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BACKGROUND: Accurate measurement of disease associated with endemic bacterial agents in pig populations is challenging due to their commensal ecology, the lack of disease-specific antemortem diagnostic tests, and the polymicrobial nature of swine diagnostic cases. The main objective of this retrospective study was to estimate temporal patterns of agent detection and disease diagnosis for five endemic bacteria that can cause systemic disease in porcine tissue specimens submitted to the Iowa State University Veterinary Diagnostic Laboratory (ISU VDL) from 2017 to 2022. The study also explored the diagnostic value of specific tissue specimens for disease diagnosis, estimated the frequency of polymicrobial diagnosis, and evaluated the association between phase of pig production and disease diagnosis. RESULTS: S. suis and G. parasuis bronchopneumonia increased on average 6 and 4.3%, while S. suis endocarditis increased by 23% per year, respectively. M. hyorhinis and A. suis associated serositis increased yearly by 4.2 and 12.8%, respectively. A significant upward trend in M. hyorhinis arthritis cases was also observed. In contrast, M. hyosynoviae arthritis cases decreased by 33% average/year. Investigation into the diagnostic value of tissues showed that lungs were the most frequently submitted sample, However, the use of lung for systemic disease diagnosis requires caution due to the commensal nature of these agents in the respiratory system, compared to systemic sites that diagnosticians typically target. This study also explored associations between phase of production and specific diseases caused by each agent, showcasing the role of S. suis arthritis in suckling pigs, meningitis in early nursery and endocarditis in growing pigs, and the role of G. parasuis, A. suis, M. hyorhinis and M. hyosynoviae disease mainly in post-weaning phases. Finally, this study highlighted the high frequency of co-detection and -disease diagnosis with other infectious etiologies, such as PRRSV and IAV, demonstrating that to minimize the health impact of these endemic bacterial agents it is imperative to establish effective viral control programs. CONCLUSIONS: Results from this retrospective study demonstrated significant increases in disease diagnosis for S. suis, G. parasuis, M. hyorhinis, and A. suis, and a significant decrease in detection and disease diagnosis of M. hyosynoviae. High frequencies of interactions between these endemic agents and with viral pathogens was also demonstrated. Consequently, improved control programs are needed to mitigate the adverse effect of these endemic bacterial agents on swine health and wellbeing. This includes improving diagnostic procedures, developing more effective vaccine products, fine-tuning antimicrobial approaches, and managing viral co-infections.
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Actinobacillus suis , Artrite , Endocardite , Infecções por Mycoplasma , Mycoplasma hyorhinis , Mycoplasma hyosynoviae , Streptococcus suis , Doenças dos Suínos , Humanos , Suínos , Animais , Infecções por Mycoplasma/veterinária , Iowa/epidemiologia , Estudos Retrospectivos , Universidades , Doenças dos Suínos/diagnóstico , Doenças dos Suínos/epidemiologia , Doenças dos Suínos/microbiologia , Artrite/veterinária , Endocardite/veterináriaRESUMO
We evaluated an active participatory design for the regional surveillance of notifiable swine pathogens based on testing 10 samples collected by farm personnel in each participating farm. To evaluate the performance of the design, public domain software was used to simulate the introduction and spread of a pathogen among 17,521 farms in a geographic region of 1,615,246 km2. Using the simulated pathogen spread data, the probability of detecting ≥ 1 positive farms in the region was estimated as a function of the percent of participating farms (20%, 40%, 60%, 80%, 100%), farm-level detection probability (10%, 20%, 30%, 40%, 50%), and regional farm-level prevalence. At 0.1% prevalence (18 positive farms among 17,521 farms) and a farm-level detection probability of 30%, the participatory surveillance design achieved 67%, 90%, and 97% probability of detecting ≥ 1 positive farms in the region when producer participation was 20%, 40%, and 60%, respectively. The cost analysis assumed that 10 individual pig samples per farm would be pooled into 2 samples (5 pigs each) for testing. Depending on the specimen collected (serum or swab sample) and test format (nucleic acid or antibody detection), the cost per round of sampling ranged from EUR 0.017 to EUR 0.032 (USD 0.017 to USD 0.034) per pig in the region. Thus, the analysis suggested that an active regional participatory surveillance design could achieve detection at low prevalence and at a sustainable cost.
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Biosecurity practices aim to reduce the frequency of disease outbreaks in a farm, region, or country and play a pivotal role in fortifying the country's pork industry against emerging threats, particularly foreign animal diseases (FADs). This article addresses the current biosecurity landscape of the US swine industry by summarizing the biosecurity practices reported by the producers through the United States Swine Health Improvement Plan (US SHIP) enrollment surveys, and it provides a general assessment of practices implemented. US SHIP is a voluntary, collaborative effort between industry, state, and federal entities regarding health certification programs for the swine industry. With 12,195 sites surveyed across 31 states, the study provides a comprehensive snapshot of current biosecurity practices. Key findings include variability by site types that have completed Secure Pork Supply plans, variability in outdoor access and presence of perimeter fencing, and diverse farm entry protocols for visitors. The data also reflect the industry's response to the threat of FADs, exemplified by the implementation of the US SHIP in 2020. As the US SHIP program advances, these insights will guide industry stakeholders in refining biosecurity practices, fostering endemic re-emerging and FAD preparedness, and ensuring the sustainability of the swine industry in the face of evolving challenges.
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This study evaluated the use of endemic enteric coronaviruses polymerase chain reaction (PCR)-negative testing results as an alternative approach to detect the emergence of animal health threats with similar clinical diseases presentation. This retrospective study, conducted in the United States, used PCR-negative testing results from porcine samples tested at six veterinary diagnostic laboratories. As a proof of concept, the database was first searched for transmissible gastroenteritis virus (TGEV) negative submissions between January 1st, 2010, through April 29th, 2013, when the first porcine epidemic diarrhea virus (PEDV) case was diagnosed. Secondly, TGEV- and PEDV-negative submissions were used to detect the porcine delta coronavirus (PDCoV) emergence in 2014. Lastly, encountered best detection algorithms were implemented to prospectively monitor the 2023 enteric coronavirus-negative submissions. Time series (weekly TGEV-negative counts) and Seasonal Autoregressive-Integrated Moving-Average (SARIMA) were used to control for outliers, trends, and seasonality. The SARIMA's fitted and residuals were then subjected to anomaly detection algorithms (EARS, EWMA, CUSUM, Farrington) to identify alarms, defined as weeks of higher TGEV-negativity than what was predicted by models preceding the PEDV emergence. The best-performing detection algorithms had the lowest false alarms (number of alarms detected during the baseline) and highest time to detect (number of weeks between the first alarm and PEDV emergence). The best-performing detection algorithms were CUSUM, EWMA, and Farrington flexible using SARIMA fitted values, having a lower false alarm rate and identified alarms 4 to 17 weeks before PEDV and PDCoV emergences. No alarms were identified in the 2023 enteric negative testing results. The negative-based monitoring system functioned in the case of PEDV propagating epidemic and in the presence of a concurrent propagating epidemic with the PDCoV emergence. It demonstrated its applicability as an additional tool for diagnostic data monitoring of emergent pathogens having similar clinical disease as the monitored endemic pathogens.
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Infecções por Coronavirus , Vírus da Diarreia Epidêmica Suína , Doenças dos Suínos , Vírus da Gastroenterite Transmissível , Animais , Suínos , Vírus da Gastroenterite Transmissível/genética , Vírus da Gastroenterite Transmissível/isolamento & purificação , Vírus da Diarreia Epidêmica Suína/isolamento & purificação , Vírus da Diarreia Epidêmica Suína/genética , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/veterinária , Infecções por Coronavirus/virologia , Infecções por Coronavirus/epidemiologia , Doenças dos Suínos/virologia , Doenças dos Suínos/diagnóstico , Estudos Retrospectivos , Gastroenterite Suína Transmissível/diagnóstico , Gastroenterite Suína Transmissível/virologia , Gastroenterite Suína Transmissível/epidemiologia , Reação em Cadeia da Polimerase/métodos , Deltacoronavirus/genética , Deltacoronavirus/isolamento & purificação , Estados Unidos/epidemiologiaRESUMO
A porcine reproductive and respiratory syndrome virus (PRRSV) type 2 (PRRSV-2) isolate was obtained from lung samples collected from a 4.5-month-old pig at a wean-to-finish site in Indiana, USA, although no gross or microscopic lesions suggestive of PRRSV infection were observed in the lung tissue. Phylogenetic and molecular evolutionary analyses based on the obtained virus sequences indicated that PRRSV USA/IN105404/2021 was a natural recombinant isolate from Ingelvac PRRS® MLV and Prevacent® PRRS, which are PRRSV-2-modified live virus vaccines commercially available in the United States. This study is the first to report the detection of a PRRSV-2 recombinant strain consisting entirely of two modified live virus vaccine strains under field conditions. Based on clinical data and the absence of lung lesions, this PRRSV-2 recombinant strain was not virulent in swine, although its pathogenicity needs to be confirmed by clinical trials.
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Sow mortality has significantly increased throughout the world over the past several years, and it is a growing concern to the global swine industry. Sow mortality increases economic losses, including higher replacement rates, affects employees' morale, and raises concerns about animal well-being and sustainability. This study aimed to assess herd-level risk factors associated with sow mortality in a large swine production system in the Midwestern United States. This retrospective observational study used available production, health, nutritional, and management information between July 2019 and December 2021. A Poisson mixed regression model was used to identify the risk factors and to build a multivariate model using the weekly mortality rate per 1000 sows as the outcome. Different models were used to identify the risk factors according to this study's main reasons for sow mortality (total death, sudden death, lameness, and prolapse). The main reported causes of sow mortality were sudden death (31.22 %), lameness (28.78 %), prolapse (28.02 %), and other causes (11.99 %). The median (25th-75th percentile) distribution of the crude sow mortality rate/1000 sows was 3.37 (2.19 - 4.16). Breeding herds classified as epidemic for porcine reproductive and respiratory syndrome virus (PRRSV) were associated with higher total death, sudden death, and lameness death. Open pen gestation was associated with a higher total death and lameness compared with stalls. Pulses of feed medication was associated with lower sow mortality rate for all outcomes. Farms not performing bump feeding were associated with higher sow mortality due to lameness and prolapses, while Senecavirus A (SVA)-positive herds were associated with a higher mortality rate for total deaths and deaths due to lameness. Disease interactions (herds Mycoplasma hyopneumoniae positive and epidemic for PRRSV; SVA positive herds and epidemic for PRRSV) were associated with higher mortality rates compared to farms with single disease status. This study identified and measured the major risk factors associated with total sow mortality rate, sudden deaths, lameness deaths, and prolapse deaths in breeding herds under field conditions.
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Vírus da Síndrome Respiratória e Reprodutiva Suína , Doenças dos Suínos , Animais , Feminino , Coxeadura Animal , Meio-Oeste dos Estados Unidos/epidemiologia , Fatores de Risco , Suínos , Doenças dos Suínos/epidemiologiaRESUMO
Influenza A virus (IAV) is an endemic respiratory pathogen affecting swine worldwide and is a public health concern as a zoonotic pathogen. Veterinarians may respond to IAV infection in swine with varied approaches depending on their perception of its economic impact on human and animal health. This study considered three primary veterinary practice categories: swine exclusive veterinary practitioner, large animal practitioner, which corresponds to veterinarians that work predominantly with food animals including but not exclusively porcine, and mixed animal practitioner, which corresponds to veterinarians working with companion and food animals. This survey aimed to assess U.S. veterinarian perceptions, biosecurity practices, and control methods for IAV in swine. In this study, 54.5% (188/345) of the veterinarians that were targeted responded to all portions of the survey. The study results presented different perceptions regarding IAV among veterinarians in different types of veterinary practices and the current IAV mitigation practices implemented in swine farms based on strategic decisions. Collectively, this study also revealed the veterinarians' perceptions that IAV as a health problem in swine is increasing, IAV has a moderate economic impact, and there is a high level of concern regarding IAV circulating in swine. These findings highlight the need for IAV surveillance data, improved vaccine strategies, as well as important opportunities regarding methods of control and biosecurity. Additionally, results of this survey suggest biosecurity practices associated with the veterinarian's swine operations and prevention of zoonotic diseases can be strengthened through annual IAV vaccination of humans and support of sick leave policies for farm workers.
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The performance of five forecasting models was investigated for predicting nursery mortality using the master table built for 3242 groups of pigs (~13 million animals) and 42 variables, which concerned the pre-weaning phase of production and conditions at placement in growing sites. After training and testing each model's performance through cross-validation, the model with the best overall prediction results was the Support Vector Machine model in terms of Root Mean Squared Error (RMSE = 0.406), Mean Absolute Error (MAE = 0.284), and Coefficient of Determination (R2 = 0.731). Subsequently, the forecasting performance of the SVM model was tested on a new dataset containing 72 new groups, simulating ongoing and near real-time forecasting analysis. Despite a decrease in R2 values on the new dataset (R2 = 0.554), the model demonstrated high accuracy (77.78%) for predicting groups with high (>5%) or low (<5%) nursery mortality. This study demonstrated the capability of forecasting models to predict the nursery mortality of commercial groups of pigs using pre-weaning information and stocking condition variables collected post-placement in nursery sites.
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Aggregated diagnostic data collected over time from swine production systems is an important data source to investigate swine productivity and health, especially when combined with records concerning the pre-weaning and post-weaning phases of production. The combination of multiple data streams collected over the lifetime of the pigs is the essence of the whole-herd epidemiological investigation. This approach is particularly valuable for investigating the multifaceted and ever-changing factors contributing to wean-to-finish (W2F) swine mortality. The objective of this study was to use a retrospective dataset ("master table") containing information on 1,742 groups of pigs marketed over time to identify the major risk factors associated with W2F mortality. The master table was built by combining historical breed-to-market performance and health data with disease diagnostic records (Dx Codes) from marketed groups of growing pigs. After building the master table, univariate analyses were conducted to screen for risk factors to be included in the initial multivariable model. After a stepwise backward model selection approach, 5 variables and 2 interactions remained in the final model. Notably, the diagnosis variable significantly associated with W2F mortality was porcine reproductive and respiratory syndrome virus (PRRSV). Closeouts with clinical signs suggestive of Salmonella spp. or Escherichia coli infection were also associated with higher W2F mortality. Source sow farm factors that remained significantly associated with W2F mortality were the sow farm PRRS status, average weaning age, and the average pre-weaning mortality. After testing for the possible interactions in the final model, two interactions were significantly associated with wean-to-finish pig mortality: (1) sow farm PRRS status and a laboratory diagnosis of PRRSV and (2) average weaning age and a laboratory diagnosis of PRRS. Closeouts originating from PRRS epidemic or PRRS negative sow farms, when diagnosed with PRRS in the growing phase, had the highest W2F mortality rates. Likewise, PRRS diagnosis in the growing phase was an important factor in mortality, regardless of the average weaning age of the closeouts. Overall, this study demonstrated the utility of a whole-herd approach when analyzing diagnostic information along with breeding-to-market productivity and health information, to measure the major risk factors associated with W2F mortality in specified time frames and pig populations.
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Introduction: The porcine reproductive and respiratory syndrome virus (PRRSV) continues to challenge swine production in the US and most parts of the world. Effective PRRSV surveillance in swine herds can be challenging, especially because the virus can persist and sustain a very low prevalence. Although weaning-age pigs are a strategic subpopulation in the surveillance of PRRSV in breeding herds, very few sample types have been validated and characterized for surveillance of this subpopulation. The objectives of this study, therefore, were to compare PRRSV RNA detection rates in serum, oral swabs (OS), nasal swabs (NS), ear-vein blood swabs (ES), and family oral fluids (FOF) obtained from weaning-age pigs and to assess the effect of litter-level pooling on the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of PRRSV RNA. Methods: Three eligible PRRSV-positive herds in the Midwestern USA were selected for this study. 666 pigs across 55 litters were sampled for serum, NS, ES, OS, and FOF. RT-qPCR tests were done on these samples individually and on the litter-level pools of the swabs. Litter-level pools of each swab sample type were made by combining equal volumes of each swab taken from the pigs within a litter. Results: Ninety-six piglets distributed across 22 litters were positive by PRRSV RT-qPCR on serum, 80 piglets distributed across 15 litters were positive on ES, 80 piglets distributed across 17 litters were positive on OS, and 72 piglets distributed across 14 litters were positive on NS. Cohen's kappa analyses showed near-perfect agreement between all paired ES, OS, NS, and serum comparisons (). The serum RT-qPCR cycle threshold values (Ct) strongly predicted PRRSV detection in swab samples. There was a ≥ 95% probability of PRRSV detection in ES-, OS-, and NS pools when the proportion of positive swab samples was ≥ 23%, ≥ 27%, and ≥ 26%, respectively. Discussion: ES, NS, and OS can be used as surveillance samples for detecting PRRSV RNA by RT-qPCR in weaning-age pigs. The minimum number of piglets to be sampled by serum, ES, OS, and NS to be 95% confident of detecting ≥ 1 infected piglet when PRRSV prevalence is ≥ 10% is 30, 36, 36, and 40, respectively.
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The open reading frames (ORF)5 represents approximately 4% of the porcine reproductive and respiratory syndrome virus (PRRSV)-2 genome (whole-PRRSV) and is often determined by the Sanger technique, which rarely detects >1 PRRSV strain if present in the sample. Next-generation sequencing (NGS) may provide a more appropriate method of detecting multiple PRRSV strains in one sample. This work assessed the effect of PRRSV genetic variability and recombination events, using NGS, on the time-to-low prevalence (TTLP) and total losses in breeding herds (n 20) that detected a PRRSV outbreak and adopted measures to eliminate PRRSV. Serum, lung or live virus inoculation material collected within 3-weeks of outbreak, and subsequently, processing fluids (PFs) were tested for PRRSV by RT-qPCR and NGS. Recovered whole-PRRSV or partial sequences were used to characterize within and between herd PRRSV genetic variability. Whole-PRRSV was recovered in five out of six (83.3%) lung, 16 out of 22 (72.73%) serum and in five out of 95 (5.26%) PF. Whole-PRRSV recovered from serum or lung were used as farm referent strains in 16 out of 20 (80%) farms. In four farms, only partial genome sequences were recovered and used as farm referent strains. At least two wild-type PRRSV strains (wt-PRRSV) were circulating simultaneously in 18 out of 20 (90%) and at least one vaccine-like strain co-circulating in eight out of 20 (40%) farms. PRRSV recombination events were detected in 12 farms (59%), been 10 out of 12 between wt-PRRSV and two out of 12 between wt-PRRSV and vaccine-like strains. Farms having ≥3 strains had a 12-week increase TTLP versus herds ≤2 strains detected. Farms with ≤2 strains (n 10) had 1837 and farms with no recombination events detected (n 8) had 1827 fewer piglet losses per 1000 sows versus farms with ≥3 PRRSV strains (n 8) or detected recombination (n 10), respectively. NGS outcomes and novel visualization methods provided more thorough insight into PRRSV dynamics, genetic variability, detection of multiple strains co-circulating in breeding herds and helped establish practical guidelines for using PRRSV NGS outputs.
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Síndrome Respiratória e Reprodutiva Suína , Vírus da Síndrome Respiratória e Reprodutiva Suína , Doenças dos Suínos , Vacinas Virais , Animais , Feminino , Sequenciamento de Nucleotídeos em Larga Escala/veterinária , Fases de Leitura Aberta , Síndrome Respiratória e Reprodutiva Suína/epidemiologia , Síndrome Respiratória e Reprodutiva Suína/prevenção & controle , Vírus da Síndrome Respiratória e Reprodutiva Suína/genética , SuínosRESUMO
Family oral fluids (FOFs) are an aggregate sample type shown to be a cost-efficient and convenient option for determining the porcine reproductive and respiratory syndrome virus (PRRSV) status of weaning age pigs. This study investigates the effect of pooling PRRSV-positive FOF samples with PRRSV-negative FOF samples at different levels (1/3, 1/5, 1/10, 1/20) on the probability of PRRSV RNA detection by reverse-transcription real-time polymerase chain reaction (RT-rtPCR). Mathematical models were built to assess how much the probability of RT-rtPCR PRRSV detection changed with increasing proportion of PRRSV-positive samples present within pools and how partially sampling a farrowing room influenced the probability of RT-rtPCR detection of PRRSV RNA in pooled samples at different prevalence scenarios. A general example of a guideline for FOF-based sampling under different prevalence scenarios to detect PRRSV RNA by RT-rtPCR with at least 95 % certainty is presented. At the sample level, the probability of detecting PRRSV RNA by RT-rtPCR decreased from 100 % to 87 %, 68 %, and 26 % when diluting up to 1/20 for PRRSV positive FOF having an initial Cycle threshold (Ct) below 34, between 34 and 36, or above 36, respectively. When PRRSV prevalence is near-zero (1 or 2 litters positive out of 56), the most cost-efficient farrowing room sampling strategy to detect PRRSV RNA with at least 95 % certainty was pooling FOF samples up to 1/10; at higher prevalence (≥ 3 of 56 litters positive), the most cost-efficient strategy was submitting samples in pools of 20. Subsampling a farrowing room for FOF pools was also demonstrated to be a valuable cost-saving strategy. Overall, based on the conditions of this study, pooling FOFs up to 1/20 is a valid option in situations of cost constraint and regardless of pooling level chosen, capturing as many litters as possible improves the probability of PRRSV detection.
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Síndrome Respiratória e Reprodutiva Suína , Vírus da Síndrome Respiratória e Reprodutiva Suína , Doenças dos Suínos , Animais , Anticorpos Antivirais/análise , Síndrome Respiratória e Reprodutiva Suína/diagnóstico , Síndrome Respiratória e Reprodutiva Suína/epidemiologia , Vírus da Síndrome Respiratória e Reprodutiva Suína/genética , Probabilidade , RNA , Saliva/química , SuínosRESUMO
Swine wean-to-finish (W2F) mortality is a multifactorial, dynamic process and a key performance indicator of commercial swine production. Although swine producers typically capture the relevant data, analysis of W2F mortality risk factors is often hindered by the fact that, even if data is available, they are typically in different formats, non-uniform, and dispersed among multiple unconnected databases. In this study, an automated framework was created to link multiple data streams to specific cohorts of market animals, including sow farm productivity parameters, sow farm and growing pig health factors, facilities, management factors, and closeout data from a Midwestern USA production system. The final dataset (master-table) contained breeding-to-market data for 1,316 cohorts of pigs marketed between July 2018 and June 2019. Following integration into a master-table, continuous explanatory variables were categorized into quartiles averages, and the W2F mortality was log-transformed, reporting geometric mean mortality of 8.69 % for the study population. Further, univariate analyses were performed to identify individual variables associated with W2F mortality (p < 0.10) for further inclusion in a multivariable model, where model selection was applied. The final multivariable model consisted of 13 risk factors and accounted for 68.2 % (R2) of the variability of the W2F mortality, demonstrating that sow farm health and performance are closely linked to downstream W2F mortality. Higher sow farm productivity was associated with lower subsequent W2F mortality and, conversely, lower sow farm productivity with higher W2F mortality e.g., groups weaned in the highest quartiles for pre-weaning mortality and abortion rate had 13.5 %, and 12.5 %, respectively, which was statistically lower than the lowest quartiles for the same variables (10.5 %, and 10.6 %). Moreover, better sow farm health status was also associated with lower subsequent W2F mortality. A significant difference was detected in W2F mortality between epidemic versus negative groups for porcine reproductive and respiratory syndrome virus (15.4 % vs 8.7 %), and Mycoplasma hyopneumoniae epidemic versus negative groups (13.7 % vs 9.9 %). Overall, this study demonstrated the application of a whole-herd analysis by aggregating information of the pre-weaning phase with the post-weaning phase (breeding-to-market) to identify and measure the major risk factors of W2F mortality.
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Mortalidade , Mycoplasma hyopneumoniae , Vírus da Síndrome Respiratória e Reprodutiva Suína , Suínos , Aborto Animal , Animais , Feminino , Meio-Oeste dos Estados Unidos , Gravidez , Fatores de Risco , DesmameRESUMO
The control of porcine reproductive and respiratory syndrome virus (PRRSV) hinges on monitoring and surveillance. The objective of this study was to assess PRRSV RNA detection by RT-PCR in tongue tips from dead suckling piglets compared to serum samples, processing fluids, and family oral fluids. Tongue tips and serum samples were collected from three PRRSV-positive breeding herd farms (farms A, B, and C) of three different age groups: newborns (<24 h), processing (2 to 7 days of age), and weaning (18 to 22 days of age). Additionally, processing fluids and family oral fluids were collected from 2-7 days of age and weaning age, respectively. In farms A and B, PRRSV RNA was detected in tongue tips from all age groups (100 and 95%, respectively). In addition, PRRSV RNA was detected in pooled serum samples (42 and 27%), processing fluids (100 and 50%), and family oral fluids (11 and 22%). Interestingly, the average Ct value from tongue tips was numerically lower than the average Ct value from serum samples in the newborn age. In farm C, PRRSV RNA was only detected in serum samples (60%) and family oral fluids (43%), both from the weaning age. Further, no PRRSV RNA was detected in tongue tips when pooled serum samples from the same age group tested PRRSV RNA-negative. Taken together, these results demonstrate the potential value of tongue tips for PRRSV monitoring and surveillance.
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Porcine reproductive and respiratory syndrome (PRRS) is an important economic swine disease. The usage of PRRS-modified live vaccines (MLV) is the predominant breeding herd immunologic solution used in the United States to minimize the economic losses associated with wild-type PRRS infection. Most of the current information on the effects of contemporary PRRS MLV vaccination on breeding herd performance under field conditions comes from herds with previous PRRS virus (PRRSV) exposure. Hence, there is little information on key performance indicators (KPI) changes after the exposure to a PRRS MLV in PRRSV-naïve breeding herds. The main objective of this longitudinal observational study was to describe selected KPI changes in a naïve breeding herd after PRRS MLV exposure. The secondary objective was to describe the pattern of detection of PRRSV RNA by the quantitative reverse transcriptase-polymerase chain reaction in processing fluid samples. There were transient increases for mummies during weeks 4-23 (+0.86%); increased pre-weaning mortality on weeks 3-5 (+3.76%); a decrease in live born on weeks 4-5 (-0.46) leading to a decreased pig weaned/litter on weeks 5-10 (-0.69) and increased repeated services on weeks 3-23 (+5.53%). Transient changes observed after PRRS MLV exposures did not move total pigs weaned to outside the control intervals. Starting on week 83 and for 53 consecutive weeks, there was no PRRSV detection in processing fluids, even though two whole-herd MLV exposures occurred within that period.
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Síndrome Respiratória e Reprodutiva Suína , Vírus da Síndrome Respiratória e Reprodutiva Suína , Doenças dos Suínos , Vacinas Virais , Animais , Suínos , Vacinação/veterinária , Vacinas AtenuadasRESUMO
Porcine reproductive and respiratory syndrome (PRRS) is a disease caused by the PRRS virus (PRRSV) that has spread globally in the last 30 years and causes huge economic losses every year. This research aims to 1) investigate the relationship between the PRRSV detection in two age categories (wean-to-market and adult/sow farm), and 2) examine the extent to which the wean-to-market PRRSV positive rate forecasts the adult/sow farm PRRSV positive rate. The data we used are the PRRSV RNA detection results between 2007 and 2019 integrated by the US Swine Disease Reporting System project that represent 95% of all porcine submissions tested in the US National Animal Health Network. We first use statistical tools to investigate to what extent the increase in PRRSV positive submissions in the wean-to-market is related to the PRRSV increase in adult/sow farms. The statistical analysis confirms that an increase in the PRRSV positive rate of wean-to-market precedes the increase in the adult/sow farms to a large extent. Then we create the dynamic exponentially weighted moving average control charts to identify out-of-control points (i.e., signals) in the PRRSV rates for both wean-to-market and adult/sow farms. This control-chart-based analysis finds that 78% of PRRSV signals in the wean-to-market are followed by a PRRSV rate signal in the adult/sow farms within eight weeks. We expect that our findings will help the producers and veterinarians to justify and reinforce the implementation of bio-security and bio-contaminant practices to curb disease spread across farms.
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Síndrome Respiratória e Reprodutiva Suína/epidemiologia , Vírus da Síndrome Respiratória e Reprodutiva Suína , RNA Viral/análise , Fatores Etários , Criação de Animais Domésticos/estatística & dados numéricos , Animais , Feminino , Modelos Estatísticos , Síndrome Respiratória e Reprodutiva Suína/diagnóstico , Síndrome Respiratória e Reprodutiva Suína/virologia , Vírus da Síndrome Respiratória e Reprodutiva Suína/genética , Suínos/virologia , Estados Unidos/epidemiologiaRESUMO
A porcine reproductive and respiratory syndrome virus 2 strain was identified in lung samples from nursery piglets associated with a 17.15% mortality rate on a swine farm in Iowa. Open reading frame 5 (ORF5) sequencing indicated that this strain is a restriction fragment length polymorphism (RFLP) 1-4-4 lineage 1C variant strain, and its complete coding genome sequence was determined.
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The genetic diversity of porcine reproductive and respiratory syndrome virus (PRRSV) increases over time. In 1998, restriction-fragment length polymorphism (RFLP) pattern analysis was introduced to differentiate PRRSV wild-type strains from VR2332, a reference strain from which a commercial vaccine (Ingelvac PRRS MLV) was derived. We have characterized here the PRRSV genetic diversity within selected RFLP families over time and U.S. geographic space, using available ISU-VDL data from 2007 to 2019. The 40,454 ORF5 sequences recovered corresponded to 228 distinct RFLPs. Four RFLPs [2-5-2 (21.2%), 1-7-4 (15.6%), 1-4-4 (11.8%), and 1-8-4 (9.9%)] represented 58.5% of all ORF5 sequences and were used for cluster analysis. Over time, there was increased detection of RFLPs 2-5-2, 1-7-4, 1-3-4, 1-3-2, and 1-12-4; decreased detection of 1-4-2, 1-18-4, 1-18-2, and 1-2-2; and different detection trends for 1-8-4, 1-4-4, 1-26-1, 1-22-2, and 1-2-4. An over-time cluster analysis revealed a single cluster for RFLP 2-5-2, supporting that sequences within RFLP 2-5-2 are still relatively conserved. For 1-7-4, 1-4-4, and 1-8-4, there were multiple clusters. State-wise cluster analysis demonstrated 4 main clusters for RFLP 1-7-4 and 1-8-4, and 6 for RFLP 1-4-4. For the other RFLPs, there was a significant genetic difference within them, particularly between states. RFLP typing is limited in its ability to discriminate among different strains of PRRSV. Understanding the magnitude of genetic divergence within RFLPs helps develop PRRSV regional control programs, placement, herd immunization strategies, and design of appropriate animal movements across borders to minimize the risk of PRRSV transmission.
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Síndrome Respiratória e Reprodutiva Suína , Vírus da Síndrome Respiratória e Reprodutiva Suína , Doenças dos Suínos , Animais , Variação Genética , Filogenia , Polimorfismo de Fragmento de Restrição , Síndrome Respiratória e Reprodutiva Suína/epidemiologia , Vírus da Síndrome Respiratória e Reprodutiva Suína/genética , Suínos , Estados Unidos/epidemiologiaRESUMO
Accurate and timely results of diagnostic investigations and laboratory testing guide clinical interventions for the continuous improvement of animal health and welfare. Infectious diseases can severely limit the health, welfare, and productivity of populations of animals. Livestock veterinarians submit thousands of samples daily to veterinary diagnostic laboratories (VDLs) for disease diagnosis, pathogen monitoring, and surveillance. Individual diagnostic laboratory reports are immediately useful; however, aggregated historical laboratory data are increasingly valued by clinicians and decision-makers to identify changes in the health status of various animal populations over time and geographical space. The value of this historical information is enhanced by visualization of trends of agent detection, disease diagnosis, or both, which helps focus time and resources on the most significant pathogens and fosters more effective communication between livestock producers, veterinarians, and VDL professionals. Advances in data visualization tools allow quick, efficient, and often real-time scanning and analysis of databases to inform, guide, and modify animal health intervention algorithms. Value is derived at the farm, production system, or regional level. Visualization tools allow client-specific analyses, benchmarking, formulation of research questions, and monitoring the effects of disease management and precision farming practices. We present here the approach taken to visualize trends of disease occurrence using porcine disease diagnostic code data for the period 2010 to 2019. Our semi-automatic standardized creation of a visualization platform allowed the transformation of diagnostic report data into aggregated information to visualize and monitor disease diagnosis.
Assuntos
Codificação Clínica/estatística & dados numéricos , Gestão da Saúde da População , Doenças dos Suínos/diagnóstico , Medicina Veterinária/métodos , Animais , Sus scrofa , SuínosRESUMO
Every day, thousands of samples from diverse populations of animals are submitted to veterinary diagnostic laboratories (VDLs) for testing. Each VDL has its own laboratory information management system (LIMS), with processes and procedures to capture submission information, perform laboratory tests, define the boundaries of test results (i.e., positive or negative), and report results, in addition to internal business and accounting applications. Enormous quantities of data are accumulated and stored within VDL LIMSs. There is a need for platforms that allow VDLs to exchange and share portions of laboratory data using standardized, reliable, and sustainable information technology processes. Here we report concepts and applications for standardization and aggregation of data from swine submissions to multiple VDLs to detect and monitor porcine enteric coronaviruses by RT-PCR. Oral fluids, feces, and fecal swabs were the specimens submitted most frequently for enteric coronavirus testing. Statistical algorithms were used successfully to scan and monitor the overall and state-specific percentage of positive submissions. Major findings revealed a consistently recurrent seasonal pattern, with the highest percentage of positive submissions detected during December-February for porcine epidemic diarrhea virus, porcine deltacoronavirus, and transmissible gastroenteritis virus (TGEV). After 2014, very few submissions tested positive for TGEV. Monitoring VDL data proactively has the potential to signal and alert stakeholders early of significant changes from expected detection. We demonstrate the importance of, and applications for, data organized and aggregated by using LOINC and SNOMED CTs, as well as the use of customized messaging to allow inter-VDL exchange of information.