Thursday, September 13, 2018

NORWAY How many CWD-infected animals are out there?

How many CWD-infected animals are out there?  

Publisert 11.09.2018

The discovery of Chronic Wasting Disease (CWD) in Norway in 2016 has led to extensive measures and testing of deer in Norway, and from 2018 also within the EU. But how many deer needs to be tested before we can be almost certain that a population is not infected by CWD?

A new scientific publication provides important tools for estimation of prevalence and likelihood of finding infected animals in a given population.
The paper titled “A method that accounts for differential detectability in mixed samples of long-term infections with applications to the case of Chronic Wasting Disease in cervids” is published in Methods in Ecology and Evolution. The paper is a result of a collaborative work between a multidisciplinary group of scientists from the Norwegian Veterinary Institute, Norwegian Institute for Nature Research and the University of Oslo.

Will the infected animals test positive?

– How certain can we be that an infected individual will test positive? In a long-lasting infection, like CWD, it is important to take into account the temporal pattern of test sensitivity.  The model tool in this article deals mainly with estimating test sensitivity and how it is dependent on disease progression, the age of the animal and type of tissue tested. There are many applications for this model. We will use this model to determine when specific reindeer herds in Norway hopefully can be declared free from CWD, says Hildegunn Viljugrein, senior researcher at the Norwegian Veterinary Institute.

We cannot test the whole population

Surveillance of wildlife diseases is in general logistically difficult and a recurrent challenge for disease estimation. We cannot test the whole population for CWD, as the current standard test requires samples from dead animals.
The new model tool presented addresses a pressing need in CWD diagnostics, by taking into account the inconsistent quality of hunter-collected samples and the variability of prion deposition in target tissues with disease progression. In following-up work, the model will be used for estimating the probability of freedom from CWD for Hardangervidda and Nordfjella zone 2, the wild reindeer herds closest to Nordfjella Zone 1 where CWD was detected.

Del artikkel

Research Article

A method that accounts for differential detectability in mixed samples of long‐term infections with applications to the case of Chronic Wasting Disease in cervids

First published: 07 September 2018
This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/2041‐210X.13088


    1. Surveillance of wildlife diseases is logistically difficult, and imperfect detection is a recurrent challenge for disease estimation. Using citizen science can increase sample sizes, but it is associated with a cost in terms of the anatomical type and quality of the sample. Additionally, biological tissue samples from remote areas lose quality due to autolysis. These challenges are faced in the case of emerging Chronic Wasting Disease (CWD) in cervids.
    2. Here, we develop a stochastic scenario tree model of diagnostic sensitivity, allowing for a mixture of tissue sample types (lymph nodes and brain) and qualities while accounting for different detection probabilities during the CWD infection, lasting 2‐3 years. We apply the diagnostic sensitivity in a Bayesian framework, enabling estimation of age‐class‐specific true prevalence, including the prevalence in latent, recently infected stages. We provide a simulation framework to estimate the sensitivity of the surveillance system (i.e., the probability of detecting the infection in a given population), when detectability varies among individuals due to different disease progression.
    3. We demonstrate the utility of our framework by applying it to the recent emergence of CWD in a European population of reindeer. We estimated apparent CWD prevalence at 1.2% of adults in the infected population of wild reindeer, while the true prevalence was 1.6%. The sensitivity estimation of the CWD surveillance was performed in an adjacent small (~500) and a large (~10,000) reindeer population, demonstrating low certainty of CWD absence.
    4. Our method has immediate application to the mandatory testing for CWD in EU countries commencing in 2018. Similar approaches that account for latent stages and a serial disease progression in various tissues with a temporal pattern of diagnostic sensitivity may enhance the estimation of the prevalence of wildlife diseases more generally.
    This article is protected by copyright. All rights reserved.
    Supporting Information
    mee313088-sup-0001-AppendixS1.docxWord document, 26.5 KBAppendixS1
    mee313088-sup-0002-AppendixS2.docxWord document, 15.5 KBAppendixS2
    mee313088-sup-0003-AppendixS3.docxWord document, 18.4 KBAppendixS3
    mee313088-sup-0004-AppendixS4.docxWord document, 16.1 KBAppendixS4
    mee313088-sup-0005-AppendixS5.docxWord document, 130.7 KBAppendixS5
    mee313088-sup-0006-AppendixS6.docxWord document, 2.2 MBAppendixS6
    mee313088-sup-0007-AppendixS7.docxWord document, 22.6 KBAppendixS7
    mee313088-sup-0008-AppendixS8.docxWord document, 16.8 KBAppendixS8
    mee313088-sup-0009-AppendixS9.docxWord document, 25.2 KBAppendixS9
    Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.



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