Impact of low testing numbers on chronic wasting disease apparent prevalence

TL;DR

Low testing numbers can make chronic wasting disease prevalence appear higher than it is, especially when fewer than 23 deer are tested.

Contribution

The study reveals that apparent prevalence is significantly influenced by testing numbers, not just disease cases, when testing is limited.

Findings

Apparent prevalence values ≥50% were only observed when fewer than 23 deer were tested.

Bayesian models showed a significant negative relationship between testing numbers and apparent prevalence.

The impact of testing on apparent prevalence decreases as testing increases.

Abstract

Chronic wasting disease (CWD) is a fatal, neurodegenerative disease of cervids, and its management heavily relies on diagnostic testing. Test results are commonly used to calculate ‘apparent prevalence’ (AP) – the percent of animals tested for CWD (CWD tests) with CWD-positive test results (CWD cases) – but this obscures how tests and cases individually contribute to this statistic. This is most relevant when CWD testing is limited because when few animals are tested, detection of even a single infected deer can result in a high AP that poorly reflects reality. We hypothesized that when CWD testing is limited, AP is negatively driven by testing – rather than cases – with more tests corresponding to lower APs. Graphed CWD surveillance data from townships in Illinois and Wisconsin, USA, indicate that CWD AP values ≥50% were only observed when <23 deer were tested. We used Bayesian multilevel zero-inflated Beta regression to model AP as a function of CWD tests, CWD cases and nonlinear transformations of these two terms separately for each state. The best-fit models of both identified a statistically significant negative relationship between AP and testing numbers that was modified by a positive nonlinear test covariate. This means adding tests when testing is low can have a big impact on decreasing the AP, but this relationship weakens as testing increases. We urge treating apparent prevalences ≥50% with caution and emphasize the importance of increasing the test results when initial surveillance has yielded <23 tests.

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