Diagnostic testing data can predict LPAI spread in turkeys

Researchers used diagnostic testing data from a 2018 Minnesota low pathogenicity avian influenza (LPAI) outbreak in turkeys to estimate the time of virus introduction, which could help improve tracing efforts and prevent the spread of disease.

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Joan Wozniak | iStockPhoto.com
Joan Wozniak | iStockPhoto.com

Researchers used diagnostic testing data from a 2018 Minnesota low pathogenicity avian influenza (LPAI) outbreak in turkeys to estimate the time of virus introduction, which could help improve tracing efforts and prevent the spread of disease.

“This research study shows how useful diagnostic testing can be. It is an important tool for monitoring bird health such as during high-risk periods like fall or spring migrations,” corresponding author Peter Bonney, a researcher in the College of Veterinary and Medical Sciences and a member of the Secure Food Systems Team at the University of Minnesota, explained.

“And as we show in this study, diagnostic testing can also provide useful epidemiological information on flocks infected with low pathogenicity avian influenza, in particular the time window for when a flock was first exposed to the virus, which can help epidemiological investigations. The more testing that can be done following detection, especially a combination of testing for virus and antibodies, the better estimates we can get.”

LPAI outbreaks can be highly disruptive to the poultry industry, reducing egg production and overall weight again and increased mortality in infected flocks. In some strains, LPAI can mutate into highly pathogenic avian influenza (HPAI), which typically causes nearly 100% mortality in infected flocks.

The findings were published in the open access journal, Scientific Reports.

Mathematical modeling

The researchers used mathematical modeling to estimate the rate of disease spread based on changes in diagnostic test results from five turkey barns that tested positive during the 2018 LPAI H5N2 outbreak in Minnesota.

For an example of how the modeling works, compare two infected turkey houses. In the first house, one out of ten birds test positive the first day. Three days later, ten out of ten birds are positive.

At the second turkey house, one out of ten also test positive the first day. However, when the house is retested three days later, only three out of ten birds test positive for avian influenza.

“Everything else equal, we would expect faster disease spread in the first house compared to the second house since birds are becoming infected at a faster rate. We can use this information from diagnostic testing to quantify how likely different rates of disease spread are in different poultry houses,” Bonney said.

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