Although frequentist approaches to prevalence estimation are simple to apply, there are circumstances where it is difficult to satisfy assumptions of asymptotic normality and nonsensical point estimates (greater than 1 or less than 0) may result. This is particularly true when sample sizes are small, test prevalences are low and imperfect sensitivity and specificity of diagnostic tests need to be incorporated into calculations of true prevalence. Bayesian approaches offer several advantages including direct computation of range-respecting interval estimates (e.g. intervals between 0 and 1 for prevalence) without the requirement of transformations or large-sample approximations, direct probabilistic interpretation, and the flexibility to model in a straightforward manner the probability of zero prevalence. In this review, we present frequentist and Bayesian methods for animal- and herd-level true prevalence estimation based on individual and pooled samples. We provide statistical methods for detecting differences between population prevalence and frequentist methods for sample size and power calculations. All examples are motivated using Mycobacterium avium subspecies paratuberculosis infection and we provide WinBUGS code for all examples of Bayesian estimation.

/pdf/frequentist-and-bayesian-approaches-to-prevalence-estimation-19eth22er7.pdf

Frequentist and Bayesian approaches to prevalence estimation using examples from Johne's disease.

Serological and virological BVDV prevalence and risk factor analysis for herds to be BVDV seropositive in Belgian cattle herds.

The need to detect and eliminate cattle persistently infected (PI) with bovine viral diarrhoea virus (BVDV) is key to the control of BVD and has been shown to be very effective in eradicating BVDV from infected herds. However, because of pitfalls in the detection procedures, some PI animals can be missed and, as a result, are not identified and removal is delayed. The high prevalence of BVDV in cattle populations in some countries (such as Belgium and neighbouring countries) means there is a high risk of reinfection of a herd from which BVDV has been eradicated. Based on both practical experience and a literature study, this review considers those points that are critical to minimising the number of false negatives in the detection of PI cattle.

Control of bovine virus diarrhoea at the herd level: reducing the risk of false negatives in the detection of persistently infected cattle.

Self-clearance from BVDV infections--a frequent finding in dairy herds in an endemically infected region in Peru.

Bovine viral diarrhea virus (BVDV) has a great economic impact on the United States cattle industry. The Academy of Veterinary Consultants, the American Association of Bovine Practitioners, and the National Cattlemen's Beef Association have called for the goal of BVDV control and eventual eradication in the USA. One of the key factors in such efforts will be the detection of BVDV infections, particularly targeting persistently infected animals. To assess current BVDV detection methods in the USA, 26 veterinary diagnostic laboratories in 23 states were surveyed. Survey questions related to the types of tests currently offered, the number of tests performed, the reasons for test requests, the type of samples used, whether sample pooling was performed, and whether follow-up testing or information regarding bovine viral diarrhea (BVD) management was provided after positive tests. There was no clear consensus on an individual BVDV testing method, the pooling of samples or the retesting of positive animals. Ear-notch antigen capture enzyme-linked immunosorbent assay (ACE) was the test most frequently performed based on the absolute number of

https://journals.sagepub.com/doi/pdf/10.1177/104063870601800615

A survey of bovine viral diarrhea virus testing in diagnostic laboratories in the United States from 2004 to 2005.

Detection of BVDV persistently infected animals in Belgium: evaluation of the strategy implemented.

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Detection of BVDV persistently infected animals in Belgium: evaluation of the strategy implemented.