Monitoring Disease in Dairies
Gregory M. GoodellThe Dairy Authority, LLC
Why is Disease Monitoring Important?
Basis of sound animal husbandryPractical and methodical approach to health
in herds with more than a couple of care-takers
Identifies trendsIncreases profitability
Overview
Setting up a Monitoring programData sources and data captureAnalysis
Graphs and numbers Risk calculations Attack rate tables
Types of Monitoring
Contemporaneous monitoring Common health events such as mastitis, pneumonia,
diarrhea, etc. Done to identify health trends in a herd Identify problems as they arise
Spontaneous monitoring NEFA, BHB, Rumen taps Done to rule-in/out specific disease Not performed on a routine basis
Monitoring
The veterinarian must combine the health of the cow, ability of the farm personnel to identify disease and the most prevalent presentation of the disease with goals of the dairy in order to define the case definition and create the protocols that go along with the case definition.
Case Definition
Fundamental basis of disease identificationDefines the diseaseDecreases case-to-case variabilityDecreases variability when multiple people
identifying disease within a single herd.Need to clearly define the cows at risk
(denominator) Do we include dead/sold cows Dry cows? Calves?
Case Definition for Retained Placenta
Is a placenta retained at 12 hrs? 24 hr? or 48 hrs?
Numerator Include RPs found only fresh cows? What about
aborted cows?Denominator
Based on trend trying to identify. Typically fresh cow diseases are defined only in fresh
cows Fresh cow defined as calving at 1 month or less.
Protocols
Protocols required to treat cows consistentlyCreated based on case definitionFor example a treatment protocol for a cow
that has one flake identified in her milk will be different than a protocol for a cow laterally recumbent from mastitis.
Protocols
Monitoring response to treatment is big part of monitoring
Answers… Does treatment work? What is disease recurrence? Treatment cost.
Frequency of Monitoring
Frequency of observations or the time allowed in the denominator is a compromise between time enough to get accurate numbers yet soon enough to intervene when change is needed.
Diseases typically weekly or monthlyProduction indices such as milk/cow or
DMI/cow monitored daily
Consideration of Data Sources
Ability to capture data electronicallyEase of automation and availabilityAccuracy and dependability of data source.
3 Places for Data Capture
Off-Farm (Coop, DHIA, DLab)On-Farm (cow counting, event counting,
treatment cards, clip boards)Online computerized data (milk meters,
conductivity, temperatures, podometers)
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Create forms for data collectionUse with protocols
Forms- Treatment Cards
Evt. Area Other
Date Code Remark Trtmt Drug Dosage Rte Script Clrm Clrb
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Evt. Area Other
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Cow ID
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FRESH COWS
COW ID BCS
FRESH DATE H/B TIME
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COW BREED CALF ID
CALF BREED
CALF PRES
CALF DIFF
CALF NORM
CALF LISTO
CALF SIZE
HRD MN PEN
Cow/Calf Breed Calf Presentation Calf Diff Calf Normal Calf Listo Calf Size:
H=Holstein 1 = Normal 1 = Unassisted 1 = OK 1 = OK 1. <75 lbs
B=Brown Swiss 2 = Backwards 2 = Slight Assist (1 person) 2 = Red/White 2 = DOA 2. 75-84 lbs
O=Crossbred 3 = Breach 3 = Moderate Assist (2+ people) 3 = Deformed 3 = Inj/Alive 3. 85-95 lbs
J=Jersey 4 = Excessive Assist (3+ people/mech/vet) 4 = Other 4 = Abort 4. 95-105 lbs5 = Extreme Assist (+mech/c-sect) 5. >105 lbs
Forms- Fresh Cow
Online Data
Good for daily observation or spontaneous monitoring
Milk and DMIUsually individual cow observations
Graphs and Numbers
Numbers more definitive Counts, averages, rates Rates the best
Graphs good as quick tool Draw gross observations Helpful but can be misleading in general observations Excellent for demonstrating derived numbers
Combo often the best for producer
Using the data
Raw counts Easier for lay personnel to understand Easy to calculate Ie: how many milk fevers were there last week?
Percents Most common Often more meaningful especially for disease Defining time can provide disease incidence rates
helpful for goal setting.
Herd Level Proportions
Prevalence Snapshot in time Good for broad assessment Answers how well we’ve done or how bad the problem
isIncidence
# cases/# lactating cows over a specific period Best number to look at Adjusts for seasonality
Analyze Trends Through Advanced Techniques
Risk Assessment Relative Risk Attributable Risk Population Attributable Risk Population Attributable Fraction
Attack Rate Table
Relative Risk
Incidence of disease for individuals exposed to risk factor divided by Incidence of disease for individuals not exposed to risk factor
An index of strength of the association between the risk factor and the disease
Calculate Confidence Interval (CI). If it contains 1 then it is not significant.
95% CI is best. 90% CI is okay.
Relative Risk Example
Do dry cows considered to be over conditioned have more metabolic issues?
405 cows calved in the last 30 days with 105 metabolic events (Milk Fever, Das and RP). 65 cows with metabolic disease considered overweight. There were 187 total cows considered overweight.
Incidence in fat cows = 65/187 = 34.8%Incidence in normal cows = 40/218 = 18.3%Relative Risk = 34.8% / 18.3% = 1.9
Relative Risk Example
Relative Risk = 34.8% / 18.3% = 1.995% CI = (1.35, 2.67)If includes 1 not significantIf greater then 1 than risk factor adding to dzIf less than one then risk factor is protectiveProducer interpretation: A overweight cow is
90% more likely to experience a metabolic event than a cow that is not over conditioned.
Attributable Risk
Incidence of disease for individuals exposed to risk factor MINUS Incidence of disease for individuals not exposed to risk factor
Removes background incidenceThe additional incidence of disease
attributable to specific risk factor
Attributable Risk Example
Using previous exampleIncidence of exposed was 34.8%Incidence of non-exposed is 18.3%AR = 34.8% - 18.3% = 16.4%What’s meaningful for the producer is that
16.5% of metabolic events are due to overweight cows.
Population Attributable Risk
Attributable Risk x prevalence of risk factorDescribes what part of the disease incidence
is associated with the risk factorHelps us decide on how impactful the risk
factor is on the herd. Using same example then…
Population Attributable Risk
405 cows calved in the last 30 days with 105 metabolic events (Milk Fever, DAs and RP). 65 cows with metabolic disease considered overweight.
PAR = AR x PrevalencePrevalence of the risk factor= 187 / 405 =
46.2%PAR = 46.2% x 16.5% = 7.6%Important to the producer: 7.6% of your herd
will suffer from metabolic disease due to obese dry cows
Population Attributable Fraction
Population Attributable Risk divided by total incidence of disease in population
Predicts proportion of disease eliminated through control of risk factor
Usually used when more than 1 risk factor present
Population Attributable Fraction
PAF = PAR / IncidencePAF = 7.6% x 25.9% = 29.3%Shows us what fraction of the disease
occurrence is associated with the risk factorFor producer then we can say that rate of
metabolic disease will be reduced by 29.3% if we eliminate obese cows
Attack Rate Tables
Used in acute outbreaksProvide top 3-5 risk factorsCalculate risk statistics for exposed and non-
exposed cows by risk factorEvaluate confidence intervalsAssess biological importance!!Calculate economic importance
Attack Rate Table- Mastitis Outbreak
Mastitis rate has increased by 20% in the past 6 months
Risk Factors Dry lot pen Early lactation cows (<100 DIM) Purchased cows Saw dust bedding
Attack Rate Table- Exposed Cows
Exposed Cows
Risk Factor Disease No Disease Total Incidence
Drylot Pen 113 779 892 12.7%
Less than 100 DIM 102 388 490 20.8%
Purchased Cow 68 337 405 16.8%
Saw Dust Bedding 61 315 376 16.2%
Attack Rate Table- Non-exposed cows
Cows NOT Exposed
Risk Factor Disease No Disease Total Incidence
Drylot Pen 107 1040 1147 9.3%
Less than 100 DIM 270 1279 1549 17.4%
Purchased Cow 351 1283 1634 21.5%
Saw Dust Bedding 61 710 771 7.9%
Attack Rate Table Risk Calculations
Risk Calculations
Risk Factor RR AR PAR PAF
Drylot Pen 1.4 3.3% 1.5% 2.6%
Less than 100 DIM 1.2 3.4% 0.8% 1.5%
Purchased Cow 0.8 -4.7% -0.9% -1.7%
Saw Dust Bedding 2.1 8.3% 2.7% 4.9%
Evaluation of Significance
95% Conf. Int.
Risk Factor Variance Min. Max.
Dry lot Pen 0.0162 1.06 1.74Less than 100 DIM 0.0108 0.97 1.46
Purchased Cow 0.0145 0.62 0.99
Saw Dust Bedding 0.0288 1.47 2.86
Interpretation
Dry lot pen has contributed to the mastitis rate Indicates we will eliminate 2% of mastitis rate
Cows less than 100 DIM is not a risk factorPurchased cows- risk analysis says that this is
protective. Biological significance? New cows probably haven’t been exposed to facility
long enough.Sawdust bedding has highest PAF (population
attributable fraction). Indicates we will eliminate 5% of mastitis rate
End of Stats Lesson
Advanced techniques very helpful when multiple risk factors present
Useful to show strength on how much relief a risk factor may provide
Helps convince producer (and you) of the importance of the risk factor
Can assess economics to the decision
Questions?
Mastitis Monitoring
Cases of Mastitis Measured per month (incidence) All cases in herd (prevalence)
Bulk Tank Somatic Cell data Weekly to observe for trends
Individual Somatic Cell data Monthly/quarterly to look at % lactating cows below
200KCulture data
Monthly to look for change in organism type or amount
Mastitis Case Data
Dairy management softwareTreatment cards
Allows assessment of duration Allows assessment of efficacy
Clip board Place to start if nothing else Calculate prevalence/incidence
Quantify Organisms
Gram positive environmentalsGram negative environmentalsContagiousOther
Bulk Tank SCC
Electronic Web page, creamery account
Weekly reportsMilk check
Bulk Tank SCC
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Individual Cow Data
SCC DHIA services and other labs Collect and send Cowside
California Mastitis Test (CMT) Individual quarters
Electrical Conductivity
Culture Data
Most prevalent pathogenAssociate SCC with pathogenFresh cow samplesMastitis cow samples
Contemporaneous Monitoring for BVD
Routine testing best BVD monitoring program Tested the first week of life with an individual test
(ACE or IHC) See 0.05-0.1% in our practice Individual herds as high as 0.5% Enough to cause problems Test both bulls and heifers Euthanize positives
Spontaneous BVD Monitoring
PCR on milk samples by lactating penRecommend putting as few cows as possible
in milk sampleEar notch aborted and DOA calves
Spontaneous BVD Monitoring
Advantages Less expensive
Disadvantages Will not identify BVD very quickly Often missed since only notching aborted and DOA
calvesIf BVD present result is increase in
generalized disease rates especially in youngstock
Johnes Monitoring
Many herds take long term approach of test and manage
Spontaneous monitoring Sample cows with diarrhea Utilize rates and incidence to evaluate trend of clinical
diseaseContemporaneous
All cows sampled at dry off Manage positive cows separately Utilize rates and incidence to evaluate trend of sub
clinical disease
Test Methods
Pooled fecal by PCRPooled individual by PCRELISAIn our practice most dairies will conduct long
term monitoring by sampling cows at dry off using ELISA
Clinical cows are culled and non-clinical positive cows managed separately