Risk factors for avian influenza in Danish poultry and wild birds during the epidemic from June 2020 to May 2021.

Exploring the risk factors of avian influenza (AI) occurrence helps us to monitor and control the disease. Since late 2020, the number of avian influenza outbreaks in domestic and wild birds has increased in most European countries, including Denmark. This study was conducted to identify potential risk factors for wild birds and poultry during the epidemic in 2020/2021 in Denmark. Using Danish AI surveillance data of actively surveyed poultry and passively surveyed wild birds from June 2020 to May 2021, we calculated geographical attributes for bird locations and assessed the potential risk factors of AI detections using logistic regression analyses. 4% of actively surveyed poultry and 39% of passively surveyed wild birds were detected with AI circulating or ongoing at the time. Of these, 10 and 99% tested positive for the H5/H7 AI subtypes, respectively. Our analyses did not find any statistically significant risk factors for actively surveyed poultry within the dataset. For passively surveyed wild birds, bird species belonging to the Anseriformes order had a higher risk of being AI virus positive than five other taxonomic bird orders, and Galliformes were of higher risk than two other taxonomic bird orders. Besides, every 1 km increase in the distance to wetlands was associated with a 5.18% decrease in the risk of being AI positive (OR (odds ratio) 0.95, 95% CI 0.91, 0.99), when all other variables were kept constant. Overall, bird orders and distance to wetlands were associated with the occurrence of AI. The findings may provide targets for surveillance strategies using limited resources and assist in risk-based surveillance during epidemics.

Treatment of clinically severe bovine mastitis - a scoping review.

Mastitis is a major health problem for bovines and can be categorized as non-severe or severe, based on clinical symptoms. A severe case of clinical mastitis is usually defined by the cow being affected systemically. It is important to consider how to handle severe cases because these cases can be fatal and cause high production losses. However, there are generally few detailed treatment guidelines. By conducting a scoping review on the topic, we aimed to synthesize the information that is available on treatment and outcomes, as reported from clinical trials and observational studies. This was facilitated by following the PRISMA-guidelines with a stepwise systematic screening of scientific literature on the subject, retrieved via Pubmed and Web of Science, using pre-defined selection criteria. The results yielded a total of 14 reports of treatment and outcomes in cases of naturally occurring severe clinical mastitis. Cross-trial comparison was difficult due to the different exclusion criteria and outcome definitions. Many studies focused on cases caused by gram-negative bacteria treated with intensive antibiotic protocols, often containing antibiotics that are categorized as critical for human health. Few focused on severe cases caused by gram-positive bacteria or on the relative use of non-antibiotic treatment. In general, only a small number of statistically significant differences were found in trials comparing different treatment protocols, with no obvious trends across trials. Our findings emphasize the need for more research into the treatment efficacy of antibiotic and non-antibiotic options for clinically severe mastitis. Furthermore, consideration of how trial conditions relate to the practical circumstances in a field setting could improve the applicability of reported results. This could help to provide practitioners with the information needed to make evidence-based treatment decisions in cases of clinically severe mastitis.

Are all avian influenza outbreaks in poultry the same? The predicted impact of poultry species and virus subtype.

AIMS: Outbreaks of avian influenza in poultry farms are currently increasing in frequency, with devastating consequences for animal welfare, farmers and supply chains. Some studies have documented the direct spread of the avian influenza virus between farms. Prevention of spread between farms relies on biosecurity surveillance and control measures. However, the evolution of an outbreak on a farm might vary depending on the virus strain and poultry species involved; this would have important implications for surveillance systems, epidemiological investigations and control measures. METHODS AND RESULTS: In this study, we utilized existing parameter estimates from the literature to evaluate the predicted course of an epidemic in a standard poultry flock with 10,000 birds. We used a stochastic SEIR simulation model to simulate outbreaks in different species and with different virus subtypes. The simulations predicted large differences in the duration and severity of outbreaks, depending on the virus subtypes. For both turkeys and chickens, outbreaks with HPAI were of shorter duration than outbreaks with LPAI. In outbreaks involving the infection of chickens with different virus subtypes, the shortest epidemic involved H7N7 and HPAIV H5N1 (median duration of 9 and 17 days, respectively) and the longest involved H5N2 (median duration of 68 days). The most severe outbreaks (number of chickens infected) were predicted for H5N1, H7N1 and H7N3 virus subtypes, and the least severe for H5N2 and H7N7, in which outbreaks for the latter subtype were predicted to develop most slowly. CONCLUSIONS: These simulation results suggest that surveillance of certain subtypes of avian influenza virus, in chicken flocks in particular, needs to be sensitive and timely if infection is to be detected with sufficient time to implement control measures. The variability in the predictions highlights that avian influenza outbreaks are different in severity, speed and duration, so surveillance and disease response need to be nuanced and fit the specific context of poultry species and virus subtypes.

Using registry data to identify individual dairy cows with abnormal patterns in routinely recorded somatic cell counts.

Data from the Danish milk recording system routinely enter the Danish Cattle Database, including somatic cell counts (SCC) for individual animals. Elevated SCC can signal intramammary inflammation, suggesting subclinical mastitis. Detecting mastitis is pivotal to limit severity, prevent pathogen spread, and target treatment or culling. This study aimed to differentiate normal and abnormal SCC patterns using recorded registry data. We used registry data from 2010 to 2020 for dairy cows in herds with 11 annual milk recordings. To create consistency across herds, we used data from 13,996 unique animals and eight different herds, selected based on the amount of data available, only selecting Holstein animals and conventional herds. We fitted log10-transformed SCC to days in milk (DIM) using the Wilmink and Wood's curve functions, originally developed for milk yield over the lactation. We used Nonlinear Least Square and Nonlinear Mixed Effect models to fit the log10-transformed SCC observations to DIM at animal level. Using mean squared residuals (MSR), we found a consistently better fit using a Wood's style function. Detection of MSR outliers in the model fitting process was used to identify animals with log10(SCC) curves deviating from the expected "normal" curve for that same animal. With this study, we propose a method to identify single animals with SCC patterns that indicate abnormalities, such as mastitis, based on registry data. This method could potentially lead to a registry data-based detection of mastitis cases in larger dairy herds.

Using surveillance data for early warning modelling of highly pathogenic avian influenza in Europe reveals a seasonal shift in transmission, 2016-2022.

Avian influenza in wild birds and poultry flocks constitutes a problem for animal welfare, food security and public health. In recent years there have been increasing numbers of outbreaks in Europe, with many poultry flocks culled after being infected with highly pathogenic avian influenza (HPAI). Continuous monitoring is crucial to enable timely implementation of control to prevent HPAI spread from wild birds to poultry and between poultry flocks within a country. We here utilize readily available public surveillance data and time-series models to predict HPAI detections within European countries and show a seasonal shift that happened during 2021-2022. The output is models capable of monitoring the weekly risk of HPAI outbreaks, to support decision making.

Use of Danish National Somatic Cell Count Data to Assess the Need for Dry-Off Treatment in Holstein Dairy Cattle.

In Denmark, PCR testing of dairy cattle is commonly used to select animals for the antibacterial treatment of intramammary infection (IMI) during the dry-off period. IMI is associated with a high somatic cell count (SCC), routinely recorded for milk quality control for most commercial dairy herds. This study aimed to compare SCC curves over the lactation among dairy cows with positive vs. negative PCR test results for four major IMI pathogens. Data from 133,877 PCR-tested Holstein cows from 1364 Danish conventional dairy herds were used to fit a nonlinear mixed-effects model using a modified four-parameter Wilmink function. We stratified the data into first, second, third or fourth and later parity and fitted Wilmink curves to all SCC observations between 6 and 305 days in milk. The PCR tests were taken before dry-off at the end of the lactation to investigate which animals qualified for selective dry cow therapy. A PCR Ct-value of 37 and below was used to determine if an animal was PCR positive for any of the following IMI pathogens: Staphylococcus aureus, Streptococcus agalactiae, Str. dysgalactiae and Str. uberis. Our findings showed that mean SCC curve fits were higher for PCR-positive animals in all four parity groups and across lactations. The use of SCC data fitted to the entire lactation for multiple lactations enabled quantification of overall differences in SCC curves between cattle with and without detected IMI, adjusted for parity group and stage of lactation. These findings are relevant to the use of SCC to support treatment decisions.

Lactational treatment of bovine mastitis-Development over time and factors influencing cytological cure.

Lactational treatment of bovine mastitis is a major contributor to antibiotic consumption in dairy cattle and is, therefore, important to address in light of the increasing problem of antibiotic resistance. In this large-scale database-based retrospective observational study, we combined electronic health records and routinely measured somatic cell counts from individual cows to create an overview of lactational mastitis treatment in Danish dairy herds from 2010 to 2019. Furthermore, posttreatment somatic cell count was used to approximate treatment success in terms of cytological cure. A generalized logistic regression with mixed effects was performed to combine knowledge on cow-level factors (treatment-, pathogen-, and cow-related) with the new infection risk at the herd level, and to explore the relative effect on cytological cure. The investigation revealed that the total number of lactational treatments appears to have decreased steadily over the study period, whereas treatment duration increased slightly. The proportion of cases treated with penicillin-based protocols and the proportion of milk samples sent for pathogen analysis also decreased. Meanwhile, results from the statistical analysis confirm the importance of cow-related factors, such as parity and lactation stage, for the probability of cytological cure following lactational treatment of mastitis. However, they also disclose that factors that are easier to adjust, such as optimizing treatment duration, including knowledge on causative pathogens and improving the herd-level new infection risk that can be used to positively influence the outcome. Application of this knowledge could potentially assist in promoting a more prudent use of antibiotics for dairy cattle in the future.

Treatment of mild to moderate clinical bovine mastitis caused by gram-positive bacteria: A noninferiority randomized trial of local penicillin treatment alone or combined with systemic treatment.

Bovine mastitis is one of the most important diseases in modern dairy farming, as it leads to reduced welfare and milk production and increased need for antibiotic use. Clinical mastitis in Denmark is most often treated with a combination of local and systemic treatment with penicillin. The objective of this randomized clinical trial was to assess whether worse results could be expected with local intramammary treatment with penicillin compared with a combination of local and systemic treatment with penicillin in terms of the bacteriological cure of mild and moderate clinical mastitis cases caused by gram-positive bacteria. We carried out a noninferiority trial with a noninferiority margin set to a relative reduction in bacteriological cure of 15% between these 2 treatment groups to assess the effect of reducing the total antibiotic use by a factor of 16 for each treated case. Clinical mastitis cases from 12 Danish dairy farms were considered for enrollment. On-farm selection of gram-positive cases was carried out by the farm personnel within the first 24 h after a clinical mastitis case was detected. A single farm used bacterial culture results from the on-farm veterinarian, whereas the other 11 farms were provided with an on-farm test to distinguish gram-positive bacteria from gram-negative or samples without bacterial growth. Cases with suspected gram-positive bacteria were allocated to a treatment group: either local or combination. Bacteriological cure was assessed based on the bacterial species identified in the milk sample from the clinical mastitis case and 2 follow-up samples collected approximately 2 and 3 wk after ended treatment. Identification of bacteria was carried out using MALDI-TOF on bacterial culture growth. Noninferiority was assessed using unadjusted cure rates and adjusted cure rates from a multivariable mixed logistic regression model. Of the 1,972 clinical mastitis cases registered, 345 (18%) met all criteria for inclusion (full data). The data set was further reduced to 265 cases for the multivariable analysis to include only complete registrations. Streptococcus uberis was the most commonly isolated pathogen. Noninferiority was demonstrated for both unadjusted and adjusted cure rates. The unadjusted cure rates were 76.8% and 83.1% for the local and combined treatments, respectively (full data). The pathogen and somatic cell count before the clinical case had an effect on the efficacy of treatment; thus efficient treatment protocols should be herd- and case-specific. The effect of pathogen and somatic cell count on treatment efficacy was similar irrespective of the treatment protocol. We conclude that bacteriological cure of local penicillin treatment for mild and moderate clinical mastitis cases was noninferior to the combination of local and systemic treatment using a 15% noninferiority margin. This suggests that a potential 16-fold reduction in antimicrobial use per mastitis treatment can be achieved with no adverse effect on cure rate.

Reservoirs of Staphylococcus spp. and Streptococcus spp. Associated with Intramammary Infections of Dairy Cows.

To design cost-effective prevention strategies against mastitis in dairy cow farms, knowledge about infection pathways of causative pathogens is necessary. Therefore, we investigated the reservoirs of bacterial strains causing intramammary infections in one dairy cow herd. Quarter foremilk samples (n = 8056) and milking- and housing-related samples (n = 251; from drinking troughs, bedding material, walking areas, cow brushes, fly traps, milking liners, and milker gloves), were collected and examined using culture-based methods. Species were identified with MALDI-TOF MS, and selected Staphylococcus and Streptococcus spp. typed with randomly amplified polymorphic DNA-PCR. Staphylococci were isolated from all and streptococci from most investigated locations. However, only for Staphylococcus aureus, matching strain types (n = 2) were isolated from milk and milking-related samples (milking liners and milker gloves). Staphylococcus epidermidis and Staphylococcus haemolyticus showed a large genetic diversity without any matches of strain types from milk and other samples. Streptococcus uberis was the only Streptococcus spp. isolated from milk and milking- or housing-related samples. However, no matching strains were found. This study underlines the importance of measures preventing the spread of Staphylococcus aureus between quarters during milking.

Remote Nanoscopy with Infrared Elastic Hyperspectral Lidar.

Monitoring insects of different species to understand the factors affecting their diversity and decline is a major challenge. Laser remote sensing and spectroscopy offer promising novel solutions to this. Coherent scattering from thin wing membranes also known as wing interference patterns (WIPs) have recently been demonstrated to be species specific. The colors of WIPs arise due to unique fringy spectra, which can be retrieved over long distances. To demonstrate this, a new concept of infrared (950-1650 nm) hyperspectral lidar with 64 spectral bands based on a supercontinuum light source using ray-tracing and 3D printing is developed. A lidar with an unprecedented number of spectral channels, high signal-to-noise ratio, and spatio-temporal resolution enabling detection of free-flying insects and their wingbeats. As proof of principle, coherent scatter from a damselfly wing at 87 m distance without averaging (4 ms recording) is retrieved. The fringed signal properties are used to determine an effective wing membrane thickness of 1412 nm with ±4 nm precision matching laboratory recordings of the same wing. Similar signals from free flying insects (2 ms recording) are later recorded. The accuracy and the method's potential are discussed to discriminate species by capturing coherent features from free-flying insects.

Corrigendum: A practical introduction to mechanistic modeling of disease transmission in veterinary science.

[This corrects the article DOI: 10.3389/fvets.2020.546651.].

Reservoirs of Corynebacterium spp. in the Environment of Dairy Cows.

Although Corynebacterium spp. can be regularly associated with subclinical and clinical mastitis cases in dairy cows, knowledge on their reservoirs in dairy farms is sparse. Therefore, samples were collected at 10 visits with 14 day intervals from bedding material (n = 50), drinking troughs (n = 20), different walking areas (n = 60), cow brushes (n = 8), fly traps (n = 4), the passage to pasture (n = 9) as well as milking liners (n = 80) and milker gloves (n = 20) in one dairy cow farm. Additionally, quarter foremilk samples from all lactating cows (approximately 200) were collected at each visit. All samples underwent microbiological examination and cultured isolates were identified using MALDI-TOF MS. Most Corynebacterium spp. that were cultivated from milk were also isolated from the housing environment and milking-related niches (C. amycolatum, C. confusum, C. stationis, C. variabile, C. xerosis) or from milking-related niches only (C. frankenforstense, C. pilosum, C. suicordis). C. bovis was not cultivated from any environmental niche, while being the dominant species in milk samples. This study demonstrates that many Corynebacterium spp. present in milk samples can also be isolated from the cows' environment. For C. bovis, the most relevant Corynebacterium species with regard to intramammary infections, it indicates that environmental reservoirs are of little relevance.

Household transmission of the SARS-CoV-2 Omicron variant in Denmark.

In late 2021, the Omicron SARS-CoV-2 variant overtook the previously dominant Delta variant, but the extent to which this transition was driven by immune evasion or a change in the inherent transmissibility is currently unclear. We estimate SARS-CoV-2 transmission within Danish households during December 2021. Among 26,675 households (8,568 with the Omicron VOC), we identified 14,140 secondary infections within a 1-7-day follow-up period. The secondary attack rate was 29% and 21% in households infected with Omicron and Delta, respectively. For Omicron, the odds of infection were 1.10 (95%-CI: 1.00-1.21) times higher for unvaccinated, 2.38 (95%-CI: 2.23-2.54) times higher for fully vaccinated and 3.20 (95%-CI: 2.67-3.83) times higher for booster-vaccinated contacts compared to Delta. We conclude that the transition from Delta to Omicron VOC was primarily driven by immune evasiveness and to a lesser extent an inherent increase in the basic transmissibility of the Omicron variant.

Household transmission of SARS-CoV-2 Omicron variant of concern subvariants BA.1 and BA.2 in Denmark.

SARS coronavirus 2 (SARS-CoV-2) continues to evolve and new variants emerge. Using nationwide Danish data, we estimate the transmission dynamics of SARS-CoV-2 Omicron subvariants BA.1 and BA.2 within households. Among 22,678 primary cases, we identified 17,319 secondary infections among 50,588 household contacts during a 1-7 day follow-up. The secondary attack rate (SAR) was 29% and 39% in households infected with Omicron BA.1 and BA.2, respectively. BA.2 was associated with increased susceptibility of infection for unvaccinated household contacts (Odds Ratio (OR) 1.99; 95%-CI 1.72-2.31), fully vaccinated contacts (OR 2.26; 95%-CI 1.95-2.62) and booster-vaccinated contacts (OR 2.65; 95%-CI 2.29-3.08), compared to BA.1. We also found increased infectiousness from unvaccinated primary cases infected with BA.2 compared to BA.1 (OR 2.47; 95%-CI 2.15-2.84), but not for fully vaccinated (OR 0.66; 95%-CI 0.57-0.78) or booster-vaccinated primary cases (OR 0.69; 95%-CI 0.59-0.82). Omicron BA.2 is inherently more transmissible than BA.1. Its immune-evasive properties also reduce the protective effect of vaccination against infection, but do not increase infectiousness of breakthrough infections from vaccinated individuals.

One size does not fit all: Exploring the economic and non-economic outcomes of on-farm biosecurity for bovine viral diarrhoea virus in Australian beef production.

Bovine viral diarrhoea virus (BVDV) is a disease of global importance, affecting the production and welfare of cattle enterprises through poor reproductive performance and calf mortality. In Australia, the prevention of BVDV introduction and spread is primarily achieved with on-farm biosecurity; however, the use of these practices can vary amongst producers. Economic utility is commonly identified as a contributor to the uptake of on-farm biosecurity, but other factors such as animal welfare, producer priorities and introduction risk also influence farmer behaviour. This study uses an individual-based, stochastic simulation model to examine the economic and non-economic value of 23 on-farm biosecurity combinations for the control of BVDV in Australian beef farms without (N0) and with (N1) a neighbouring population of persistently infected (PI) cattle. Combinations of quarantine of purchased bulls (Q), hygiene during herd health events (H), double-fencing adjacent boundaries with neighbouring farms (F) and vaccination against BVDV (V) were tested. This study is the first to simulate the use of strategic PI exposure (PI) as an alternative to V, a contentious practice performed by some Australian beef farmers. Introduction of BVDV into a naïve 300-breeder self-replacing beef herd was achieved through the purchase of PI bulls (N0 and N1 herds) and over-the-fence contact with neighbouring PI animals (N1 herds only). The predicted median cumulative loss due to BVDV over a 15-year period was AUD$172/breeder and AUD$453/breeder for an N0 and N1 herd, respectively. Early establishment of BVDV in the simulation period was found to be the primary factor contributing to economic loss. Consequently, the Q and QF combinations resulted in the highest predicted average annual cost-benefit for BVDV-free N0 and N1 herds. In the five years following establishment of BVDV, use of QP (N0 herds) and V (N1 herds) combinations were most cost-effective. Combinations that involved V and P (in conjunction with F in N1 herds) also resulted in the lowest number of PI animals sold to other farms or feedlots over the simulation period. However, in both N0 and N1 herds, P resulted in the highest number of infected cattle, which has implications for poor animal welfare and increased antimicrobial use on Australian beef farms. The outcomes reported in this study can guide decisions to prevent BVDV introduction and spread on extensive beef farms using on-farm biosecurity, based on the risk of BVDV exposure and the priorities of the individual farmer.

A review of estimated transmission parameters for the spread of avian influenza viruses.

Avian influenza poses an increasing problem in Europe and around the world. Simulation models are a useful tool to predict the spatiotemporal risk of avian influenza spread and evaluate appropriate control actions. To develop realistic simulation models, valid transmission parameters are critical. Here, we reviewed published estimates of the basic reproduction number (R0 ), the latent period and the infectious period by virus type, pathogenicity, species, study type and poultry flock unit. We found a large variation in the parameter estimates, with highest R0 estimates for H5N1 and H7N3 compared with other types; for low pathogenic avian influenza compared with high pathogenic avian influenza types; for ducks compared with other species; for estimates from field studies compared with experimental studies; and for within-flock estimates compared with between-flock estimates. Simulation models should reflect this observed variation so as to produce more reliable outputs and support decision-making. How to incorporate this information into simulation models remains a challenge.

Weak population genetic structure in Eurasian spruce bark beetle over large regional scales in Sweden.

The Eurasian spruce bark beetle, Ips typographus, is a major pest, capable of killing spruce forests during large population outbreaks. Recorded dispersal distances of individual beetles are typically within hundreds of meters or a few kilometers. However, the connectivity between populations at larger distances and longer time spans and how this is affected by the habitat is less studied, despite its importance for understanding at which distances local outbreaks may spread. Previous population genetic studies in I. typographus typically used low resolution markers. Here, we use genome-wide data to assess population structure and connectivity of I. typographus in Sweden. We used 152 individuals from 19 population samples, distributed over 830 km from Strömsund (63° 46' 8″ N) in the north to Nyteboda (56° 8' 50″ N) in the south, to capture processes at a large regional scale, and a transect sampling design adjacent to a recent outbreak to capture processes at a smaller scale (76 km). Using restriction site-associated DNA sequencing (RADseq) markers capturing 1409-1997 SNPs throughout the genome, we document a weak genetic structure over the large scale, potentially indicative of high connectivity with extensive gene flow. No differentiation was detected at the smaller scale. We find indications of isolation-by-distance both for relative (F ST) and absolute divergence (Dxy). The two northernmost populations are most differentiated from the remaining populations, and diverge in parallel to the southern populations for a set of outlier loci. In conclusion, the population structure of I. typographus in Sweden is weak, suggesting a high capacity to disperse and establish outbreak populations in new territories.

Effect of vaccination on household transmission of SARS-CoV-2 Delta variant of concern.

Effective vaccines protect individuals by not only reducing the susceptibility to infection, but also reducing the infectiousness of breakthrough infections in vaccinated cases. To disentangle the vaccine effectiveness against susceptibility to infection (VES) and vaccine effectiveness against infectiousness (VEI), we took advantage of Danish national data comprising 24,693 households with a primary case of SARS-CoV-2 infection (Delta Variant of Concern, 2021) including 53,584 household contacts. In this setting, we estimated VES as 61% (95%-CI: 59-63), when the primary case was unvaccinated, and VEI as 31% (95%-CI: 26-36), when the household contact was unvaccinated. Furthermore, unvaccinated secondary cases with an infection exhibited a three-fold higher viral load compared to fully vaccinated secondary cases with a breakthrough infection. Our results demonstrate that vaccinations reduce susceptibility to infection as well as infectiousness, which should be considered by policy makers when seeking to understand the public health impact of vaccination against transmission of SARS-CoV-2.

Evaluation of diagnostic test procedures for SARS-CoV-2 using latent class models.

Polymerase chain reaction (PCR) and antigen tests have been used extensively for screening during the severe acute respiratory syndrome coronavirus 2 pandemics. However, the real-world sensitivity and specificity of the two testing procedures in the field have not yet been estimated without assuming that the PCR constitutes a gold standard test. We use latent class models to estimate the in situ performance of both tests using data from the Danish national registries. We find that the specificity of both tests is very high (>99.7%), while the sensitivities are 95.7% (95% confidence interval [CI]: 92.8%-98.4%) and 53.8% (95% CI: 49.8%-57.9%) for the PCR and antigen tests, respectively. These findings have implications for the use of confirmatory PCR tests following a positive antigen test result: we estimate that serial testing is counterproductive at higher prevalence levels.