Tag: MSHMP

Science page: Evaluation of biosecurity measures to prevent indirect transmission of PEDV

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.

The objective of the study presented today was to evaluate the efficacy of of biosecurity procedures directed at minimizing transmission via personnel following different protocols in controlled experimental settings.

Four (4) groups were housed in different rooms:

  • INF: Pigs infected with PEDV
  • LB: Naive pigs which were exposed to personnel coming from the INF room without changing PPE at all
  • MB: Naive pigs which were exposed to personnel coming from the INF room after washing their hands and face as well as changing footwear and clothing.
  • HB: Naive pigs which were exposed to personnel coming from the INF room after showering as well as changing clothing and footwear.

Results are shown in the figure below. Naive pigs were exposed to personnel from 44h after the pigs in the INF group were infected with PEDV until 10 days post infection.

PEDV indirect transmission biosecurity measures
Viral shedding of pigs. Movements were terminated at 10 dpi. Data presented are average values of viral RNA copies (± SD) of infected (INF), low biosecurity (LB), medium biosecurity (MB) and high biosecurity (HB) groups

Key points:

  • PEDV transmission is likely to occur with contaminated fomites in low biosecurity scenarios.
  • Indirect contact transmission of PEDV can happen very rapidly. Transmission was detected 24h after personnel moved from infected to low biosecurity rooms (no change in clothes, boots or washing hands)
  • Changing PPE (personal protective equipment) and washing skin exposed areas is beneficial to decrease the risk of PEDV transmission.

 

Link to the facilities diagram explaining the experiment setup as well as the results on PEDV indirect transmission in this study.

Science Page: Analyzing swine movement patterns in relation with PEDV

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.

The movement of live pigs between farms is an important mechanism for disease introduction and spread. Thus, understanding the structure of livestock contacts and studying the routes, volumes, frequency, and the risks associated with animal movement is a prerequisite for effective disease surveillance and control in animal populations.
At the same time, local area spread between neighboring farms is also implicated in the spread of viruses such as porcine epidemic diarrhea virus (PEDV) and porcine reproductive and respiratory syndrome virus (PRRSV).

Even after controlling for hog density and season of the year, we showed that the number of pigs received into neighboring farms was an important predictor of PED infection risk.

relative importance of parameters in predicting PEDV
Relative importance in predicting risk, according to the Gini index

Key Points

  • Between farm transmission research in swine has primarily come from small studies rather than large scale datasets.
  • By looking at environmental/landscape, pig movements, and spatial factors, we studied the likelihood of a farm contracting PED from it’s neighbors.
  • It was found that the number of pigs received by neighboring farms was an important predictor of PEDV infection risk.

Click here to see the full Science page report on the various parameters and their relative importance in predicting risk of PEDV infection.

Translating big data into smart data for veterinary epidemiology: the MSHMP perspective

Big data can be defined as the daunting accumulation of abundant and diverse information. While recording data is the first step to measure progress or quickly identify an issue, the large amount of information collected can make it difficult to analyze.

At the University of Minnesota, one of the main projects using big data is the Morrison’s Swine Health Monitoring Program. This ongoing project collects veterinary reports and diagnostic results from numerous swine producers on a daily basis. The compiled information is then analyzed, interpreted and reported back as smart data to the participants every week. Smart data is commonly defined as a piece of information useful enough to make educated decisions.

 

Data pipeline utilized by the Morrison Swine Health Monitoring Project.jpg
Data pipeline used by the Morrison Swine Health Monitoring project for generating near real-time insight about the incidence of PRRSV

Abstract

The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing “big” data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats. The advent of big data requires the incorporation of new skills into veterinary epidemiology training, including, for example, machine learning and coding, to prepare a new generation of scientists and practitioners to engage with big data. Establishing pipelines to analyze big data in near real-time is the next step for progressing from simply having “big data” to create “smart data,” with the objective of improving understanding of health risks, effectiveness of management and policy decisions, and ultimately preventing or at least minimizing the impact of adverse animal health issues.

Review the full article

Science Page: Are the farms that broke with PED the same?

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 proud to introduce a new chart in the Morrison’s Swine Health Monitoring Project. This new addition will be able to answer a common question regarding PEDV outbreaks:

Are the farms currently breaking with PEDV the same than the ones which broke in the past?

To interpret the figure, follows these steps.

  • Horizontal axis represents all the farms that borke with PEDV during the season 2016/2017, with each tick representing an individual farm
  • Vertical axis shows the previous seasons with 2016-2017 on top and 2012-2013 at the very bottom.
  • The color of the cell (year : farm) represents the number of outbreaks experienced; darker blue meaning more outbreaks.

Here is the example of this chart presented this week:

MSHMP PEDV chart
Outbreak history of farms that broke during the 2016-2017 season.

Key points:

The farms that break with PEDV do not appear to have a history of PEDV infections in the prior season.

Of the farms that broke during the 2016/17 season, only 5 (6.5%) of them had outbreaks during the previous season and 43 (56.6%) of them had broken at some point since 2013.

Only one farm has had an outbreak every year since the beginning of the epidemic in the US (season 2013/14).

The full report is available.

Science Page: MSHMP Annual Summary

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.

The project runs from July 1st to June 30th so the year 2016-2017 just ended. Below are listed the main point for this year, more details can be found in the full report.

This year the Swine Health Monitoring Project was struck by the sudden and unexpected loss of Bob Morrison in a car accident in Prague. This was a major setback for the group and is a difficult challenge to overcome. However, we received the support of the industry to continue carrying on Bob’s legacy. Since last May the SHMP was renamed after him to Dr. Morrison’s SHMP (MSHMP).

Key points from this week edition:

  1. Monitoring pathogens
    • PRRS incidence (26%) remained stable over the last 2 years.
    • PEDv incidence remained low (7%), at the same level as last year.
    • Seneca Valley virus incidence appears to have a seasonal pattern.
    • Monitoring of VDL atypical CNS cases has been restarted.
  2. Analyzing PRRS virus sequences
    • It appears that there are several characteristic features that would signal emerging PRRSv strains, which may be used for early detection of significant emerging events.
    • Analyzed sequences coming from 3 systems to detect new emerging strains on a monthly basis.
  3. Capturing movement data and incorporating into data management capacity
    • Developed an app to capture truck movement.
    • Tested a first version of the app.
    • A second improved version will be tested shortly.
  4. Expanding enrollment
    • Added 4 production companies.
    • Currently 33 systems with 1,092 sow farms & 2.96 million sows.
    • 161 non participants receive weekly report.