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Mortality during the post-weaning phase is a critical indicator of swine production system performance, influenced by a complex interaction of multiple factors of the epidemiological triad. This study leveraged retrospective data from 1723 groups of pigs marketed within a US swine production system to develop a Wean-Quality Score (WQS) using machine learning techniques. The study evaluated three machine learning models, Random Forest, Support Vector Machine, and Gradient Boosting Machine, to classify groups having high or low 60-day mortality, where high mortality groups represented 25 % of the groups among the study population with the highest mortality values (n=431; 60-day mortality=9.98 %), and the remaining 75 % of the groups were of low mortality (n=1292; 60-day mortality=2.75 %). The best-performing model, Random Forest (RF), outperformed the other ML models in terms of accuracy (0.90), sensitivity (0.84), and specificity (0.92) metrics, and was then selected for further analysis, which consisted of creating the WQS and ranking the most important factors for classifying groups as high or low mortality. The most important factors ranked through the RF model to classify groups with high mortality were pre-weaning mortality, weaning age, average parity of litters in sow farms, and PRRS status. Additionally, stocking conditions such as stocking density and time to fill the barn were important predictors of high mortality. The WQS was developed and correlated (r = 0.74) with the actual 60-day mortality of the groups, offering a valuable tool for assessing post-weaning survivability in swine production systems before weaning. This study highlights the potential of machine learning and comprehensive data utilization to improve the assessment and management of weaned pig quality in commercial swine production, which producers can utilize to identify and intervene in groups, according to the WQS., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: A Tonsil-Oral-Scrubbing (TOSc) method was developed to sample the sow's oropharyngeal and tonsillar area without snaring and has shown comparable porcine reproductive and respiratory syndrome virus (PRRSV) RNA detection rates with tonsil scraping in infected sows. This study investigated the effect of specific TOSc collection factors on the PRRSV RT-rtPCR results (detection rates and Ct values). Those factors include whether the sow was snared or not snared at TOSc collection ("snared" vs. "not snared"); whether the sow was laying down or standing at collection ("laying down" vs. "standing"); and type of collectors used for TOSc collection ("TOSc prototype" vs. "Spiral-headed AI catheter (SHAC)"). Volume of fluid was compared between "snared" and "not snared" groups, and collection time was compared between "laying down" and "standing" groups as well., Results: The effect for each factor was assessed in three independent studies following the same design: TOSc was collected twice from each studied sow, once with the baseline level for a factor ("not snared", or "standing", or "TOSc prototype"), and another time followed by the other level of the paired factor ("snared", "laying down", or "SHAC", correspondingly). Results showed that "not snared" TOSc had numerically higher PRRSV RNA detection rate (60.7% vs. 52.5%, p = 0.11), significantly lower median Ct values (31.9 vs. 32.3, p < 0.01), and significantly higher volume of fluid than "snared" samples (1.8 mL vs. 1.2 mL, p < 0.01); "laying down" TOSc samples did not differ statistically (60.7% vs. 60.7%) in the PRRSV RNA detection rate, obtained numerically lower median Ct values (30.9 vs. 31.3, p = 0.19), but took 40% less collection time compared to "standing" TOSc samples; samples collected using the "TOSc prototype" had numerically higher PRRSV RNA detection rate (91.7% vs. 88.3%, p = 0.27) and significantly lower median Ct values (32.8 vs. 34.5, p < 0.01) than that from "SHAC"., Conclusions: Under the conditions of this study best practices for TOSc collection aiming higher detection rate of PRRSV RNA while minimizing time for collection were suggested to be sampling TOSc without snaring, when sows are laying down, and using a prototype TOSc collector., (© 2024. The Author(s).)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Magalhães, Zimmerman, Thomas, Moura, Trevisan, Schwartz, Burrough, Holtkamp, Wang, Rademacher, Silva and Linhares.)

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 (R 2 = 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 R 2 values on the new dataset (R 2 = 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.

Background: The Hungarian national eradication program of PRRS was successfully completed between 2014 and 2022. There were doubts about the efficiency of the eradication program in Hungary from the beginning to the tune that it might only be carried out efficiently through depopulation-repopulation of the infected herds, which is a very costly procedure. In our study, we investigated the impact of the depopulation-repopulation procedure, which played a prominent role in the PRRS eradication program on the productivity of the Hungarian swine sector-namely, on the number of slaughter pigs per sow per year and the total live slaughter weight per sow per year., Material and Methods: Since 2014, we monitored the evolution of the PRRS eradication through the depopulation-repopulation approach on the large-scale breeding herds in Hungary. Most producers replaced their herds with animals that were free of PRRS and other infectious diseases (mycoplasmosis, actinobacillosis, swine dysentery, atrophic rhinitis, etc.). On this basis, we evaluated the change in the number of slaughter pigs per sow per year as a consequence of depopulation-repopulation of the herds being carried out. In the statistical analysis linear regression was used., Conclusions: The results of our study demonstrate that the PRRS eradication program with the herd depopulation-repopulation approach led to a considerable improvement of the productivity of Hungarian pig farming. This result also demonstrates that, independent of the PRRS eradication, it is still necessary to consider investments into the individual production units to increase efficiency, and to carry out herd depopulation-repopulation in cases where the current genetics limits improvements in productivity.

Background: Ileitis is a wasting disease of pigs. Clinical symptoms are diarrhea in growing pigs, wasting and reduced performance. Ileitis is ubiquitous in pig producing countries all around the world. It is estimated that the economic losses caused by the disease are USD 4.65 per fattening pig, and American pig farmers lose USD 56.1 million annually. It has become necessary to develop a slaughterhouse ileitis monitoring method that is simple, feasible to perform at modern slaughter lines, leads to immediate results and is cost effective. The practical experiences of applying the method are presented below., Methods: Our studies were performed on pig herds and slaughterhouses in Central European countries (Hungary, Romania, Poland, Croatia, and Slovakia). Experiences were evaluated based on visual and palpation. The results of our investigations were evaluated by a scoring method. Authors made histological and immunohistochemical examinations of investigated ileums. The hypothetic economic losses due to the disease in each farm were determined by estimating the loss of profit according to Holtkamp's presentation in 2019., Results: The essentials of the method we have developed are: it can be performed during slaughterhouse processing, it does not interfere with or make it impossible to carry out normal technological processes, and the results of the procedure are correlated with the results of other laboratory diagnostic tests for ileitis (histology, immunohistochemistry, herd serology, fecal PCR). It is noteworthy that the results of the method can be used to immediately estimate the impact of Lawsonia intracellularis infection on the performance of the herd from which the slaughter animals come., Conclusion: Using the results of the slaughtered pigs' visual and tactile examination at the slaughterhouse, the magnitude of the loss caused by Lawsonia intracellularis infection can be estimated quickly and accurately, and the return on investment of the strategy to be applied can be accurately planned., Competing Interests: I.M., P.M., H.,S., S.v.B. are employed by MSD Animal Health, which have a commercial interest in selling pharmaceutical products for pigs. The employment did not inflict any bias regarding the study, which has been conducted as part of the first author&rsquo;s enrolment as independent researcher. Other authors declare no conflict of interest.

Porcine reproductive and respiratory syndrome virus (PRRSV) causes a significant economic impact on swine production. It has been demonstrated that PRRS modified-live virus (MLV) vaccination of pigs, with one full dose, significantly reduces clinical consequences of wild-type PRRSV infection compared to non-vaccinates. However, there is limited information about the effect that two doses of PRRSV MLV vaccine have on the performance of growing pigs, compared to vaccination with a single dose. This study was conducted with the objectives to compare (a) the wild-type PRRSV detection in oral fluids over time, (b) key closeout productivity indicators, and (c) economic performance between lots of growing pigs vaccinated with two doses of Ingelvac PRRS® MLV vaccine and lots vaccinated with a single dose of the same vaccine. This randomized field trial included 15 lots of growing pigs from PRRSV positive-unstable sow farms and 66 lots from PRRSV positive-stable sow farms, according to the American association of swine veterinarians' terminology. All pig lots received the first vaccination either around processing or weaning age. Lots allocated in the two doses group received the second vaccination three to four weeks after the first vaccination. The pig lots were monitored for PRRSV detection over time. Six oral fluids samples were collected in three weeks intervals and were tested for wild-type PRRSV-2 RNA by RT-qPCR and open reading frame 5 (ORF)- 5 sequencing. Regression models were used to compare wild-type PRRSV detection dynamics on oral fluids samples and to compare key closeout performance indicators between one dose group and two doses group. Additionally, a benefit-cost ratio analysis compared economic performance between one dose group and two doses group. The proportion of wild-type PRRSV detection on oral fluids samples and the log counts of viral RNA per ml of oral fluids from the two doses group was lower than the one dose group on lots originated from PRRSV positive-stable sow farms, with a risk ratio of 1.24 and a rate ratio of 1.17, respectively. The two doses group had a significantly lower mortality rate than the one dose group, with a rate ratio of 1.21. The effect size increased on lots originated from PRRSV positive-unstable sow farms, and on lots with higher frequency and diversity of wild-type PRRSV detection during the growth phase. No differences in growth performance were detected between two doses group and one dose group. The second MLV vaccination dose had a benefit-cost ratio of 1.83. For lots originated from PRRSV positive-unstable farms, the benefit-cost ratio was 4.45, and for lots originated from PRRSV positive-stable farms, the benefit-cost ratio was 0.45. Under study conditions, vaccinating growing pig lots with two doses of PRRS MLV vaccine was a useful strategy to immunize growing pigs against PRRSV, lowering the wild-type PRRSV detection, lowering mortality rate, and increasing profitability, compared to lots of growing pigs that received a single dose of the same vaccine., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Effective biosecurity practices in swine production are key in preventing the introduction and dissemination of infectious pathogens. Ideally, on-farm biosecurity practices should be chosen by their impact on bio-containment and bio-exclusion; however, quantitative supporting evidence is often unavailable. Therefore, the development of methodologies capable of quantifying and ranking biosecurity practices according to their efficacy in reducing disease risk has the potential to facilitate better-informed choices of biosecurity practices. Using survey data on biosecurity practices, farm demographics, and previous outbreaks from 139 herds, a set of machine learning algorithms were trained to classify farms by porcine reproductive and respiratory syndrome virus status, depending on their biosecurity practices and farm demographics, to produce a predicted outbreak risk. A novel interpretable machine learning toolkit, MrIML-biosecurity, was developed to benchmark farms and production systems by predicted risk and quantify the impact of biosecurity practices on disease risk at individual farms. By quantifying the variable impact on predicted risk, 50% of 42 variables were associated with fomite spread while 31% were associated with local transmission. Results from machine learning interpretations identified similar results, finding substantial contribution to predicted outbreak risk from biosecurity practices relating to the turnover and number of employees, the surrounding density of swine premises and pigs, the sharing of haul trailers, distance from the public road and farm production type. In addition, the development of individualized biosecurity assessments provides the opportunity to better guide biosecurity implementation on a case-by-case basis. Finally, the flexibility of the MrIML-biosecurity toolkit gives it the potential to be applied to wider areas of biosecurity benchmarking, to address biosecurity weaknesses in other livestock systems and industry-relevant diseases., (© 2021 Wiley-VCH GmbH.)

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 % (R 2 ) 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., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Porcine reproductive and respiratory syndrome virus (PRRSV) became pandemic in the 1980's and today remains one of the most significant pathogens of the global swine industry. At the herd level, control of PRRSV is complicated by its extreme genetic diversity and its ability to persist in pigs, despite an active immune response. Ultimately, PRRSV control or elimination requires the coordination and active cooperation of producers and veterinarians at the regional level. Early voluntary PRRSV regional control programs focused on routine diagnostic testing and voluntary data-sharing regarding the PRRSV status of participants' herds, but no pre-defined action plans or decision trees were developed to secure project successes (or recover from failures). Given that control of PRRSV is paramount to producer profitability, we propose a coordinated approach for detecting, controlling, and ultimately eliminating wild-type PRRSV from herds participating in regional projects. Fundamental to project success is real-time, multi-platform communication of all data, information, and events that concern the regional project and project participants. New to this approach is the concept of agreed-upon action plans to be implemented by project participants in response to specific events or situations. The simultaneous and coordinated implementation of these strategies allows for early detection of wild-type PRRSV virus introductions and rapid intervention based on agreed-upon response plans. An example is given of a project in progress in the Midwest USA., Competing Interests: DC and DG are employed by Carthage Veterinary Service, Ltd. LG is employed by TriOak Foods Inc. RP is employed by Boehringer Ingelheim Animal Health USA Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Magalhães, Zimmerman, Holtkamp, Classen, Groth, Glowzenski, Philips, Silva and Linhares.)

Because contaminated livestock trailers are a significant risk for transmitting viruses between herds, various methods of washing, disinfecting, and thermo-assisted drying and decontamination (TADD) have been evaluated for their effectiveness in inactivating porcine reproductive and respiratory syndrome virus (PRRSV) on contaminated surfaces. Information on when to expect negative qRT-PCR results after adequate trailer sanitation is lacking. The objective of this study was to evaluate whether there are conditions associated with washing-disinfectant-TADD procedures that will consistently produce a negative qRT-PCR result for the purpose of monitoring compliance with trailer sanitation and decontamination protocols for PRRSV on metal surfaces. 144 diamond plate aluminum coupons were spiked with PRRSV or phosphate-buffered saline (PBS) and treated with a designated disinfectant protocol. Disinfectants evaluated included multiple accelerated® hydrogen peroxide (AHP) disinfectants and a quaternary ammonium and glutaraldehyde combination disinfectant. Disinfectant was applied for 5 or 60 minutes of contact time at either 20 °C or -10 °C in a matrix of feces or PBS. All coupons were heated until the surface temperature of the coupon reached 71 °C and then held for 10 minutes to simulate TADD under field conditions. Post-treatment swabs for all treatment groups, except negative control groups, were positive by PRRSV qRT-PCR. Under the conditions evaluated in this study, consistently negative qRT-PCR results after treatments were not found. Therefore, for the purpose of monitoring compliance with trailer sanitation and decontamination protocols for PRRSV, alternatives to qRT-PCR should be explored., (Copyright © 2021 Elsevier B.V. All rights reserved.)