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PRRS EpidemiologyBest principles of control at a regional level

Andres Perez, DVM, PhDEndowed Chair of Global Animal Health and Food SafetyUniversity of Minnesotaaperez@umn.eduChicago, December 2015

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Swine Group, University of MinnesotaMike Murtaugh:Xiong WangBob Morrison:Carl BetlachAndres Perez:Pablo Valdes, Moh Alkhamis, Julio Alvarez, Kim VanderWaal

Team workProject participantsSwine Health Monitoring Program: 4 anonymous participantsRegional Control Program N212 (RCP N212): Dave Wright (coordinator) and anonymous program participants

SponsorsSwine Health Information CenterNational Pork BoardUniversity of Minnesota Population Systems and MnDrive programsBoehringer Ingelheim

Vaccination or exposure to live-virus Elimination +sows (test-removal)On-site/off-site testng Cleaning & disinfections of trucksAerosol filtrationImprove biosecurity Control at the farm levelStrategies to control at the farm-level perform reasonably well, but we still need to understand how to control the disease at the regional level (Polson, Mondaca, Cano 2006)

To develop methodological frameworks to:Evaluate progress of Regional Control Programs, RCPs (study 1)Identify the emergence and monitor the spread of new PRRSv strains (study 2)

Objectives

Study 1: Methodological framework to evaluate progress of RCPsPablo Valdes-Donoso, Lovell S. Jarvis, Dave Wright, Julio Alvarez, Andres M. Perez. Measuring progress on the control of porcine reproductive and respiratory syndrome (PRRS) at a regional level: the Minnesota N212 regional control project (RCP) as a working example. PLOS One. Submitted.Objectives: To evaluate:Demographics of enrollmentDemographics of active participation (sharing PRRS status)Trend and spatial distribution of incident cases

So we wanted to propose a methodological

Data: N2126Geographical locationDate of enrollmentPRRS status (weekly)Type of farms

Farm levelLongitudinal (weekly)June 2012 June 2014 (2 years)

Demographics of enrollmentProportion of farms (with sows, SS and without sows, NSS) enrolled in the RCP-N212ANOVANull hypothesis: the proportion of SS and NS farms enrolled in the RCP-N212 was constant through timeStatistical analysis (1/3)

Demographics of active participationGLME model for binary response Response variable: Sharing PRRS status (Y=1, N=0)Effects:Fixed Effects: Time, farm type Random Effects: Site, countySpatial and temporal analysis of sharing PRRS: Normal Scan Statistic Test (SaTScan)Statistical analysis (2/3)

Trend and distribution of PRRS incidenceStatistical analysis (3/3)-GLME model for binary response - Response variable: PRRS status (Pos=1, Neg=0) - Effects: - Fixed Effects: Time, farm type, probability of reporting PRRS, Farm density in the county, Proportion of vaccinated farms in the county - Random Effects: Site, county- Time-space correlation of pairs of incident cases

Results 1/3Number of farms enrolled and geographical coverage increasedRatio: 1/3 sites SS/NSSProportion of SS and NSS, did not change over time (p>0.05)

Demographics of enrollment

Results 2/3Demographics of active participation (sharing)Participation increased significantly (p