Getting in Front of Chronic Wasting Disease: Model-Informed Proactive Approach for Managing an Emerging Wildlife Disease

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.

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.

Canine detection of chronic wasting disease (CWD) in laboratory and field settings

Chronic wasting disease (CWD) is a fatal transmissible spongiform encephalopathy that affects both free-ranging and farmed cervid species, including mule deer, white-tailed deer, and elk (Odocoileus hemionus, Odocoileus virginianus, and Cervus canadensis). Due to the long incubation period and variability of clinical signs, CWD can expand and spread to new areas before they reach diagnostically detectable levels. Antemortem testing methods currently available can be difficult to obtain and to be applied to the large numbers required for adequate surveillance. However, key volatile biomarkers could be harnessed for non-invasive antemortem surveillance. Detection dogs are the most effective tool currently available for volatile detection; dogs can effectively complete wildlife surveys at rates surpassing that of humans. This study is the first to demonstrate that trained detection dogs can be used as an antemortem test for CWD. First, we trained three dogs to differentiate between CWD-positive and CWD-negative white-tailed deer faeces in a laboratory setting. Dogs spent significantly more time at the positive sample than the negative samples, suggesting that they differentiated between the positive and negative volatile signatures. We then trained the same dogs to search for CWD-positive faecal samples in a more naturalistic field setting. In the field, dogs found 8/11 CWD-positive samples and had an average false detection rate of 13%. These results suggest that dogs can be trained to differentiate CWD-positive faeces from CWD-negative faeces in both laboratory and field settings. Future studies will compare canine accuracy to other antemortem methods, as well as improved canine training methods.

A microfluidic biosensor for the diagnosis of chronic wasting disease

Cervids are affected by a neurologic disease that is always fatal to individuals and has population effects. This disease is called chronic wasting disease (CWD) and is caused by a misfolded prion protein. The disease is transmitted via contact with contaminated body fluids and tissue or exposure to the environment, such as drinking water or food. Current CWD diagnosis depends on ELISA screening of cervid lymph nodes and subsequent immunohistochemistry (IHC) confirmation of ELISA-positive results. The disease has proven to be difficult to control in part because of sensitivity and specificity issues with the current test regimen. We have investigated an accurate, rapid, and low-cost microfluidic microelectromechanical system (MEMS) biosensing device for the detection of CWD pathologic prions in retropharyngeal lymph nodes (RLNs), which is the current standard type of CWD diagnostic sample. The device consists of three novel regions for concentrating, trapping, and detecting the prion. The detection region includes an array of electrodes coated with a monoclonal antibody against pathologic prions. The experimental conditions were optimized using an engineered prion control antigen. Testing could be completed in less than 1 hour with high sensitivity and selectivity. The biosensor detected the engineered prion antigen at a 1:24 dilution, while ELISA detected the same antigen at a 1:8 dilution. The relative limit of detection (rLOD) of the biosensor was a 1:1000 dilution of a known strong positive RLN sample, whereas ELISA showed a rLOD of 1:100 dilution. Thus, the biosensor was 10 times more sensitive than ELISA, which is the currently approved CWD diagnostic test. The biosensor's specificity and selectivity were confirmed using known negative RPLN samples, a negative control antibody (monoclonal antibody against bovine coronavirus BCV), and two negative control antigens (bluetongue virus and Epizootic hemorrhagic disease virus). The biosensor's ability to detect pathogenic prions was verified by testing proteinase-digested positive RLN samples.

Risk-based surveillance of chronic wasting disease in semi-domestic reindeer

Reindeer pastoralism is a widespread practise across Fennoscandia and Russia. An outbreak of chronic wasting disease (CWD) among wild reindeer (Rangifer tarandus) poses a severe threat to the semi-domestic reindeer herding culture. Establishing surveillance is therefore key, but current models for surveillance of CWD are designed for wild cervids and rely on samples obtained from recreational hunters. Targeting animal groups with a higher infection probability is often used for more efficient disease surveillance. CWD has a long incubation period of 2-3 years, and the animals show clinical signs in the later stages of the infection i.e. 1-4 months prior to death. The semi-domestic reindeer are free-ranging most of the year, but during slaughtering in late fall, herders stress the animals in penned areas. This allows removal of animals with deviant behaviour or physical appearance, and such removals are likely to include animals in the clinical stages of CWD if the population is infected. In Norway, the semi-domestic reindeer in Filefjell is adjacent to a previously CWD infected wild population. We developed a risk-based surveillance method for this semi-domestic setting to establish the probability of freedom from infection over time, or enable early disease detection and mitigation. The surveillance scheme with a scenario tree using three risk categories (sample category, demographic group, and deviations in behaviour or physical appearance) was more effective and less invasive as compared to the surveillance method developed for wild reindeer. We also simulated how variation in susceptibility, incubation period and time for onset of clinical signs (linked to variation in the prion protein gene, PRNP) would potentially affect surveillance. Surveillance for CWD was mandatory within EU-member states with reindeer (2018-2020). The diversity of management systems and epidemiological settings will require the development of a set of surveillance systems suitable for each different context. Our surveillance model is designed for a population with a high risk of CWD introduction requiring massive sampling, while at the same time aiming to limit adverse effects to the populations in areas of surveillance.

A Landscape Epidemiological Approach for Predicting Chronic Wasting Disease: A Case Study in Virginia, US

Many infectious diseases in wildlife occur under quantifiable landscape ecological patterns useful in facilitating epidemiological surveillance and management, though little is known about prion diseases. Chronic wasting disease (CWD), a fatal prion disease of the deer family Cervidae, currently affects white-tailed deer (Odocoileus virginianus) populations in the Mid-Atlantic United States (US) and challenges wildlife veterinarians and disease ecologists from its unclear mechanisms and associations within landscapes, particularly in early phases of an outbreak when CWD detections are sparse. We aimed to provide guidance for wildlife disease management by identifying the extent to which CWD-positive cases can be reliably predicted from landscape conditions. Using the CWD outbreak in Virginia, US from 2009 to early 2020 as a case study system, we used diverse algorithms (e.g., principal components analysis, support vector machines, kernel density estimation) and data partitioning methods to quantify remotely sensed landscape conditions associated with CWD cases. We used various model evaluation tools (e.g., AUC ratios, cumulative binomial testing, Jaccard similarity) to assess predictions of disease transmission risk using independent CWD data. We further examined model variation in the context of uncertainty. We provided significant support that vegetation phenology data representing landscape conditions can predict and map CWD transmission risk. Model predictions improved when incorporating inferred home ranges instead of raw hunter-reported coordinates. Different data availability scenarios identified variation among models. By showing that CWD could be predicted and mapped, our project adds to the available tools for understanding the landscape ecology of CWD transmission risk in free-ranging populations and natural conditions. Our modeling framework and use of widely available landscape data foster replicability for other wildlife diseases and study areas.

Harvest strategies for the elimination of low prevalence wildlife diseases

The intensive harvesting of hosts is often the only practicable strategy for controlling emerging wildlife diseases. Several harvesting approaches have been explored theoretically with the objective of lowering transmission rates, decreasing the transmission period or specifically targeting spatial disease clusters or high-risk demographic groups. Here, we present a novel model-based approach to evaluate alternative harvest regimes, in terms of demographic composition and rates, intended to increase the probability to remove all infected individuals in the population during the early phase of an outbreak. We tested the utility of the method for the elimination of chronic wasting disease based on empirical data for reindeer (Rangifer tarandus) in Norway, in populations with (Nordfjella) and without (Hardangervidda) knowledge about exact disease prevalence and population abundance. Low and medium harvest intensities were unsuccessful in eliminating the disease, even at low prevalence. High-intensity harvesting had a high likelihood of eliminating the disease, but probability was strongly influenced by the disease prevalence. We suggest that the uncertainty about disease prevalence can be mitigated by using an adaptive management approach: forecast from models after each harvest season with updated data, derive prevalence estimates and forecast further harvesting. We identified the problems arising from disease surveillance with large fluctuations in harvesting pressure and hence sample sizes. The elimination method may be suitable for pathogens that cause long-lasting infections and with slow epidemic growth, but the method should only be attempted if there is a low risk of reinfection, either by a new disease introduction event (e.g. dispersing hosts) or due to environmental reservoirs. Our simulations highlighted the short time window when such a strategy is likely to be successful before approaching near complete eradication of the population.