This is our Friday rubric: every week a new Science Page from the Bob Morrison’s Swine Health Monitoring Project. The previous editions of the science page are available on our website.
This week we are sharing a report by Dr. Daniel Linhares’ lab at Iowa State University. The report summarizes the findings of his study regarding the factors making a sow farm vulnerable for PPRS introduction.
Key Points:
A model to quantify and identify biosecurity vulnerability in breeding herds is now available.
Events related to swine movements, transmission by air and water, and people movements were the variables most associated with PRRS outbreak.
Biosecurity vulnerability scores may help producers/veterinarians prioritize biosecurity investments.
Study Summary:
Herd-specific biosecurity assessments are needed to determine herd-specific risk for PRRS outbreaks. Thus, we developed and validated a biosecurity vulnerability score (BVS) that measures the relative vulnerability of swine breeding herds to PRRSv introduction. The BVS was based on a multi-criteria decision algorithm that ranked risk events associated with outbreaks. A comprehensive biosecurity assessment was used to obtain information of the biosecurity practices from each participating herd. The practices performed in each herd were weighted by the relative importance of each event obtained from an expert opinion panel resulting in a score that identifies the events that should be prioritized. In two independent data sets, the scores consistently revealed that farms with higher scores had a higher frequency of PRRS outbreaks. In addition, results suggest that events related to swine movements,transmission by air and water, and people movements should be prioritized.
Follow-up study:
We are developing a new screening tool to validate the minimum number of questions associated with frequency of PRRS outbreak. Study farms will be asked to fill out a short survey. This can help producers and veterinarians to identify sites at relatively higher risk of PRRSv introduction.
To enroll or to request additional clarification please contact: Gustavo Silva at Iowa State University (gustavos-at-iastate.edu)
We hope you all had a great Thanksgiving! An ever increasing amount of you is visiting this blog every month so thank you, we appreciate your support!
This is our Friday rubric: every week a new Science Page from the Bob Morrison’s Swine Health Monitoring Project. The previous editions of the science page are available on our website.
Monitoring cab cleaning and hot shot handle cleaning via Glo Germ Gel is simple and cost-effective.
Wiping down the cab interior with intervention wipes only adds around 5 minutes. These minor cost and time additions to truck wash procedures can help to prevent a million-dollar PRRS break.
Truck wash crew and trailer washers are often overlooked but perform a job that is essential in maintaining biosecurity and disease outbreak and therefore herd health.
The objective of this study was to assess overall biosecurity at the truck wash and identify potential areas of concern, measure and evaluate these areas of concern, and suggest solutions.
Potential Areas of Concern Identified
Cab Cleaning
Glo Germ Gel under a UV light when the door handle was not cleaned (left) and was wiped down (right).
The areas observed for cleaning included: steering wheel, dash, handles, climate control buttons, and radio. These areas were not being focused on; but are critical areas touched each time a driver is in the cab. In addition, it was difficult for monitors to tell if a cab had been cleaned or not by visual inspection alone.
Equipment Movement
After the three-day observation period, it became apparent that all equipment besides hot shots stayed in the dryers. Thus, hot shots were identified as the main equipment of concern. They were not returning with each trailer load, leading to biosecurity concerns.
Monitor Movement
Monitors inspect both PRRS positive and PRRS negative trailers throughout the day, before the wash crew is allowed to disinfect each trailer. Although monitors change boots and put on Tyvek before inspecting negative trailers, there is no true clean / dirty line where they change shoes.
Evaluation
Cab Cleaning
Steering wheel, dash, door handle, climate control buttons, and radio control buttons were evaluated on how well they were cleaned with a Glo Germ Gel product. The Glo Germ Gel was applied while the trucks were waiting in line to be cleaned. The assessment was performed using an UV light for any trace of the Glo Germ, indicating whether the surface had or had not been cleaned. The interior of cabs were not being cleaned as well as possible as evidenced by the amount of fluorescence that was detected in those five critical areas.
Equipment Movement
All of the hot shot handles and prods were numbered in both the PRRS positive and PRRS negative equipment sheds on a Sunday. Every night for the next five days it was checked if each hot shot was present, which equipment shed it was in, and new ones were numbered as they appeared. Throughout the course of those five days hot shot handles and prods were not being returned on a consistent basis. However, the equipment was not switched between the PRRS positive and PRRS negative sheds.
Monitor Movement
Glo Germ Gel and Powder was applied to the shoes of monitors and on positive trailers before monitors inspected them. Although no Glo Germ was appreciated in the PRRS negative areas, it may still be a potential area of concern and should be further evaluated.
Interventions
Cab Cleaning
In order to ensure that the interior of cabs were being cleaned as well as possible,the truck wash crew was shown images of the cab interiors with the Glo Germ Gel comparing interiors that were wiped down and those that were not. Current protocols could be clarified, and the importance of cab cleaning should be emphasized. Glo Germ Gel also gives the monitors the ability to do random internal audits of cab cleaning.
Equipment Movement
In order to check hot shot handle and prod cleanliness Glo Germ can be applied at the same time monitors put Glo Germ in the cabs. To encourage returning hot shots the truck wash crew can continue to write down cull and gilt trailers that do not return with a hotshot. To stop any potential cross-contamination, the PRRS-positive hot shots could be painted red.
Monitor Movement
Although no Glo Germ was appreciated it is possible that monitor movement is still a potential biosecurity risk and should be further evaluated. It appears that the Glo Germ washed right off as the trailers were wet when the monitors inspected them.
This is our Friday rubric: every week a new Science Page from the Bob Morrison’s Swine Health Monitoring Project. The previous editions of the science page are available on our website.
Nearly one-third of clinical E. coli isolates collected from swine samples were ceftiofur or enrofloxacin resistant
Genetic analysis revealed presence of rarely reported genes in antimicrobial resistant isolates
Most of the isolates were multi-drug resistant on both routine lab tests and genetic analysis
In a previous study, we analyzed the antimicrobial resistance in Escherichia coli isolates recovered from swine clinical samples from across USA during 2006-2016 at the University of Minnesota Veterinary Diagnostic Laboratory (UMN-VDL), and found a 47% annual increase in the prevalence of enrofloxacin resistance (from 1.5% in 2006 to 32% in 2016) while no trend was observed for the resistance to ceftiofur (that ranged between 32-39%). A follow-up study was conducted to evaluate the genetic basis of resistance against enrofloxacin and ceftiofur in E. coli isolates using whole genome sequencing (WGS).
153 swine clinical E. coli isolates collected in 2014-15 from 14 states across USA were selected and genes causing ceftiofur and enrofloxacin resistance were identified using WGS.
21 (out of 106) enrofloxacin-resistant isolates from 6 states harbored diverse plasmid mediated quinolone resistance (PMQR) genes (qnrB19, qnrB2, qnrS1, qnrS2 and qnrS15). The presence of PMQR genes alone was associated with clinical levels of resistance.
The most prevalent genes associated with ceftiofur resistance were blaCMY-2 (89/106, 84%). Moreover, 24 ceftiofur-resistant isolates harbored various blaCTX-M and blaSHV genes.
Additionally, bacteria carrying blaCTX-M and qnr genes also contained genes coding for resistance mechanisms against other antimicrobial classes and were commonly resistant against ampicillin, tetracyclines, gentamycin, trimethoprim and sulfonamides.
These genes (blaCTX-M, qnr) have been rarely reported from farm animals in USA and have been implicated as important genetic mechanisms behind extended spectrum cephalosporin and fluoroquinolone resistance in human and animal populations in several countries. These genes are present on plasmids, making their dissemination across bacterial populations faster by horizontal transfer.
The presence of multiple antimicrobial resistance genes on the same plasmids also makes mitigation of this problem more difficult because of the possibility that using one antimicrobial class will exert positive selection pressure for resistance against other antimicrobial classes.
This new publication in Veterinary Microbiology describes the best methodology to monitor 3-day-old piglets for PRRS, using both serum and processing fluid samples. The first author of the publication is Dr. Carles Vilalta, member of the Morrison Swine Health Monitoring Program (MSHMP) team.
Key points
Processing fluids (PF) constitute a useful sample to detect PRRSV infections at processing.
PRRSV can circulate in the farm at a low prevalence, increasing the chances of a re-break.
Young parity female litters should be targeted for PRRSV detection.
Current practice to bleed 30 pigs could be underestimating PRRSV prevalence in the herd.
The decrease in sensitivity at the litter level can be compensated by sampling more litters to detect PRRSV at the herd level.
Methods
The study was conducted in a 6,000 sow farm with a PRRS stable status. Every 3 weeks, serum samples and processing fluids were collected from all piglets in 10 randomly chosen litters. This process was then repeated 8 times, meaning that the farm was monitored for a total of 24 weeks. All samples were tested via PCR. 3 samples with the lowest Ct value were tested by virus isolation and sequencing of the ORF5 gene was performed.
Results
10.6% of the piglets tested positive for PRRSv via serum PCR, representing 29.8% of the litters. The same number of litters tested positive via processing fluid PCR testing.
The percentage of processing fluid positive samples was significantly higher is parity 1 and 2 sows compared to parity 3 and older sows. Additionally, a significant association between parity and probability of detecting a positive pig was observed.
A significant higher proportion of positive serum samples was observed in males compared to females. A similar trend was obtained when comparing positive Ct values by gender with values from males being lower (i.e., higher viral load) than those from females.
Cycle threshold (Ct) positive (≤35) and suspect (between >35 and 40) value distribution for serum (S, triangle) and processing fluid (P, circle) samples overtime (2, 5, 8, 11, 14, 17, 20 and 23 weeks post outbreak). Horizontal black lines indicate the mean Ct values for each week and sample type
Using a Ct value of 37, processing fluid samples had a Se and Sp of 87% (95% CI: 66%–97%) and 94% (95% CI: 85%–99%), respectively when compared with litter RT-PCR results obtained from individual serum samples. The total agreement between both tests was 92.2% and the positive and negative predictive values were 87% (95% CI: 66%–97%) and 94% (95% CI: 85%–99%), respectively. False negative processing fluids were identified in litters having 2 or less PRRSV positive piglets
The agreement between the PF and serum results was kappa = 0.81 (95% CI: 0.59–1.00). The difference in the proportion of positive samples between both types of sample was not statistically significant (McNemar test, p = 1).
Abstract:
Collection of serum samples of pigs at weaning to monitor for porcine reproductive and respiratory syndrome virus (PRRSV) has become a common practice to determine PRRSV herd infection status. Diagnostic sensitivity of this practice is low in herds undergoing PRRSV elimination once prevalence of infection is near zero. Thus, the goal of this study was to characterize the dynamics of PRRSV infection in 3 day-old pigs overtime using serum and serosanguineous fluids obtained as part of castration and tail docking practices (processing fluids (PF)). Secondary goal was to estimate sensitivity and specificity of PF in the 3 day old population. A 6000 breed-to-wean sow herd was monitored every three weeks for 23 weeks after a PRRSV outbreak by collecting both PF and individual serum samples from all pigs in the selected litters. Out of the 77 litters tested, 23 (29.8%) were identified as positive using the PF and the serum samples, with a Cohen’s kappa statistic of 0.81 (95% CI: 0.59–1) between the results obtained in each sample type. The sensitivity and specificity of the PF relative to the results in serum was 87% (95% CI: 66%–97%) and 94% (95% CI: 85%–99%) respectively. The percentage of PRRSV positive litters decreased over time and litters from gilts were more likely to test positive than those from older sows. Overall, the study demonstrates that PF can be a convenient and reliable specimen to monitor PRRSV infection in breeding herds.
This is our Friday rubric: every week a new Science Page from the Bob Morrison’s Swine Health Monitoring Project. The previous editions of the science page are available on our website.
Recording PRRSv RFLP and sequences will provide better insights into the epidemiology of the disease at local, state and national level.
Building a RFLP database will allow us to assess which factors could be involved or related with the emergence of a new RFLP.
The predominant pattern RFLP in this quarterly review is the 1-7-4.
In the first quarter of the 2018/2019 incidence year, 20 breaks affecting 12 production systems were reported. Out of these, 4 occurred in July, 13 in August and 3 in September.
Of those 20 farms, three had a break while still being status 1, one was status 2 in the process of eliminating the disease (not using any immunization protocol at that point), 6 were using field virus as the acclimatization protocol (2fvi), 8 were using vaccine (2vx), one was provisionally negative (status 3) and one broke from a status 4 after being almost 4 years completely negative (see figure below).
The distribution of the breaks is wide and affects different states. Thus, we had 6, 1, 4, 1, 4, 2, 1 and 1 break in the states of IA, IN, MN, MO, NC, NE, OK and PA, respectively. The closest 2 farms that broke were 1.2 miles apart, belonged to the same company and had the break a week from each other (no sequences was provided).
Eight out of the 20 breaks reported were accompanied by the associated RFLP. The predominant (4 out of 8) RFLP pattern since July is 1-7-4. Iowa was the state with the highest number of 1-7-4 cases.
