Disease. Treatment decisions. Identify sick cows

Transcription

1 w l $3 $7 $12 $15 $21 $25 Visual observation of estrus cost 1 person 3 h per day at $12.5 per hour of labor Julio Giordano, DVM, MS, PhD Dairy Cattle Biology and Management Laboratory Net Value ($/cow/yr) Difference with baseline B Activity Tag Cost = $90 per tag 3 yr life expectancy c 5yr life expectancy 7 yr life expectancy -$5 $3 $ Scenario (% of cows AI at detected estrus) Health conditions to monitor post-partum period: Retained placenta Metritis Mastitis Displaced abomasum Ketosis Hypocalcemia Diarrhea Pneumonia Identify sick cows Treatment decisions Immune Response & (-)EB Disease Improved wellbeing and productivity Substantial variation across farms frequency of checks, type of evaluation, labor demand and aids used Health monitoring programs costly time consuming require qualified labor

2 Reduce burden associated with monitoring programs? More consistent and objective evaluation? Reduce disruption of cow normal behavior? (1)Performance of the HR system to identify cows with health disorders (HD). (2)When does the HR system identify cows with CD compared to farm personnel? Days Daily Amount Health Cow Lactation Days in Activity Ruminati Group from Last Ruminati Of Index for Number Status Lactation Peak on Peak Breeding on Evaluatio Non Before Before Before No Heat Colostrum Before Before Colostrum No Heat Ready Before Before Ready Ready Before Evaluate the ability of Health Index (HI) score to identify cows with health disorders. Baseline data Rumination, Activity, and Health index Score raw data (every 2 h) Collection Health monitoring = RP, MF, MET, MAST, KET, DA and IND Collars on (HR-Tags) Calving N=1,121 cows Study period: November 2013 to October 2014 Collars off (HR-Tags)

3 Disorder Cows detected Se, % (95% CI) HI <86 to CD (d) DA (n = 41) 98 (93-100) -3 (-3.7 to -2.3; P<0.01) Ketosis (n = 54) 91 (83-99) -1.5 (-2.3 to -1.0; P<0.01) Indig. (n = 9) 89 (68-100) -0.5 (-1.5 to 0.5; P=0.28) All metabolic & dig. (n = 104) 93 (89-98) -2.1 (-2.5 to -1.6; P<0.01) Stangaferro et al., 2016 (JDS; 99(9): ) Health Index Score arbitrary units/d HEALTH INDEX * Group: P<0.001 Day: P=0.59 Group *Day: P< Days relative to clinical diagnosis DAILY ACTIVITY * Rumination (min/d) DAILY RUMINATION * Group: P<0.001 Day: P<0.001 Group *Day: P< Days relative to clinical diagnosis Group: P<0.001 Day: P=0.66 (n = 451) Group *Day: P<0.001 (n = 1) (n = 40) Days relative to clinical diagnosis Stangaferro et al., 2016 (JDS; 99(9): ) Cows detected Se, % (95% CI) HI <86 to DCD (d) Disorder Metritis ALL (n = 349) 55 (49-60) -1.2 (-1.6 to -0.7; P<0.01) Antibiotic treatment Cephalosp. (n = 292) 49 (43-55) -1.1 (-1.6 to -0.6; P = 0.17) DA Ampi./Oxytet. (n = 57) 83 (70-91) -1.4 (-2.1 to -0.7; P = 0.17) Stangaferro et al., 2016 (JDS; 99(9): )

4 Group: P = 0.11 Day: P<0.001 Group *Day: P = Multiparous (n = 451) (n = 156) (n = 184) Primiparous Stangaferro et al., 2016 (JDS; 99(9): ) Stangaferro et al., 2016 (JDS; 99(9): ) Disease Cows detected % Se (95% CI) HR Flag to DCD (days) Mastitis (n = 165) 53 (45-61) -0.6 (-1.1 to -0.2; P<0.01) Clinical (n = 123) 58 (49-67) -1.2 (-2.7 to 0.3; P=0.12) By Pathogen E. Coli. (n = 31) 81(67-95) -0.5 (-1.1 to 0.2; P=0.18) Gram + (n = 39) 49 (32-65) -0.5 (-1.4 to 0.5; P=0.31) Staph. Aureus (n = 11) 46 (17-77) -1.4 (-4.1 to 1.3; P=0.23) No growth 48 h (n = 25) 48 (28-69) -0.2 (-1.4 to 1.1; P=0.78) Gram (+) = Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus uberis, Streptococcus species, Staphylococcus species, Actinobacillus pyogenes. Group: P<0.001 Day: P<0.001 Group *Day: P<0.001 Stangaferro et al., 2016 (JDS; 99(9): ) Stangaferro et al., 2016 (JDS; 99(9): )

5 False positives 2.4 (1,955/72,423) % (n/n) 95% CI Specificity 97.6 (70,695/72,423 ) Accuracy 95.6 (73,111/76,519) Each day was considered a new test , 95.7 Total number of days in the study was determined for individual cows until 80 DIM or DIM at which cows left the herd (sold or died) Stangaferro et al., 2016 (JDS; In Press) The HR system is most effective to identify cows suffering metabolic and digestive disorders. A relatively lower Se to identify cows with MET and MAST might be explained by less severe systemic illness and type of mastitis-causing pathogen. The HR system identified cows with DA, KET, MET and MAST earlier than farm personnel. Stangaferro et al., 2016 (JDS; In Press) Opportunities Earlier treatment: -improved response -improved well-being -prevent associated disorders Challenges Treatment decisions in the absence of clinical signs? Prophylactic treatment?

6 w l $3 $7 $12 $15 $21 $25 Visual observation of estrus cost 1 person 3 h per day at $12.5 per hour of labor Add HI report to fresh cow check list Greatest benefit for DZ that occur after 3 DIM Farms with little-to-no intervention identify more cows with health disorders Farms with intensive health monitoring reduce labor & cow manipulation DIM = 1 100% ED Calving DIM = 1 ED + TAI Calving DIM = 1 100% TAI Calving VWP VWP Presynch ED Most common + 1 st AI strategy used by dairy farms ED + 2 nd AI TAI1 ED + AI Synch ED + AI VWP TAI1 Synch Combination of ED + estrus detection 3 rd AI and timed AI TAI2 Synch ED + AI TAI2 Synch B 30 Activity Tag Cost = $90 per tag Net Value ($/cow/yr) Difference with baseline yr life expectancy c 5yr life expectancy 7 yr life expectancy -$5 $3 $ Scenario (% of cows AI at detected estrus) CUT-OFF ED + 4 th AI ED + 5 th AI DNB TAI 3 CUT-OFF Synch DNB TAI 3 CUT-OFF Synch DNB

7 Days Daily Amount Health Cow Lactation Days in Activity Ruminati Group from Last Ruminati Of Index for Number Status Lactation Peak on Peak Breeding on Evaluatio Non Before Before Before No Heat Colostrum Before Before Colostrum No Heat Ready Before Before Ready Ready Before Difficulties with traditional methods Poor compliance Subjectivity of method Variation among cows Labor intensive and repetitive Potential benefits of AED systems Continuous monitoring Objective evaluation of behavior or physiological status Elimination or substantial labor reduction Automated estrus detection of interest Difficulties with traditional methods to: Poor compliance Subjectivity of method Variation among cows Labor intensive and repetitive Potential benefits of AED systems Continuous monitoring Objective evaluation of behavior or physiological status 1. Farms that struggle with traditional estrus detection methods 2. Prefer to allocate labor resources and time to other activities Elimination or substantial labor reduction 3. Others add-on to other technologies, likes technology Behavioral Estrus in Dairy Cattle Secondary signs Sniffing Mucus discharge Redness vulva Mounting activity Increased physical activity Activity Tag Reader or antenna Wi-Fi Software Activity change (arbitrary units) Raw activity (arbitrary units)

8 Episode duration Episode duration Mean ~10 to 16 h Physical Activity Estrus alert threshold Increment compared with baseline Increased physical activity during estrus - 300% more steps - pedometers or accelerometers (Dolecheck et al., 2015; Madureira et al., 2015) - 200% more activity - neck or ear-mounted accelerometers (Liu and Sphar 1993; Dolecheck et al., 2015; Madureira et al., 2015) Physical Activity Estrus alert threshold Increment compared with baseline Valenza et al., (2012) Time Time AAM System (n = 88) Physical Activity Estrus alert threshold Mean ~25 to 29 h 68% Heat-Ovu Heat-NoOvu NoHeat-Ovu NoHeat-NoOvu 10% 3% Valenza et al., (2012) 19% Time Valenza et al., 2012

9 AAM System (n = 88) Heat-Ovu NoHeat-Ovu Heat-NoOvu NoHeat-Ovu NoHeat-NoOvu 68% 10% Heat-NoOvu 3% Physical Activity Estrus alert threshold 19% NoHeat-NoOvu Stevenson et al., (2014) Time Valenza et al., anestrus Extended DIM to first AI vs. 2-ovulatory failure 3-anestrus and anovulation Valenza et al., (2012) Stevenson et al., (2014) vs. Scenario Time Window Michaelis et al., 2014 (Reprod. Domes. Anim. 49:621-8) Collar type Gs(+) milking (no.) Gs(-) milking (no.) SN (%) SP (%) PPV (%) All , AO , AR , Kamphuis et al., 2012 (JDS 95: ) Sensitivity = 90% False positives = 17% Aungier et al., 2015 Sensitivity = 74 to 87% PPV = 65 to 95% Chanvallon et al., 2014 Delayed re-insemination

10 1-anestrus Extended DIM to first AI P = 0.38 P = 0.15 HR % CI= ovulatory failure 3-anestrus and anovulation Valenza et al., (2012) Stevenson et al., (2014) Fricke et al., 2014 (JDS 97: ) Giordano et al., 2015 (JDS 98:2488:2501) Sensitivity = 90% False positives = 17% Aungier et al., 2015 Delayed re-insemination P = 0.97 HR % CI= Sensitivity = 74 to 87% PPV = 65 to 95% Chanvallon et al., 2014 Stevenson et al., 2014 (JDS 97: ) Dolecheck et al., 2016 (JDS 99: ) Summary Programs that incorporate AIACT are Fricke comparable et al., 2014 to programs Giordano that et al., 2015 rely (JDS 97: ) (JDS 98:2488:2501) more on TAI P = 0.15 P = 0.38 HR % CI= AIACT + TAI In all cases some level of hormonal intervention was implemented to ensure timely insemination Dolecheck et al., 2016 (JDS 99: ) P = 0.97 HR % CI= Key facts: -minimizes use of hormonal treatments -beneficial to use timed AI after period of AIACT Stevenson et al., 2014 (JDS 97: )

11 PGF + AIACT + TAI 1 st AI = PGF + AIACT + TAI 2 nd AI = PGF + AICT + TAI or TAI Key facts: -increases cows AIACT after VWP and non-pregnancy diagnosis -beneficial to use synch protocol after PGF treatment -unnecessary PGF treatment for cows without a CL Key facts: -increases cows AIACT after VWP and non-pregnancy diagnosis -treatment adapted to cow physiological status for 2+ AI -beneficial to use synch protocol after PGF treatment Activity Tag Improvement in ED rate to breakeven or be profitable depends largely on: 1. Baseline proportion of cows EDAI with current VO program Greatest returns when current cows EDAI = 30%. Smaller returns and less likely to be more profitable when cows EDAI = 60% 2. Life expectancy of system and upfront cost Lasts for at least 5 years Life expectancy more relevant than tag cost 3. Cost of current program for VO of estrus Greatest resturn for herds with expensive VO program cost Other potential benefits not accounted for!!!

12 Thank you! Calving VWP Recheck Calving ~50% ~100% Type of tag Labor $$$ -Action lists -Compliance -Enhanced estrus alerts Julio Giordano