Unveiling invisible farm-to-farm PRRSV-2 transmission links and routes through transmission tree and network analysis.

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.

Mapping the Dynamics of Contemporary PRRSV-2 Evolution and Its Emergence and Spreading Hotspots in the U.S. Using Phylogeography.

The repeated emergence of new genetic variants of PRRSV-2, the virus that causes porcine reproductive and respiratory syndrome (PRRS), reflects its rapid evolution and the failure of previous control efforts. Understanding spatiotemporal heterogeneity in variant emergence and spread is critical for future outbreak prevention. Here, we investigate how the pace of evolution varies across time and space, identify the origins of sub-lineage emergence, and map the patterns of the inter-regional spread of PRRSV-2 Lineage 1 (L1)-the current dominant lineage in the U.S. We performed comparative phylogeographic analyses on subsets of 19,395 viral ORF5 sequences collected across the U.S. and Canada between 1991 and 2021. The discrete trait analysis of multiple spatiotemporally stratified sampled sets (n = 500 each) was used to infer the ancestral geographic region and dispersion of each sub-lineage. The robustness of the results was compared to that of other modeling methods and subsampling strategies. Generally, the spatial spread and population dynamics varied across sub-lineages, time, and space. The Upper Midwest was a main spreading hotspot for multiple sub-lineages, e.g., L1C and L1F, though one of the most recent emergence events (L1A(2)) spread outwards from the east. An understanding of historical patterns of emergence and spread can be used to strategize disease control and the containment of emerging variants.

Interplay between cross sectional analysis of risk factors associated with Toxoplasma gondii infection in pregnant women and their domestic cats.

Toxoplasmosis is a global zoonotic disease caused by Toxoplasma gondii (T. gondii). The primary aim of this study was to identify hygienic and cat management practices that could affect the occurrence of T. gondii in cats and their owners in Sharqia Governorate, Egypt. T. gondii infection was evaluated in 80 pregnant women and 29 domestic cats using Real-time PCR. A questionnaire was administered to obtain information regarding the risk factors associated with T. gondii infection. Blood samples were collected from enrolled pregnant women, and fecal samples were collected from their pet cats. Firth logistic regression model complemented with random forest (RF) analysis was used to evaluate the association of different hygiene and cat management practices with T. gondii infection in pregnant women. T. gondii infection was identified in 27.5% of pregnant women and 17% of domestic cats. Drinking raw milk and contacting stray and pet cats were significantly associated with higher odds of T. gondii infection. The proportion of T. gondii-positive women who ate raw meat (60.0%) was higher than those ate heat-cooked meat (25.3%). Moreover, women who did not wash their hands after contact with cats were 6 times (OR 6.12; CI: 3.03-9.21) more likely to experience T. gondii infection than those washed their hands after cat contact. The RF analysis showed that washing hands constitute a serious yet preventable public health concern that requires targeted, community-specific efforts. Cat owners, particularly pregnant women, need to be aware about the risk of T. gondii infection, while handling cat and pet's owner should be advised to take necessary hygienic measures to prevent its infection.

Predicting Antigenic Distance from Genetic Data for PRRSV-Type 1: Applications of Machine Learning.

The control of porcine reproductive and respiratory syndrome (PRRS) remains a significant challenge due to the genetic and antigenic variability of the causative virus (PRRSV). Predominantly, PRRSV management includes using vaccines and live virus inoculations to confer immunity against PRRSV on farms. While understanding cross-protection among strains is crucial for the continued success of these interventions, understanding how genetic diversity translates to antigenic diversity remains elusive. We developed machine learning algorithms to estimate antigenic distance in silico, based on genetic sequence data, and identify differences in specific amino acid sites associated with antigenic differences between viruses. First, we obtained antigenic distance estimates derived from serum neutralization assays cross-reacting PRRSV monospecific antisera with virus isolates from 27 PRRSV1 viruses circulating in Europe. Antigenic distances were weakly to moderately associated with ectodomain amino acid distance for open reading frames (ORFs) 2 to 4 (ρ < 0.2) and ORF5 (ρ = 0.3), respectively. Dividing the antigenic distance values at the median, we then categorized the sera-virus pairs into two levels: low and high antigenic distance (dissimilarity). In the machine learning models, we used amino acid distances in the ectodomains of ORFs 2 to 5 and site-wise amino acid differences between the viruses as potential predictors of antigenic dissimilarity. Using mixed-effect gradient boosting models, we estimated the antigenic distance (high versus low) between serum-virus pairs with an accuracy of 81% (95% confidence interval, 76 to 85%); sensitivity and specificity were 86% and 75%, respectively. We demonstrate that using sequence data we can estimate antigenic distance and potential cross-protection between PRRSV1 strains. IMPORTANCE Understanding cross-protection between cocirculating PRRSV1 strains is crucial to reducing losses associated with PRRS outbreaks on farms. While experimental studies to determine cross-protection are instrumental, these in vivo studies are not always practical or timely for the many cocirculating and emerging PRRSV strains. In this study, we demonstrate the ability to rapidly estimate potential immunologic cross-reaction between different PRRSV1 strains in silico using sequence data routinely collected by production systems. These models can provide fast turn-around information crucial for improving PRRS management decisions such as selecting vaccines/live virus inoculation to be used on farms and assessing the risk of outbreaks by emerging strains on farms previously exposed to certain PRRSV strains and vaccine development among others.

Potential Novel N-Glycosylation Patterns Associated with the Emergence of New Genetic Variants of PRRSV-2 in the U.S.

Glycosylation of proteins is a post-translational process where oligosaccharides are attached to proteins, potentially altering their folding, epitope availability, and immune recognition. In Porcine reproductive and respiratory syndrome virus-type 2 (PRRSV-2), positive selection pressure acts on amino acid sites potentially associated with immune escape through glycan shielding. Here, we describe the patterns of potential N-glycosylation sites over time and across different phylogenetic lineages of PRRSV-2 to better understand how these may contribute to patterns of coexistence and emergence of different lineages. We screened 19,179 PRRSV GP5 sequences (2004−2021) in silico for potential N-glycosylated sites. The emergence of novel combinations of N-glycosylated sites coincided with past PRRSV epidemics in the U.S. For lineage L1A, glycosylation at residues 32, 33, 44, 51, and 57 first appeared in 2012, but represented >62% of all L1A sequences by 2015, coinciding with the emergence of the L1A 1-7-4 strain that increased in prevalence from 8 to 86% of all L1A sequences from 2012 to 2015. The L1C 1-4-4 strain that emerged in 2020 also had a distinct N-glycosylation pattern (residues 32, 33, 44, and 51). From 2020 to 2021, this pattern was responsible for 44−47% of the L1C sequences, contrasting to <5% in years prior. Our findings support the hypothesis that antigenic evolution contributes to the sequential dominance of different PRRSV strains and that N-glycosylation patterns may partially account for antigenic differences amongst strains. Further studies on glycosylation and its effect on PRRSV GP5 folding are needed to further understand how glycosylation patterns shape PRRSV occurrence.

Ecological and evolutionary dynamics of multi-strain RNA viruses.

Potential interactions among co-circulating viral strains in host populations are often overlooked in the study of virus transmission. However, these interactions probably shape transmission dynamics by influencing host immune responses or altering the relative fitness among co-circulating strains. In this Review, we describe multi-strain dynamics from ecological and evolutionary perspectives, outline scales in which multi-strain dynamics occur and summarize important immunological, phylogenetic and mathematical modelling approaches used to quantify interactions among strains. We also discuss how host-pathogen interactions influence the co-circulation of pathogens. Finally, we highlight outstanding questions and knowledge gaps in the current theory and study of ecological and evolutionary dynamics of multi-strain viruses.

Factors influencing usage of antimicrobial drugs among pastoralists in Kenya.

Agricultural use of antimicrobials in food animal production may contribute to the global emergence of antimicrobial resistance (AMR). However, considerable gaps exist in research on the use of antimicrobial drugs (AMDs) in food animals in small-scale production systems in low- and middle-income countries, despite the minimal regulation of antimicrobials in such regions. The aim of this study was to identify factors that may influence AMD use in livestock among pastoral communities in Kenya. We collected data related to household and herd demographics, herd health, and herd management from 55 households in the Maasai Mara ecosystem, Kenya, between 2018 and 2019. We used multi-model logistic regression inference (supervised machine learning) to ascertain trends in AMD use within these households. AMD use in cattle was significantly associated with AMD use in sheep and goats (p = 0.05), implying that decisions regarding AMD use in cattle or sheep and goats were interdependent. AMD use in sheep and goats was negatively associated with vaccination against the foot and mouth disease (FMD) virus in cattle (OR = 0.06, 95% CI 0.01-0.67, p = 0.02). Less AMD use was observed for vaccine-preventable diseases like contagious ecthyma when households had access to state veterinarians (OR = 0.06, p = 0.05, 95% CI 0.004-0.96). Overall, decisions to use AMDs were associated with vaccine usage, occurrence of respiratory diseases, and access to animal health advice. This hypothesis-generating study suggests that applying community-centric methods may be necessary to understand the use of AMDs in pastoral communities.

Measuring How Recombination Re-shapes the Evolutionary History of PRRSV-2: A Genome-Based Phylodynamic Analysis of the Emergence of a Novel PRRSV-2 Variant.

While the widespread and endemic circulation of porcine reproductive and respiratory syndrome virus type 2 (PRRSV-2) causes persistent economic losses to the U.S. swine industry, unusual increases of severe cases associated with the emergence of new genetic variants are a major source of concern for pork producers. Between 2020 and 2021, such an event occurred across pig production sites in the Midwestern U.S. The emerging viral clade is referred to as the novel sub-lineage 1C (L1C) 1-4-4 variant. This genetic classification is based on the open reading frame 5 (ORF5) gene. However, although whole genome sequence (WGS) suggested that this variant represented the emergence of a new strain, the true evolutionary history of this variant remains unclear. To better elucidate the variant's evolutionary history, we conducted a recombination detection analysis, time-scaled phylogenetic estimation, and discrete trait analysis on a set of L1C-1-4-4 WGSs (n = 19) alongside other publicly published WGSs (n = 232) collected over a 26-year period (1995-2021). Results from various methodologies consistently suggest that the novel L1C variant was a descendant of a recombinant ancestor characterized by recombination at the ORF1a gene between two segments that would be otherwise classified as L1C and L1A in the ORF5 gene. Based on analysis of different WGS fragments, the L1C-1-4-4 variant descended from an ancestor that existed around late 2018 to early 2019, with relatively high substitution rates in the proximal ORF1a as well as ORF5 regions. Two viruses from 2018 were found to be the closest relatives to the 2020-21 outbreak strain but had different recombination profiles, suggesting that these viruses were not direct ancestors. We also assessed the overall frequency of putative recombination amongst ORF5 and other parts of the genome and found that recombination events which leave detectable numbers of descendants are not common. However, the rapid spread and high virulence of the L1C-1-4-4 recombinant variant demonstrates that inter-sub-lineage recombination occasionally found amongst the U.S. PRRSV-2 might be an evolutionary mechanisms that contributed to this emergence. More generally, recombination amongst PRRSV-2 accelerates genetic change and increases the chance of the emergence of high fitness variants.

A Molecular and Epidemiological Description of a Severe Porcine Reproductive and Respiratory Syndrome Outbreak in a Commercial Swine Production System in Russia.

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.

Dynamic network connectivity influences the spread of a sub-lineage of porcine reproductive and respiratory syndrome virus.

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.

Integrating animal movements with phylogeography to model the spread of PRRSV in the USA.

Viral sequence data coupled with phylodynamic models have become instrumental in investigating the outbreaks of human and animal diseases, and the incorporation of the hypothesized drivers of pathogen spread can enhance the interpretation from phylodynamic inference. Integrating animal movement data with phylodynamics allows us to quantify the extent to which the spatial diffusion of a pathogen is influenced by animal movements and contrast the relative importance of different types of movements in shaping pathogen distribution. We combine animal movement, spatial, and environmental data in a Bayesian phylodynamic framework to explain the spatial diffusion and evolutionary trends of a rapidly spreading sub-lineage (denoted L1A) of porcine reproductive and respiratory syndrome virus (PRRSV) Type 2 from 2014 to 2017. PRRSV is the most important endemic pathogen affecting pigs in the USA, and this particular virulent sub-lineage emerged in 2014 and continues to be the dominant lineage in the US swine industry to date. Data included 984 open reading frame 5 (ORF5) PRRSV L1A sequences obtained from two production systems in a swine-dense production region (∼85,000 mi2) in the USA between 2014 and 2017. The study area was divided into sectors for which model covariates were summarized, and animal movement data between each sector were summarized by age class (wean: 3-4 weeks; feeder: 8-25 weeks; breeding: ≥21 weeks). We implemented a discrete-space phylogeographic generalized linear model using Bayesian evolutionary analysis by sampling trees (BEAST) to infer factors associated with variability in between-sector diffusion rates of PRRSV L1A. We found that between-sector spread was enhanced by the movement of feeder pigs, spatial adjacency of sectors, and farm density in the destination sector. The PRRSV L1A strain was introduced in the study area in early 2013, and genetic diversity and effective population size peaked in 2015 before fluctuating seasonally (peaking during the summer months). Our study underscores the importance of animal movements and shows, for the first time, that the movement of feeder pigs (8-25 weeks old) shaped the spatial patterns of PRRSV spread much more strongly than the movements of other age classes of pigs. The inclusion of movement data into phylodynamic models as done in this analysis may enhance our ability to identify crucial pathways of disease spread that can be targeted to mitigate the spatial spread of infectious human and animal pathogens.

Phylogenetically Distinct Near-Complete Genome Sequences of Porcine Reproductive and Respiratory Syndrome Virus Type 2 Variants from Four Distinct Disease Outbreaks at U.S. Swine Farms over the Past 6 Years.

Porcine reproductive and respiratory syndrome virus (PRRSV) continues to mutate, causing disruptive PRRS outbreaks in farms that lead to reproductive failure and respiratory disease-associated mortality. We present four new PRRSV type 2 variants in the United States belonging to four distinct orf5 sublineages within lineage 1.

Chronic Wasting Disease Transmission Risk Assessment for Farmed Cervids in Minnesota and Wisconsin.

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.

Phylogenetic Structure and Sequential Dominance of Sub-Lineages of PRRSV Type-2 Lineage 1 in the United States.

The genetic diversity and frequent emergence of novel genetic variants of porcine reproductive and respiratory syndrome virus type-2 (PRRSV) hinders control efforts, yet drivers of macro-evolutionary patterns of PRRSV remain poorly documented. Utilizing a comprehensive database of >20,000 orf5 sequences, our objective was to classify variants according to the phylogenetic structure of PRRSV co-circulating in the U.S., quantify evolutionary dynamics of sub-lineage emergence, and describe potential antigenic differences among sub-lineages. We subdivided the most prevalent lineage (Lineage 1, accounting for approximately 60% of available sequences) into eight sub-lineages. Bayesian coalescent SkyGrid models were used to estimate each sub-lineage's effective population size over time. We show that a new sub-lineage emerged every 1 to 4 years and that the time between emergence and peak population size was 4.5 years on average (range: 2-8 years). A pattern of sequential dominance of different sub-lineages was identified, with a new dominant sub-lineage replacing its predecessor approximately every 3 years. Consensus amino acid sequences for each sub-lineage differed in key GP5 sites related to host immunity, suggesting that sub-lineage turnover may be linked to immune-mediated competition. This has important implications for understanding drivers of genetic diversity and emergence of new PRRSV variants in the U.S.

Temporal stability of swine movement networks in the U.S.

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.

Implications of farmed-cervid movements on the transmission of chronic wasting disease.

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.

Treatment of cows that fail to respond to pre-synchronization treatments with a CIDR-Ovsynch regimen improves the overall pregnancy percentage after a double Ovsynch treatment regimen.

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-PGF2α-56h-GnRH2-16h-FTAI), CIDR-OVS (n = 1001; OVS plus CIDR inserts between GnRH1 and PGF2α), 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.

Contrasting animal movement and spatial connectivity networks in shaping transmission pathways of a genetically diverse virus.

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.

Sero-prevalence and risk factors of infectious bovine rhinotracheitis virus (type 1) in Meru County, Kenya.

The aim of the study was to determine the antibody sero-prevalence of Bovine Herpesvirus-1 which cause Infectious Bovine Rhinotracheitis (IBR) and to identify risk factors associated with BHV-1 antibody seropositivity among smallholder dairy farms in Meru County, Kenya. A cross-sectional study was conducted in the Naari area of Meru County, Kenya between September-October 2016 and March-April 2017. The 149 farmers were randomly selected from members of the Naari Dairy Farmers Cooperative Society who were actively delivering milk to the society at the time of the study. Serum samples were obtained from 403 female dairy cattle. Farm level management and animal factors were collected through direct interviews with the owner or someone who was knowledgeable about the animals. All serum samples were processed with an indirect enzyme-linked immunosorbent assay (gB ELISA) to determine the presence of antibodies to BHV-1. The overall farm-level and animal-level sero-prevalences of BHV-1 antibodies were 30.9 % (95 % CI: 23.6%-39.0%) and 17.4 % (95 % CI: 13.8%-21.4%), respectively. In the final multivariable analysis, the factors significantly associated with BHV-1 antibodies included; age of the dairy cattle (OR = 1.200, p = 0.001), age of the principal female farmers (OR = 0.182, p = 0.001) and rearing goats in the farm (OR = 26.77, p = 0.000). There was a significant interaction between rearing goats on the farm and age of the dairy cattle (p < 0.010); younger cattle seemed to have been exposed to BHV or a cross-reacting caprine herpesvirus when goats were on the farm. The results showed that BHV-1 was circulating among the cattle population in the Naari area of Meru County. Given that there is not BHV-1 vaccination use in this study population, training on the importance of biosecurity and vaccination for BHV-1 are recommended to reduce the transmission and impacts of BHV-1.