Renate W. Hakze-Van der Honing

BACKGROUND: Tick-borne encephalitis virus (TBEV) was detected in the Netherlands in 2015. Current monitoring through serology in deer, tick collection and reported human cases, may underestimate areas of virus circulation. Including estimates of suitability of the habitat for TBEV can guide risk-based monitoring. AIM: We aimed to improve the accuracy of the TBEV distribution map by adding estimates of TBEV habitat suitability to guide targeted tick monitoring in newly identified risk regions. METHODS: Habitat suitability for TBEV was assessed by calculating the basic reproduction number (R ₀ ) for 1 km ² grid cells aggregating various data sources for tick hosts such as mice or voles, tick abundance and TBEV transmission. The importance of different tick hosts was determined in scenario analyses. The baseline scenario was validated against data on seropositive roe deer and TBEV-positive ticks and rodents. RESULTS: The suitability (R ₀ ≥ 1) was associated with tick habitat suitability and the abundance of competent host species. Variation in competent host densities had a greater effect on R ₀ estimates than incompetent hosts. Monitoring data corresponded well with model-predicted high-risk areas and confirmed further spread of TBEV. CONCLUSION: The TBEV suitability map is a useful tool for targeted sentinel surveillance by identifying new risk areas, informing local municipal health services of endemic areas for potential human exposure. Our results support targeted efforts for awareness, preparedness and outbreak response, even in regions where TBEV has not yet been detected. Integrating One Health monitoring with spatial modelling can strengthen preparedness in emerging TBEV regions.

Starting December 2019, a novel coronavirus (SARS‐CoV‐2) spread among humans across the world. From 2020 onward, farmed mink were found susceptible to the virus. In this paper, we describe the Dutch surveillance system and the added surveillance components for early detection of SARS‐CoV‐2 outbreaks and their results in Dutch mink farms. In the Netherlands, a surveillance system was in place in which mink farmers could submit carcasses for postmortem evaluation and could contact a telephone helpdesk for veterinary advise. Through this system, the first SARS‐CoV‐2 outbreak in two mink farms was detected in April 2020. Immediately, the Dutch Ministry of Agriculture commissioned a consortium of statutory and research institutes to intensify the surveillance system. The program consisted of both passive surveillance, i.e., mandatory notifications and active surveillance components, i.e., serological screenings and weekly risk‐based sampling of dead mink for early detection of new SARS‐CoV‐2 infections. When one of the surveillance components indicated a suspicion of a possible SARS‐CoV‐2 infection, follow‐up samplings were conducted and at confirmation, all mink were culled. During 2020, 67 out of 124 mink farms that were under surveillance became infected with SARS‐CoV‐2 (54%). Of these, 31 were detected based on clinical signs (passive surveillance of clinical signs) and 36 were detected through active surveillance. From the mink farms with a new SARS‐CoV‐2 outbreak that was detected through the surveillance, in 19% of the farms (n = 7), the mink never showed any clinical signs of SARS‐CoV‐2 and might have been missed by the passive notification system. This study underlines the added value of a surveillance system that can quickly be intensified. The subsequent combination of both passive and active surveillance has shown to be effective in the early detection of emerging pathogens, which is important to minimize the risk of zoonotic spill‐over.

Hepatitis E virus (HEV) is a positive-sense single-stranded RNA virus and a major cause of acute viral hepatitis. HEV is responsible for 20 million infections worldwide in humans every year. HEV-3 and HEV-4 are zoonotic and are responsible for most of the HEV cases in developed countries. Consumption of contaminated pig meat or pig products is considered to be the main transmission route of HEV HEV-3 in Europe. Prevalence studies for HEV generally use PCR methods to detect the presence or absence of genomic RNA. However, these methods do not discriminate infectious virus particles from non-infectious material. Previously developed HEV cell culture systems only worked with high efficiency after cell line adaptation of the subjected virus strains. In this manuscript, the development of a culture system for the detection of infectious HEV strains is described. For this purpose, we optimized the isolation and the growth of primary hepatocytes from young piglets. Subsequently, the isolated hepatocytes were used to culture HEV of different origins, such as liver tissue samples and sausage samples. This method can be applied to better assess the risk of infection through consumption of food products associated with HEV RNA contamination.

Pigs are a reservoir of hepatitis E virus (HEV), which causes hepatitis in humans. To study the epidemiology of HEV in pig farms, sampling methods are currently used that cause discomfort to pigs, such as rectal sampling. In line with the 3Rs principle, we aimed to evaluate non-invasive methods to detect pens with HEV-shedding pigs. Twenty-eight pens of one farm were sampled cross-sectionally. Individual rectal swabs (IRS) were collected to determine prevalence within pens. Four pen-level samples were compared: a pool of IRS per pen (P), boot socks (BS), oral fluid (OF) and pooled faecal droppings (FD). Each sample was tested by RT-PCR and the sensitivity and specificity of each method was determined by Bayesian latent class analysis. According to IRS, 19/28 pens were HEV positive. BS had a sensitivity of 95% and detected HEV in pens with 10% of pigs shedding; however, specificity was below 30%. FD were comparably accurate to P, with a sensitivity and specificity of 94% and 86%, respectively. BS sampling is thus advised to detect early shedding of HEV or pen contamination, and FD to determine the duration of shedding. This study demonstrates that non-invasive sampling can replace rectal swabs in research on HEV in pigs.

Wind-supported transport of particle matter (PM) contaminated with excreta from highly pathogenic avian influenza virus (HPAIv)-infected wild birds may be a HPAIv-introduction pathway, which may explain infections in indoor-housed poultry. The primary objective of our study was therefore to measure the nature and quantity of PM entering poultry houses via air-inlets. The air-inlets of two recently HPAIv-infected poultry farms (a broiler farm and a layer farm) were equipped with mosquito-net collection bags. PM was harvested every 5 days for 25 days. Video-camera monitoring registered wild bird visits. PM was tested for avian influenza viruses (AIV), Campylobacter and Salmonella with PCR. Insects, predominantly mosquitoes, were tested for AIV, West Nile, Usutu and Schmallenberg virus. A considerable number of mosquitoes and small PM amounts entered the air-inlets, mostly cobweb and plant material, but no wild bird feathers. Substantial variation in PM entering between air-inlets existed. In stormy periods, significantly larger PM amounts may enter wind-directed air-inlets. PM samples were AIV and Salmonella negative and insect samples were negative for all viruses and bacteria, but several broiler and layer farm PM samples tested Campylobacter positive. Regular wild (water) bird visits were observed near to the poultry houses. Air-borne PM and insects—potentially contaminated with HPAIv or other pathogens—can enter poultry air-inlets. Implementation of measures limiting this potential introduction route are recommended.

SARS-CoV-2 outbreaks on 69 Dutch mink farms in 2020 were studied to identify risk factors for virus introduction and transmission and to improve surveillance and containment measures. Clinical signs, laboratory test results, and epidemiological aspects were investigated, such as the date and reason of suspicion, housing, farm size and distances, human contact structure, biosecurity measures, and presence of wildlife, pets, pests, and manure management. On seven farms, extensive random sampling was performed, and age, coat color, sex, and clinical signs were recorded. Mild to severe respiratory signs and general diseases such as apathy, reduced feed intake, and increased mortality were detected on 62/69 farms. Throat swabs were more likely to result in virus detection than rectal swabs. Clinical signs differed between virus clusters and were more severe for dark-colored mink, males, and animals infected later during the year. Geographical clustering was found for one virus cluster. Shared personnel could explain some cases, but other transmission routes explaining farm-to-farm spread were not elucidated. An early warning surveillance system, strict biosecurity measures, and a (temporary) ban on mink farming and vaccinating animals and humans can contribute to reducing the risks of the virus spreading and acquisition of potential mutations relevant to human and animal health.

In the first wave of the COVID-19 pandemic (April 2020), SARS-CoV-2 was detected in farmed minks and genomic sequencing was performed on mink farms and farm personnel. Here, we describe the outbreak and use sequence data with Bayesian phylodynamic methods to explore SARS-CoV-2 transmission in minks and humans on farms. High number of farm infections (68/126) in minks and farm workers (>50% of farms) were detected, with limited community spread. Three of five initial introductions of SARS-CoV-2 led to subsequent spread between mink farms until November 2020. Viruses belonging to the largest cluster acquired an amino acid substitution in the receptor binding domain of the Spike protein (position 486), evolved faster and spread longer and more widely. Movement of people and distance between farms were statistically significant predictors of virus dispersal between farms. Our study provides novel insights into SARS-CoV-2 transmission between mink farms and highlights the importance of combining genetic information with epidemiological information when investigating outbreaks at the animal-human interface.

The COVID-19 pandemic has illustrated the need for the development of fast and reliable testing methods for novel, zoonotic, viral diseases in both humans and animals. Pathologies lead to detectable changes in the Volatile Organic Compound (VOC) profile of animals, which can be monitored, thus allowing the development of a rapid VOC-based test. In the current study, we successfully trained honeybees ( Apis mellifera ) to identify SARS-CoV-2 infected minks ( Neovison vison ) thanks to Pavlovian conditioning protocols. The bees can be quickly conditioned to respond specifically to infected mink’s odours and could therefore be part of a wider SARS-CoV-2 diagnostic system. We tested two different training protocols to evaluate their performance in terms of learning rate, accuracy and memory retention. We designed a non-invasive rapid test in which multiple bees are tested in parallel on the same samples. This provided reliable results regarding a subject’s health status. Using the data from the training experiments, we simulated a diagnostic evaluation trial to predict the potential efficacy of our diagnostic test, which yielded a diagnostic sensitivity of 92% and specificity of 86%. We suggest that a honeybee-based diagnostics can offer a reliable and rapid test that provides a readily available, low-input addition to the currently available testing methods. A honeybee-based diagnostic test might be particularly relevant for remote and developing communities that lack the resources and infrastructure required for mainstream testing methods.

In assessing species susceptibility for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and in the search for an appropriate animal model, multiple research groups around the world inoculated a broad range of animal species using various SARS-CoV-2 strains, doses and administration routes. Although in silico analyses based on receptor binding and diverse in vitro cell cultures were valuable, exact prediction of species susceptibility based on these tools proved challenging. Here, we assessed whether precision-cut lung slices (PCLS) could facilitate the selection of animal models, thereby reducing animal experimentation. Pig, hamster and cat PCLS were incubated with SARS-CoV-2 and virus replication was followed over time. Virus replicated efficiently in PCLS from hamsters and cats, while no evidence of replication was obtained for pig PCLS. These data corroborate the findings of many research groups that have investigated the susceptibility of hamsters, pigs and cats towards infection with SARS-CoV-2. Our findings suggest that PCLS can be used as convenient tool for the screening of different animal species for sensitivity to newly emerged viruses. To validate our results obtained in PCLS, we employed the hamster model. Hamsters were inoculated with SARS-CoV-2 via the intranasal route. Susceptibility to infection was evaluated by body weight loss, viral loads in oropharyngeal swabs and respiratory tissues and lung pathology. The broadly used hamster model was further refined by including activity tracking of the hamsters by an activity wheel as a very robust and sensitive parameter for clinical health. In addition, to facilitate the quantification of pathology in the lungs, we devised a semi-quantitative scoring system for evaluating the degree of histological changes in the lungs. The inclusion of these additional parameters refined and enriched the hamster model, allowing for the generation of more data from a single experiment.