Estimating epidemiological parameters using diagnostic testing data from low pathogenicity avian influenza infected turkey houses

Limiting spread of low pathogenicity avian influenza (LPAI) during an outbreak is critical to reduce the negative impact on poultry producers and local economies. Mathematical models of disease transmission can support outbreak control efforts by estimating relevant epidemiological parameters. In this article, diagnostic testing data from each house on a premises infected during a LPAI H5N2 outbreak in the state of Minnesota in the United States in 2018 was used to estimate the time of virus introduction and adequate contact rate, which determines the rate of disease spread. A well-defined most likely time of virus introduction, and upper and lower 95% credibility intervals were estimated for each house. The length of the 95% credibility intervals ranged from 11 to 22 with a mean of 17 days. In some houses the contact rate estimates were also well-defined; however, the estimated upper 95% credibility interval bound for the contact rate was occasionally dependent on the upper bound of the prior distribution. The estimated modes ranged from 0.5 to 6.0 with a mean of 2.8 contacts per day. These estimates can be improved with early detection, increased testing of monitored premises, and combining the results of multiple barns that possess similar production systems.

Automated summary

Limiting the spread of low pathogenicity avian influenza (LPAI) during an outbreak is crucial to minimize the negative impact on poultry producers and local economies. Mathematical models were used to estimate key epidemiological parameters such as the time of virus introduction and contact rate during a LPAI H5N2 outbreak in Minnesota, USA in 2018. Results suggest that early detection, increased testing, and combining data from similar production systems can improve estimation accuracy.