This is the second invited presentation I gave in Bangkok at the 38th ICVS. It provides a number of examples of economic calculations to support veterinary decisions at various levels.

1. Economic side of veterinary work
2. Practical applications

2. What to expect?
 Approach to economic calculations
 The cow level: reproduction
 The herd level: mastitis
 The herd level: PRRSV
 Country level: foot and mouth disease
 Human health: BSE
 Final remarks

3. Remember …. animal diseases cost money
 10 % of the gross production volume
~ 40-50 % of the net income (Dijkhuizen, 1990)
 £ 180/cow/year
~ 20 % of the average gross margin (Esslemont and Kossaibati,
1995)

4. How to study animal disease?
 Changes in output of farm, given farm structure,
input and diseases
 Necessary data:
● Economics and disease data
● Not available
 Attempts unto sofar
● Low precision in diseases (e.g., Rougoor et al.,
1997)
● Low number of farms (e.g., Rougoor et al., 1999)

5. Modelling to estimate effects of diseases
and disease control
 Simulation model
 Input data based on data, literature, expertise
 Relatively cheap
 Pragmatic approach
 Bio-economic modelling: economics combined with
detailed physiological basis

6. Models ……. do not capture the complexity
of the real situation

7. Models……. are sometimes nicer than
reality (too good to be true)

8. Some terminology
 Static vs dynamic
● behaviour over time
 Deterministic 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

9. What to expect?
 Approach to economic calculations
 The cow level: reproduction
 The herd level: mastitis
 The herd level PRRSV
 Country level: foot and mouth disease
 Human health: BSE
 Final remarks

10. Two decisions around reproduction
 When do I start with
inseminations
 When do I stop with
insemination

11. 11
Difficult calculation
Cow factors
● First ovulation
● Probability of detection
● Probability of conception
● Milk production level
● Reproductive disorders
Economical factors A complex
system of
● Milk price dynamics and
● Costs of insemination interactions
● Costs of culling
● Costs of calving management

12. Model
 Monte Carlo stochastic simulation
 Interactions and dynamics at cow level
 Time steps of 1 week
 Different VWP (6-15 wks) for the same cow
 Input for Dutch situation
(Inchaisri et al., 2010)
● Literature
● Expertise

13. Stochastic dynamic modelling
Cow
• Breed
• Parity
• Month of calving
• Milk production
• Farm level
• Relative performance
• Persistence
START OF CYCLE

14. 14
cow
Probabilities
no based on cow
Ovulation
yes factors
no Oestrus
detected
yes
no Insemination
yes
no Conception
yes
Calf

15. 15
Average results
Voluntary waiting periods
6 wk 7 wk 9 wk 11 wk 13 wk 15 wk
First insemination
10.9 11.5 13.1 14.8 16.8 18.5
Calving interval
391 393 401 410 421 433
MP/cow/year (kg)
8200 8188 8157 8112 8056 7997
Insemations
1.89 1.86 1.78 1.74 1.70 1.69
Calves/cow/year
0.93 0.93 0.91 0.89 0.87 0.84
Not pregnant (%) 0.018 0.019 0.021 0.025 0.030 0.037

16. Economic consequences
(€/cow/year)
Voluntary waiting periods
7 wks 9 wks 11 wks 13 wks 15 wks
Milk 2.2 8.9 18.3 32.4 46.4
production
Calves 0.1 0.3 0.6 1.0 1.7
Culling 0.4 1.6 3.4 6.3 10.1
Inseminations -0.5 -1.6 -2.0 -2.8 -3.1
Calf -0.1 -0.5 -1.0 -1.8 -2.9
Management
Net total 2.1 8.6 19.0 34.2 52.2
(-16-22) (-11-32) (-6-53) (4-78) (13-106)
16

17. Average
60
50
Net losses (€/cow/year)
40
30
20
10
0
6 7 8 9 10 11 12 13 14 15
VWP (weeks)

18. 18
But 6 weeks not always optimal
40
35
30
Percentage cows
25
20
15
10
5
0
6 7 8 9 10 11 12 13 14 15
Optimal VWP (wks)

19. 19
Longer VWP when ….
Cow factors Economical factors
● Parity = 1 ● Lower costs low milk
● Not Holstein Frisian production
● High persistence ● High costs of
inseminations
● Low production
● High costs culling
● Late peak in production
● Calved in winter
● Bad oestrus detection
● Late first ovulation
● Reproduction diseases

20. What to expect?
 Approach to economic calculations
 The cow level: reproduction
 The herd level: mastitis
 The herd level: PRRSV
 Country level: foot and mouth disease
 Human health: BSE
 Final remarks

21. Costs of mastitis
 Mastitis is a costly disease
 Estimiations between € 55 – 97 per cow per year
● The Netherlands: €78/cow/year (Huijps et al.,2008)
● USA: €61/cow/year (Bar et al., 2008)
● Sweden: €97/cow/year (Hagnestam- Nielsen and
Østergaard, (2009)
● The Netherlands: €84/cow/year (Halasa et al., 2009)
● Sweden: €55/cow/year (Nielsen et al., 2010)

22. Total costs of disease
 These costs are only half of the story
 Definition of costs of an animal disease (McInerny et al., 1992):
Costs = Losses + Expenditures
●Loss : Benefit taken away (our estimations)
●Expenditures : Extra input into livestock production
(preventive measures)

23. Remember this one?
High losses, low control
expenditures
Failure
costs
(€)
Optimal Low losses,
high control
expenditures
Preventive costs (€)

24. Material
 Questionaire dataset of 189 farms (Santman-Berends et al., 2011)
● General questions
● Livestock management
● Lactating cows
● Milking process
● Feed
 Pathogen dataset of 120 farms
● Pathogens present on individual farms
 Milk recording services dataset of 120 fairy farms
● Testday records (e.g. milk production, SCC)

25. Normative calculations losses


26. Costs of prevention
 When present the following were calculated according to
Huijps et al. (2010):
● Cleaning cubicles
● Cleaning lanes
● Drying off
● Pre-stripping
● Clean dirty udders
● Milker gloves
● Clean cluster after clinical case
● Milk high SCC cow last
● Post milking teat disinfection
● Fixing cows after milking

27. Estimated costs (€/cow/year) for mastitis
Average 5% 95%
percentile percentile
Clinical mastitis 62 16 151
Subclinical mastitis 14 9 21
Failure costs 76 26 164
mastitis
Prevention costs 88 43 131
Costs of mastitis 164 99 281

28. Failure costs vs preventive costs

29. Cost-effectiveness of preventive measures
-18 management measures (Huijps et al., 2010)
-Quantify effect
-436 scientific papers (1996-2006)
-43 relevant and useful
- Expert sessions
-Effect 100 % contagious
-Effect 100 % environmental
-Efffect on BMSCC
-Efffect on clinical mastitis

30. Additional Reduced
expenditures losses Net benefit
Milk cows with clinical mastitis last 37 16 -21
Milk cows with subclinical mastitis last 104 20 -84
Use of separate cloths during udder preparation 26 9 -17
Wash dirty udders during udder preparation 3 9 6
Prestripping 34 9 -25
Use of milkers’ gloves during milking 1 9 8
Post milking teat disinfection 31 31 -0
Back-flushing clusters after milking a cow with clinical
mastitis 1 11 10
Back-flushing clusters after milking a cow with subclinical
mastitis 123 15 -108
Replace teat cup liners in time 13 11 -2
Use of a treatment protocol 7 15 8
Application of blanket dry cow therapy 9 36 27
Keep cows standing after milking 2 12 10
Feed additional dry cow minerals 13 13 0
Prevent overcrowding 23 13 -10
Clean boxes 54 15 -39
Clean yards 51 8 -43
Optimize feed ration

31. What to expect?
 Approach to economic calculations
 The cow level: reproduction
 The herd level: mastitis
 The herd level: PRRSV
 Country level: foot and mouth disease
 Human health: BSE
 Final remarks

32. Economic effects of PRRS
• Decrease in litter size
• Decline in average daily gain and feed efficiency
• Reproductive losses
• Increase of mortality
• Increase in healthcare costs
Costs of outbreaks:
• Cost of outbreaks USA: € 255/sow (Holck and Polson, 2003)
• Cost initial outbreaks NL: € 98/sow (Brouwer, 1994)
• Mean loss per sow NL: €126/sow (€59 - €379) (Nieuwenhuis et al, 2012)
Costs of endemic infection less clear

33. Methods
• Two strategies:
– Depopulation – repopulation
– Herd closure with off-site rearing of weaned piglets
• PRRS elimination reached after 4, 8 and 12 months.
– Compared with old situation (endemic PRRSV)
• Input parameters:
– Farm production parameter-estimates derived from 900 Dutch
sow farms (Topigs 2009) or aggregated production
(deterministic) figures (Agrovision B.V., 2010) of 2009
– Additional parameters (stochastic and deterministic) derived from
literature or experts: LEI & KWIN
• Stochastic simulation model
• Commercial production farm with 436 sows

34. Results
 Depop-repop, equal piglet price: Breakeven in 11.8 yrs
 Depop-repop, higher piglet price: Breakeven in 2.2 yrs
 Herd closure with elimination: Breakeven < 1 yr
1.5
2
P robability
1
.5
0
0 5 10 15 20
Years till breakeven
20% increase pigletprice no increase pigletprice

35. What to expect?
 Approach to economic calculations
 The cow level: reproduction
 The herd level: mastitis
 The herd level: PRRSV
 Country level: foot and mouth disease
 Human health: BSE
 Final remarks

36. Foot and mouth disease
 EU is free of FMD
 What do with outbreak?
 EU regulations
 Additional measurements
 Problem is:
● Stochastic
● Dynamic
● Spatial

37. Inter-FMD: a simulation model
 Monte Carlo simulation
● 100 replications to obtain insight in variation of
outcomes
 Examples of output parameters
● number of infected farms
● duration of epidemic
● number of farms slaughtered, vaccinated, in MCZ,…
● number of animals slaughtered, vaccinated, in MCZ,…
● etc……
 Output = Input economic model

38. What to expect…..
• of an outbreak on a dairy farm
surrounded by
•240 farms in a radius of 10 km (A)
•1923 farms in a radius of 10 km
(B)
• using only EU measures?

39. EU control measures
Sparse (A) Dense(B)
50% 95% 50% 95%
# infected farms 3 38 1583 3621
# prev. culled farms 8 49 679 1053
# farms in MCZ (10km) 335 4,406 12,895 58,165
Length epidemic (days) 38 105 375 end

40. Other measures (dense)
EU Prev-1 Vacc-2 Vacc-4
Farms
rendered 2.262 281 76 74
vaccinated 0 0 593 1.184
MC 12.895 3.447 3.318 3.334
Animals
culled 569.476 65.066 16.230 15.718
vaccinated 0 0 151.089 270.080
Length (days) 375 60 62 57

41. Adding economics (* mln €)
EU Prev-1 Vacc-2 Vacc-4
live cull live cull
Control >4.620 421 94 174 80 235
Consequential > 2.540 200 166 121 171 111
Marketdamage > 499 511 623 467 636 477
Total >7.659 1.132 883 762 886 824

42. What to expect?
 Approach to economic calculations
 The cow level: reproduction
 The herd level: mastitis
 The herd level: PRRSV
 Country level: foot and mouth disease
 Human health: BSE
 Final remarks

43. 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 decreasing
● 39 suspected cases in 2002
● 7 suspected cases in 2005

44. Model
 Stochastic
 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 like
51)

45. 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

46. 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

47. Costs (mln €)
2002 2003 2004 2005
Year
SRM removal
19.22 18.27 19.29 19.82
Post-mortem testing
38.16 29.56 26.57 21.12
Cohort culling
6.97 4.80 3.41 2.43
Total costs
64.34 52.64 49.27 43.37

48. Cost-effectiveness

49. Cost-effectiveness 2002-2005

50. What to expect?
 Approach to economic calculations
 The cow level: reproduction
 The herd level: mastitis
 The herd level: PRRSV
 Country level: foot and mouth disease
 Human health: BSE
 Final remarks

51. Key messages from examples
 Inseminations
● Start early
 Mastitis
● Be careful with additional prevention
● Work farm-specific
 PRRSV
● Eradication iscost-effective
 Foot and mouth disease
● Have a good look at eradication programs
 Zoönoses
● Look at costs vs utility

52. Farmers underestimate costs of disease
200
180
160
140
Real costs (€/cow)
120
100
80
60
40
46 under estimators
20
0
0 20 40 60 80 100 120 140 160 180 200
Expected costs (€ per cow)
Huijps et al.,

53. There is more than economics
 Money is only one motivator for a farmer

54. Thank you for your attention
On-line courses on
@henkhogeveen Veterinary Economics on:
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