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.

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.

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.

Nationwide study on SARS-CoV-2 transmission within households from lockdown to reopening, Denmark, 27 February 2020 to 1 August 2020.

BackgroundThe COVID-19 pandemic is one of the most serious global public health threats of recent times. Understanding SARS-CoV-2 transmission is key for outbreak response and to take action against the spread of disease. Transmission within the household is a concern, especially because infection control is difficult to apply within this setting.AimThe objective of this observational study was to investigate SARS-CoV-2 transmission in Danish households during the early stages of the COVID-19 pandemic.MethodsWe used comprehensive administrative register data from Denmark, comprising the full population and all COVID-19 tests from 27 February 2020 to 1 August 2020, to estimate household transmission risk and attack rate.ResultsWe found that the day after receiving a positive test result within the household, 35% (788/2,226) of potential secondary cases were tested and 13% (98/779) of these were positive. In 6,782 households, we found that 82% (1,827/2,226) of potential secondary cases were tested within 14 days and 17% (371/2,226) tested positive as secondary cases, implying an attack rate of 17%. We found an approximate linear increasing relationship between age and attack rate. We investigated the transmission risk from primary cases by age, and found an increasing risk with age of primary cases for adults (aged ≥ 15 years), while the risk seems to decrease with age for children (aged < 15 years).ConclusionsAlthough there is an increasing attack rate and transmission risk of SARS-CoV-2 with age, children are also able to transmit SARS-CoV-2 within the household.

Dynamics of somatic cell count (SCC) and differential SCC during and following intramammary infections.

Somatic cell count is frequently used as an indicator of intramammary infections (IMI) in dairy cattle worldwide. The newly introduced differential SCC (DSCC) can potentially contribute to detection of IMI. The purpose of this study was to investigate the dynamics of SCC and DSCC after IMI. We used a data set with monthly samples from 2 Danish dairy herds through 1 yr, using bacterial culture to identify IMI. The dynamics of SCC and DSCC with regard to IMI were assessed at quarter level following new IMI with each of 3 defined pathogen groups, major, minor, or "other" pathogens, using general additive models. Both SCC and DSCC increased after IMI, with a more pronounced increase if major or other pathogens were detected compared with minor pathogens. We found that DSCC increased after IMI with other pathogens in both herds and, in herd 2, after IMI caused by major and minor pathogens. We also estimated the duration of increased SCC and DSCC when they exceeded a threshold, done separately for each pathogen group. Major pathogens had the longest-lasting effect in both herds for both SCC and DSCC. We conclude that the magnitude and duration of response of SCC and DSCC to IMI differs between herds and causative pathogens.

A cohort study of the effect of Streptococcus agalactiae on milk yield and somatic cell count in Norwegian dairy cows.

The primary objective of the present study was to estimate the effect of Streptococcus agalactiae intramammary infection on milk production and somatic cell count (SCC) in Norwegian dairy cows. A secondary objective was to assess differences in the effect of common Strep. agalactiae sequence types (ST) found in Norwegian dairy herds. We performed a cohort study combining registry data with sequence-type data from Strep. agalactiae isolates. Herds in which Strep. agalactiae had been detected in individual animals (bacteriological culture or quantitative PCR) between 2012 and 2015 were included. We accessed monthly test-day milk yield records for the entire period to compare milk yield and SCC between cows that were Strep. agalactiae positive and all other cows, within each herd. The study sample consisted of 150 herds, 15,757 cows, 30,850 lactations, and 204,126 test days. We evaluated the effects of Strep. agalactiae on test-day milk yield and SCC using mixed linear regression models, controlling for clustering by herd, cow, and lactation. Multilocus sequence typing of Strep. agalactiae was available for isolates from 86 herds. Additional models were fit to a subset of herds (n = 59) in which ST1, ST23, ST103, and ST196 had been found, to compare the effects of ST on milk production and SCC. In the period 3 to 2 mo before diagnosis, Strep. agalactiae-positive cows produced an average of 1.3 kg more DIM-adjusted milk/d than their negative herd mates. At the time of diagnosis, production was on average 0.13 kg less DIM-adjusted milk/d in Strep. agalactiae-positive cows than in negative cows; 2 to 3 mo after diagnosis, they produced 1.24 kg less DIM-adjusted milk/d than negative cows. Losses persisted for the rest of the investigated period. Cows with ST23, ST103, and ST196 followed a similar pattern as the overall analysis with respect to milk production, whereas ST1-affected cows produced similar amounts of milk before diagnosis as the negative cows. Cows with ST1 experienced the largest milk loss 1 to 2 mo after diagnosis but then recovered to some extent; for cows with ST103, the severe milk loss persisted for the rest of the investigation period. The cow-associated ST103 elicited a lower response in peak SCC compared with ST23, ST103, and ST196. The results indicate an effect of Strep. agalactiae on milk production and SCC. Production was lowest 2 to 3 mo after a positive sample. Peak SCC was reached the month before diagnosis, with notable differences between sequence types.

Economic and epidemiological impact of different intervention strategies for clinical contagious mastitis.

The overall aim of this study was to compare different intervention strategies for clinical intramammary infections (IMI). We conducted a simulation study to represent a Danish dairy cattle herd with IMI caused mostly by Staphylococcus aureus and 9 different intervention strategies for clinical IMI. A standard intervention of 3 d of treatment consisting of intramammary injections for all clinical cases was used. Two of the strategies reflected the use of more antibiotics and 6 strategies reflected cow-specific treatment or culling decisions. For these strategies, we assessed the cost and effectiveness of culling as an IMI intervention. Our results showed that nearly all strategies could reduce the number of IMI cases [e.g., a median of 37 clinical cases with the extended intramammary treatment over 5 d strategy (Basic5) and 30 clinical cases with the cow culled with recovery probability below 50% (Before50)] compared with the standard intervention (median of 42 clinical cases). This happened alongside either increased antibiotic usage (e.g., from a median of 123 treatment days up to 179 treatment days with strategy Basic5) or an increased number of cows culled in relation to IMI (e.g., from a median of 16 up to 24 cows with strategy Before50). Strategies with more antibiotics or reactive culling had a slightly higher net income (e.g., €190,014 median net income with strategy Basic5 or €196,995 with strategy Before50 compared with €187,666 with the standard strategy). This shows that a cow-specific clinical intervention approach can be cost-effective in reducing IMI incidence.

A strain-, cow-, and herd-specific bio-economic simulation model of intramammary infections in dairy cattle herds.

Intramammary infections (IMI) in dairy cattle lead to economic losses for farmers, both through reduced milk production and disease control measures. We present the first strain-, cow- and herd-specific bio-economic simulation model of intramammary infections in a dairy cattle herd. The model can be used to investigate the cost-effectiveness of different prevention and control strategies against IMI. The objective of this study was to describe a transmission framework, which simulates spread of IMI causing pathogens through different transmission modes. These include the traditional contagious and environmental spread and a new opportunistic transmission mode. In addition, the within-herd transmission dynamics of IMI causing pathogens were studied. Sensitivity analysis was conducted to investigate the influence of input parameters on model predictions. The results show that the model is able to represent various within-herd levels of IMI prevalence, depending on the simulated pathogens and their parameter settings. The parameters can be adjusted to include different combinations of IMI causing pathogens at different prevalence levels, representing herd-specific situations. The model is most sensitive to varying the transmission rate parameters and the strain-specific recovery rates from IMI. It can be used for investigating both short term operational and long term strategic decisions for the prevention and control of IMI in dairy cattle herds.

Determinants of antimicrobial treatment for udder health in Danish dairy cattle herds.

Societal pressure to limit the use of antibiotics in livestock production systems, including dairy cattle systems, is consistently increasing. To motivate farmers to reduce antibiotic usage, it is important to understand the factors that determine whether a cow will be treated with antibiotics or not. If farmers' usual practices regarding antibiotic treatments are taken into account, they may be motivated to adopt control measures that can facilitate prudent use of antibiotics and are at the same time cost-effective. In this study, we analyzed database recordings of milk yield and somatic cell count from the routine milk recording scheme, clinical registrations of mastitis and PCR results, and cow factors such as days in milk and parity in relation to antibiotic treatments for 518 dairy herds in Denmark. Farm-wise logistic regressions were used to predict antimicrobial treatment based on these factors. The resulting regression coefficients of 422 herds were further analyzed by principal component analysis and clustering to determine the driving predictors for treatment in different groups of farms. The results showed that determinants that were most important for predicting antibiotic treatments vary from one farm to another. Health indicators such as PCR or somatic cell count were most indicative for treatment on some farms, whereas other groups seemed to depend more on production factors (milk yield) or later culling of the cows. This shows that farmers behave differently and differences can be identified in register data. This information can be considered when developing cost-effective herd-specific control measures of mastitis to promote prudent use of antibiotics in Danish dairy cattle farms.

Epidemiological and economic consequences of purchasing livestock infected with Mycobacterium avium subsp. paratuberculosis.

BACKGROUND: Paratuberculosis (PTB) is a chronic disease which may lead to reduced milk yield, lower animal welfare and death in cattle. The causative agent is Mycobacterium avium subsp. paratuberculosis (MAP). The economic consequences are particularly important incentives in the control and eradication of the infection. One strategy to control PTB in a herd is to purchase animals from farms with a low risk of MAP infection. We wanted to investigate the epidemiological and economic consequences of buying livestock from different supplier farms of low, medium or high risk, as well as farms with unknown status. We also wanted to estimate the probability of spontaneous fadeout if the farmer of an initially MAP-free herd bought a specified number of infected animals in a single year, or continually bought infected animals. This was achieved through simulation modeling, and the effects of consistently introducing one, five or ten infected animals annually into an initially infection-free herd was also modeled. RESULTS: Our findings show that once infected, a farm can relatively safely purchase animals from other low and medium-risk farms without experiencing an increase in the prevalence, highlighting the importance of certification programmes. Furthermore, farms free of MAP are highly susceptible and cannot purchase more than a small number of animals per year without having a high risk of being infected. The probability of spontaneous fadeout after 10 years was 82% when introducing a single infected animal into an initially MAP-free herd. When purchasing ten infected animals, this probability was 46%. The continual purchase of infected animals resulted in very low probabilities of spontaneous fadeout. CONCLUSIONS: We demonstrated that MAP-free farms can purchase a small number of animals, preferably from certified farms, each year and still remain free of MAP. Already infected farms have little risk of increasing the prevalence on a farm when purchasing animals from other farms.

Mean effective sensitivity for Mycobacterium avium subsp. paratuberculosis infection in cattle herds.

BACKGROUND: Mycobacterium avium subsp. paratuberculosis (MAP) infections in cattle are generally challenging to detect and cost-effective test strategies are consequently difficult to identify. MAP-specific antibody ELISAs for milk and serum are relatively inexpensive, but their utility is influenced by a number of factors such as herd size, herd composition and diagnostic sensitivity. The sensitivity of the test increases with the age of the tested animal, and therefore the general, or "mean effective sensitivity" (defined as the mean of the sensitivities for all animals within a population, MES), for detecting MAP within a herd is dependent upon the age distribution of the herd. For this study we used a dataset of cattle from 4,259 dairy herds and 4,078 non-dairy herds. The aim was to investigate the MES for groups of cattle considered to be reasonable entities for MAP surveillance and control, in order to assist the decision-makers in planning and optimizing these programs economically. We compared six different groups of cattle (three dairy and three non-dairy) in Denmark by calculating the MES for each herd in each group. RESULTS: The distribution of MES showed a large variation within and between groups, and in some groups we found a bimodal distribution of MES. Dairy herds generally showed higher MES than non-dairy herds. Dairy herds in a control programme for paratuberculosis showed a MES similar to all other dairy herds from which animals > 2.0 years were tested (both groups had a median MES = 0.60). For the non-dairy groups, the sensitivity became much higher when animals < 2.0 years and herds with less than 25 cattle were excluded, resulting in a median MES of 0.65. CONCLUSION: The results showed that MES could indicate the effectivity of testing different cattle groups for MAP, given that the data used are unbiased.

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.

Digital twin simulation modelling shows that mass testing and local lockdowns effectively controlled COVID-19 in Denmark.

BACKGROUND: Following the COVID-19 pandemic, it is important to evaluate different mitigation strategies for future preparedness. Mass testing and local lockdowns were employed during the Alpha wave in Denmark, which led to ten times more tests than the typical European member state and incidence-based restrictions at the parish level. This study aims to quantify the effects of these interventions in terms of hospital admissions and societal freedom. METHODS: This study assesses the effectiveness of these strategies via counterfactual scenarios using a detailed, individual-based simulation model that replicates the entire Danish population. The model considers multiple factors, including evolving societal restrictions, vaccination roll-out, seasonal influences, and varying intensities of PCR and antigen testing across different age groups and degree of completed vaccination. It also integrates adaptive human behavior in response to changes in incidences at the municipality and parish levels. RESULTS: The simulations show, that without mass testing in Denmark, there would have been a 150% increase in hospital admissions, and additional local lockdowns equivalent to 21 days of strict national lockdown. Without the policy of local lockdowns, hospitalizations would have increased by 50%. CONCLUSIONS: In conclusion, the combination of mass testing and local lockdowns likely prevented a large increase in hospitalizations while increasing overall societal freedom during the Alpha wave in Denmark. In future epidemics, mass testing and local lockdowns can likely prevent overwhelming healthcare systems in phases of high transmission and hospitalization risks.

This study looked at how Denmark handled the COVID-19 pandemic, specifically focusing on mass testing and local lockdowns during the Alpha-wave. Compared to other European countries, Denmark conducted ten times more tests and implemented restrictions at the parish level based on local incidence. Using a detailed simulation model, the researchers explored what would have happened without these measures. Without mass testing, hospital admissions would have increased by 150%, and without local lockdowns, they would have gone up by 50%. Furthermore, mass testing prevented 21 days of strict national lockdown. In essence, mass testing and local lockdowns in Denmark prevented a substantial rise in hospitalizations while allowing more overall societal freedom. This highlights the importance of these strategies for future pandemic preparedness.

A registry-based comparative analysis of antibiotic usage reporting for adult cattle on Danish dairy farms.

BACKGROUND: Antimicrobial resistance (AMR) is a significant global health concern, necessitating the monitoring of antimicrobial usage (AMU). However, there is a lack of consensus on the standardized collection and reporting of AMU data in the veterinary field. In Denmark, the Danish Cattle Database (DCDB) contains treatment information on animal level, which allows counting of number of treatments carried out, used daily doses (UDD). The Danish VetStat database (VetStat) contains information on veterinary medicinal prescriptions at farm level and uses fixed standard doses of each product to calculate number of daily treatments, animal daily doses (ADD). This study aimed to compare two different numerators, UDD and ADD, used to describe AMU on Danish cattle farms, and estimate their correlation. RESULTS: Routinely collected registry data from conventional dairy farms in Denmark for 2019 were used, including a total of 2,197 conventional dairy farms. The data from VetStat and the DCDB were aggregated and analysed, and treatment frequencies (TF) were calculated for both UDD and ADD, adjusting for farm size. Spearman correlation analysis and Bland-Altman plots were employed to assess the relationship and agreement between TF for ADD and UDD, respectively. The results showed a high correlation between TF for ADD and UDD for most prescription groups, i.e., groups used to categorise antibiotics based on target organs. An exception is found for the Udder prescription group, where a systematic underreporting of UDD compared to ADD was observed. This discrepancy may be due to combination treatments, and potential missing or grouped registrations in the DCDB. CONCLUSIONS: Our UDD and ADD comparison yields valuable insights on farm-level AMU. We observe strong correlations between UDD and ADD, except for udder treatments, where some farms report only 1/3 UDD compared to ADD, indicating potential underreporting. Further investigations are needed to understand the factors contributing to these patterns and to ensure the accuracy and completeness of recorded information. Standardizing AMU data collection and reporting remains crucial to tackle the global challenge of AMR effectively.

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.

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.

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.

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 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.