Best practices to submit samples: new UMN VDL handouts available

If you are unsure about how to submit processing fluids or laryngeal swabs, the University of Minnesota Veterinary Diagnostic Laboratory put together one-age illustrated handouts to guide you towards best practices for each commonly used sample type. Each one of them is available in a downloadable pdf format for convenience.

The handouts can be found on the VDL website.

OptisampleTM: Open web-based application to optimize sampling strategies for active surveillance activities at the herd level illustrated using PRRS

This past Saturday during the 49th AASV annual meeting, Dr. Rovira presented OptisampleTM, an online open-access tool to determine sample strategies for disease surveillance.

Did you miss this presentation? Click here to see the schedule of our talks during the 2018 AASV meeting!

Dr. Ana Alba who created this tool published an open-access article on how to use Optisample for PRRS active surveillance.

Several inputs are needed to use this web-based application: herd size, frequency of testing, minimum prevalence to detect…

3 different herd examples are then shown to test for PRRSV surveillance. The input and outputs of those examples are show in the figure below:

If you want to try out OptisampleTM, click here.

Abstract

Porcine reproductive and respiratory syndrome virus (PRRSv) infection causes a devastating economic impact to the swine industry. Active surveillance is routinely conducted in many swine herds to demonstrate freedom from PRRSv infection. The design of efficient active surveillance sampling schemes is challenging because optimum surveillance strategies may differ depending on infection status, herd structure, management, or resources for conducting sampling. Here, we present an open web-based application, named ‘OptisampleTM’, designed to optimize herd sampling strategies to substantiate freedom of infection considering also costs of testing. In addition to herd size, expected prevalence, test sensitivity, and desired level of confidence, the model takes into account the presumed risk of pathogen introduction between samples, the structure of the herd, and the process to select the samples over time. We illustrate the functionality and capacity of ‘OptisampleTM’ through its application to active surveillance of PRRSv in hypothetical swine herds under disparate epidemiological situations. Diverse sampling schemes were simulated and compared for each herd to identify effective strategies at low costs. The model results show that to demonstrate freedom from disease, it is important to consider both the epidemiological situation of the herd and the sample selected. The approach illustrated here for PRRSv may be easily extended to other animal disease surveillance systems using the web-based application available at http://stemma.ahc.umn.edu/optisample.