Porcine Deltacoronavirus Occurrence in the United States Breeding Herds since Its Emergence in 2014.

PDCoV, an enveloped RNA virus, causes atrophic enteritis in neonatal piglets, leading to diarrhea, malabsorption, dehydration, and death. The study aims to fill the gap in the current epidemiological information about PDCoV in the U.S. pig population after its emergence in 2014. Data from the Morrison Swine Health Monitoring Project (MSHMP) between January 2015 and December 2023 were analyzed, representing approximately 60% of the U.S. breeding herd. Participating herds report weekly PDCoV health status. In total, 244 PDCoV outbreaks occurred in 186 sites from 22 production systems across 16 states. Case counts peaked during winter, and incidence ranged from 0.44% in 2017 to 4.28% in 2023. For sites that experienced more than one PDCoV outbreak during the study period, the interval between outbreaks was a median of 2.11 years. The South and Midwest regions reported the majority of cases. In 2017, a shift in the spatial distribution of cases from the Midwest to the South was observed. The findings underscore the importance of continued monitoring and strengthened control measures to mitigate the impact of PDCoV in U.S. breeding herds.

Evaluating variations in metabolic profiles during the dry period related to the time of hyperketonemia onset in dairy cows.

Hyperketonemia (HYK) in early lactation can have a different impact on health and productivity depending on the timing of HYK onset. While specific metabolites measured during the dry period may serve as biomarkers of HYK, the correlations between metabolites represent a challenge for the use of metabolic profiles dataset, and little has been explored on HYK. This exploratory cohort study aimed a) to characterize the correlations among metabolites measured during the late dry period in dairy cows, and b) to identify biomarkers in the late dry period associated with the onset of HYK at the first (wk1) and second (wk2) week of lactation. Individual blood samples from 440 Holstein dairy cows were collected at 21 ± 3 days before expected parturition. From each sample, 36 different metabolites were measured in serum and plasma. Hyperketonemia was diagnosed in wk1 and wk2 of lactation based on the blood concentration of beta-hydroxybutyrate (BHB > 1.2 mmol/L). Principal component analysis (PCA) was performed to reduce metabolites to a smaller number of uncorrelated components. Multivariable logistic regression models were applied to assess the associations between principal components (PC) and HYK at wk1 only (HYK+ wk1), wk2 only (HYK+ wk2), or both weeks (HYK+ wk1-2). The incidence of HYK was 16.2% in the first week, 13.0% in the second week, and 21.2% within the first two weeks of lactation. The results of PCA highlighted 10 PCs from which two were associated with HYK+ wk1 as compared with cows without HYK during the first two weeks of lactation (non-HYK); the PC a2 led by bilirubin and non-esterified fatty acids (OR = 1.29; 95%CI: 1.02-1.68), and the PC a5 led by alkaline phosphatase (ALP) and gamma-glutamyl transferase (GGT) (OR = 2.77; 95%CI: 1.61-4.97). There was no evidence of an association between any PC and HYK+ wk2 (vs. non-HYK cows). Cows with elevated PC a5 (led by ALP and GGT) in the dry period were 3.18 times more likely to be HYK+ wk1 than HYK+ wk2 (OR: 3.18, 95%CI: 1.34-8.73; P = 0.013). Overall, the main hypothesis generated by our exploratory study suggests that cows with biomarkers of liver dysfunction (ALP, GGT, bilirubin) assessed by PCA at 3 weeks before calving are more likely to develop HYK during the first week of lactation compared to the second week. In addition, results suggest that cows with HYK in both of the first two weeks of lactation had an overall metabolic disbalance during the onset of the late dry period, which based on PCs, encompass biomarkers related to glucogenic and ketogenic metabolic pathways as well as liver dysfunction and fatty liver. Further research is needed to determine the underlying mechanisms associated with the different adaptations between cows that develop HYK during the first and second week of lactation.

Disentangling transport movement patterns of trucks either transporting pigs or while empty within a swine production system before and during the COVID-19 epidemic.

Transport of pigs between sites occurs frequently as part of genetic improvement and age segregation. However, a lack of transport biosecurity could have catastrophic implications if not managed properly as disease spread would be imminent. However, there is a lack of a comprehensive study of vehicle movement trends within swine systems in the Midwest. In this study, we aimed to describe and characterize vehicle movement patterns within one large Midwest swine system representative of modern pig production to understand movement trends and proxies for biosecurity compliance and identify potential risky behaviors that may result in a higher risk for infectious disease spread. Geolocation tracking devices recorded vehicle movements of a subset of trucks and trailers from a production system every 5 min and every time tracks entered a landmark between January 2019 and December 2020, before and during the COVID-19 pandemic. We described 6,213 transport records from 12 vehicles controlled by the company. In total, 114 predefined landmarks were included during the study period, representing 5 categories of farms and truck wash facilities. The results showed that trucks completed the majority (76.4%, 2,111/2,762) of the recorded movements. The seasonal distribution of incoming movements was similar across years (P > 0.05), while the 2019 winter and summer seasons showed higher incoming movements to sow farms than any other season, year, or production type (P < 0.05). More than half of the in-movements recorded occurred within the triad of sow farms, wean-to-market stage, and truck wash facilities. Overall, time spent at each landmark was 9.08% higher in 2020 than in 2019, without seasonal highlights, but with a notably higher time spent at truck wash facilities than any other type of landmark. Network analyses showed high connectivity among farms with identifiable clusters in the network. Furthermore, we observed a decrease in connectivity in 2020 compared with 2019, as indicated by the majority of network parameter values. Further network analysis will be needed to understand its impact on disease spread and control. However, the description and quantification of movement trends reported in this study provide findings that might be the basis for targeting infectious disease surveillance and control.

Release of live baitfish by recreational anglers drives fish pathogen introduction risk.

Emerging diseases of wildlife are an existential threat to biodiversity, and human-mediated movements of live animals are a primary vector of their spread. Wildlife disease risk analyses offer an appealing alternative to precautionary approaches because they allow for explicit quantification of uncertainties and consideration of tradeoffs. Such considerations become particularly important in high-frequency invasion pathways with hundreds of thousands of individual vectors, where even low pathogen prevalence can lead to substantial risk. The purpose of this study was to examine the landscape-level dynamics of human behavior-mediated pathogen introduction risk in the context of a high-frequency invasion pathway. One such pathway is the use and release of live fish used as bait by recreational anglers. We used a stochastic risk assessment model parameterized by angler survey data from Minnesota, USA, to simulate one year of fishing in Minnesota and estimate the total number of risky trips for each of three pathogens: viral hemorrhagic septicemia virus, the microsporidian parasite Ovipleistophora ovariae, and the Asian fish tapeworm Schizocotyle acheilognathi. We assessed the number of introductions under four scenarios: current/baseline conditions, outbreak conditions (increased pathogen prevalence), source-focused control measures (decreased pathogen prevalence), and angler-focused control measures (decreased rates of release). We found that hundreds of thousands of introduction events can occur per year, even for regulated pathogens at low pathogen prevalence. Reducing the rate of illegal baitfish release had significant impact on risky trips in scenarios where a high number of anglers were involved, but was less impactful in circumstances with limited outbreaks and fewer affected anglers. In contrast, reducing pathogen prevalence in the source populations of baitfish had relatively little impact. In order to make meaningful changes in pathogen introduction risk, managers should focus efforts on containing local outbreaks and reducing illegal baitfish release to reduce pathogen introduction risk. Our study also demonstrates the risk associated with high-frequency invasion pathways and the importance of incorporating human behaviors into wildlife disease models and risk assessments.

Standardization of Data Analysis for RT-QuIC-Based Detection of Chronic Wasting Disease.

Chronic wasting disease (CWD) is a disease affecting cervids and is caused by prions accumulating as pathogenic fibrils in lymphoid tissue and the central nervous system. Approaches for detecting CWD prions historically relied on antibody-based assays. However, recent advancements in protein amplification technology provided the foundation for a new class of CWD diagnostic tools. In particular, real-time quaking-induced conversion (RT-QuIC) has rapidly become a feasible option for CWD diagnosis. Despite its increased usage for CWD-focused research, there lacks a consensus regarding the interpretation of RT-QuIC data for diagnostic purposes. It is imperative then to identify a standardized and replicable method for determining CWD status from RT-QuIC data. Here, we assessed variables that could impact RT-QuIC results and explored the use of maxpoint ratios (maximumRFU/backgroundRFU) to improve the consistency of RT-QuIC analysis. We examined a variety of statistical analyses to retrospectively analyze CWD status based on RT-QuIC and ELISA results from 668 white-tailed deer lymph nodes. Our results revealed an MPR threshold of 2.0 for determining the rate of amyloid formation, and MPR analysis showed excellent agreement with independent ELISA results. These findings suggest that the use of MPR is a statistically viable option for normalizing between RT-QuIC experiments and defining CWD status.

Time Farms Stay Naïve for Porcine Reproductive and Respiratory Syndrome.

BACKGROUND: Hesitation on eliminating Porcine Reproductive and Respiratory Syndrome virus (PRRSV) from breeding herds exists since it is difficult to predict how long the herd will remain virus-free. We aimed to estimate the time that breeding herds remained virus-free (naïve) after PRRSV elimination was achieved. METHODS: Production systems voluntarily shared their breeding herds' health status weekly between July 2009 and October 2021. PRRSV incidence rate and the total number of days a breeding herd remained virus-free were estimated. RESULTS: A total of 221 (17%) herds reached the naïve status 273 times. The median time sites remained in this status was approximately two years. The overall PRRS incidence rate after sites achieved a naïve status was 23.43 PRRS outbreaks per 100 farm years. CONCLUSION: Estimates obtained here provide insights on how frequently and for how long sites remain naïve, which contribute to informing management practices for PRRS control.

Assessment of Real-Time Quaking-Induced Conversion (RT-QuIC) Assay, Immunohistochemistry and ELISA for Detection of Chronic Wasting Disease under Field Conditions in White-Tailed Deer: A Bayesian Approach.

Chronic wasting disease (CWD) is a transmissible prion disease of the cervidae family. ELISA and IHC tests performed postmortem on the medial retropharyngeal lymph nodes (RPLN) or obex are considered diagnostic gold standards for prion detection. However, differences in CWD transmission, stage of infection, pathogenesis, and strain can limit performance. To overcome these uncertainties, we used Bayesian statistics to assess the accuracy of RT-QuIC, an increasingly used prion amplification assay, to diagnose CWD on tonsil (TLN), parotid (PLN) and submandibular lymph nodes (SMLN), and ELISA/IHC on RPLN of white-tailed deer (WTD) sampled from Minnesota. Dichotomous RT-QuIC and ELISA/IHC results from wild (n = 61) and captive (n = 46) WTD were analyzed with two-dependent-test, one-population models. RT-QuIC performed on TLN and SMLN of the wild WTD population had similar sensitivity (median range (MR): 92.2-95.1) to ELISA/IHC on RPLN (MR: 91.1-92.3). Slightly lower (4-7%) sensitivity estimates were obtained from farmed animal and PLN models. RT-QuIC specificity estimates were high (MR: 94.5-98.5%) and similar to ELISA/IHC estimates (MR: 95.7-97.6%) in all models. This study offers new insights on RT-QuIC and ELISA/IHC performance at the population level and under field conditions, an important step in CWD diagnosis and management.

Subdistrict-Level Reproductive Number for Foot and Mouth Disease in Cattle in Northern Thailand.

Foot and mouth disease (FMD) is an important contagious transboundary disease that causes a significant economic loss for several countries. The FMD virus (FMDV) can spread very rapidly by direct and indirect transmission among susceptible animals. The complexity and magnitude of FMDV transmission at the initial stages of the epidemic can be expressed by the basic reproductive number (R 0), and furthermore, control strategies can be assessed by the estimation of the effective reproductive number. In this study, we aimed to describe FMD outbreaks among smallholder cattle farms by subdistricts in the northern Thailand and compute the effective reproductive number for outbreaks caused by FMDV serotype O and overall serotypes, including serotype O, serotype A, and unidentified serotype, at the subdistrict level (R sd ) using an epidemic doubling time method. Field data of FMD outbreaks during 2015-2017 that affected 94 subdistricts in northern Thailand were assessed to estimate the R sd . Results showed that 63.38% (90/142) of the FMD outbreak episodes in cattle were caused by FMDV serotype O. The average doubling time and the R sd estimated of the outbreaks caused by FMDV serotype O and overall serotype were 2.80 and 4.67 months, and 1.06 and 1.04, respectively. Our results indicated that transmission of FMD in cattle at the subdistrict level in northern Thailand was not controlled (R sd > 1), which indicates the endemicity of the disease in the region. Although control measures are in place, the results from this study highlighted the need for enhancing FMD monitoring and control strategies in northern Thailand.

Emergence of a New Lineage 1C Variant of Porcine Reproductive and Respiratory Syndrome Virus 2 in the United States.

We report an ongoing regional outbreak of an emerging porcine reproductive and respiratory syndrome virus (PRRSV2) variant within Lineage 1C affecting 154 breeding and grow-finishing sites in the Midwestern U.S. Transmission seemed to have occurred in two waves, with the first peak of weekly cases occurring between October and December 2020 and the second starting in April 2021. Most of cases occurred within a 120 km radius. Both orf5 and whole genome sequencing results suggest that this represents the emergence of a new variant within Lineage 1C distinct from what has been previously circulating. A case-control study was conducted with 50 cases (sites affected with the newly emerged variant) and 58 controls (sites affected with other PRRSV variants) between October and December 2020. Sites that had a market vehicle that was not exclusive to the production system had 0.04 times the odds of being a case than a control. A spatial cluster (81.42 km radius) with 1.68 times higher the number of cases than controls was found. The average finishing mortality within the first 4 weeks after detection was higher amongst cases (4.50%) than controls (0.01%). The transmission of a highly similar virus between different farms carrying on trough spring rises concerns for the next high transmission season of PRRS.

Modelling the effect of test-and-slaughter strategies to control bovine tuberculosis in endemic high prevalence herds.

Bovine tuberculosis (bTB) prevalence substantially increased over the past two decades with relatively high impact on large dairy herds, raising the concern of regulatory authorities and industry stakeholders, and threatening animal and public health. Lack of resources, together with the economic and social consequences of whole-herd stamping-out, makes depopulation an impractical disease control alternative in these herds. The increase in bTB prevalence was associated with demographic and management changes in the dairy industry in Uruguay, reducing the efficacy of the current control programme (i.e. status quo) based on intradermal serial testing with caudal fold- and comparative-cervical tuberculin test-and-slaughter of reactors (CFT-CCT). Here, we aimed to assess the epidemiological effectiveness of six alternative control scenarios based on test-and-slaughter of positive animals, using mathematical modelling to infer bTB-within-herd dynamics. We simulated six alternative control strategies consisting of testing adult cattle (>1 year) in the herd every 3 months using one test (in vivo or in vitro) or a combination in parallel of two tests (CFT, interferon-gamma release assay-IGRA- or enzyme-linked immunosorbent assay). Results showed no significant differences overall in the time needed to reach bTB eradication (median ranging between 61 and 82 months) or official bovine tuberculosis-free status (two consecutive negative herd tests) between any of the alternative strategies and the status quo (median ranging between 50 and 59 months). However, we demonstrate how alternative strategies can significantly reduce bTB prevalence when applied for restricted periods (6, 12 or 24 months), and in the case of IGRAc (IGRA using peptide-cocktail antigens), without incurring on higher unnecessary slaughter of animals (false positives) than the status quo in the first 6 months of the programme (p-value < .05). Enhanced understanding bTB-within-herd dynamics with the application of different control strategies help to identify optimal strategies to ultimately improve bTB control and bTB eradication from dairies in Uruguay and similar endemic settings.

Corrigendum: Dairy Calves in Uruguay Are Reservoirs of Zoonotic Subtypes of Cryptosporidium parvum and Pose a Potential Risk of Surface Water Contamination.

[This corrects the article DOI: 10.3389/fvets.2020.00562.].

Dairy Calves in Uruguay Are Reservoirs of Zoonotic Subtypes of Cryptosporidium parvum and Pose a Potential Risk of Surface Water Contamination.

Cryptosporidium parvum, a major cause of diarrhea in calves, is of concern given its zoonotic potential. Numerous outbreaks of human cryptosporidiosis caused by C. parvum genetic subtypes are reported yearly worldwide, with livestock or water being frequently identified sources of infection. Although cryptosporidiosis has been reported from human patients in Uruguay, particularly children, epidemiologic information is scant and the role of cattle as reservoirs of zoonotic subtypes of C. parvum has not been explored. In this study, we aimed to (a)-identify C. parvum subtypes infecting dairy calves in Uruguay (including potentially zoonotic subtypes), (b)-assess their association with calf diarrhea, (c)-evaluate their spatial clustering, and (d)-assess the distance of infected calves to surface watercourses draining the farmlands and determine whether these watercourses flow into public water treatment plants. Feces of 255 calves that had tested positive for Cryptosporidium spp. by antigen ELISA were selected. Samples had been collected from 29 dairy farms in seven Uruguayan departments where dairy farming is concentrated and represented 170 diarrheic and 85 non-diarrheic calves. Selected samples were processed by nested PCRs targeting the 18S rRNA and gp60 genes followed by sequencing to identify C. parvum subtypes. Of seven C. parvum subtypes detected in 166 calves, five (identified in 143 calves on 28/29 farms) had been identified in humans elsewhere and have zoonotic potential. Subtype IIaA15G2R1 was the most frequent (53.6%; 89/166), followed by IIaA20G1R1 (24.1%; 40/166), IIaA22G1R1 (11.4%; 19/166), IIaA23G1R1 (3.6%; 6/166), IIaA17G2R1 (3%; 5/166), IIaA21G1R1 (2.4%; 4/166), and IIaA16G1R1 (1.8%; 3/166). There were no significant differences in the proportions of diarrheic and non-diarrheic calves infected with any of the C. parvum subtypes. Two spatial clusters were detected, one of which overlapped with Uruguay's capital city and its main water treatment plant (Aguas Corrientes), harvesting surface water to supply ~1,700,000 people. Infected calves on all farms were within 20-900 m of a natural surface watercourse draining the farmland, 10 of which flowed into six water treatment plants located 9-108 km downstream. Four watercourses flowed downstream into Aguas Corrientes. Calves are reservoirs of zoonotic C. parvum subtypes in Uruguay and pose a public health risk.

Association between results of diagnostic tests for bovine tuberculosis and Johne's disease in cattle.

BACKGROUND: Bovine tuberculosis (bTB) diagnosis is impaired by numerous factors including cross-reactivity with Mycobacterium avium subspecies paratuberculosis, which causes Johne's disease (JD). In addition, the effect of repeated bTB-intradermal testing on the performance of JD diagnostic tests is not fully understood. This study aimed to evaluate the impact of repeated bTB-intradermal tests under field conditions in Spain on the JD serological status of cattle. METHODS: bTB-positive herds (n=264) from Castilla-y-Leon region were selected and matched with officially tuberculosis-free control herds. The association between JD and bTB status at the herd level was assessed using conditional logistic regression and, in herds with both JD-positive and bTB-positive animals, a Bayesian hierarchical mixed-effect model was used for individual-level analysis. RESULTS: A significantly higher risk of being JD positive (OR: 1.48; 95 per cent CI: 1.01 to 2.15) was found for bTB-positive herds compared with controls. Individual results indicated that cattle tested more than three times per year, within the last 90 days and more than 12 months were more likely to be JD positive. A skin test-related boost in antibody response could be the cause of an apparent increase of the sensitivity of the JD-absorbed ELISA. CONCLUSION: The results demonstrate the interaction between bTB repeated testing and JD individual and herd-level results and this improved knowledge will facilitate the design of more effective control programmes in herds coinfected with two of the most important endemic diseases affecting cattle in Spain.

Modeling the Accuracy of Two in-vitro Bovine Tuberculosis Tests Using a Bayesian Approach.

Accuracy of new or alternative diagnostic tests is typically estimated in relation to a well-standardized reference test referred to as a gold standard. However, for bovine tuberculosis (bTB), a chronic disease of cattle, affecting animal and public health, no reliable gold standard is available. In this context, latent-class models implemented using a Bayesian approach can help to assess the accuracy of diagnostic tests incorporating previous knowledge on test performance and disease prevalence. In Uruguay, bTB-prevalence has increased in the past decades partially because of the limited accuracy of the diagnostic strategy in place, based on intradermal testing (caudal fold test, CFT, for screening and comparative cervical test, CCT, for confirmation) and slaughter of reactors. Here, we evaluated the performance of two alternative bTB-diagnostic tools, the interferon-gamma assay, IGRA, and the enzyme-linked immunosorbent assay (ELISA), which had never been used in Uruguay in the absence of a gold standard. In order to do so animals from two heavily infected dairy herds and tested with CFT-CCT were also analyzed with the IGRA using two antigens (study 1) and the ELISA (study 2). The accuracy of the IGRA and ELISA was assessed fitting two latent-class models: a two test-one population model (LCA-a) based on the analysis of CFT/CFT-CCT test results and one in-vitro test (IGRA/ELISA), and a one test-one population model (LCA-b) using the IGRA or ELISA information in which the prevalence was modeled using information from the skin tests. Posterior estimates for model LCA-a suggested that IGRA was as sensitive (75-78%) as the CFT and more sensitive than the serial use of CFT-CCT. Its specificity (90-96%) was superior to the one for the CFT and equivalent to the use of CFT-CCT. Estimates from LCA-b models consistently yielded lower posterior Se estimates for the IGRA but similar results for its Sp. Estimates for the Se (52% 95%PPI:44.41-71.28) and the Sp (92% 95%PPI:78.63-98.76) of the ELISA were however similar regardless of the model used. These results suggest that the incorporation of IGRA for detection of bTB in highly infected herds could be a useful tool to improve the sensitivity of the bTB-control in Uruguay.

Mapping changes in the spatiotemporal distribution of lumpy skin disease virus.

Lumpy skin disease virus (LSDV) is an infectious disease of cattle transmitted by arthropod vectors which results in substantial economic losses due to impact on production efficiency and profitability, and represents an emerging threat to international trade of livestock products and live animals. Since 2015, the disease has spread into the Northern Hemisphere including Azerbaijan, Kazakhstan, the Russian Federation and the Balkans. The rapid expansion of LSDV in those regions represented the emergence of the virus in more temperate regions than those in which LSDV traditionally occurred. The goal of this study was to assess the risk for further LSDV spread through the (a) analysis of environmental factors conducive for LSDV, and (b) estimate of the underlying LSDV risk, using a combination of ecological niche modelling and fine spatiotemporally explicit Bayesian hierarchical model on LSDV outbreak occurrence data. We used ecological niche modelling to estimate the potential distribution of LSDV outbreaks for 2014-2016. That analysis resulted in a spatial representation of environmental limits where, if introduced, LSDV is expected to efficiently spread. The Bayesian space-time model incorporated both environmental factors and the changing spatiotemporal distribution of the disease to capture the dynamics of disease spread and predict areas in which there is an increased risk for LSDV occurrence. Variables related to the average temperature, precipitation, wind speed, as well as land cover and host densities were important drivers explaining the observed distribution of LSDV in both modelling approaches. Areas of elevated LSDV risks were identified mainly in Russia, Turkey, Serbia and Bulgaria. The results suggest that, if current ecological and epidemiological conditions persist, further spread of LSDV in Eurasia may be expected. The results presented here advance our understanding of the ecological requirements of LSDV in temperate regions and may help in the design and implementation of prevention and surveillance strategies in the region.