Vaccination of poultry against highly pathogenic avian influenza - Part 2. Surveillance and mitigation measures.

Selecting appropriate diagnostic methods that take account of the type of vaccine used is important when implementing a vaccination programme against highly pathogenic avian influenza (HPAI). If vaccination is effective, a decreased viral load is expected in the samples used for diagnosis, making molecular methods with high sensitivity the best choice. Although serological methods can be reasonably sensitive, they may produce results that are difficult to interpret. In addition to routine molecular monitoring, it is recommended to conduct viral isolation, genetic sequencing and phenotypic characterisation of any HPAI virus detected in vaccinated flocks to detect escape mutants early. Following emergency vaccination, various surveillance options based on virological testing of dead birds ('bucket sampling') at defined intervals were assessed to be effective for early detection of HPAIV and prove disease freedom in vaccinated populations. For ducks, virological or serological testing of live birds was assessed as an effective strategy. This surveillance could be also applied in the peri-vaccination zone on vaccinated establishments, while maintaining passive surveillance in unvaccinated chicken layers and turkeys, and weekly bucket sampling in unvaccinated ducks. To demonstrate disease freedom with > 99% confidence and to detect HPAI virus sufficiently early following preventive vaccination, monthly virological testing of all dead birds up to 15 per flock, coupled with passive surveillance in both vaccinated and unvaccinated flocks, is recommended. Reducing the sampling intervals increases the sensitivity of early detection up to 100%. To enable the safe movement of vaccinated poultry during emergency vaccination, laboratory examinations in the 72 h prior to the movement can be considered as a risk mitigation measure, in addition to clinical inspection; sampling results from existing surveillance activities carried out in these 72 h could be used. In this Opinion, several schemes are recommended to enable the safe movement of vaccinated poultry following preventive vaccination.

One Health surveillance of colistin-resistant Enterobacterales in Belgium and the Netherlands between 2017 and 2019.

BACKGROUND: Colistin serves as the last line of defense against multidrug resistant Gram-negative bacterial infections in both human and veterinary medicine. This study aimed to investigate the occurrence and spread of colistin-resistant Enterobacterales (ColR-E) using a One Health approach in Belgium and in the Netherlands. METHODS: In a transnational research project, a total of 998 hospitalized patients, 1430 long-term care facility (LTCF) residents, 947 children attending day care centres, 1597 pigs and 1691 broilers were sampled for the presence of ColR-E in 2017 and 2018, followed by a second round twelve months later for hospitalized patients and animals. Colistin treatment incidence in livestock farms was used to determine the association between colistin use and resistance. Selective cultures and colistin minimum inhibitory concentrations (MIC) were employed to identify ColR-E. A combination of short-read and long-read sequencing was utilized to investigate the molecular characteristics of 562 colistin-resistant isolates. Core genome multi-locus sequence typing (cgMLST) was applied to examine potential transmission events. RESULTS: The presence of ColR-E was observed in all One Health sectors. In Dutch hospitalized patients, ColR-E proportions (11.3 and 11.8% in both measurements) were higher than in Belgian patients (4.4 and 7.9% in both measurements), while the occurrence of ColR-E in Belgian LTCF residents (10.2%) and children in day care centres (17.6%) was higher than in their Dutch counterparts (5.6% and 12.8%, respectively). Colistin use in pig farms was associated with the occurrence of colistin resistance. The percentage of pigs carrying ColR-E was 21.8 and 23.3% in Belgium and 14.6% and 8.9% in the Netherlands during both measurements. The proportion of broilers carrying ColR-E in the Netherlands (5.3 and 1.5%) was higher compared to Belgium (1.5 and 0.7%) in both measurements. mcr-harboring E. coli were detected in 17.4% (31/178) of the screened pigs from 7 Belgian pig farms. Concurrently, four human-related Enterobacter spp. isolates harbored mcr-9.1 and mcr-10 genes. The majority of colistin-resistant isolates (419/473, 88.6% E. coli; 126/166, 75.9% Klebsiella spp.; 50/75, 66.7% Enterobacter spp.) were susceptible to the critically important antibiotics (extended-spectrum cephalosporins, fluoroquinolones, carbapenems and aminoglycosides). Chromosomal colistin resistance mutations have been identified in globally prevalent high-risk clonal lineages, including E. coli ST131 (n = 17) and ST1193 (n = 4). Clonally related isolates were detected in different patients, healthy individuals and livestock animals of the same site suggesting local transmission. Clonal clustering of E. coli ST10 and K. pneumoniae ST45 was identified in different sites from both countries suggesting that these clones have the potential to spread colistin resistance through the human population or were acquired by exposure to a common (food) source. In pig farms, the continuous circulation of related isolates was observed over time. Inter-host transmission between humans and livestock animals was not detected. CONCLUSIONS: The findings of this study contribute to a broader understanding of ColR-E prevalence and the possible pathways of transmission, offering insights valuable to both academic research and public health policy development.

Seroprevalence of SARS-CoV-2 antibodies among healthcare workers in Dutch hospitals after the 2020 first wave: a multicentre cross-sectional study with prospective follow-up.

BACKGROUND: We aimed to estimate the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence and describe its determinants and associated symptoms among unvaccinated healthcare workers (HCWs) after the first wave of the pandemic. METHODS: HCWs from 13 Dutch hospitals were screened for antibodies against the spike protein of SARS-CoV-2 in June-July 2020 and after three months. Participants completed a retrospective questionnaire on determinants for occupational and community exposure to SARS-CoV-2 and symptoms suggestive of COVID-19 experienced since January 2020. The seroprevalence was calculated per baseline characteristic and symptom at baseline and after follow-up. Adjusted odds ratios (aOR) for seropositivity were determined using logistic regression. RESULTS: Among 2328 HCWs, 323 (13.9%) were seropositive at enrolment, 49 of whom (15%) reported no previous symptoms suggestive of COVID-19. During follow-up, only 1% of the tested participants seroconverted. Seroprevalence was higher in younger HCWs compared to the mid-age category (aOR 1.53, 95% CI 1.07-2.18). Nurses (aOR 2.21, 95% CI 1.34-3.64) and administrative staff (aOR 1.87, 95% CI 1.02-3.43) had a higher seroprevalence than physicians. The highest seroprevalence was observed in HCWs in the emergency department (ED) (aOR 1.79, 95% CI 1.10-2.91), the lowest in HCWs in the intensive, high, or medium care units (aOR 0.47, 95% CI 0.31-0.71). Chronic respiratory disease, smoking, and having a dog were independently associated with a lower seroprevalence, while HCWs with diabetes mellitus had a higher seroprevalence. In a multivariable model containing all self-reported symptoms since January 2020, altered smell and taste, fever, general malaise/fatigue, and muscle aches were positively associated with developing antibodies, while sore throat and chills were negatively associated. CONCLUSIONS: The SARS-CoV-2 seroprevalence in unvaccinated HCWs of 13 Dutch hospitals was 14% in June-July 2020 and remained stable after three months. A higher seroprevalence was observed in the ED and among nurses, administrative and young staff, and those with diabetes mellitus, while a lower seroprevalence was found in HCWs in intensive, high, or medium care, and those with self-reported lung disease, smokers, and dog owners. A history of altered smell or taste, fever, muscle aches and fatigue were independently associated with the presence of SARS-CoV-2 antibodies in unvaccinated HCWs.

Vaccination of poultry against highly pathogenic avian influenza - part 1. Available vaccines and vaccination strategies.

Several vaccines have been developed against highly pathogenic avian influenza (HPAI), mostly inactivated whole-virus vaccines for chickens. In the EU, one vaccine is authorised in chickens but is not fully efficacious to stop transmission, highlighting the need for vaccines tailored to diverse poultry species and production types. Off-label use of vaccines is possible, but effectiveness varies. Vaccines are usually injectable, a time-consuming process. Mass-application vaccines outside hatcheries remain rare. First vaccination varies from in-ovo to 6 weeks of age. Data about immunity onset and duration in the target species are often unavailable, despite being key for effective planning. Minimising antigenic distance between vaccines and field strains is essential, requiring rapid updates of vaccines to match circulating strains. Generating harmonised vaccine efficacy data showing vaccine ability to reduce transmission is crucial and this ability should be also assessed in field trials. Planning vaccination requires selecting the most adequate vaccine type and vaccination scheme. Emergency protective vaccination is limited to vaccines that are not restricted by species, age or pre-existing vector-immunity, while preventive vaccination should prioritise achieving the highest protection, especially for the most susceptible species in high-risk transmission areas. Model simulations in France, Italy and The Netherlands revealed that (i) duck and turkey farms are more infectious than chickens, (ii) depopulating infected farms only showed limitations in controlling disease spread, while 1-km ring-culling performed better than or similar to emergency preventive ring-vaccination scenarios, although with the highest number of depopulated farms, (iii) preventive vaccination of the most susceptible species in high-risk transmission areas was the best option to minimise the outbreaks' number and duration, (iv) during outbreaks in such areas, emergency protective vaccination in a 3-km radius was more effective than 1- and 10-km radius. Vaccine efficacy should be monitored and complement other surveillance and preventive efforts.

Epidemiology-driven approaches to surveillance in HPAI-vaccinated poultry flocks aiming to demonstrate freedom from circulating HPAIV.

Incursion pressure of high pathogenicity avian influenza viruses (HPAIV) by secondary spread among poultry holdings and/or from infected migratory wild bird populations increases worldwide. Vaccination as an additional layer of protection of poultry holdings using appropriately matched vaccines aims at reducing clinical sequelae of HPAIV infection, disrupting HPAIV transmission, curtailing economic losses and animal welfare problems and cutting exposure risks of zoonotic HPAIV at the avian-human interface. Products derived from HPAIV-vaccinated poultry should not impose any risk of virus spread or exposure. Vaccination can be carried out with zero-tolerance for infection in vaccinated herds and must then be flanked by appropriate surveillance which requires tailoring at several levels: (i) Controlling appropriate vaccination coverage and adequate population immunity in individual flocks and across vaccinated populations; (ii) assessing HPAI-infection trends in unvaccinated and vaccinated parts of the poultry population to provide early detection of new/re-emerged HPAIV outbreaks; and (iii) proving absence of HPAIV circulation in vaccinated flocks ideally by real time-monitoring. Surveillance strategies, i.e. selecting targets, tools and random sample sizes, must be accommodated to the specific epidemiologic and socio-economic background. Methodological approaches and practical examples from three countries or territories applying AI vaccination under different circumstances are reviewed here.

Farm biosecurity measures to prevent hepatitis E virus infection in finishing pigs on endemically infected pig farms.

Hepatitis E virus (HEV) can be transmitted from pigs to humans and cause liver inflammation. Pigs are a major reservoir of HEV and most slaughter pigs show evidence of infection by presence of antibodies (ELISA) or viral RNA (PCR). Reducing the number of HEV infected pigs at slaughter would likely reduce human exposure, yet how this can be achieved, is unknown. We aimed to identify and quantify the effect of biosecurity measures to deliver HEV negative batches of pigs to slaughter. A case-control study was performed with Dutch pig farms selected based on results of multiple slaughter batches. Case farms delivered at least one PCR and ELISA negative batch to slaughter (PCR-ELISA-), indicating absence of HEV infection, and control farms had the highest proportion of PCR and/or ELISA positive batches (PCR+ELISA+), indicating high within-farm transmission. Data about biosecurity and housing were collected via a questionnaire and an audit. Variables were selected by regularization (LASSO regression) and ranked, based the frequency of variable selection. The odds ratios (OR) for the relation between case-control status and the highest ranked variables were determined via grouped logistic regression. Thirty-five case farms, with 10 to 60% PCR-ELISA- batches, and 38 control farms with on average 40% PCR+ELISA+ batches, were included. Rubber and steel floor material in fattening pens had the highest ranking and increased the odds of a PCR-ELISA- batch by 5.87 (95%CI 3.03-11.6) and 7.13 (95%CI 3.05-16.9) respectively. Cleaning pig driving boards weekly (OR 1.99 (95%CI 1.07-3.80)), and fly control with predatory flies (OR 4.52 (95%CI 1.59-13.5)) were protective, whereas a long fattening period was a risk. This study shows that cleaning and cleanability of floors and fomites and adequate fly control are measures to consider for HEV control in infected farms. Yet, intervention studies are needed to confirm the robustness of these outcomes.

Efficient Direct and Limited Environmental Transmission of SARS-CoV-2 Lineage B.1.22 in Domestic Cats.

The susceptibility of domestic cats to infection with SARS-CoV-2 has been demonstrated by several experimental studies and field observations. We performed an extensive study to further characterize the transmission of SARS-CoV-2 between cats, through both direct and indirect contact. To that end, we estimated the transmission rate parameter and the decay parameter for infectivity in the environment. Using four groups of pair-transmission experiment, all donor (inoculated) cats became infected, shed virus, and seroconverted, while three out of four direct contact cats got infected, shed virus, and two of those seroconverted. One out of eight cats exposed to a SARS-CoV-2-contaminated environment became infected but did not seroconvert. Statistical analysis of the transmission data gives a reproduction number R0 of 2.18 (95% CI = 0.92 to 4.08), a transmission rate parameter ß of 0.23 day-1 (95% CI = 0.06 to 0.54), and a virus decay rate parameter µ of 2.73 day-1 (95% CI = 0.77 to 15.82). These data indicate that transmission between cats is efficient and can be sustained (R0 > 1), however, the infectiousness of a contaminated environment decays rapidly (mean duration of infectiousness 1/2.73 days). Despite this, infections of cats via exposure to a SARS-CoV-2-contaminated environment cannot be discounted if cats are exposed shortly after contamination. IMPORTANCE This article provides additional insight into the risk of infection that could arise from cats infected with SARS-CoV-2 by using epidemiological models to determine transmission parameters. Considering that transmission parameters are not always provided in the literature describing transmission experiments in animals, we demonstrate that mathematical analysis of experimental data is crucial to estimate the likelihood of transmission. This article is also relevant to animal health professionals and authorities involved in risk assessments for zoonotic spill-overs of SARS-CoV-2. Last but not least, the mathematical models to calculate transmission parameters are applicable to analyze the experimental transmission of other pathogens between animals.

Evaluation of Non-Invasive Sampling Methods for Detection of Hepatitis E Virus Infected Pigs in Pens.

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.

Biosecurity and antimicrobial use in broiler farms across nine European countries: toward identifying farm-specific options for reducing antimicrobial usage.

Broiler chickens are among the main livestock sectors worldwide. With individual treatments being inapplicable, contrary to many other animal species, the need for antimicrobial use (AMU) is relatively high. AMU in animals is known to drive the emergence and spread of antimicrobial resistance (AMR). High farm biosecurity is a cornerstone for animal health and welfare, as well as food safety, as it protects animals from the introduction and spread of pathogens and therefore the need for AMU. The goal of this study was to identify the main biosecurity practices associated with AMU in broiler farms and to develop a statistical model that produces customised recommendations as to which biosecurity measures could be implemented on a farm to reduce its AMU, including a cost-effectiveness analysis of the recommended measures. AMU and biosecurity data were obtained cross-sectionally in 2014 from 181 broiler farms across nine European countries (Belgium, Bulgaria, Denmark, France, Germany, Italy, the Netherlands, Poland and Spain). Using mixed-effects random forest analysis (Mix-RF), recursive feature elimination was implemented to determine the biosecurity measures that best predicted AMU at the farm level. Subsequently, an algorithm was developed to generate AMU reduction scenarios based on the implementation of these measures. In the final Mix-RF model, 21 factors were present: 10 about internal biosecurity, 8 about external biosecurity and 3 about farm size and productivity, with the latter showing the largest (Gini) importance. Other AMU predictors, in order of importance, were the number of depopulation steps, compliance with a vaccination protocol for non-officially controlled diseases, and requiring visitors to check in before entering the farm. K-means clustering on the proximity matrix of the final Mix-RF model revealed that several measures interacted with each other, indicating that high AMU levels can arise for various reasons depending on the situation. The algorithm utilised the AMU predictive power of biosecurity measures while accounting also for their interactions, representing a first step toward aiding the decision-making process of veterinarians and farmers who are in need of implementing on-farm biosecurity measures to reduce their AMU.

Coverage and Representativeness of Passive Surveillance Components for Cattle and Swine in The Netherlands.

Common aims of animal health surveillance systems are the timely detection of emerging diseases and health status monitoring. This study aimed to evaluate the coverage and representativeness of passive surveillance components for cattle and swine in the Netherlands from 2015-2019. The passive surveillance components consisted of a telephone helpdesk for veterinary advice and diagnostic and postmortem facilities. Spatial analysis showed heterogeneity (range in RR = 0.26-5.37) of participation across the Netherlands. Generalized linear mixed models showed that distance to the diagnostic facility and farm density were associated with the number of contacts of farmers with the helpdesk and postmortem examination. The contact rate of veterinary practices was associated with their number of clients, ranging in RR from 0.39 to 1.59. We concluded that the evaluation indicated differences in coverage of the passive surveillance components across regions, farms and veterinary practices. Due to the absence of emerging infections in the study period, we were unable to estimate the consequences of the observed differences for the early detection of disease. Nevertheless, regions and veterinary practices with low participation in passive surveillance might be a risk for early detection, and consequently, further understanding of the motivation to participate in passive surveillance components is needed.

SARS-CoV-2 infection in dogs and cats is associated with contact to COVID-19-positive household members.

Several domestic and wild animal species are susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Reported (sero)prevalence in dogs and cats vary largely depending on the target population, test characteristics, geographical location and time period. This research assessed the prevalence of SARS-CoV-2-positive cats and dogs (PCR- and/or antibody positive) in two different populations. Dogs and cats living in a household with at least one confirmed COVID-19-positive person (household (HH) study; 156 dogs and 152 cats) and dogs and cats visiting a veterinary clinic (VC) (VC study; 183 dogs and 140 cats) were sampled and tested for presence of virus (PCR) and antibodies. Potential risk factors were evaluated and follow-up of PCR-positive animals was performed to determine the duration of virus shedding and to detect potential transmission between pets in the same HH. In the HH study, 18.8% (27 dogs, 31 cats) tested SARS-CoV-2 positive (PCR- and/or antibody positive), whereas in the VC study, SARS-CoV-2 prevalence was much lower (4.6%; six dogs, nine cats). SARS-CoV-2 prevalence amongst dogs and cats was significantly higher in the multi-person HHs with two or more COVID-19-positive persons compared with multi-person HHs with only one COVID-19-positive person. In both study populations, no associations could be identified between SARS-CoV-2 status of the animal and health status, age or sex. During follow-up of PCR-positive animals, no transmission to other pets in the HH was observed despite long-lasting virus shedding in cats (up to 35 days). SARS-CoV-2 infection in dogs and cats appeared to be clearly associated with reported COVID-19-positive status of the HH. Our study supports previous findings and suggests a very low risk of pet-to-human transmission within HHs, no severe clinical signs in pets and a negligible pet-to-pet transmission between HHs.

Repeated cross-sectional sampling of pigs at slaughter indicates varying age of hepatitis E virus infection within and between pig farms.

Humans can become infected with hepatitis E virus (HEV) by consumption of undercooked pork. To reduce the burden of HEV in humans, mitigation on pig farms is needed. HEV is found on most pig farms globally, yet within-farm seroprevalence estimates vary considerably. Understanding of the underlying variation in infection dynamics within and between farms currently lacks. Therefore, we investigated HEV infection dynamics by sampling 1711 batches of slaughter pigs from 208 Dutch farms over an 8-month period. Four farm types, conventional, organic, and two types with strict focus on biosecurity, were included. Sera were tested individually with an anti-HEV antibody ELISA and pooled per batch with PCR. All farms delivered seropositive pigs to slaughter, yet batches (resembling farm compartments) had varying results. By combining PCR and ELISA results, infection moment and extent per batch could be classified as low transmission, early, intermediate or late. Cluster analysis of batch infection moments per farm resulted in four clusters with distinct infection patterns. Cluster 1 farms delivered almost exclusively PCR negative, ELISA positive batches to slaughter (PCR-ELISA+), indicating relatively early age of HEV infection. Cluster 2 and 3 farms delivered 0.3 and 0.7 of batches with intermediate infection moment (PCR+ELISA+) respectively and only few batches with early infection. Cluster 4 farms delivered low transmission (PCR-ELISA-) and late infection (PCR+ELISA-) batches, demonstrating that those farms can prevent or delay HEV transmission to farm compartments. Farm type partly coincided with cluster assignment, indicating that biosecurity and management are related to age of HEV infection.

Risks related to a possible reduction of the waiting period for dogs after rabies antibody titration to 30 days compared with 90 days of the current EU legislative regime.

EFSA received a mandate from the European Commission to assess the risks related to a possible reduction of the waiting period after rabies antibody titration test to 30 days compared with 90 days of the current EU legislation, for dogs moving from certain non-EU countries to the EU. This Scientific Report assessed the probability of introduction of rabies into the EU through commercial and non-commercial movements of vaccinated dogs with a positive titration test (≥ 0.5 IU/mL) if the waiting period decreases from 90 to 30 days. Assuming that all the legal requirements are complied with, the risk of transmission of rabies through the movement of a vaccinated dog is related to the risk of introducing an animal incubating rabies that was infected before the day of vaccination or shortly after vaccination but before the development of immunity (21 days post-vaccination). Using published data on the incubation period for experimental and field cases in dogs and considering the rabies incidence data in certain countries, the aggregated probability for the annual introduction of rabies through dogs was assessed. Considering the uncertainty related to the duration of the incubation period, the number of imported dogs, and the disease incidence in some countries it was concluded with a 95% certainty that the maximum number of rabies-infected imported dogs complying with the regulations in a 20-year period could increase from 5 to 20 when decreasing the waiting period from 90 to 30 days. Nevertheless, the potential impact of even a small increase in probability means the risk is increased for a region like the EU where rabies has long been a focus for eradication, to protect human and animal health.

Does having a cat in your house increase your risk of catching COVID-19?

Due to the zoonotic origin of SARS-Coronavirus 2 (SARS-CoV-2), the potential for its transmission from humans back to animals and the possibility that it might establish ongoing infection pathways in other animal species has been discussed. Cats are highly susceptible to SARS-CoV-2 and were shown experimentally to transmit the virus to other cats. Infection of cats has been widely reported. Domestic cats in COVID-19-positive households could therefore be a part of a human to animal to human transmission pathway. Here, we report the results of a qualitative risk assessment focusing on the potential of cat to human transmission in such settings. The assessment was based on evidence available by October 2021. After the introduction of SARS-CoV-2 to a household by a human, cats may become infected and infected cats may pose an additional infection risk for other members of the household. In order to assess this additional risk qualitatively, expert opinion was elicited within the framework of a modified Delphi procedure. The conclusion was that the additional risk of infection of an additional person in a household associated with keeping a domestic cat is very low to negligible, depending on the intensity of cat-to-human interactions. The separation of cats from humans suffering from SARS-CoV-2 infection should contribute to preventing further transmission.

Quantitative Risk Assessment for the Introduction of Carbapenem-Resistant Enterobacteriaceae (CPE) into Dutch Livestock Farms.

Early detection of emerging carbapenem-resistant Enterobacteriaceae (CPE) in food-producing animals is essential to control the spread of CPE. We assessed the risk of CPE introduction from imported livestock, livestock feed, companion animals, hospital patients, and returning travelers into livestock farms in The Netherlands, including (1) broiler, (2) broiler breeder, (3) fattening pig, (4) breeding pig, (5) farrow-to-finish pig, and (6) veal calf farms. The expected annual number of introductions was calculated from the number of farms exposed to each CPE source and the probability that at least one animal in an exposed farm is colonized. The total number of farms with CPE colonization was estimated to be the highest for fattening pig farms, whereas the probability of introduction for an individual farm was the highest for broiler farms. Livestock feed and imported livestock are the most likely sources of CPE introduction into Dutch livestock farms. Sensitivity analysis indicated that the number of fattening pig farms determined the number of high introductions in fattening pigs from feed, and that uncertainty on CPE prevalence impacted the absolute risk estimate for all farm types. The results of this study can be used to inform risk-based surveillance for CPE in livestock farms.

Second compartment widens plasmid invasion conditions: Two-compartment pair-formation model of conjugation in the gut.

Understanding under which conditions conjugative plasmids encoding antibiotic resistance can invade bacterial communities in the gut is of particular interest to combat the spread of antibiotic resistance within and between animals and humans. We extended a one-compartment model of conjugation to a two-compartment model, to analyse how differences in plasmid dynamics in the gut lumen and at the gut wall affect the invasion of plasmids. We compared scenarios with one and two compartments, different migration rates between the lumen and wall compartments, and different population dynamics. We focused on the effect of attachment and detachment rates on plasmid dynamics, explicitly describing pair formation followed by plasmid transfer in the pairs. The parameter space allowing plasmid invasion in the one-compartment model is affected by plasmid costs and intrinsic conjugation rates of the transconjugant, but not by these characteristics of the donor. The parameter space allowing plasmid invasion in the two-compartment model is affected by attachment and detachment rates in the lumen and wall compartment, and by the bacterial density at the wall. The one- and two-compartment models predict the same parameter space for plasmid invasion if the conditions in both compartments are equal to the conditions in the one-compartment model. In contrast, the addition of the wall compartment widens the parameter space allowing invasion compared with the one-compartment model, if the density at the wall is higher than in the lumen, or if the attachment rate at the wall is high and the detachment rate at the wall is low. We also compared the pair-formation models with bulk-conjugation models that describe conjugation by instantaneous transfer of the plasmid at contact between cells, without explicitly describing pair formation. Our results show that pair-formation and bulk-conjugation models predict the same parameter space for plasmid invasion. From our simulations, we conclude that conditions at the gut wall should be taken into account to describe plasmid dynamics in the gut and that transconjugant characteristics rather than donor characteristics should be used to parameterize the models.

SARS-CoV-2 infection in cats and dogs in infected mink farms.

Animals like mink, cats and dogs are susceptible to SARS-CoV-2 infection. In the Netherlands, 69 out of 127 mink farms were infected with SARS-CoV-2 between April and November 2020 and all mink on infected farms were culled after SARS-CoV-2 infection to prevent further spread of the virus. On some farms, (feral) cats and dogs were present. This study provides insight into the prevalence of SARS-CoV-2-positive cats and dogs in 10 infected mink farms and their possible role in transmission of the virus. Throat and rectal swabs of 101 cats (12 domestic and 89 feral cats) and 13 dogs of 10 farms were tested for SARS-CoV-2 using PCR. Serological assays were performed on serum samples from 62 adult cats and all 13 dogs. Whole Genome Sequencing was performed on one cat sample. Cat-to-mink transmission parameters were estimated using data from all 10 farms. This study shows evidence of SARS-CoV-2 infection in 12 feral cats and 2 dogs. Eleven cats (18%) and two dogs (15%) tested serologically positive. Three feral cats (3%) and one dog (8%) tested PCR-positive. The sequence generated from the cat throat swab clustered with mink sequences from the same farm. The calculated rate of mink-to-cat transmission showed that cats on average had a chance of 12% (95%CI 10%-18%) of becoming infected by mink, assuming no cat-to-cat transmission. As only feral cats were infected it is most likely that infections in cats were initiated by mink, not by humans. Whether both dogs were infected by mink or humans remains inconclusive. This study presents one of the first reports of interspecies transmission of SARS-CoV-2 that does not involve humans, namely mink-to-cat transmission, which should also be considered as a potential risk for spread of SARS-CoV-2.

Experimental and field investigations of exposure, replication and transmission of SARS-CoV-2 in pigs in the Netherlands.

In order to assess the risk of SARS-CoV-2 infection, transmission and reservoir development in swine, we combined results of an experimental and two observational studies. First, intranasal and intratracheal challenge of eight pigs did not result in infection, based on clinical signs and PCR on swab and lung tissue samples. Two serum samples returned a low positive result in virus neutralization, in line with findings in other infection experiments in pigs. Next, a retrospective observational study was performed in the Netherlands in the spring of 2020. Serum samples (N =417) obtained at slaughter from 17 farms located in a region with a high human case incidence in the first wave of the pandemic. Samples were tested with protein micro array, plaque reduction neutralization test and receptor-binding-domain ELISA. None of the serum samples was positive in all three assays, although six samples from one farm returned a low positive result in PRNT (titers 40-80). Therefore we conclude that serological evidence for large scale transmission was not observed. Finally, an outbreak of respiratory disease in pigs on one farm, coinciding with recent exposure to SARS-CoV-2 infected animal caretakers, was investigated. Tonsil swabs and paired serum samples were tested. No evidence for infection with SARS-CoV-2 was found. In conclusion, Although in both the experimental and the observational study few samples returned low antibody titer results in PRNT infection with SARS-CoV-2 was not confirmed. It was concluded that sporadic infections in the field cannot be excluded, but large-scale SARS-CoV-2 transmission among pigs is unlikely.

Factors associated with antimicrobial use in pig and veal calf farms in the Netherlands: A multi-method longitudinal data analysis.

Minimizing antimicrobial use (AMU) in livestock is needed to control antimicrobial resistance (AMR). In the Netherlands, the livestock sector reduced AMU by almost 70 % since 2009, but this reduction stagnated in recent years. With only therapeutic AMU allowed, it is clear that besides socio-economic and behavioral factors, also the farm technical characteristics influence the conditions under which farmers need AMU. These characteristics pertain to farm management, including biosecurity, vaccination schemes, nutrition, micro-climate and husbandry practices. Identifying farm-related risk factors for AMU is needed to control AMR in a sustainable and pragmatic way. This need, often concerns the overall contribution of seemingly related (rather than individualized) factors. Here, risk factors for AMU in pig and calf farms were determined using two approaches: a typical risk factor analysis based on generalized estimating equations (GEEs) or hierarchical mixed-effects models and a multiblock partial least-squares regression analysis. These methods were applied to longitudinal data from two previous studies, i.e. a panel study and an intervention study involving 36 multiplier pig farms and 51 veal calf farms in the Netherlands, respectively. The multiblock analysis allowed us to quantify the importance of each factor and their respective block (i.e. farm management domain). For pigs, factors related to internal biosecurity had the highest impact on AMU, while for calves, these were mainly related to micro-climate. Structural characteristics, such as farm size and production type, followed in importance for both sectors. While both methods provided similar outcomes, the multiblock approach provided further insights by grouping and comparing factors believed to be inter-related.

Chicken gut microbiome members limit the spread of an antimicrobial resistance plasmid in Escherichia coli.

Plasmid-mediated antimicrobial resistance is a major contributor to the spread of resistance genes within bacterial communities. Successful plasmid spread depends upon a balance between plasmid fitness effects on the host and rates of horizontal transmission. While these key parameters are readily quantified in vitro, the influence of interactions with other microbiome members is largely unknown. Here, we investigated the influence of three genera of lactic acid bacteria (LAB) derived from the chicken gastrointestinal microbiome on the spread of an epidemic narrow-range ESBL resistance plasmid, IncI1 carrying blaCTX-M-1, in mixed cultures of isogenic Escherichia coli strains. Secreted products of LAB decreased E. coli growth rates in a genus-specific manner but did not affect plasmid transfer rates. Importantly, we quantified plasmid transfer rates by controlling for density-dependent mating opportunities. Parametrization of a mathematical model with our in vitro estimates illustrated that small fitness costs of plasmid carriage may tip the balance towards plasmid loss under growth conditions in the gastrointestinal tract. This work shows that microbial interactions can influence plasmid success and provides an experimental-theoretical framework for further study of plasmid transfer in a microbiome context.