Animal health economics and precision farming
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Economics of animal health and precision farming
Henk Hogeveen
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Who am I Born on a dairy farm (1966) Animal science at Wageningen University
●Epidemiology (simulation model of management regarding cystic ovaries)
●Economics (long term effects of herd health management programs)
PhD at Fac. Veterinary Medicine (AI to diagnose mastitis) Professor in Animal health management
Business economics group, Wageningen UniversityFaculty of Veterinary Medicine, Utrecht University
@henkhogeveen slideshare.net
animal-health-management.blogspot.com
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Outline The Dutch dairy sector Economics of animal health Disease control: optimization Modeling economics of animal health Examples normative modelling Empirical modelling Modern management: Precision dairy farming Final remarks
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Cattle through the last 14 years (* 1,000)Now: ~1.3 bln kg milk
1999 2002 2005 2008 2011 20143650000
3700000
3750000
3800000
3850000
3900000
3950000
4000000
4050000
4100000
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Grass-based system
Summer●Fresh grass + corn silage + concentrates
Winter●Grass silage + corn silage + concentrates●Half mixed ratio
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Dutch dairy sector
Increasing farm seizes Mostly own (family) labour Half grass-based system
●Grazing under pressure (farm management)●Stimulated (societal preference)
Volatile milk prices More challenges on management
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and …..
Animal health is becoming more and more important Stimulated by dairy industry
●Improvement of udder health●Improvement of claw health●Improvement of longevity
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Outline The Dutch dairy sector Economics of animal health Disease control: optimization Modeling economics of animal health Examples normative modelling Empirical modelling Modern management: Precision dairy farming Final remarks
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Economic effects of animal disease
Output
MilkMeatEggsDraft power…….
After: McInerney, 1996
Human benefit (utility)
Input
LandLabourCapital
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The field: Economic effects of animal disease
Output
MilkMeatEggsDraft power…….
Disease
1. Lower efficiency
2. Lower suitability for consumption
3. Lower human well-being
Human benefit (utility)
Input
LandLabourCapital
1.
2. 3.
Most economic work
J. Agricultural Economics, 1996
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Types of animal diseases Production diseases
●On-farm optimization●Externalities ●E.g., mastitis, lameness, APP
Endemic contagious diseases●On-farm control decision● Interaction between farms●E.g., BVD, Aujeszky’s disease
Notifiable contagious diseases●Regional control decisions (eradication)●Surveillance●E.g., FMD, AI, rabies, BSE
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The management problem
Consequences animal health
Epidemiological consequences
Veterinary knowledge of diseases
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The management problem
Consequences animal welfare
Consequences human health
Consequences animal health
Epidemiological consequences
Knowledge about externalities
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The management problem
Consequences animal welfare
Consequences human health
Costs of intervention
Consequences animal health
Epidemiological consequences
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Decisons become increasingly complex
Decision makerObjectives
Available resources
Consequences animal welfare
Consequences human health
Costs of intervention
Consequences animal health
Epidemiological consequences
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Levels of decision making Individual animals
● Treatment● Culling● Interaction
Groups of animals (herd/farm)● Prevention● Eradication
Sector● Control● Eradication
Region● Control● Eradication
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Levels of decision making Individual animals
● Treatment● Culling● Interaction
Groups of animals (herd/farm)● Prevention● Eradication
Sector● Control● Eradication
Region● Control● Eradication
Production diseases& Endemic contagious diseases
Type of disease
Contagious notifiable diseases
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Levels of decision making Individual animals
● Treatment● Culling● Interaction
Groups of animals (herd/farm)● Prevention● Eradication
Sector● Control● Eradication
Region● Control● Eradication
Farmer, supported by advisor
Farmer’s organisationProcessors
Government
Decision maker
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Outline The Dutch dairy sector Economics of animal health Disease control: optimization Modeling economics of animal health Examples normative modelling Empirical modelling Modern management: Precision dairy farming Final remarks
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Maximization
Veterinarians want to maximize animal health
●If there is a vaccine, use it●If there is a (better) treatment, use it●In case of doubt: treat (better safe than sorry)
Medical doctors also want to maximize health
●And minimize risk of infectionMicrobiologists want to maximize detection
●If there are more precise tests, use it
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But ……. Is it optimal?
There is more than only the health of animals:●Money●Time●Availability of drugs or vaccin
So measures need to be balanced
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Economic effects of diseases
Expenditures (additional resources) ●Drugs●Veterinarian●Labour●Expenditures to control disease
Losses (decrease in production)●Decreased production level●Discarded milk●Changes in milk price (milk quality)●Culling
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Total costs
Expenditures + losses Often overlooked 90 % of studies only look at losses Farmers tend to look at expenditures We need to optimize
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Control vs failure
Control expenditures (€)
Output losses (€)
J. Agricultural Economics, 1996
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Source: McInerney et al., Prev. Vet. Med, 1992
High losses, low control expenditures
Control vs failure
Control expenditures (€)
Output losses (€)
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Source: McInerney et al., Prev. Vet. Med, 1992
Low losses, high control expenditures
Control vs failure
Control expenditures (€)
Output losses (€)
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Source: McInerney et al., Prev. Vet. Med, 1992
Optimal
Control vs failure
Control expenditures (€)
Output losses (€)
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Outline The Dutch dairy sector Economics of animal health Disease control: optimization Modeling economics of animal health Examples normative modelling Empirical modelling Modern management: Precision dairy farming Final remarks
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Basic approach
Normative modelling●Relate costs of intervention
with animal health andepidemiological consequences
●Cost-benefit analysis (alternative: cost effective or cost utility analysis)
●Assuming profit maximising behaviour of farmers●Basis for on-farm decision support tools
Empirical modelling●Use data to compare farms/animals/groups of
animals with and without intervention●Experiments or existing datasets (accountancy data)
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Normative models
Simulation model Input data based on data, literature, expertise Relatively cheap Pragmatic approach Bio-economic modelling: economics combined with
detailed physiological basis
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Models ……. do not capture the complexity of the real situation
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Models……. are sometimes nicer than reality (too good to be true)
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Some terminologyStatic vs dynamic
●behaviour over timeDeterministic vs stochastic
●definite predictions or averages (deterministic)●output is probability distributions (stochastic)●variability of the system uncertainty of knowledge
Spatial●Space effects play a role
Optimization vs simulation●optimum solution, given an objective●outcome given a pre-defined set of input
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Economics is about money. Right?
What about●Human disease (zoönoses)●Welfare●The environment●…….
Express these in money ……
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Different approaches
Cost-minization analysis Cost-effectiveness analysis Cost-utility analysis Cost-benefit analysis
Differ in: measurement of effect
utility benefit
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Outline The Dutch dairy sector Economics of animal health Disease control: optimization Modeling economics of animal health Examples normative modelling Empirical modelling Modern management: Precision dairy farming Final remarks
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First step in all modelling
Costs of disease●Costs of rabies control on Flores island●Costs of Foot and Mouth Disease in Ethiopia●Costs of Avian Influenza in Central Java
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Costs of control of rabies
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 20110
100
200
300
400
500
600
700
800 PET human
Trace back investigationDiagnostic costs in animals
Dog-bite investigationDog cullingDog vaccination
Year
Cost
s of
con
trol
mea
sure
s (x
1000
$U
S)
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SPIN project:
Data collection to calculate costs of poultry diseases in Western Java
4 types of poultry farms Overall costs Variation between farms and farm types
Dikky Indrawan, Much. Gumilang & Eko Rudi Cahjadi
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Dry cow therapy
Treatment of cows that dry off (before calving) Antibiotics Individual cow decision Two modes of action:
●Cure of existing (chronic) intramammary infections●Prevention of new infections during dry period
Often herd decision (blanket dry cow therapy)
Debate on selective vs blanket dry cow therapy
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Stochastic model
Cow as basic unit Dynamic around dry period Results summarized for whole herd Accounting for differences between pathogens Dutch circumstances
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Selective dry cow treatment cheapest
Blanket Selective NoIMIdo (%) 15 (7.7, 23.1) 15 (7.7, 23.1) 15 (7.7, 23.1)
Treatment (%) 100 35 (23, 46) 0IMI at calving 7.5 (3.1, 12.3) 12.3 (6.2, 20) 19.3 (12.3, 27.7)
Clinical mastitis (%) 1.8 (0, 4.6) 3.2 (0, 7.7) 5.1 (1.5, 10.8)
Treatment costs (€/cow) 10.1 (10.1, 10.1) 3.5 (2.3, 4.7) 0
Production losses (€/cow) 1.3 (0.5, 2.2) 2.1 (1.0, 3.4) 3.3 (2.0, 4.7)
Clinical mastitis (€/cow) 4.2 (0, 14.6) 8.1 (0, 22.9) 14.7 (2.0, 38.5)
Total costs (€/cow) 15.6 (10.6, 26.6) 13.7 (4.9, 29.4) 18.0 (4.1, 42.6)
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Little different results with extended model4 scenarios
Total net costs of scenarios:1 (BDCT): € 8,8002 (BDCT + TS): € 9,1783 (SDCT): € 9.2434 (SDCT + TS): € 9.435
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New discussion onantibiotic resistance
Resistance of mastitis pathogens●Self-interest●No increase seen (Hogan, IDF-factsheet)
Antibiotic resistance in humans●Externality●Dairy cattle has very minor contribution (Oliver et al., 2011)
Decision of government In the Netherlands (self) regulation
●Maximum amount of antibiotics to be used (< 50 %)
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Optimizing: linear programming (Maas, 2014, MSc thesis)
Farm level Cows with high SCC are treated
●Primiparous > 150.000 cells/ml●Multiparous > 250.000 cells/ml
Other cows selective Categorized at SCC level Optimization to minimize total costs of treatment and
mastitis around dry periodBased on: Maas, 2014, MSc thesis
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We’re also interested in amount of AB
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Constraining antibiotic use has economic effects
100%
95%90%85%80%75%70%65%60%55%50%45%40%35%30%25%20%15%10% €39
€41
€43
€45
€47
€49
€51
€53
Average farmLow BTSCC farmHigh BTSCC farm
Percentage allowed antibiotics (%)
Cost
s pe
r lo
w S
CC c
ow
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Outline
Decision making on animal health●The decision problem●The levels of decision making
Some examples of analyses●Dry cow therapy●Slaughterhouse measures to reduce the BSE
load●Blue tongue control●Veterinary herd health and management programs
Final words
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Bovine Somato Encyphaleomytis
Mad cow disease
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BSE
1986 first described 1996 -> link with Creutzveldt Jacobs Disease (vCJD) Since August 1989 measures against BSE in the
Netherlands●Since 1990 feed ban (no animal protein)●Since 2000 dead cattle older than 30 m tested●Since 2001 slaughtered cattle older than 30 m
tested●Disposal of BSE risk materials●Culling of cohort of detected animal
Incidence of BSE is virtually 0
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Are preventive measures cost-effective?
Simulation modelling●Static●Stochastic●Simulation
Monte carlo model●1 iteration = 1 year●Baseline: no intervention●Alternative: one or more interventions
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Model
3 types of BSE●Clinically affected●Test detectable●Non detectable (3 for every detectable)
Per BSE type of BSE load (from different organs) of the food supply was calculated
Based on Infectious doses, risk of vCJD Prevented case of vCJD -> life years saved (most likely
51) Comparison: do nothing vs intervention
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Costs
Removal of specific risk material (~60 kg): €/kg slaughtered weight
Transport of specific risk material Post mortem testing: € 90 per head Costs of cohort culling
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Results - retrospective
Year 2002 2005
Number of BSE cases (total, at slaughter) 24, 12 3, 2
BSE load of the food supply Mean 5th – 95th Mean 5th – 95th.
Baseline scenario 34,857 30,213-39,602 5,502 3,592-7,620
SRM removal 2,330 2,020-2,648 368 240-509
Post-mortem testing (PMT) 7,455 4,846-10,306 939 198-2,091
PMT and cohort culling 7,059 4,505-9,865 939 197-2088
SRM removal and PMT 498 324-689 63 13-140
SRM removal and PMT and cohort culling 472 301-659 63 13-139
Food risk (life years lost) Mean 5th – 95tb Mean 5th – 95th pct.
Baseline scenario 16.98 8.66-26.70 2.69 1.25-4.61
SRM removal 1.14 0.58-1.79 0.18 0.08-0.31
Post-mortem testing (PMT) 3.63 1.67-6.27 0.46 0.08-1.11
PMT and cohort culling 3.44 1.56-5.94 0.46 0.08-1.11
SRM removal and PMT 0.24 0.11-0.42 0.03 0.005-0.07
SRM removal and PMT and cohort culling 0.23 0.10-0.40 0.03 0.005-0.07
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Costs (mln €)
Year2002 2003 2004 2005
SRM removal19.22 18.27 19.29 19.82
Post-mortem testing38.16 29.56 26.57 21.12
Cohort culling6.97 4.80 3.41 2.43
Total costs64.34 52.64 49.27 43.37
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Cost-effectiveness
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Cost-effectiveness 2002-2005
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Outline
Decision making on animal health●The decision problem●The levels of decision making
Some examples of analyses●Dry cow therapy●Slaughterhouse measures to reduce the BSE load●Blue tongue control●Veterinary herd health and management programs
Final words
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Blue tongue disease
Viral disease Generic disease effects Production losses
Several subtypes BTV 8 problem
Spread by midges
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First step: decision analysis
6 7
2
1
3 5
4
Vaccinate yes or no
Herd
exposure to BTV-8
Disease effects
Export effects
Income effects
Consideration 1: Reduces the impact of BTV-8 in the risk period of infection (1, 2, 3)
Consideration 2: Almost guarantees that heifer meant for export can be exported during the epidemic (4, 5)
Consideration 3: Helps to control the transmission (vaccination behaviour over time) (6, 7)
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DE 1
HE 1
V 1
EXR 1
NV1
NV2
HE 2
V 2
DE 2
Export restriction
Disease effects
Herd exposureVaccinate?Vaccinate?
Herd exposure
Disease effects
Export restriction
EXR 2
Probability of disease effects in year 1
Economic consequences of DE1 calculated with model Velthuis (2010)
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Vaccinate againt BTV8 or not
Vaccination
No vaccination
Income losses (Euro)
Prob
abili
ty d
ensi
ty
BTV8 outbreakYear 1: high net expected utility of vaccinationYear 2: risk attitude important
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After theory of reasoned action and theory of planned behaviour
Fishbein and Azjen reunite Reasoned action approach Addition of actual control Injunctive norms and descriptive norms Addition of background factors and feedback loops
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I = A(b+e)+Ni(s+m)+Nd(s+m)+PBC(s+p)
• Ni: perception of what the reference is thinking about what he/she should do
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I = A(b+e)+Ni(s+m)+Nd(s+m)+PBC(s+p)
• Nd: perceived behavior of others (farmers)
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RRA and questionnaire
Constructs Items Preceding phrase Item description
If Bluetongue would turn up in the environment this year, is preventive vaccination of my herd …
unsatisfying – satisfying1
disadvantageous – advantageous2
necessary – unnecessary2
unimportant – important2
acceptable – unacceptable1
If Bluetongue would turn up in the environment this year …
then people who have something to do with my farm expect me to vaccinate my herd preventively.
then people in the industry whose opinions I value would approve of me vaccinating my herd preventively.
then people who are important to me think that I should vaccinate my herd preventively.are farmers like me going to vaccinate their herd preventively.
If Bluetongue would turn up in the environment this year, and a voluntary vaccination programme would be announced ...
do I have the possibility to vaccine my herd preventively.3
could I vaccinate my herd preventively, if I wanted to.3
is it up to me whether I vaccinate my herd preventively.4
If Bluetongue would turn up in the environment this year, and a voluntary vaccination programme would be announced …
am I going to vaccinate my herd preventively.
do I want to vaccinate my herd preventively.
am I willing to vaccinate my herd preventively.1 = experiential dimension, 2 = instrumental dimension, 3 = capacity dimension and 4 = autonomy dimension.
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QUESTIONNAIRE
If I vaccinate my herd preventively when Bluetongue would be in my vicinity next year,
Not very likely > > > > Very likely
1 2 3 4 5
get my cows to do with negative side effects and/or stress. ⃝ ⃝ ⃝ ⃝ ⃝
Will the following motive be of importance when deciding to vaccinate your herd preventively, when Bluetongue would be in your vicinity next year?
Of no importance < < > > Of importance
-2 -1 0 +1 +2
Negative side effect and/or stress with my cows ⃝ ⃝ ⃝ ⃝ ⃝
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Approach: Vaccination for BTV8
• A two-step modelling approach:• Step 1: Estimate a measurement model (MM) using Confirmatory
Factor Analysis (CFA)• Step 2: Estimate a structural model (SM)
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Final results
1.00 0.62* 1.00 0.33* 0.50* 1.00 0.36* 0.25* 0.06 1.00 0.78*
0.62* 0.38* 0.36* 1.00
* = < 0.001
0.61
( < 0.001)0.18
( < 0.002)0.09
( < 0.05)0.08
( < 0.10) 35%
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Outline The Dutch dairy sector Economics of animal health Disease control: optimization Modeling economics of animal health Examples normative modelling Empirical modelling Modern management: Precision dairy farming Final remarks
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Empirical modelling
Using economic performance of farms Difficult (lack of data) Link performance to disease situation Econometrics
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Veterinary herd health management
We want farmers to uptake VHHM●Better health●Better welfare●Better
Prevention vs cure Farmers have to pay
We did not do any fully normative modelling
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Data collection 1
5,000 farms (207 veterinary practises) Questionnaire about VHHM 695 replies (69 % VHHM) Milk production and fertility data available Analyses on MPR data in relation to VHHM
●ANOVA/T-test●Linear regression, herd size●Linear mixed model
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Effects VHHM
Participation●More milk (+336 kg/cow/year)●Lower SCC (-8,340 cells/mL)●Lower first calving age ALVA (-12 d) ●Lower % non return 56-d (−3.34%)●More inseminations per cow (+0.09). ●More culled cows (+1.05%)●Lower age at culling (−70 d).
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Two economic studies
Semi-empirical Empirical Question:
If you compare the costs of VHHM with the economic value of improvements, is VHHM cost-effective?
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Semi-empirical study
All farms from previous study Look at VHHM and estimate costs (normative)
●Farm seize●Reproductive performance●Intensity of VHHM
Calculate net returns milk production Calculate costs of replacement
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Used normative factors
Variable Abbreviation Value
Call-out costs of veterinary visit (€/visit) Cv 30
Costs of time of veterinarian (€/hour) Ct 120
Time necessary for a pregnancy check (min.) Pt 2
Time necessary to discuss the first topic (min.) Tt1 10
Time necessary for each additional topic (min.) Tt2 5
Costs of replacement heifer (€) Ch 888
Table 2. Assumptions to calculate the costs of VHHM based on farm data.
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Results
VHHM* NVHHM
Min Max Mean Min Max Mean
NRmilk 1452 3160 2403 1173 3066 2293
Cvhhm
Startup cost vet visit 1.06 26.00 4.71 - - -
Cost of pregnancy check 0 10.00 8.09 - - -
Cost of time for discussion 0.56 40.48 6.79 - - -
Total 1.62 67 19.62 - - -
NRvhhm 1429 3138 2388 1173 3066 2293
Costs of replacement heifer 51 415 224 76 464 212
NRtot 1198 2887 2164 1018 2851 2081
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Empirical study
Bookkeeping firm (Alfa Accountants) Questionnaire send to 572 farms 187 replied (85 participants, 102 non part) All farm economic data available Stochastic frontier analysis
●Looking at efficiency of farms●4 models: financial data per cow/kg milk and
including/excluding farm structure variables
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Farm efficiency (DEA)
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Variable Participant Mean (sd) se P-value
Total revenue/100 kg cmilk yes 35.52 (3.28) 0.36 0.16
no 34.71 (4.32) 0.43
Feed costs/100 kg cmilk yes 7.44 (1.40) 0.15 0.80
no 7.38 (1.75) 0.17Health and med costs/100 kg cmilk yes 1.31 (0.59) 0.07 <0.01
no 1.01 (0.43) 0.04Cattle costs/100 kg cmilk yes 2.84 (0.71) 0.08 <0.01
no 2.35 (0.63) 0.06Land costs/100 kg cmilk yes 1.58 (0.41) 0.04 0.26
no 1.50 (0.53) 0.05Non-operational costs/100 kg cmilk yes 39.58 (7.67) 0.87 0.99
no 39.57 (7.05) 0.72
Total revenue/cow yes 3185.39 (528.69) 57.34 <0.01
no 2949.44 (501.22) 49.63
Feed costs/cow yes 671.96 (174.43) 18.92 0.11
no 631.18 (173.88) 17.22
Health and med costs/cow yes 111.05 (48.09) 5.38 <0.01
no 11.98 (36.23) 3.72
Cattle costs/cow yes 256.56 (80.43) 8.72 <0.01
no 200.36 (62.51) 6.19
Land costs/cow yes 142.17 (42.84) 4.65 0.02
no 126.90 (46.48) 4.60
Non-operational costs /cow yes 3517.20 (830.11) 94.60 0.07
no 3314.43 (556.35) 57.08
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No differences between groups
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Problem with empirical studies
Ceteris paribus assumption Co-variance
Farmer
Disease managemen
t
Othermanagemen
t
Disease
Other diseases
Productivity
Financial results
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Outline The Dutch dairy sector Economics of animal health Disease control: optimization Modeling economics of animal health Examples normative modelling Empirical modelling Modern management: Precision dairy farming Final remarks
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Precision dairy farming
1970’s: Development of individual cow ID 1980’s: Sensors for disease detection 1990’s: Automatic milking 2000’s: Revival of sensors 2010’s: New generation of sensors
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Past developments
0102030405060708090
100
0 10 20 30 40 50 60 70
year since introduction
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Where are we now
700
102030405060708090
100
0 10 20 30 40 50
year since introduction
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Milking throughout time
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Milking with milking machines
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Modern large milking machine
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Automatic milking is not an issue anymore
They function Service and maintenance (infrastructure) is good Reasons pro
●Labour savings, quality of labour●More milkings per cow
Reasons against●Price (investment)●Flexibility of expansion
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Economic effects (€/100 kg milk) No robot robot Before After
Capital costs 10.38 9.72 13.97
Labour costs
12.38 11.69 11.30
Variable costs
19.45 18.66 19.80
Revenues
46.28 43.93 46.38
Profit 4.07 3.86 1.31
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Current demands to dairy industry
Animal well-being Consumer demands Environment Labor Economics
We have to reduce the use of scarce resourcesSo: explore the full potential of each individual
dairy cow
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Is individual cow management possible?
Easy
(too) difficult
Don’t even think about it
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Sensor system
SensorData
AlertAlgorithm
SOPDecision support
Decision
Otherdata
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Review of sensor systems until now
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Success factors
System specifications Cost efficiency Non-economic factors
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Outline The Dutch dairy sector Economics of animal health Disease control: optimization Modeling economics of animal health Examples normative modelling Empirical modelling Modern management: Precision dairy farming Final remarks
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Take home message
Animal health management decisions are taken daily Economics are useful/necessary to support decisions A first step are “cost of disease” studies
●General interest●Supporting stakeholders (negotiations)
Start for “economics of intervention” studiesCost-effectivity, cost-utility and cost-benefit
Empirical studies useful, but difficult
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Remember, there is more than money to motivate farmers
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Thank you for your attention