US PRRSv surveillance using risk mapping and species distribution modeling

Today, we are sharing a publication from the Preventive Veterinary Medicine journal, by Dr. Andres Perez and the STEMMA laboratory. The goal of the study was to quantify the combined effect of factors such as season and herd size on the spatial range of high-risk areas for PRRSV outbreaks. Using Species Distribution Model, the team extracted associations between hypothesized risk factors and disease occurrence.

Highlights

  • A species distribution model was used, to predict the spatial risk of PRRSv in swine populations across the U.S.
  • All of the Maxent spatial models identified high-risk areas, with probabilities greater than 0.5.
  • Relative contribution of pig density to PRRSv risk was higher in densely pig populated areas.
  • Relative contribution of climate and land cover to PRRSv risk were important in areas with relative low pig densities.
  • Ecological dynamics of PRRSv are different between swine production region in the U.S.

The largest number of PRRSv outbreaks in the U.S., as reported in the MSHMP, was observed in north central parts of Iowa, followed by south central areas of Minnesota. However, our crude U.S. Maxent model identified eastern North Carolina, southern Minnesota, and northern Iowa as high-risk areas for PRRSv outbreaks. As expected, pig density accounted for most of the PRRSv spatial risk (81.3% relative contribution). Climate (interpreted as the percentage of day-to-night temperature oscillation compared with the summer-to-winter oscillation, and mean temperature of the warmest quarter) accounted for the remaining spatial risk. Overall, the crude Maxent model suggested geographical areas with high pig densities and with a low level of daily temperature variability to the year are mostly suitable for circulation and maintenance of PRRSv.

Factors percent contribution PRRS outbreak Perez 2017
Summary charts of the estimated relative percent contribution of each environmental and demographic variable of the final Maxent model for each swine production region in the U.S.

The model for the South East region indicated that pig density was the most important predictor; followed by precipitation of the wettest month, land cover, and temperature seasonality. The relative contribution of pig density was smaller for this region compared to the Midwest. Specifically, geographical locations with high pig density, precipitation amount between 120 and 200 mm during the wettest months, and that were located within croplands were mostly suitable for PRRSv outbreaks in North Carolina and Northern South Carolina.

Additionally, the spread of PRRSV under certain conditions was more evident for the regions where pig density is relatively low. For example, in Illinois and Indiana and Kansas, Colorado, Oklahoma and Texas, wet weather and temperatures above 0 °C were more important in predicting the spatial risk of PRRSv than pig density.

Click here to read the entire publication on US PRRSv surveillance using risk mapping and species distribution modeling.

 

PRedicting and mapping PRRSV outbreaks PEREZ 2017.jpg

Abstract

Porcine reproductive and respiratory syndrome virus (PRRSv) outbreaks cause significant financial losses to the U.S. swine industry, where the pathogen is endemic. Seasonal increases in the number of outbreaks are typically observed using PRRSv epidemic curves. However, the nature and extent to which demographic and environmental factors influence the risk for PRRSv outbreaks in the country remains unclear. The objective of this study was to develop risk maps for PRRSv outbreaks across the United States (U.S.) and compare ecological dynamics of the disease in five of the most important swine production regions of the country. This study integrates spatial information regarding PRRSv surveillance with relevant demographic and environmental factors collected between 2009 and 2016. We used presence-only Maximum Entropy (Maxent), a species distribution modeling approach, to model the spatial risk of PRRSv in swine populations. Data fitted the selected model relatively well when the modeling approach was conducted by region (training and testing AUCs < 0.75). All of the Maxent models selected identified high-risk areas, with probabilities greater than 0.5. The relative contribution of pig density to PRRSv risk was highest in pig-densely populated areas (Minnesota, Iowa and North Carolina), whereas climate and land cover were important in areas with relatively low pig densities (Illinois, Indiana, South Dakota, Nebraska, Kansas, Oklahoma, Colorado, and Texas). Although many previous studies associated the risk of PRRSv with high pig density and climatic factors, the study here quantifies, for the first time in the peer-reviewed literature, the spatial variation and relative contribution of these factors across different swine production regions in the U.S. The results will help in the design and implement of early detection, prevention, and control strategies for one of the most devastating diseases affecting the swine industry in the U.S.

A new multidrug resistant Salmonella enterica serotype found in Midwestern swine

Text reproduced from the Center for Infectious Disease Research and Policy (CIDRAP)

A new study by Dr. Julio Alvarez‘s team from the STEMMA laboratory, published  in Clinical infectious Diseases suggests that a Salmonella strain circulating in pigs in the US Midwest is part of an emerging clade from Europe that is resistant to multiple antibiotics and may pose a public health risk.

The strain, Salmonella 4,[5],12:i:-, causes many foodborne disease outbreaks mostly tied to pigs and pork products and is expanding in the United States, according to the report by researchers from Minnesota and the United Kingdom.

The team used whole-genome sequencing to assess the relatedness of 659 S 4,[5],12:i:- isolates and 325 S Typhimurium isolates from various sources and locations in the United States and Europe. They also searched for resistance genes and other virulence factors and, for 50 livestock isolates and 22 human isolates, determined the antimicrobial resistance phenotypes.

The researchers found that the S 4,[5],12:i:- isolates fell into two main clades, regardless of their host or place of origin. Eighty-four percent of the US isolates recovered from 2014 through 2016, including nearly all those from pigs in the Midwest, were part of an emerging clade. This clade carried multiple genetic markers for antimicrobial resistance, including resistance to ampicillin, streptomycin, sulphonamides, and tetracyclines.

In addition, phenotypic (actual) resistance to enrofloxacin and ceftiofur was found in 11 of the 50 tested livestock isolates and 9 of the 22 human isolates. This was accompanied by plasmid-mediated resistance genes.

The authors conclude that S 4,[5],12:i:- strains circulating in Midwestern swine herds “are likely part of an emerging multidrug resistant clade first reported in Europe, and can carry plasmid-mediated resistance genes that may be transmitted horizontally to other bacteria and thus could represent a public-health concern.”

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salmonella enterica multidru resistant Alvarez 2017

Abstract

Background
Salmonella 4,[5],12:i:-, a worldwide emerging pathogen that causes many foodborne outbreaks mostly attributed to pig and pig products, is expanding in the U.S

Methods
Whole genome sequencing was applied to conduct multiple comparisons of 659 S. 4,[5],12:i:- and 325 S. Typhimurium from different sources and locations (i.e. U.S. and Europe) to assess their genetic heterogeneity, with a focus on strains recovered from swine in the U.S. Midwest. In addition, presence of resistance genes and other virulence factors was detected and the antimicrobial resistance phenotype of 50 and 22 isolates of livestock and human origin, respectively, was determined.

Results
The S. 4,5,12:i:- strains formed two main clades regardless of their source and geographical origin. Most (84%) of the U.S. isolates recovered in 2014–2016, including those (50/51) recovered from swine in the U.S. Midwest, were part of an emerging clade. In this clade, multiple genotypic resistance determinants were predominant, including resistance against ampicillin, streptomycin, sulphonamides and tetracyclines (ASSuT). Phenotypic resistance to enrofloxacin (11/50) and ceftiofur (9/50) was found in conjunction with the presence of plasmid-mediated resistance genes (qnrB19/qnrB2/qnrS1 and blaCMY-2/blaSHV-12, respectively). Also, higher similarity was found between S. 4,[5],12:i:- from the emerging clade and S. Typhimurium from Europe than with S. Typhimurium from the U.S.

Conclusions
Salmonella 4,[5],12:i:- currently circulating in swine in the U.S. Midwest are likely part of an emerging multidrug resistant clade first reported in Europe, and can carry plasmid-mediated resistance genes that may be transmitted horizontally to other bacteria and thus could represent a public-health concern.

Influenza Herd-Level Prevalence and Seasonality in Breed-to-Wean Pig Farms in the Midwestern United States

The Torremorell lab is continuing to explore swine influenza epidemiology in this recent publication from Dr. Fabian Chamba Pardo in Frontiers in Veterinary Science. After showing that multiple genome constellations of similar and distinct influenza viruses co-circulate in pigs, the group is now presenting new data about influenza herd-level prevalence in the Midwest, and how it is influenced by seasons. Click on the banner below to read the entire research article.

Influenza seasonal prevalence Midwest herds Chamba 2017

60 sow farms from a single Midwestern production system were enrolled in this study. Between one and seven oral fluid samples were collected at each farm weekly and meteorological data (air temperature and relative humidity) was compiled from stations located from the farms.

Swine herd level prevalence Chamba 201728% of submissions had at least one influenza positive result. All farms tested positive at least once during study period. Herd-level prevalence ranged from 7% to 57% as show in the figure above. Prevalence was low in summer, rose during fall, and peaked twice in both early winter (December) and late spring (May). August was the month with the lowest prevalence. Influenza herd-level prevalence was higher when both mean outdoor air temperature and air humidity were lower.

The most common clades identified were H1 delta 1, H1 gamma 1, and clusters H3 IV A  and H3 IV B. Furthermore, 21% of the farms had 3 different influenza genetic clades circulating during the study period and 18% had 2.

Abstract

Influenza is a costly disease for pig producers and understanding its epidemiology is critical to control it. In this study, we aimed to estimate the herd-level prevalence and seasonality of influenza in breed-to-wean pig farms, evaluate the correlation between influenza herd-level prevalence and meteorological conditions, and characterize influenza genetic diversity over time. A cohort of 34 breed-to-wean farms with monthly influenza status obtained over a 5-year period in piglets prior to wean was selected. A farm was considered positive in a given month if at least one oral fluid tested influenza positive by reverse transcriptase polymerase chain reaction. Influenza seasonality was assessed combining autoregressive integrated moving average (ARIMA) models with trigonometric functions as covariates. Meteorological conditions were gathered from local land-based weather stations, monthly aggregated and correlated with influenza herd-level prevalence. Influenza herd-level prevalence had a median of 28% with a range from 7 to 57% and followed a cyclical pattern with levels increasing during fall, peaking in both early winter (December) and late spring (May), and decreasing in summer. Influenza herd-level prevalence was correlated with mean outdoor air absolute humidity (AH) and temperature. Influenza genetic diversity was substantial over time with influenza isolates belonging to 10 distinct clades from which H1 delta 1 and H1 gamma 1 were the most common. Twenty-one percent of farms had three different clades co-circulating over time, 18% of farms had two clades, and 41% of farms had one clade. In summary, our study showed that influenza had a cyclical pattern explained in part by air AH and temperature changes over time, and highlighted the importance of active surveillance to identify high-risk periods when strategic control measures for influenza could be implemented.

A constellation of strains co-circulate in pigs during influenza epidemics

This recent publication in Nature comes from the Torremorell’s lab and aims at answering the question of the number of strains circulating in pigs during an influenza outbreak and how genetically different they may be. The full article is available in open access, click on the banner below to access it.

Constellation influenza banner Torremorell

To answer the question of multiple strains of influenza in pigs, the group followed a cohort of 132 pigs placed in a 2,200-head a wean-to-finish barn, endemic for influenza. All the pigs originated from the same sow farm . The history of past influenza episodes did not include any information regarding the strain of viruses circulating in the barn. Nasal swabs were collected for each individual pig and were tested in the laboratory by PCR.

Results from this study showed that:

  • Only 2 pigs out of 132 tested negative every week during the entire duration of the study.
  • Around 88% of the pigs tested positive for influenza more than once.
  • 20.5% of pigs were positive for influenza at weaning.
  • Weekly influenza prevalence ranged between 0% and 65%.
  • 3 different viral groups were identified VG1, VG2, and VG3.
  • Groups belonged to the swine H1-gamma, H1-beta and H3-cluster-IV influenza A respectively. (Here is a review of the H1 genetic clades and one of the H3 genotype patterns)

The figure below shows the genetic make up of the influenza strains isolated each week, the viral group each genetic segment belonged to and the number of times this specific combination was found.

For example, the second line can be interpreted as: during week one, one sample in which 10 sequences were recovered, had influenza virus with segments 1, 2, 3, 4, 5, and 7 belonging to the Viral Group 1 (H1 gamma) and segments 6 and 8 were from Viral groups 1 and 3.

Influenza constellation Torremorell

In conclusion, this study shows that influenza infections in pigs after weaning and under field conditions are complex. The influenza virus genome is diverse and changes rapidly. Prolonged persistence of influenza viruses in pigs could be the result of multiple influenza epidemic events that take place repeatedly over time or the re-infection with influenza viruses that are closely related to each other.

Abstract

Swine play a key role in the ecology and transmission of influenza A viruses (IAVs) between species. However, the epidemiology and diversity of swine IAVs is not completely understood. In this cohort study, we sampled on a weekly basis 132 3-week old pigs for 15 weeks. We found two overlapping epidemic events of infection in which most pigs (98.4%) tested PCR positive for IAVs. The prevalence rate of infection ranged between 0 and 86% per week and the incidence density ranged between 0 and 71 cases per 100 pigs-week. Three distinct influenza viral groups (VGs) replicating as a “swarm” of viruses were identified (swine H1-gamma, H1-beta, and H3-cluster-IV IAVs) and co-circulated at different proportions over time suggesting differential allele fitness. Furthermore, using deep genome sequencing 13 distinct viral genome constellations were differentiated. Moreover, 78% of the pigs had recurrent infections with IAVs closely related to each other or IAVs clearly distinct. Our results demonstrated the molecular complexity of swine IAVs during natural infection of pigs in which novel strains of IAVs with zoonotic and pandemic potential can emerge. These are key findings to design better health interventions to reduce the transmission of swine IAVs and minimize the public health risk.

Longitudinal study of Senecavirus shedding and viremia in sows and piglets

How long do sows and piglets shed Senecavirus A after a clinical outbreak? How long is the viremia? Those are the questions answered in this case study of a Senecavirus A outbreak in one US farm.

Objective and Methods

Senecavirus A is a challenge for producers and veterinarians because of its clinical similarity to Food and Mouth Disease (FMD). In this study, 34 sows and 30 individual piglets from 15 different litters were sampled at day 1 post-outbreak and later at 1, 2, 3, 4, 6, and 9 weeks post-outbreak (PO). Serum, and tonsil, rectal, and vesicular swabs were collected for all of the pigs included in the study. The objective of the study was to explore the viremia and shedding patterns in those infected animals. All samples were submitted to the University of Minnesota, Veterinary Diagnostic Laboratory to be tested by PCR.

longitudinal study of senecavirus figures Tousignant 2017.gif
Percentage of serum (a), tonsil swabs (b), and rectal swabs (c) positive for Senecavirus A. Clinical outbreak happened in sow farm 1 (S1) and piglets from sow farm 2 (S2) were mixed with piglets from S1 at weaning.

 

Results

Vesicular lesions were seen in sows only for 2 weeks and had the highest amount of virus. In sows, the detection of Senecavirus A in tonsil and rectal swabs was greater than 90% at 0 week PO and remained as high as 50% through 5 weeks PO. Generally, viremia was detected up to 1 week PO in sows but it is important to note that viremia was not detected in 11 out of 34 (32%) of the sows at any point during the study. Viremia was detected in 18 out of 30 (60%) and 19 out of 30 (63%) in the suckling piglets from site 1. Similar to sows, viremia was not detected in 9 out of 30 (30%) of the site 1 piglets enrolled in the study.

The detection of Senecavirus A in sows tonsil swabs peaked 1 week PO (94% positive) whereas it peaked at day 1 PO for piglets (83% positive). The detection of virus shedding decreased over time in sows and piglets, and a single sow and piglet tested positive at 9 weeks PO.

The peak of Senecavirus A detection from rectal swabs in sows (91%) occurred at day 1 PO and continued to steadily decrease and was not detected at 9 weeks PO. In site 1 piglets, the detection of SVA peaked at 1 week PO (90% positive). 64% of the rectal swabs were positive at 4 weeks PO in site 1 piglets. At 6 weeks PO, the detection of Senecavirus A was same for both site 1 and 2 piglets (11%); however, a single piglet from site 1 was still shedding SVA at 9 weeks PO.

Discussion

The study assessed the shedding pattern of SVA in sows and piglets during an outbreak on a farm in the US and investigated the spread of SVA between pigs during the post weaning period. Vesicular lesions were seen in sows only for 2 weeks and had the highest amount of virus. In sows, the detection of SVA in tonsil and rectal swabs was greater than 90% at 0 week PO and remained as high as 50% through 5 weeks PO, these sample types should be collected and submitted, in addition to vesicular lesion swabs and fluid (if present), as part of FAD investigations for the detection of SVA.

 

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longitudinal study of senecavirus Tousignant 2017

Abstract

Background: The study highlights the shedding pattern of Senecavirus A (SVA) during an outbreak of vesicular disease in a sow farm from the South-central Minnesota, USA. In this study, 34 individual, mixed parity sows with clinical signs of vesicular lesions and 30 individual piglets from 15 individual litters from sows with vesicular lesions were conveniently selected for individual, longitudinal sampling. Serum, tonsil, rectal, and vesicular swabs were collected on day 1 post outbreak, and then again at 1, 2, 3, 4, 6, and 9 weeks post outbreak. Samples were tested at the University of Minnesota Veterinary Diagnostic Laboratory for SVA via Real Time Polymerase Chain Reaction (RT-PCR)
Results: In sows, vesicular lesions had the highest concentration of SVA, but had the shortest duration of detection lasting only 2 weeks. Viremia was detected for 1 week post outbreak, and quickly declined thereafter. SVA was detected at approximately the same frequency for both tonsil and rectal swabs with the highest percentage of SVA positive samples detected in the first 6 weeks post outbreak. In suckling piglets, viremia quickly declined 1 week post outbreak and was prevalent in low levels during the first week after weaning (4 weeks post outbreak) and was also detected in piglets that were co-mingled from a SVA negative sow farm. Similar to sows, SVA detection on rectal and tonsil swabs in piglets lasted approximately 6 weeks post outbreak.
Conclusion: The study illustrates the variation of SVA shedding patterns in different sample types over a 9 week period in sows and piglets, and suggests the potential for viral spread between piglets at weaning.

How much floor space does a pregnant sow need in a group-housing system with electronic sow feeders?

floor-allowance-gestating-sows
Sows housed in groups at the UMN facility in Morris

The University of Minnesota – Morris owns a swine research facility which provides an excellent set up to study the behavior of sows housed in groups. In the past few years, swine producers have committed to change the conditions in which the sows are housed in farms and to keep them in groups where they can interact with each other instead of housing them individually. Putting sows in group reminded us that pigs need a hierarchy and that they will compete and fight to establish it. Because space allowance can impact sows behavior we wondered what the optimum floor space is.

Read the entire report on floor space allowance for sows by Dr. Yuzhi Li

Determining floor space allowance for gestating sows can be controversial because more floor space allowance means low output per square footage of the barn and will potentially reduce profitability for producers. On the other hand, floor space allowance less than sow requirement can compromise sow welfare and performance. To answer the question in the title of this article, we conducted a two-year project (titled ‘Determining the Minimal Floor Space Allowance for Gestating Sows Kept in Pens with Electronic Sow Feeders’). The project was partially sponsored by the National Pork Board, and the research team includes Yuzhi Li and Lee Johnston from the WCROC in Morris, and Sam Baidoo from the SCROC (Southern Research and Outreach Center) in Waseca.[…]

 

M.hyopneumoniae: knowledge gaps for improved disease control

Enzootic pneumoniae is a chronic respiratory disease caused by Mycoplasma hyopneumoniae in pigs. It has been present in the industry for decades and causes significant economic losses. Yet, control methods like vaccination have not been able to contain the disease. Why is that? What information are we missing to design more effective control methods? This is the goal of the review paper co-authored by Dr. Maria Pieters from the University of Minnesota.

Focusing on various aspects of the disease like epidemiology, pathogenicity, diagnostics, and control measures, this publication regroups all the knowledge we currently have of Mycoplasma hyopneumoniae and identifies what we need to investigate to improve disease control.

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Update on Mhyopneumoniae infections in pig Pieters 2017

Abstract:

Mycoplasma hyopneumoniae (M. hyopneumoniae) is the primary pathogen of enzootic pneumonia, a chronic respiratory disease in pigs. Infections occur worldwide and cause major economic losses to the pig industry. The present paper reviews the current knowledge on M. hyopneumoniae infections, with emphasis on identification and analysis of knowledge gaps for optimizing control of the disease. Close contact between infected and susceptible pigs is the main route of M. hyopneumoniae transmission. Management and housing conditions predisposing for infection or disease are known, but further research is needed to better understand M. hyopneumoniae transmission patterns in modern pig production systems, and to assess the importance of the breeding population for downstream disease control. The organism is primarily found on the mucosal surface of the trachea, bronchi and bronchioles. Different adhesins and lipoproteins are involved in the adherence process. However, a clear picture of the virulence and pathogenicity of M. hyopneumoniae is still missing. The role of glycerol metabolism, myoinositol metabolism and the Mycoplasma Ig binding protein—Mycoplasma Ig protease system should be further investigated for their contribution to virulence. The destruction of the mucociliary apparatus, together with modulating the immune response, enhances the susceptibility of infected pigs to secondary pathogens. Clinical signs and severity of lesions depend on different factors, such as management, environmental conditions and likely also M. hyopneumoniae strain. The potential impact of strain variability on disease severity is not well defined. Diagnostics could be improved by developing tests that may detect virulent strains, by improving sampling in live animals and by designing ELISAs allowing discrimination between infected and vaccinated pigs. The currently available vaccines are often cost-efficient, but the ongoing research on developing new vaccines that confer protective immunity and reduce transmission should be continued, as well as optimization of protocols to eliminate M. hyopneumoniae from pig herds.