Economic analysis for different levels of decision making

Economic analysis for different levels of decision making

Henk Hogeveen

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 managementIn between Wageningen University and Faculty of Vet. Med. (since 2001)

@henkhogeveen

animal-health-management.blogspot.com

Outline

Decision making on animal health

●The decision problem

●The levels of decision making

Some examples of analyses

●Dry cow therapy

●Q fever outbreak

●Slaughterhouse measures to reduce the BSE load

Final words

Economic effects of animal disease

Output

MilkMeatEggsDraft power…….

After: McInerney, 1996

Human benefit (utility)

Input

LandLabourCapital

The field: Economic effects of animal disease

Output

MilkMeatEggsDraft power…….

Disease

1. Lower efficiency

2. Lower suitability for consumption

3. Lower human well-being

After: McInerney, 1996

Human benefit (utility)

Input

LandLabourCapital

1.

2. 3.

Most economic work

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

The management problem

Consequences animal health

Epidemiological consequences

Veterinary knowledge of diseases

The management problem

Consequences animal welfare

Consequences human health

Consequences animal health

Epidemiological consequences

Knowledge about externalities

The management problem

Consequences animal welfare

Consequences human health

Costs of intervention

Consequences animal health

Epidemiological consequences

Decisons become increasingly complex

Decision maker

ObjectivesAvailable resources

Consequences animal welfare

Consequences human health

Costs of intervention

Consequences animal health

Epidemiological consequences

Outline

Decision making on animal health

●The decision problem

●The levels of decision making

Some examples of analyses

●Dry cow therapy

●Q fever outbreak

●Slaughterhouse measures to reduce the BSE load

Final words

Levels of decision making

Individual animals

● Treatment

● Culling

● Interaction

Groups of animals (herd/farm)

● Prevention

● Eradication

Sector

● Control

● Eradication

Region

● Control

● Eradication

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 nofiable diseases

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

Basic approach

Normative modelling

●Relate costs of interventionwith 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)

Challenges Handle multiple objectives

Handle multiple objectives

●Internal (farmer)

●External (societal, chain)

●On-farm decision support models

●Capturing complexity

●Useful for farm-specific modelling

Outline

Decision making on animal health

●The decision problem

●The levels of decision making

Some examples of analyses

●Dry cow therapy

●Q fever outbreak

●Slaughterhouse measures to reduce the BSE load

Final words

Dry cow therapy

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

Stochastic model (Huijps et al., 2007)

Cow as basic unit

Dynamic around dry period

Results summarized for whole herd

Accounting for differences between pathogens

Dutch circumstances

Selective dry cow treatment cheapest

  Blanket Selective No

IMIdo (%) 15 (7.7, 23.1) 15 (7.7, 23.1) 15 (7.7, 23.1)

Treatment (%) 100 35 (23, 46) 0

IMI 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)

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 %)

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 period

Based on: Maas, 2014, MSc thesis, in

preparation

We’re also interested in amount of AB

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 (%)

Costs

per

lo w

SC

C c

ow

Outline

Decision making on animal health

●The decision problem

●The levels of decision making

Some examples of analyses

●Dry cow therapy

●Q fever outbreak

●Slaughterhouse measures to reduce the BSE load

Final words

Q fever outbreak

In 2005 Coxiella burnetii diagnosed in the Netherlands as cause of abortion problems on a dairy goat farm

In 2007 the first Q fever outbreak in humans was diagnosed

Since then thousands of people got infected, which reached a climax in 2009

Year and week of notification

Source: www.eurosurveillance.org

Roest et al., 2011

Government involved

Control measures

• Vaccination programme

• Culling of (pregnant) goats from infected farms

• Animal movement restrictions

• Breeding ban

• Bulk milk monitoring -> no good confirmation

• Extra hygiene programmes

Around 62,500 dairy goats were culled significant drop in milk production

Economic impact (Gonggrijp et al., 2014)

How large was the negative economic impact for affected farmers?

Were other actors of the industry also negatively affected by the control measures?

Were the relations of the actors and their behaviour in the industry still the same?

Objective:

Study the impact of Q fever control measures on the Dutch dairy goat industry with the use of a quantified value chain analysis

Value chain analysis

Mapping the value chain

Governance in the value chain

Upgrading in the value chain

Distribution of value in the value chain

Value chain analysis

Information on the structure, the trade flows and all the relations between the involved actors of a livestock sector

Often qualitative and descriptive

In this value chain analysis focus on quantification

Preliminary map of the value chain

Final map of the value chain

The distribution of goat milk and milk equivalents 2009

Goat farmers Milk collectors Prim. dairy processors

Second. dairy processors

(Feed) suppliers Meat processing Retail Total0

10,000,000

20,000,000

30,000,000

40,000,000

50,000,000

60,000,000

70,000,000

80,000,000

90,000,000

100,000,000

20092010

Eur

o (€

) x 1

0⁶

Gross margins of the Dutch dairy goat industry in 2009 - 2010

Gross margin results

Decrease of gross margins in 2010 of the total industry of -12% and -23% for farmers compared to 2009

Enormous difference in decrease between affected farmers (-53%) and non-affected farmers (-12%)

Primary dairy processors, meat processing and retail not negatively affected

Outline

Decision making on animal health

●The decision problem

●The levels of decision making

Some examples of analyses

●Dry cow therapy

●Q fever outbreak

●Slaughterhouse measures to reduce the BSE load

Final words

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

Are preventive measures cost-effective?(Benedictus et al., 2009)

Simulation modelling

●Static

●Stochastic

●Simulation

Monte carlo model

●1 iteration = 1 year

●Baseline: no intervention

●Alternative: one or more interventions

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

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

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

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

Cost-effectiveness

Cost-effectiveness 2002-2005

Outline

Decision making on animal health

●The decision problem

●The levels of decision making

Some examples of analyses

●Dry cow therapy

●Q fever outbreak

●Slaughterhouse measures to reduce the BSE load

Final words

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

Choose appropriate method for level of decision making

More importantly: choose appriate approach in model:animal vs farm vs sector vs society

Combine economic modelling knowledge with domain knowledge

Thank you for your attention