Sow Herd Monitoring Tools in PRRSv Control Programs PRRS Diagnostic and Control Workshop Thessaloniki, Greece. August, 2012 Jose Angulo DVM Boehringer Ingelheim Animal Health GmbH – Global PRRS Solutions Jose.angulo@boehringer-ingelheim.com Outline PRRSv Sow herd stability Measurement tools Applications (sharing field examples) PRRS control / Sow Herd Stability Prevent Infection Maximize Herd Immunity Minimize Exposure Definition: Absent of clinical signs attributed to PRRSv and NO EVIDENCE of resident virus circulation within the population. = Weaning PCR negative pigs.* *Gillespie(2003), Dufresne (2004) First milestone in PRRSv control: To Achieve Sow Herd Stability Using dx test as monitoring tool Goal of testing Accuracy and Confidence level Cost of the sampling and testing Frequency of the sampling Vs size sampling Characteristics of the test (Sp,Se) Using ELISA IDEXX Herd Check Commercial kit (Standard) Reliable and well implemented across D-Labs. Costless vs PCR Keep in mind: Measure Exposure, NO protection. Consistent absent of anamnesic Ab response in present of complete protection vs disease ( ab ≠ protection) Unable to differentiate Field exposure vs Vaccine Seropositive pigs become seronegative overtime or following repeated vaccination Murtaugh (2005) Measuring sow herd stabilization Serum Profiles. • ELISA (IDEXX Herd Check) measures exposure. – – – – Population test SP value average (>0.4 +) SP value Standard Variation StD % Positive Reduce Resident virus circulation within Sow Herd & Weaning negative pigs. Gradual (%) Understanding the serological picture with ELISA Idexx Comportamiento Serologico Hembras de Reemplazo Inoculo Vivo (LVI) 1.0000 100% 90% 0.6000 70% 60% 0.4000 50% 0.2000 40% 30% 0.0000 D77/L D77/K D77/J D77/I D77/H D77/G D77/F D77/E D77/D D77/C D77/B D77/A D28/L D28/K D28/J D28/I D28/H D28/G D28/F D28/E D28/D D28/C D28/B D28/A -0.2000 % Positivos 80% D0/L D0/K D0/J D0/I D0/H D0/G D0/F D0/E D0/D D0/C D0/B D0/A Desviacion Estandar 0.8000 -0.4000 10% 0% DS Replacement naive gilts batches LVI in GDU (n=35) 20% % Pos Poly. (DS) Days in GDU D0 Standard Dev 0.004 D28 D77 0.652 0.476 Angulo, Private practice, 2003 Understanding the serological picture with ELISA Idexx Seguimiento perfiles serologico hato 3 100% 90% 2,5 80% 70% Post 2 sp 60% 1,5 50% 40% 1 30% 20% 0,5 10% 0 0% 2003 n=35 (Parity structure) Sow herd serum profile monitoring along the line with MLV mass vaccinations. 2004 Apr 05 Prom s/p Okt 05 Dev. Stand. % Positivos 2003 2004 Abril-05 Octubre -05 SP Avg 2.393a 0.848b 0.575b 0.422b Stand Dev 1.015 0.622 0.989 0.319 % Positive 100 70 57 57 Angulo, IPVS proceedings, 2006 Applying quality tools in the analysis: Box Plot. NWA Quality Analyst Software Oneway Analysis of SP PRRS Hato By Fecha 4 SP PR R S H ato Data exploration tool to analyze and find trends and relationships identifying unique characteristics of the data analyzed. Facilitating its description and interpretation. 3 2 1 0 agost 07 JMP Software Feb-0 8 Fecha Quantiles Level Minimum 10% 25% Media n 75% 90% Maximum agost 07 0 0.114795 0.440744 0.944229 1.658523 2.356496 2.896979 Feb-0 8 0 0.395297 0.944963 1.743764 2.620429 3.028118 4.027211 Std Err Mean Means and Std Deviations Daniel (2004). Biostats, 4th ed. Level Mean Std Dev agost 07 Number 60 1.11777 0.785800 0.10145 Low e r 95 % 0.9148 Upper 95% 1.3208 Feb-0 8 60 1.74107 0.978845 0.12637 1.4882 1.9939 Using Box Plot in Serology Profiles Information about: Shape, Dispersion and Center of the data. Boxplot of 1, 2, 3 Largest Value 4 Outlier 75th Percentile 3 Data 50th Median » Central Tendency Percentile 2 » Dispersion stats Mean 25th1Percentile » Skew » Outlying 0 Smallest Value 1 2 Interval coefficient 3 Measurements » Quick look at expected values MINITAB, 2012 Sow Herd PRRSv serology Variable Samples Mean Std. Dev. Target Hato reproductor Vx PRRS Ma Pre Vx PRRS PRRS_MARZO_08 70 1.03543 1.18679 0.4 PRRS_HR_AGO08 70 0.369097 0.417897 0.4 s/p 0 0.5 1 1.5 2 2.5 3 3.5 4 Based on Median and Quartiles Target Specs PRRSv Serology after PRRSv program implementation Oneway Analysis of SP PRRS Sitio 5 hato By Mes 6 Sitio 5 hato SP PR R S 5 4 3 2 1 0 7-Jun Dic 07 Mes Quantiles Level Minimum 10% 25% Median 75% 90% Maximum 7-Jun 0.046 0.409 0.9145 1.932 3.848 4.7236 5.617 Dic 07 0.186 0.413 0.689 1.311 1.748 1.9088 2.375 Means and Std Deviations Level Number Mean Std Dev Std Err Mean Low er 95% Upper 95% 7-Jun 37 2.38370 1.62982 0.26794 1.8403 2.9271 Dic 07 35 1.26434 0.60027 0.10146 1.0581 1.4705 PRRSv Serology: Outbreak Recovery picture (4,500 sows) Variable Mean Std. Dev. Minimum MaximumConf Level 0.740294 0.027 2.988 95 S_J_I_NOV_04 1.019 S_J_I_ENE_05 1.69907 1.5696 0.054 4.296 95 S_J_I_MAR_05 2.17 0.414104 0.996 2.771 95 S_J_I_JUL_05 1.13127 0.602007 0.193 2.204 95 S_J_I_NOV_05 0.628467 0.469602 1.745 95 0 0 0.5 11.5 22.5 3 3.5 4 4.5 Based on Median and Quartiles Target Specs PRRSv Serology: Outbreak picture Variable Mean Std. Dev . Minimum Maximum Conf Level 48% post SP_ABR05 0.627769 0.639422 0 3.045 95 2.11 95 1.805 95 74% post SP_SEP05 0.853828 0.568553 0.09 57% post SP_FEB06 0.641371 0.516166 0 71% post SP_SEPT_06 0.837429 0.581574 0.092 2.112 95 0.899152 0.688371 0.103 2.842 95 7.488 95 79% post SP_ABR_07 72% post SP_JUL_07 2.02106 2.13882 0 1 2 Based on Median and Quartiles 3 4 5 6 7 0 8 Target Specs Monitoring control strategies Variable Mean Std. Dev . Minimum MaximumConf Lev el % pos 96.6 SP_DIC03 1.63167 0.810751 0.25 3.07 95 1.64286 0.951137 0.2 3.64 95 1.55743 0.785521 0.25 3.07 95 3.6081 95 1.884 95 % pos 94.2 SP_MAY 04 % pos 94.2 SP_J UL_04 Context: • 2,000 sows FF farm. • Mass Vx every 6 months (04). • 2006 Mass Vx every 3 months. % pos 68.5 SP_F EB_06 1.01923 0.863162 0 % pos 83 SP_J UL_06 0.9045710.465189 0 0.5 1 Based on Median and Quartiles 1.5 2 2.5 3 3.5 0.195 4 Target Specs Angulo, AMVEC, 2006 Home take messages Tools for measuring sow herd stability are available Understanding of diagnostic tests is critical Add all measurements to bring the general picture Link tools with goals Simple tools like Box Plot can add value to the analysis, interpretation and decision making process. » Statistic Software or Excel!! Thanks for your attention