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Porcine epidemic diarrhea virus (PEDV) emerged in the United States (U.S.) swine population in 2013, initiating an initial significant epidemic followed by a state of endemicity in the U.S. Despite continued monitoring, the epidemiology of PEDV during its endemic phase remains inadequately researched. Our study aimed to characterize the spatial–temporal distribution of postepidemic PEDV cases in the U.S. breeding herd and identify associated risk factors. Data from 1089 breeding farms in 27 states, reported to the Morrison Swine Health Monitoring Project from July 2014 to June 2021, were analyzed. We stratified the data into six U.S. regions and employed SaTScan for spatiotemporal permutation and cluster analysis. Survival analysis was used to assess risk factors. A notable seasonal clustering of PEDV cases was observed in winter (January–March; p = 0.001, relative risk = 2.2) with regional variation. Ten high‐rate spatial–temporal clusters (p < 0.05) were identified ranging from 2.5 to 833.7 km2 and lasting 1–5 months, occurring in four regions between 2015 and 2021. For the study period, a total of 625 cases of PEDV were recorded on 372 farms. The total number of PEDV cases decreased from 95 breeding farms in 32 counties (2014–2015) to 53 farms in 28 counties (2020–2021), indicating an overall reduction in occurrence and spatial extent. Feed mitigants demonstrated a protective effect, significantly reducing the risk of PEDV occurrence (hazard ratio = 0.3, p = 0.003), while air filtration systems exhibited marginal benefits (hazard ratio = 0.3, p = 0.06). Other important risk factors included county farm density with farms in high‐density regions (>31 farms/100 km2) being 1.3 times more likely to experience outbreaks than in medium‐density regions (13–31 farms/1000 km2; p < 0.001). Additionally, farms in region E had higher odds of outbreaks compared to region B. The overall decline in PEDV cases and reduced spatial extent reflect industry efforts in postepidemic control and elimination. The protective effects of feed mitigants warrant further investigation. Our findings underscore the opportunity for coordinated efforts to eliminate PEDV in the U.S. and emphasize the need for comprehensive risk profiling associated with industry practices. [ABSTRACT FROM AUTHOR]

The United States (U.S.) swine industry has struggled to control porcine reproductive and respiratory syndrome (PRRS) for decades, yet the causative virus, PRRSV‐2, continues to circulate and rapidly diverges into new variants. In the swine industry, the farm is typically the epidemiological unit for monitoring, prevention, and control; breaking transmission among farms is a critical step in containing disease spread. Despite this, our understanding of farm transmission still is inadequate, precluding the development of tailored control strategies. Therefore, our objective was to infer farm‐to‐farm transmission links, estimate farm‐level transmissibility as defined by reproduction numbers (R), and identify associated risk factors for transmission using PRRSV‐2 open reading frame 5 (ORF5) gene sequences, animal movement records, and other data from farms in a swine‐dense region of the U.S. from 2014 to 2017. Timed phylogenetic and transmission tree analyses were performed on three sets of sequences (n = 206) from 144 farms that represented the three largest genetic variants of the virus in the study area. The length of inferred pig‐to‐pig infection chains that corresponded to pairs of farms connected via direct animal movement was used as a threshold value for identifying other feasible transmission links between farms; these links were then transformed into farm‐to‐farm transmission networks and calculated farm‐level R‐values. The median farm‐level R was one (IQR = 1–2), whereas the R value of 28% of farms was more than one. Exponential random graph models were then used to evaluate the influence of farm attributes and/or farm relationships on the occurrence of farm‐to‐farm transmission links. These models showed that, even though most transmission events cannot be directly explained by animal movement, movement was strongly associated with transmission. This study demonstrates how integrative techniques may improve disease traceability in a data‐rich era by providing a clearer picture of regional disease transmission. [ABSTRACT FROM AUTHOR]

Swine production in the United States is characterized by dynamic farm contacts through animal movements; such movements shape the risk of disease occurrence on farms. Pig movements have been linked to the spread of a virulent porcine reproductive and respiratory syndrome virus (PRRSV), RFLP type 1‐7‐4, herein denoted as phylogenetic sub‐lineage 1A [L1A]. This study aimed to quantify the contribution of pig movements to the risk of L1A occurrence on farms in the United States. Farms were defined as L1A‐positive in a given 6‐month period if at least one L1A sequence was recovered from the farm. Temporal network autocorrelation modelling was performed using data on animal movements and 1,761 PRRSV ORF5 sequences linked to 494 farms from a dense pig production area in the United States between 2014 and 2017. A farm's current and past exposure to L1A and other PRRSV variants was assessed through its primary and secondary contacts in the animal movement network. Primary and secondary contacts with an L1A‐positive farm increased the likelihood of L1A occurrence on a farm by 19% (p =.04) and 23% (p =.03), respectively. While the risk posed by primary contacts with PRRS‐positive farms is unsurprising, the observation that secondary contacts also increase the likelihood of infection is novel. Risk of L1A occurrence on a farm also increased by 3.0% (p =.01) for every additional outgoing shipment, possibly due to biosecurity breaches during loading and transporting pigs from the farm. Finally, use of vaccines or field virus inoculation on sow farms one year prior reduced the risk of L1A occurrence in downstream farms by 36% (p =.04), suggesting that control measures that reduce viral circulation and enhance immunological protection in sow farms have a carry‐over effect on L1A occurrence in downstream farms. Therefore, coordinated disease management interventions between farms connected via animal movements may be more effective than individual farm‐based interventions. [ABSTRACT FROM AUTHOR]

Porcine reproductive and respiratory syndrome (PRRS) is an economically devastating disease of swine in many parts of the world. Porcine reproductive and respiratory syndrome virus (PRRSV) type 1 is endemic in Europe, and prevalence of the subtypes differ spatially. In this study, we investigated a severe PRRS outbreak reported in 30 farms located in eastern Russia that belong to a large swine production company in the region that was also experiencing a pseudorabies outbreak in the system. Data included 28 ORF5 sequences from samples across 18 of the 25 infected sites, reverse transcriptase real-time polymerase chain reaction (RT-qPCR) results from diagnostic testing, reports of clinical signs, and animal movement records. We observed that the outbreak was due to two distinct variants of wildtype PRRSV type 1 subtype 1 with an average genetic distance of 15%. Results suggest that the wildtype PRRSV variants were introduced into the region around 2019, before affecting this production system (i.e., sow farms, nurseries, and finisher farms). Clinical signs did not differ between the variants, but they did differ by stage of pig production. Biosecurity lapses, including movement of animals from infected farms contributed to disease spread. [ABSTRACT FROM AUTHOR]

As a consequence of multi-site pig production practiced in North America, frequent and widespread animal movements create extensive networks of interaction between farms. Social network analysis (SNA) has been used to understand disease transmission risks within these complex and dynamic production ecosystems and is particularly relevant for designing risk-based surveillance and control strategies targeting highly connected farms. However, inferences from SNA and the effectiveness of targeted strategies may be influenced by temporal changes in network structure. Since farm movements represent a temporally dynamic network, it is also unclear how many months of data are required to gain an accurate picture of an individual farm's connectivity pattern and the overall network structure. The extent to which shipments between two specific farms are repeated (i.e., "loyalty" of farm contacts) can influence the rate at which the structure of a network changes over time, which may influence disease dynamics. In this study, we aimed to describe temporal stability and loyalty patterns of pig movement networks in the U.S. swine industry. We analyzed a total of 282,807 animal movements among 2724 farms belonging to two production systems between 2014 and 2017. Loyalty trends were largely driven by contacts between sow farms and nurseries and between nurseries and finisher farms; mean loyalty (percent of contacts that were repeated at least once within a 52-week interval) of farm contacts was 51–60 % for farm contacts involving weaned pigs, and 12–22% for contacts involving feeder pigs. A cyclic pattern was observed for both weaned and feeder pig movements, with episodes of increased loyalty observed at intervals of 8 and 17–20 weeks, respectively. Network stability was achieved when six months of data were aggregated, and only small shifts in node-level and global network metrics were observed when adding more data. This stability is relevant for designing targeted surveillance programs for disease management, given that movements summarized over too short a period may lead to stochastic swings in network metrics. A temporal resolution of six months would be reliable for the identification of potential super-spreaders in a network for targeted intervention and disease control. The temporal stability observed in these networks suggests that identifying highly connected farms in retrospective network data (up to 24 months) is reliable for future planning, albeit with reduced effectiveness. [ABSTRACT FROM AUTHOR]

Chronic wasting disease is a transmissible spongiform encephalopathy that affects cervids with a clinical picture of muscle wasting in infected animals. The objective of this study was to quantify movement patterns of farmed cervids in the state of Minnesota as a model for identifying potential disease mitigation points. Time aggregated network analysis was performed on data consisting of 1221 intra-state cervid movements from farms located within Minnesota (n = 432 farms). Intra-state movements accounted for 48.2 % of all documented movements (2578) in Minnesota from 2013 to 2018; the remaining movements were inter-state. Annual networks were sparse in nature with low graph densities (6.9 × 10−4 - 1.4 × 10-3) and transitivity (0.06−0.12). Frequency of movements increased significantly (p < 0.05) in the months of September and October before decreasing in November, which coincided with the breeding and hunting seasons. Some of these contacts were as far as 500 km apart. The median length of infection chains for CWD positive farms was estimated to be 5.0 and 6.0 farms in-and out-going infection chains, respectively. A k -test analysis demonstrated that the observed median number of infected farms directly connected to other infected farms was 2.0, which was significantly higher than a fortuitous event (p = 0.002). Movements of cervids between farms were largely unpredictable with very low edge overlap (mean 0.02 %) from year to year, suggesting that persistent commercial relationships among farms were rare. In conclusion, long distance trade movements present a risk for spread of chronic wasting disease in Minnesota. The sparse networks and unpredictable farm contacts could be because cervid production is not as vertically integrated as other species-differentiated and established industries, such as swine or poultry. Our analytical approach can be used to understand chronic wasting disease in other states in the U.S. and North America in general. [ABSTRACT FROM AUTHOR]

In this study, there was evaluation of pregnancy per AI (P/AI) as a result of the first postpartum AI following four ovulation-synchronization treatments. Treatment regimens were Ovsynch-56 (OVS, n = 875; GnRH1-7d-PGF 2α -56h-GnRH2-16h-FTAI), CIDR-OVS (n = 1001; OVS plus CIDR inserts between GnRH1 and PGF 2α), Double-Ovsynch (DOVS, n = 663; imposing Pre-OVS followed by breeding-OVS 7 days later), and Modified-DOVS (M-DOVS, n = 1397; imposing Pre-OVS followed either by breeding-OVS or CIDR-OVS based upon the ovarian structure at GnRH1). Cows with a corpus luteum were assigned to a breeding-OVS treatment regimen and those that did not have a corpus luteum were assigned to the CIDR-OVS treatment regimen. Compared with OVS, the P/AI of the cows in the M-DOVS (OR = 1.5, P = 0.001) and CIDR-OVS (OR = 1.4, P = 0.017) was greater at day 30. At day 70, only in the M-DOVS group was there a greater P/AI compared with the OVS group (OR = 1.7, P < 0.001). Pregnancy loss between days 30 and 70 was greater in cows of the CIDR-OVS (OR = 1.9, P = 0.014) compared with those of the OVS group. In cows of the M-DOVS, the dominant ovarian structures (follicle, corpus luteum or cyst) at different time-points of the pre-synchronization period and occurrence of estrus at the end of this period were not associated with P/AI at day 30 post-AI. In conclusion, imposing CIDR-OVS in cows that did not respond to pre-synchronization treatments, resulted in an enhanced pregnancy percentage with the use of the DOVS. [ABSTRACT FROM AUTHOR]

CWD (chronic wasting disease) has emerged as one of the most important diseases of cervids and continues to adversely affect farmed and wild cervid populations, despite control and preventive measures. This study aims to use the current scientific understanding of CWD transmission and knowledge of farmed cervid operations to conduct a qualitative risk assessment for CWD transmission to cervid farms and, applying this risk assessment, systematically describe the CWD transmission risks experienced by CWD-positive farmed cervid operations in Minnesota and Wisconsin. A systematic review of literature related to CWD transmission informed our criteria to stratify CWD transmission risks to cervid operations into high-risk low uncertainty, moderate-risk high uncertainty, and negligible-risk low uncertainty categories. Case data from 34 CWD-positive farmed cervid operations in Minnesota and Wisconsin from 2002 to January 2019 were categorized by transmission risks exposure and evaluated for trends. The majority of case farms recorded high transmission risks (56%), which were likely sources of CWD, but many (44%) had only moderate or negligible transmission risks, including most of the herds (62%) detected since 2012. The presence of CWD-positive cervid farms with only moderate or low CWD transmission risks necessitates further investigation of these risks to inform effective control measures. [ABSTRACT FROM AUTHOR]

The Egyptian domestic (Baladi) dog has been increasingly adopted as a companion animal. Breed-specific cardiovascular reference intervals (RIs) are useful for clinicians in identifying abnormalities. The study aimed to estimate RIs for different heart indices in healthy male Baladi dogs. Twenty-six dogs were recruited to the study. Dogs were approved to be healthy. Afterwards, they were consciously examined by electrocardiography, echocardiography, and radiography. RIs were estimated using a bias-corrected bootstrapping approach. Electrocardiographic RIs were heart rate: 103 – 132 (beats/minute); P: 0.02 - 0.04, T: 0.03 - 0.04 waves durations (seconds); P: 0.13 - 0.23, R: 1.19 - 1.51, T: 0.20 - 0.27 waves amplitudes (mV); and PR: 0.11 - 0.17, QRS: 0.06 - 0.08, QT: 0.41 - 0.44 intervals (seconds). Echocardiographic parameters included end (diastolic: 29.95 - 46.49, systolic: 5.54 - 10.32) volumes (ml); ejection fraction: 76.23 - 83.41 (%); stroke volume 25.13 - 37.41 (ml); fractional shortening: 0.43 - 0.51 (%); interventricular septal thickness (diastole: 7.61 - 8.55; systole: 12.19 - 14.12 mm); left atrial to aortic root ratio (0.98 - 1.06); left ventricular diameter (diastole: 27.86 - 33.34, systole:14.42 - 18.14 mm) and left ventricular posterior wall thickness (diastole: 9.71 - 13.5; systole: 14.73 - 18.33 mm). Right lateral radiographs heart axes (long: 5.31 - 5.67, short 3.67 - 4.03 vertebrae) and VHS: 9.04 - 9.64 (vertebrae). No significant associations were identified between the measurements and body weight, age, and heart rate. In conclusions our results emphasized the importance of establishing Baladi‐specific RIs. [ABSTRACT FROM AUTHOR]

Analyses of livestock movement networks has become key to understanding an industry's vulnerability to infectious disease spread and for identifying farms that play disproportionate roles in pathogen dissemination. In addition to animal movements, many pathogens can spread between farms via mechanisms mediated by spatial proximity. Heterogeneities in contact patterns based on spatial proximity are less commonly considered in network studies, and studies that jointly consider spatial connectivity and animal movement are rare. The objective of this study was to determine the extent to which movement versus spatial proximity networks determine the distribution of an economically important endemic virus, porcine reproductive and respiratory syndrome virus (PRRSV), within a swine-dense region of the U.S. PRRSV can be classified into numerous phylogenetic lineages. Such data can be used to better resolve between-farm infection chains and elucidate types of contact most associated with transmission. Here, we construct movement and spatial proximity networks; farms within the networks were classified as cases if a given PRRSV lineage had been recovered at least once in a year for each of three years analyzed. We evaluated six lineages and sub-lineages across three years, and evaluated the epidemiological relevance of each network by applying network k-tests to statistically evaluate whether the pattern of case occurrence within the network was consistent with transmission via network linkages. Our results indicated that animal movements, not local area spread, play a dominant role in shaping transmission pathways, though there were differences amongst lineages. The median number of case farms inter-linked via animal movements was approximately 4.1x higher than random expectations (range: 1.7–13.7; p < 0.05, network k- test), whereas this measure was only 2.7x higher than random expectations for farms linked via spatial proximity (range: 1.3–5.4; p < 0.05, network k- test). For spatial proximity networks, contact based on proximities of <5 km appeared to have greater epidemiological relevance than longer distances, likely related to diminishing probabilities of local area spread at greater distances. However, the greater overall levels of connectivity of the spatial network compared to the movement network highlights the vulnerability of pig populations to widespread transmission via this route. By combining genetic data with network analysis, this research advances our understanding of dynamics of between-farm spread of PRRSV, helps establish the relative importance of transmission via animal movements versus local area spread, and highlights the potential for targeted control strategies based upon heterogeneities in network connectivity. [ABSTRACT FROM AUTHOR]