information was specified for all parameters; posterior medians were Se scELISA 89%, Sp scELISA 88%, Sp lpcELISA 95% Se lpcELISA 98%, and prevalence (pi) of 99%, without the use of gold standard analysis to measure specific anti-rabies antibodies.