Assessing freedom from chronic wasting disease in semi-domesticated reindeer in Norway and Sweden.

Establishing freedom from disease is a key component of surveillance and may have direct consequences for trade and economy. Transboundary populations pose challenges in terms of variable legislation, efforts, and data availability between countries, often limiting surveillance efficiency. Chronic wasting disease (CWD) is a contagious prion disease of cervids. The long incubation period and slow initial epidemic growth make it notoriously difficult to detect CWD in the early phase of an epidemic. The recent emergence of CWD in wild reindeer in Norway poses a threat to approximately 250,000 semi-domesticated reindeer in Norway and 250,000 in Sweden, including transboundary populations. Here, we provide a first analysis of surveillance data (2016-2022) from all reindeer districts in Norway and Sweden to determine the probability of freedom from CWD infection. During the six years, 6017 semi-domesticated reindeer were tested in Sweden and 51,974 in Norway. Most samples came from healthy slaughtered animals (low risk). Reindeer use large and remote areas and (high risk) samples from fallen stock and animals with clinical signs were difficult to obtain. A scenario tree model was run for seven different set of values for the input parameters (design prevalence within and between districts, probability of introduction, and relative risks) to determine the effect on surveillance sensitivity. At the national level, the mean probability of disease freedom was 59.0 % in Sweden and 87.0 % in Norway by 2021. The most marked effect on sensitivity was varying the design prevalence both within and between districts. Uncertainty about relative risk ratios affected sensitivity for Sweden more than for Norway, due to the higher proportion of animals in the high-risk group in the former (13.8 % vs. 2.1 %, respectively). A probability of disease freedom of 90 % or higher was reached in 8.2 % of the 49 districts in Sweden and 43.5 % of the 46 districts in Norway for a design prevalence of 0.5 %. The probability of freedom remained below 60 % in 29 districts (59.2 %) in Sweden and 10 districts (21.7 %) in Norway. At the national level, only Norway had a sufficiently large number of samples to reach a probability of more than 95 % of disease freedom within a period of 10 years. Our cross-border assessment forms an important knowledge base for designing future surveillance efforts depending on the spatial pattern of prevalence of CWD and risk of spread.

Review state-of-the-art of output-based methodological approaches for substantiating freedom from infection.

A wide variety of control and surveillance programmes that are designed and implemented based on country-specific conditions exists for infectious cattle diseases that are not regulated. This heterogeneity renders difficult the comparison of probabilities of freedom from infection estimated from collected surveillance data. The objectives of this review were to outline the methodological and epidemiological considerations for the estimation of probabilities of freedom from infection from surveillance information and review state-of-the-art methods estimating the probabilities of freedom from infection from heterogeneous surveillance data. Substantiating freedom from infection consists in quantifying the evidence of absence from the absence of evidence. The quantification usually consists in estimating the probability of observing no positive test result, in a given sample, assuming that the infection is present at a chosen (low) prevalence, called the design prevalence. The usual surveillance outputs are the sensitivity of surveillance and the probability of freedom from infection. A variety of factors influencing the choice of a method are presented; disease prevalence context, performance of the tests used, risk factors of infection, structure of the surveillance programme and frequency of testing. The existing methods for estimating the probability of freedom from infection are scenario trees, Bayesian belief networks, simulation methods, Bayesian prevalence estimation methods and the STOC free model. Scenario trees analysis is the current reference method for proving freedom from infection and is widely used in countries that claim freedom. Bayesian belief networks and simulation methods are considered extensions of scenario trees. They can be applied to more complex surveillance schemes and represent complex infection dynamics. Bayesian prevalence estimation methods and the STOC free model allow freedom from infection estimation at the herd-level from longitudinal surveillance data, considering risk factor information and the structure of the population. Comparison of surveillance outputs from heterogeneous surveillance programmes for estimating the probability of freedom from infection is a difficult task. This paper is a 'guide towards substantiating freedom from infection' that describes both all assumptions-limitations and available methods that can be applied in different settings.

Sporadic cases of chronic wasting disease in old moose - an epidemiological study.

Transmissible spongiform encephalopathies or prion diseases comprise diseases with different levels of contagiousness under natural conditions. The hypothesis has been raised that the chronic wasting disease (CWD) cases detected in Nordic moose (Alces alces) may be less contagious, or not contagious between live animals under field conditions. This study aims to investigate the epidemiology of CWD cases detected in moose in Norway, Sweden and Finland using surveillance data from 2016 to 2022.In total, 18 CWD cases were detected in Nordic moose. All moose were positive for prion (PrPres) detection in the brain, but negative in lymph nodes, all were old (mean 16 years; range 12-20) and all except one, were female. Age appeared to be a strong risk factor, and the sex difference may be explained by few males reaching high age due to hunting targeting calves, yearlings and males.The cases were geographically scattered, distributed over 15 municipalities. However, three cases were detected in each of two areas, Selbu in Norway and Arjeplog-Arvidsjaur in Sweden. A Monte Carlo simulation approach was applied to investigate the likelihood of such clustering occurring by chance, given the assumption of a non-contagious disease. The empirical P-value for obtaining three cases in one Norwegian municipality was less than 0.05, indicating clustering. However, the moose in Selbu were affected by different CWD strains, and over a 6 year period with intensive surveillance, the apparent prevalence decreased, which would not be expected for an ongoing outbreak of CWD. Likewise, the three cases in Arjeplog-Arvidsjaur could also indicate clustering, but management practices promotes a larger proportion of old females and the detection of the first CWD case contributed to increased awareness and sampling.The results of our study show that the CWD cases detected so far in Nordic moose have a different epidemiology compared to CWD cases reported from North America and in Norwegian reindeer (Rangifer tarandus tarandus). The results support the hypothesis that these cases are less contagious or not contagious between live animals under field conditions. To enable differentiation from other types of CWD, we support the use of sporadic CWD (sCWD) among the names already in use.