In this article written for the National Hog Farmer, PhD candidate April Estrada describes the high diversity of Streptococcus suis (S.suis) isolates.
Continue reading “Distribution of pathogenic Streptococcus suis in the US”PRRS Exponentially Weighted Moving Average by State
This week,we are sharing a report by Dr. Juan Sanhueza from the MSHMP team regarding EWMAs by state.
Key points
- Across states, different EWMA patterns continue to be observed.
- The expected high PRRS incidence during fall/winter was not as marked both in duration and magnitude in some states during the 2018-2019 season.
Reminder: What is the EWMA?
The Exponential Weighted Moving Average (EMWA) is a statistical method that averages data over time, continually decreasing the weight of data as it moves further back in time. An EWMA chart is particularly good at monitoring processes that drift over time and is used to detect small shifts in a trend.
In our project, EWMA is used to follow the evolution of the % of farms at risk that broke with PRRSV every week. EWMA incorporates all the weekly percentages recorded since the beginning of the project and gives less and less weight to the results as they are more removed in time. Therefore, the % of farms at risk that broke with PRRSV last week will have much more influence on the EMWA than the % of farms at risk that broke with PRRSV during the same week last year.
The charts depict: 1)the number of new cases (green dots – secondary Y axis) during a specific week and 2)the percentage of farms that broke during that week of the total in the MSHMP project in a smoothed way (blue line/Y axis). The red horizontal line indicates the threshold (upper confidence limit – UCL). This UCL is calculated based on the average of cases during the lowest PRRS months in the year, June, July and August and is recalculated every two years.
When there are more cases than expected, the blue line crosses the threshold (red line) indicating there is an epidemic.
The formula used in the EWMA chart is the following:
where E is the smoothed % of infected herds, lambda the constant smoothing the curve, I the % of infected herds during that week and Et-1 is the smoothed % of infected herds during the previous week.
EWMAs by state
Minnesota: As expected, this season EWMA crossed the epidemic threshold by the end of October/beginning of November 2018. However, the magnitude and duration of the epidemic was lower and shorter than in the 2017-2018 season. Incidence dropped during December 2018-January 2019 but lingered above the epidemic threshold until Mid-February, 2019.
Iowa: The 2018/2019 PRRS season started slightly earlier than in Minnesota and it was higher in magnitude than in any other of the assessed states. Although it reached a similar peak than in the 2017-2018 PRRS season in Iowa, its duration appeared to have been shorter since the EWMA went below the epidemic threshold during Mid-February 2019, which was about three months earlier than in the previous season.
North Carolina: As the 2017-2018 PRRS season, the epidemic begun on Nov of 2018. However, the 2018-2019 PRRS season was about three months shorter than the 2017-2018 PRRS season. The EWMA crossed the epidemic threshold momentarily in September/October 2018 but dropped below it until Mid-November when it crossed the epidemic threshold again to remain above it for about four months.
Oklahoma: Had a drastically different PRRS pattern than the 2017Ͳ2018 MSHMP season. The 2017-2018 PRRS season continued well into the summer, and only stayed below the epidemic threshold for about two months. PRRS incidence during the 2018-2019 season has been drastically lower than the one during the 2017-2018 season, staying at around 0.5%, and moving below the epidemic threshold several times.
Nebraska: The 2018-2019 fall/winter were characterized by a pattern of fewer, and more intermittent cases than the 2017-2018 fall/winter. No obvious PRRS season can be observed since PRRS outbreaks occurred sporadically throughout the year.
Illinois: Had a long PRRS season in 2017-2018 with the EWMA remaining mostly above the epidemic threshold for almost a year. In comparison, the 2018-2019 PRRS season started almost three months later in the year and its incidence has been lower than in 2017-2018, with the EWMA sporadically crossing above the epidemic threshold during the 2018Ͳ2019 fall and winter.
Evaluation of the feasibility of Mycoplasma hyopneumoniae detection in processing fluids
This report is the February edition of the Swine Disease Eradication Center (SDEC) research update. Not sure what the SDEC is? Check out this quick read about our research group collaborating with industry partners to solve problems faced by the swine industry.
Dr. Vilalta collaborated with Minnesota-based producers, the Veterinary Diagnostic Laboratory and the MycoLab to investigate processing fluids as a sample type for the detection of Mycoplasma hyopneumoniae.
Continue reading “Evaluation of the feasibility of Mycoplasma hyopneumoniae detection in processing fluids”A quick guide to Mycoplasma hyopneumoniae diagnostics
Sample types for early detection of Mycoplasma hyopneumoniae is a popular post on this blog. Dr. Pieters, head of the MycoLAb at the University of Minnesota created an online quick guide to help swine practitioners decide which sample type they should collect if they are looking for Mycoplasma hyopneumoniae.
This guide is available at http://z.umn.edu/MycoplasmaDiagnostics
Continue reading “A quick guide to Mycoplasma hyopneumoniae diagnostics”Gilt management for improved sow lifetime productivity
A glitch in WordPress prevented this post from being released on Friday, so we are sharing it with you this morning. Sorry for the inconvenience, we are working with the platform to fix the issue.
This week, we are sharing a report by Drs. Patterson and Foxcroft about gilt management. Previously, we shared the recording of her presentation during the 2018 Leman conference. Below is an update on her work at the University of Alberta.
Key Points
- Successful replacement gilt management starts at birth
- A low individual birth weight and a “Low litter birth weight sow phenotype” are key factors determining the efficiency of replacement gilt production
- Good gilt selection and pre-breeding programs remove early culling for reproductive problems as a factor in sow life time productivity
Gilt are the foundation of good production (Tubbs, 2015) and drive farm success (Ketchem and Rix, 2015).Low individual gilt birth weights have
been linked to increased preͲweaning mortality (Magnabosco et al., 2015), poor growth until finishing, compromised ovarian and uterine development (Deligeorgis et al., 1985), fewer pigs produced over three parities and earlier removal from the herd (Magnabosco et al. 2016). At sow level, a low litter “birth weight phenotype“(BWP) carries all the same risks as a low individual birth weight, but as a “litter” trait. As part of a National Pork Board-funded project to investigate links between litter BWP and sow lifetime productivity (SLP) conducted in collaboration with Holden Farms Inc., litter BWP was determined over at least two successive parities.
Multiplication sows (n = 651) were then classified as having either a low (L, < 1.18 kg, n=63), lowͲmedium (LM,> or = 1.16 to < or = 1.36 kg, n=281), medium-high (MH, > 1.36 and < or =1.6 kg, n=254) or high (H, > 1.6 kg, n=53) average litter BWP. Low BWP sows produced progeny with limited survivability after birth, poor retention during gilt development, and overall had a lower efficiency of replacement gilt production. Although BWP had a significant effect on weight and growth rate at the time of Pre-Selection (170 days), when puberty stimulation commenced at around 182 days of age, BWP did not affect the days to recorded first estrus.
Therefore, the growth performance of even the lighter gilts born did not delay the onset of pubertal estrus. Furthermore, for those low birth
weight pigs that survived and were selected as replacements on the basis of a recorded pubertal estrus event, a low BWP did not affect total pigs
born over four parities, or longevity in the sow herd. In contrast, gilts born in litters with a high BWP had lower retention rates in the sow herd.
Take home messages
Low birth weights affect the efficiency of replacement gilt production because these gilts either die, or are voluntarily non-selected because of relatively poor growth performance: However, if they survive, they have an equal chance of being bred and have better performance in the breeding herd that had high birth weight gilts.
Irrespective of gilt origin, earlier maturing gilts that have a recorded standing heat (HNS) within 30 days of starting boar exposure are the premium “Select” gilt population. They are inseminated earlier, have fewer non-productive days (NPD), are culled less due to reproductive problems, have higher farrowing rates, have more pigs born alive and are culled later (see Patterson and Foxcroft, 2019).
To be reliable and cost-effective, the stimulation program must involve daily direct contact between the gilts and high libido boars: This maximizes the “boar effect” and drives the efficiency in the gilt development unit (GDU). Adequate resources need to be allocated to the GDU (staffing, facilities, focus and time) and daily records of GDU performance should drive key management decisions (e.g. PG600 intervention). Only breeding-eligible gilts with a recorded HNS should be delivered to the sow farm or moved to the pre-breeding area. Breeding gilts at 2nd or 3rd estrus, at a target body weight of 135-150 kg, and after utilizing at least a 14-day pre-breeding “acclimation period” during which gilts are essentially on full feed, are the next crucial steps in optimizing SLP.
Take home message
Individual recording of gilt performance in the GDU is as critical as, and has longer-lasting consequences than, individual recording of breeding sow performance after weaning.
References are available on the original document.