benefit-cost analysis of animal identification for disease … · benefit-cost analysis of animal...

IntroductionThis analysis provides a conceptual model for the evaluationof the economic usefulness of improved animal identificationsystems in reducing the consequences of foreign animaldiseases (FADs). All countries are concerned with theprevention and control of FADs. Accounting for the benefitsattributable to improved animal identification systems duringFAD outbreaks captures the principal benefits of improvedanimal identification systems. These benefits include limitingthe spread of a FAD, enabling faster traceback of infectedanimals, limiting production losses due to disease presence,reducing the costs of government control, intervention anderadication, and ultimately minimising potential trade losses.Trade effects are an important aspect of the benefits of animal

disease control. The Uruguay Round of the GeneralAgreement on Tariffs and Trade increased the focus on theinternational trade aspects of agriculture. With the reductionin tariff- and quota-based barriers to trade, regulationsdesigned to prevent the movement of disease agents into newareas now play a larger role in trade of livestock and livestockproducts (4, 6, 17, 24).

Improved animal identification systems offer many otherpotential benefits, beyond the ability to control a FADincursion. Improved animal identification can reduce theeconomic consequences of endemic animal diseases that arealready in an eradication phase. Additional safeguards in theanimal food supply chain help to promote consumerconfidence in the national livestock industry (17). Improvedanimal identification systems may also contribute to substantial

Rev. sci. tech. Off. int. Epiz., 2001, 20 (2), 385-405

Benefit-cost analysis of animal identification fordisease prevention and control

SummaryIndividual animal identification is an important consideration for many countries toimprove animal traceback systems. The analysis presented by the authorsprovides a conceptual benefit-cost framework for evaluating the economicusefulness of improved animal identification systems designed to reduce theconsequences of foreign animal diseases (FAD). For cattle in situations similar tothose found in the United States of America, results show that improved levels ofanimal identification may provide sufficient economic benefits, in terms of thereduced consequences of FAD, to justify the improvements. In contrast, the resultsof similar studies in swine show that the economic benefits of the reduced FADconsequences are not sufficient to justify improvements in animal identificationsystems. Vertically integrated industries, in which animals have only one owner ina closed system from birth to slaughter, may not require individual animalidentification for traceback purposes. However, additional benefits, not quantifiedin this analysis, could contribute to favourable benefit-cost ratios for improvedidentification in certain sectors of the swine industry.

KeywordsAnimal identification – Benefit-cost – Disease control – Economics – Traceability –Traceback – Trade.

W.T. Disney (1), J.W. Green (1), K.W. Forsythe (1), J.F. Wiemers (2) & S. Weber (1)

(1) Center for Animal Disease Information and Analysis, Centers for Epidemiology and Animal Health, VeterinaryServices, Animal and Plant Health Inspection Service (APHIS), United States Department of Agriculture (USDA),555 South Howes, Suite 300, Fort Collins, Colorado 80521, United States of America(2) National Animal Identification Co-ordinator, Animal Health Programs, Veterinary Services, Animal and PlantHealth Inspection Service, United States Department of Agriculture, 2100 S. Lake Storey Road, Galesburg, Illinois61401, United States of America

little attention to economic costs or impacts. However,increasingly more sophisticated systems require substantialinvestments for which the economic feasibility is not self-evident. For sound decision-making, information on theepidemiological and economic consequences of new systems isessential, as is the evaluation of current systems in the light ofnew and developing animal industry practices. This paperfocuses on the implementation of conventional visualidentification systems. Automated systems generally provide forremote/electronic reading. These systems will be necessary toobtain the production efficiencies required for marketingprogrammes emphasising organically-grown, hormone-free, orother special product qualities demanded by consumers.

Analysis strategyA benefit-cost analysis of animal identification systems for FADeradication and control programmes is extremely difficult.Benefits are uncertain and often not quantifiable. Evenidentifying the various range of benefits is difficult. Thesebenefits depend on uncertain and variable future diseaseevents, environmental conditions and susceptible hosts.Epidemiological models must be used to generate estimates ofvarious states of nature for a variety of possible scenarios. Thisuncertainty and variability must be addressed and thenreflected in the resulting economic impact values. The methodsemployed in this benefit-cost analysis attempt to take intoaccount this uncertainty and variability (3).

The strategy for this analysis follows several steps which areoutlined below to give the reader an overview of the analysis.The methodology is described more fully in the respectivesections of the paper.

Firstly, previous research on animal identification systems isreviewed (1, 7, 19, 22, 30). This includes a description of thecurrent animal identification systems in the United States ofAmerica (USA). Secondly, Federal animal health managers inthe USA were surveyed to evaluate the traceback characteristicsof animal identification systems in the country. The results ofthis survey are compiled and used as inputs for a series ofepidemiological disease spread simulations.

Simulations are developed to reflect the spread of foot andmouth disease (FMD), given the results of the professionalsurvey as to how each animal identification level affects theability to traceback infected and suspected animals, and thuslimit disease spread (12). Economic parameters are attached tomeasure consequences for each simulation. Economic results ofsimulations are combined to compare the decline inconsequences between low levels of animal identification andhigh levels of animal identification. Those economic differencesare considered the benefits of improvements in animalidentification systems.

producer gains from improved genetics and carcass quality,herd certification and premium prices for products, if improvedanimal identification systems allow the benefits of non-homogenous superior products to be traced to superior animalmanagement practices.

The results reported below underestimate the full potentialbenefit, as these additional types of benefits, as noted above, arenot included. The benefit-cost ratios for improved animalidentification systems that are developed in this analysis form a‘floor’ for the true benefit-cost ratios. This analysis is not allencompassing, but serves as a useful basis for discussion thatwill help to direct future research efforts in the field of animalhealth economics and may serve as a model for other countriesto consider when evaluating the benefits and costs of animalidentification.

Purpose of animal tracebacksystemsAnimal traceback systems are essential for the control anderadication of animal diseases and the elimination ofcontaminated animal products. An improved animalidentification system alone will not reduce the risk of initialexposure to a FAD, but can directly reduce the consequences ofthat exposure. An animal identification system can help toreduce the time required to locate infected animals, therebyreducing the opportunities for exposing other susceptibleanimals and the consequences of these additional exposures.Due to recent advances in technology, traceback systems havebecome more sophisticated. Many systems now includeindividual animal identification.

The principal purpose of traceback systems in diseaseprevention and control programmes is to identify other animalsexposed to the disease agent. This is accomplished by collectingreliable and up-to-date information on movements, locationsand contacts of animals with other animals and with the humanpopulation.

Rapid tracing of potentially infected animals, herds, orcontaminated products is an essential initial step for rapidcontrol and eradication of a FAD outbreak. Animalidentification systems, when effective and working properly canfacilitate such activities (21). Animal identification systems alsohelp to foster participation of producers or industryorganisations in the eradication of endemic diseases. Thesesystems help to reassure consumers of animal products thatthese products are safeguarded from both perceived and realfood safety threats.

Much of the published research on animal identification andrapid traceback systems has been of a technical nature with

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Similarly, costs are determined by comparing costs of higherlevels of animal identification systems with costs of lower levelsof identification systems.

The resulting benefit-cost ratios are determined stochastically tocapture the variability and uncertainty associated with diseaseoutbreaks. The benefits are based on an assumption that asingle primary FMD outbreak will occur in the USA over a 50-year time frame. A further assumption is that this outbreakis as likely to occur at any given point within this time frame,as it is to occur at any other given point within the time frame.In other words, the outbreak is assumed to be as likely to occurtomorrow as it is 10 years from now, 50 years from now, or atany other time in the next 50 years. This assumption of oneprimary outbreak in a 50-year time frame implies that theprobability each year of a primary FMD outbreak occurring is0.02. In this stochastic environment, if no outbreak occurs,then the benefits are zero, but costs continue to be incurred ona yearly basis.

At present, no exhaustive risk analysis has been conducted todetermine the actual annual probability of a primary FMDoutbreak occurring in the USA. Additional detailed researchwould be required to accurately estimate the actual probabilityof FMD occurring in the USA, or in other countries that may beconsidering improvements to animal identification systems.This research is beyond the scope of the current study, but thetime frame of 50 years has been chosen for illustrate purposes,based on the following observations:

– the last outbreak of FMD in the USA occurred in 1929; a timeframe of at least 72 years. The global and domestic animalhealth situation has changed substantially since this lastoutbreak

– recent outbreaks of FMD in Europe have raised concern overthe probability of an outbreak in the USA

– outbreaks of FMD occurred in the United Kingdom (UK),France, the Netherlands and Ireland in 2001. The lastoutbreaks in these countries occurred in 1981 in France andthe UK, in 1984 in the Netherlands and in 1941 in Ireland;time frames of 20 years, 17 years and 60 years

– periodic FMD outbreaks are also occurring in many otherparts of the world.

BackgroundEconomics of animal health and identificationsystemsAnimal health economics is a relatively new discipline which isworking to develop a framework of concepts, procedures anddata to support decision-making in animal health management.Research has dealt primarily with quantifying the financialeffects of animal disease, developing methods for optimising

decisions affecting individual animals, herds or populations anddetermining the benefits and costs of disease controlprogrammes (5, 11, 13, 14, 20).

Dijkhuizen et al. describe the four most common economicmodelling techniques (partial budgeting, benefit-cost analysis,decision analysis and systems simulation) (5). These are appliedto three levels of veterinary decision-making, namely: theanimal, herd and national levels. Dijkhuizen et al. stress theimportance of the close link between economics andepidemiology for future development, as well as the need for aninternational exchange of models and procedures (5). If thesubject of research deals with long-term disease controlprogrammes at regional or national levels, then benefit-costanalysis is typically the methodology of choice. This analysismakes use of all four of the above modelling techniques.

Animal identification in BelgiumA study of animal identification in Belgium supported thecombined economic and epidemiological approach andprovided useful information. Saatkamp et al. evaluated fournational animal identification systems for the pig industry inBelgium using a computer simulation model (23). The foursystems were as follows:

a) Ear tags with Manual recording and the use of Documents(EMD): a system that meets the minimum requirements of theEuropean Union (EU).

b) Ear tags with Manual recording and the use of Documentsand Computerised data storage (EMDC): the revised systemintroduced to Belgium in 1995.

c) Transponders with Electronic recording and Computeriseddata storage (TEC): a system based on electronic identificationwhich is in the final development stage.

d) TMEC: a TEC system with biosensors added to thetransponders, thus allowing individual Monitoring ofphysiological parameters.

The study indicates that the following four factors wereinfluential in economic decision-making with respect to animalidentification systems:

– economic losses per epidemic of classical swine fever (CSF)

– frequency of CSF epidemics

– operational costs of the system

– possibilities for additional uses of the system for purposesother than control of CSF.

Saatkamp et al. concluded that replacement of the EMD systemwith the EMDC system was economically justifiable (23). As aresult of high operational costs, electronic identification systemswere economically feasible only in very specific situations (i.e. when a higher degree of additional use is possible or witha relatively high frequency of CSF epidemics). However, thissituation will change as the cost of electronic identification

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systems decreases, the problems surrounding the use of thesesystems are solved and the value of international trade beingplaced at risk increases.

Economic losses in this situation in Belgium can be categorisedas direct losses associated with control of the disease andindirect losses resulting from market disruption (bans onexports from Belgium by other countries). The economic lossesdue to restrictions imposed by other countries on exports fromBelgium were a significant part of total economic losses.

The size of the quarantine zone was very important in thiscountry. The zone affected the delineation of export-eligibleregions, because of the complete ban on animal movementswithin the zone. Regionalisation reduced the likelihood of tradedisruption when free movement and export were allowedoutside the quarantine zone.

Transport bans and movement restrictions caused temporaryshortages of supply and consequent price increases. After thelifting of restrictive measures and massive restocking in thepreviously quarantined area, a price decrease was observedwhen fattened pigs were ready for slaughter.

The principle factors in this study were the density of animals(economic losses per simulated epidemic were very significantin high-density areas), eradication in specific areas, transportbans in protection and surveillance zones, and additional pre-emptive removal of all herds within a 0.5 km radius around anaffected herd. These factors are included in the disease-spreadmodel described later in this paper.

Animal identification in the United States of AmericaThe study in Belgium described above relates to swine only. Ata minimum, evaluation of the benefits and costs of animalidentification systems in the USA requires the assessment ofthese systems as they currently apply to both swine and cattle.Animal identification systems inherently require recordkeeping. This paper defines both the identification and record-keeping systems currently in use in the USA.

Current national animal identification systems for the cattle andswine industries in the USA were implemented to supportdomestic animal disease eradication and control programmes.Identification devices may be applied at farms, feedlots, swine-buying stations or livestock markets. Animal records collectedfor the national eradication and control programmes aregenerated at vaccination events and surveillance testing atfarms, markets and slaughter establishments. Programmerecords are kept on standardised databases maintained at thestate or regional level. Summary records of programmeactivities are transmitted to national databases, but these datado not include animal identification. Many production unitsutilise herd identification and information systems for farmmanagement. Production and sales records are maintained invarious formats at farms, feedlots, swine-buying stations orlivestock markets. In the event of a traceback, all of theserecords may be accessed.

The total cost of an animal identification system is related toboth the identification device (e.g. tag) and the records of theidentification that must be maintained. For example, a givenidentification device may be relatively inexpensive, but couldrequire the animal to be restrained during application, thusincreasing labour costs. Identification devices that are difficultand time-consuming to read may also increase labour costs.However, a more expensive device that can be read at adistance, without restraining the animal, may reduce labourcosts. In modern systems, computerised records can expeditethe data entry and retrieval process and help to reduceadministrative costs (27).

Currently, five primary identification levels exist for cattle atslaughter plants in the USA, as follows:

– Level 1. No identification tag, paper trail only

– Level 2. Back tag and paper trail

– Level 3. Back tag, paper trail and unofficial bangle tag

– Level 4. Back tag, paper trail and official ear tag

– Level 5. Back tag, paper trail and brucellosis calf-hoodvaccination ear tag.

The following four levels exist for swine:

– Level 1. No identification tag, paper trail only

– Level 2. Back tag and paper trail

– Level 3. Back tag, paper trail and unofficial bangle tag

– Level 4. Back tag, paper trail and official individual animalidentification ear tag.

The paper trail is usually computerised (i.e. data frominspections or vaccinations are entered into a computeriseddatabase at multiple sites). Centralised, integrated access tothese state databases at the national level is not currentlyavailable.

Back tags are intended for short-term identification. The tagsare easily applied with glue and the animals rarely need to berestrained. The tags are retained for a few days to a week. Swineback tags have an average retention rate from farm to slaughterof approximately 20%. Cattle back tags have a much higherretention rate. Back tags are very inexpensive and difficult toalter. The tags are very easily collected at slaughter for tracebackpurposes.

Bangle tags are larger plastic ear tags which are fastened to theear and usually hang down. These tags are more easily readfrom a distance than metal ear tags, but cost ten times morethan metal tags. Application generally requires that the animalbe restrained, but is easily performed with a minimum oftraining.

Ear tags are the most widely used method of farm animalidentification in the USA. Metal-clasp type tags are the mostinexpensive, but can only be read at very close range while theanimal is restrained. Although retention is poor, recent


refers to a specific class of animal in the USA; typically a cullcow going to slaughter, over two years of age and usually testedfor programme diseases.

– Exercise 2: feedlot steer at slaughter that must be traced to thelast farm of ownership. A ‘feedlot steer’ in this context refers toan animal that has always been destined for slaughter as a meatanimal. The animal may be a cow or aster, but is not a breedinganimal. The steer is born, raised, fattened and slaughtered,usually at an age of approximately two years.

– Exercise 3: adult swine at slaughter that must be traced to lastfarm of ownership. The term ‘adult swine’ in this context refersto a specific class of animal in the USA; a cull animal whoseuseful life as a breeder is over or that is being culled from theherd for some other reason.

– Exercise 4: market pig at slaughter that must be traced to thelast farm of ownership. A ‘market pig’ in this context is ananimal that has been born, raised and fattened for slaughter.The animal has not been considered for any other purpose andis usually slaughtered at a weight of approximately 200 lbs.

Table I summarises the results obtained from the animalidentification traceback survey. The numbers reported are theaverage of the responses for each exercise and identificationlevel.


technology continues to reduce this problem. More moderntags are also more tamper-resistant. The tags are easily retrievedat slaughter for traceback purposes.

The cost calculations described later were based on level 1,paper-only records for animals at slaughter that did not have eartags, back tags or individual animal identification, and level 5(cattle) or level 4 (swine) animals with ear tags, back tags andpaper records.

The professional surveyAn animal identification and traceback survey involvingnineteen Federal animal health managers was conducted toacquire basic inputs for the illustrative benefit-cost analysisdescribed in subsequent sections of this paper. Each managerwas presented with the above levels of identification in each ofthe following traceback exercises and asked to determine, foreach exercise, how many days would be required to trace theanimal, and the probability that the correct farm would beidentified. Exercise 1 from the survey is presented in Figure 1.

– Exercise 1: adult cattle at slaughter that must be traced to thelast farm of ownership. The term ‘adult cattle’ in this context

Suppose you find an adult bovine animal at slaughter that needs tobe traced to the last farm of ownership. Fill in the table with yourbest estimates based on the experience in your area. Please berealistic in your figures. Our conclusions are only as good as theassumptions on which they are based

How often is Time needed to Probabilitythis level of conduct trace that the correct

Level of identification (days/hours) farm has beenidentification present for this found (%)

class of animal?(current %)

No identificationtag; paper trail only

Back tag andpaper trail

Back tag, papertrail and unofficialbangle tag

Back tag, paper trailand MCI ear tag

Back tag, paper trailand brucellosis calf-hood vaccinationear tag

MCI: market cattle investigation

Fig. 1Exercise 1 from the survey on animal identification andtraceback sent to Federal animal health managers

Table IAnimal identification levels: number of days required to tracethe animal and probability of finding the correct farm, UnitedStates of America, 2000

Exercise LevelAverage time Average time

Average

identification required toprobability

level is trace (days)of tracing

present (%)correct

farm (%)

Trace adult cattle 1 11 12 68at slaughter 2 43 4 93to the last farm 3 6 4 93ownership

4 20 4 935 20 3 97

Trace feedlot steer 1 72 12 59at slaughter 2 16 13 49to the last farm 3 7 10 78ownership

4 3 11 815 2 1 100

Trace adult swine 1 50 12 53at slaughter 2 37 6 90to the last farm 3 7 4 89ownership

4 6 3 95

Trace market pig 1 79 11 61at slaughter 2 13 6 82to the last farm 3 5 4 94ownership

4 3 3 95

Source: survey results from nineteen animal health managers at Federal headquarters orregional offices

Systems that incorporate forms of identification that aresuperior to a paper trail decrease the number of days requiredto complete a trace and increase the probability of identifyingthe correct herd. All exercises show that substantialimprovements are achieved by using some type of tag ratherthan paper identification alone.

All the identification levels in Table I are currently used in theUSA. In three out of the four exercises, half or more of theanimals at the slaughter plant must be traced using paper onlybecause no tags are present. Tamper-proof, permanent tags areessential for rapid traceback and to limit quarantine zones to asmall area. Confidence levels for identifying the correct herdcould also be improved, although many existing tag systems arenear 100% confidence levels. The costs of animal identificationdevices are a small part of the cost of most identificationsystems.

The benefit-cost analysisframeworkThis section describes the methodology used to derive thebenefit-cost analysis results. Table II is presented to assist theunderstanding of the various situations, scenarios and levelsdiscussed in the following sections. Components in the processare briefly described.

Analysis steps

Determining benefit. Step 1: the contagious diseasespread modelThe contagious disease spread model (CDSM) simulates thespread of disease from a FAD introduction. The CDSMincorporates a state transition algorithm with Monte Carlosimulation of direct contact, indirect contact and air-bornespread of a contagious disease agent. Parameters allow formoderating the spread in a simulated outbreak, based on therates of contact. Optional mitigation strategies may also besimulated, including surveillance, slaughter of detected andcontact herds and ring vaccination around detected herds.Adjustments to the mitigation parameters vary the rate ofdetection, onset and procedure for slaughter, onset ofvaccination and size of the vaccination rings. The CDSM wasdeveloped based on earlier work simulating the spread of FMD(8, 10, 15, 25). A complete documentation on the CDSMmodel will soon be submitted for publication by Schoenbaumand Disney.

A parameter in the model imposes increased effectiveness ofanimal identification system improvements on the simulation.This parameter is adjusted to reflect the different levels oftraceback based on results of the professional survey (Table II).Four traceback exercises incorporate four levels (for swine) or

five levels (for cattle) of animal identification and are used todevelop alternative scenarios for the CDSM. The first set ofduration times and probability estimates in the descriptioncolumn of Table II were obtained from averages calculated fromthe surveys. The second set of duration times and probabilityestimates in the same column were necessary to create acurvilinear animal traceback curve for the CDSM. One point onthe traceback curve is the origin, i.e. no animal has been tracedat the time of disease discovery. A second point on the curve isthe average traceback time and probability of correctness


Table IIScenario development for contagious disease spread model

Situation/ IdentificationDescriptionsscenario system (a)

Situation 1: adult cattleScenario 1 Level 1 68% probability correct in 12 days (b)

84% maximum in 60 days (c)

Scenario 2 Level 5 97% probability correct in 4 days (b)


Situation 2: feedlot steerScenario 3 Level 1 60% probability correct in 13 days (b)




Situation 3: adult swineScenario 5 Level 1 53% probability correct in 11 days (b)




Situation 4: market pigScenario 7 Level 1 61% probability correct in 11 days (b)




a) see previous descriptions of identification levelsb) averages from surveyc) sixty days is the upper limit to find the infected herd; the probability is half the differencebetween the average probability and 100%

Level: a method of animal identification system used in the UnitedStates of AmericaExercise: the realistic simulation parameters presented to managersto obtain information on the prevalence of alternative levels ofidentification present in their area, the time required to trace an animaland the probability of identifying the correct farmScenario: the conversion of survey exercise results to inputs for thedisease spread model. For example, Exercise 1 in the survey traced anadult cow from the slaughter plant to the last farm of ownership.Results from Exercise 1 were combined with other inputs to createScenarios 1 (level 1 identification system) and 2 (level 5 identificationsystem) evaluated in the disease-spread modelSituation: the combination of scenarios created to compare costs andbenefits of upgrading identification levels. For example, Situation 1evaluates the benefits and costs of increasing identification levels foradult cattle traced to the last farm of ownership from paper-only(level 1) to level 5 (back tag, paper trail and brucellosis calf-hoodvaccination ear tag)

calculated from the survey (the first set in the descriptioncolumn). The third point (second set in the descriptioncolumn) represents the best result that can be obtained in 60days. Feedback from managers surveyed suggested that if theanimal could not be traced in 60 days, it would be futile tocontinue. The probability estimate in the second set ofestimates was one-half the difference between the firstprobability estimate and 100%. Thus, it was assumed that if upto 60 days were allowed for the traceback, one-half of theremaining untraced animals could be traced to the last farm ofownership.

For each animal-type scenario, a CDSM simulation isconducted at animal identification level 1 and again at animalidentification level 4 (swine) or 5 (cattle). The CDSM providesinformation about the duration of a simulated outbreak, thenumber of animals infected and/or destroyed and the numberof premises infected. Results from these simulations provideinput to the economic consequence model (ECM) componentof the CDSM which produces estimated changes in economicconsequences. These changes represent the benefit of theimprovement in identification system for each animal type.

Determining benefit. Step 2: the economicconsequence model component of the contagiousdisease spread modelThe economic cost of a disease outbreak is dependent on theduration of the outbreak and the methods used to control theoutbreak. The ECM component of the CDSM uses a partialbudgeting approach to measure the direct economic cost of theoutbreak, the slaughter cost, additional surveillance costs andvaccination costs. Furthermore, the ECM component measuresthe indirect economic costs of trade losses due to restrictions onexports. Each cost is described below (2).

The ECM component also accounts for production impacts onaffected livestock. Once the value of affected animals iscalculated, additional impacts (due to downtime, efficiency,losses, etc.) are extremely small and are not further considered.Average indemnification values are assumed to equal fairmarket value (FMV), these values are taken from emergencyresponse simulation exercises (26). Including the value ofremoved animals would constitute double counting, becausethe partial budgets already account for indemnity payments toproducers based on FMV less salvage (which here would beFMV, since FMD carcasses are assumed to be destroyed).

Direct economic cost: slaughter costSlaughter costs are estimated, based on partial budgets for theremoval, euthanasia and disposal of herds of infected animals.Government indemnification of animals surrendered and thecost of cleaning and disinfecting premises after the removal ofanimals are included. The parameters in the model can beadjusted to reflect various economic conditions and herddemographics in the area of the outbreak. For the purposes of

this analysis, all economic parameters are held constant to focusthe analysis on the effects of changes in FAD detection.

Direct economic cost: surveillance costSurveillance costs are based on partial budgets for diagnostictesting of suspect herds and for surveillance visits to infected,suspected and surrounding farms. Again, the parameters in themodel can be adjusted to reflect economic conditions andherd/disease demographics in the area of the outbreak.

Direct economic cost: vaccination costVaccination costs are based on partial budgets for thevaccination crew visiting the farm. In addition, variable costsper dose are imposed for each animal vaccinated. Theparameters in the model can be adjusted to reflect economicconditions and herd/disease demographics in the area of theoutbreak. The vaccination options were turned off in thescenarios analysed for this paper.

Indirect economic cost: gross trade lossesTrade losses occur when a trading partner refuses to acceptimports from regions in which the outbreak has occurred. Forexample, when an outbreak of FMD occurs in a previouslyFMD-free region, the Office International des Epizooties (OIE)recommends the suspension of trade in FMD-susceptibleanimals and meat products for three months following theslaughter of the last FMD-infected animal. If vaccination isused, the OIE recommends that trade is halted until threemonths after the last vaccinated animal is slaughtered.

The ECM component captures the economic cost of trade lossby apportioning the average annual level of exports for FMD-susceptible animals and products (Table III) into equal dailyamounts.


Table IIIValue of exports of selected live animals and animal productsfrom the United States of America, 2000* (US$ millions)

Item Bovine Porcine Ovine Other Total

Live animals 199.01 26.06 26.06 35.52 286.65

Animal products 3,036.00 1,068.00 6.00 44.00 4,154.00

Total 3,235.01 1,094.06 32.06 79.52 4,440.65

* the totals for 2000 are estimated from 1996-1999 data and 9-month totals for 2000Source: United States Department of Commerce, Bureau of Census

The change in gross value of exports is used in this analysis torepresent decreases in export loss plus other non-quantifiedbenefits from improvements in the level of animalidentification. This deviates from the economic trade theorycommonly applied in benefit-cost analysis that measures thenet effects of the loss of export markets (9, 18). For example, asthe product that would have been exported is maintained in the

domestic market, prices fall, presenting a benefit to consumerswho then increase consumption in the domestic market,offsetting some of the losses experienced by producers. Otherrelevant effects include disease-induced productioninefficiencies and changes in the cost structure of producersacross many sectors of agriculture. These effects and otherswould need to be captured along with net trade effects onproducer and consumer surplus across the agricultural sector ina complete analysis of the effects of losing export markets. Acomplete evaluation of these effects is outside the scope of thecurrent analysis, and so the gross value of exports is used hereinfor the purposes of an illustrative example.

Three stages of trade losses are calculated in the CDSM, asdescribed below.

In Stage 1, exports of all FMD-susceptible animals andproducts are assumed to cease on the day the disease isdetected. These exports do not resume until the last infectedanimal is removed (Stage 1 trade loss). Each iteration of theCDSM and ECM has an associated Stage 1 trade loss,determined by the number of days required to control theoutbreak multiplied by the average daily export trade volumeof FMD-susceptible animals and products.

In Stage 2, exports are assumed to remain suspended for threemonths following the removal of the last infected animals, incompliance with OIE standards. These Stage 2 trade losses aremodelled as a constant (three months of average daily tradevolume in FMD-susceptible animals and products).

In Stage 3, the period of export suspension recommended bythe OIE standards from Stage 2 has elapsed. It is assumed thatthe time required to recover pre-outbreak export levels inFMD-susceptible animals and products (Stage 3 trade loss) isdirectly related to the duration of the outbreak.

The formula for Stage 3 trade loss is:

(DTR(1,1.1,1.2) – D) * DL

where D is the number of days an outbreak lasts, DL is the dailytrade loss and TR represents a trade recovery coefficient thatvaries stochastically between 1.0 and 1.2. This formula allowstrade to recover almost immediately if the outbreak iscontrolled rapidly, but could allow recovery to take years if theoutbreak is longer.

Other factors, such as available substitute sources, other diseaseoutbreaks, regionalisation and global economic conditions,affect market recovery but are not modelled in the currentanalysis. Uncertainty about market recovery is imposed byprobability distributions on each iteration of the CDSM andECM. Recovery of trade to pre-outbreak levels may take years.

The ability to rapidly detect and control disease outbreaks isdirectly dependent on animal identification. Direct economic

costs are substantially influenced by the extent of the outbreakand the species affected by the disease. Stage 1 trade losses arealso directly related to the number of days between diseasedetection and the removal of the last infected animal, thusmaking detection and traceback important factors. Stage 2trade losses are independent of the extent of the outbreak,based on the fixed length of time described in OIE standards.

Determining benefit. Step 3: statistical generalisationprocedureEconomic consequence estimates are derived in a two-stepgeneralisation process. In the first step, the CDSM model resultsare input variables into the calculation of direct costs, Stage 1trade losses and Stage 3 trade losses for each CDSM iteration.This procedure was necessary for two reasons. Firstly, tocompare scenarios with different numbers of CDSM iterationsand secondly, to allow further analysis on the results of theCDSM model. The CDSM modelling procedure is currently acumbersome, time-consuming process, and unequal numbersof iterations were originally completed for different scenarioswith no further opportunity to re-run (recall that two scenariosare combined for each situation). All further analysis wascompleted in the @Risk framework (16).

In step 2, the procedure uses a discrete probability distributionto replicate those calculations in a distribution that can besimulated in the @Risk framework for further analysis.Appendix A contains the frequency data used in thegeneralisation procedure for each of the eight scenarios.

Determining benefit. Step 4: combining the scenariosto measure benefitsTable IV shows how economic costs were compared acrossanimal species to derive benefits from improvements in animalidentification. The benefits of an improved animal identificationsystem are approximated by the reduction in economic costs ofan FMD outbreak when the improved animal identificationsystem is in place.


Table IVBenefits of upgrading the animal identification system

Situation Species/type Calculation of benefitsin the benefit-cost ratios

1 Adult cattle Simulated consequences Scenario 9 minussimulated consequences Scenario 11 = benefits

2 Feedlot steer Simulated consequences Scenario 10 minussimulated consequences Scenario 12 = benefits

3 Adult swine Simulated consequences Scenario 13 minussimulated consequences Scenario 15 = benefits

4 Market pig Simulated consequences Scenario 14 minussimulated consequences Scenario 16 = benefits

Table VCost calculations for upgrading animal identification systems

Tag Data Number of database Number of Total cost (b)

Situation Scenario cost entries (a) entries x cost per animals (US$ millions) Difference(US$) entry (US$) (millions)

Situation 1: adult Scenario 1: paper trail only, no ear or back tag None 2, 4-11 9 x 0.10 40 36

cattle traced to last Scenario 2: back tag, ear tag and paper 1.00 All 11 x 0.10 40 84 48

farm of ownership

Situation 2: feedlot Scenario 3: paper trail only, no ear or back tag None 2, 7-11 6 x 0.10 40 24

steer animal traced Scenario 4: back tag, ear tag and paper 1.00 1-3, 7-11 8 x 0.10 40 72 48

to last farm of

ownership

Situation 3: adult Scenario 5: paper trail only, no ear or back tag None 2, 4-11 9 x 0.10 100 90

swine traced to last Scenario 6: back tag, ear tag and paper 1.00 All 11 x 0.10 100 210 120

farm of ownership

Situation 4: market Scenario 7: paper trail only, no ear or back tag None 2, 7-11 6 x 0.10 100 60

pig traced to last Scenario 8: back tag, ear tag and paper 1.00 1-3, 7-11 8 x 0.10 100 180 120

farm of ownership

a) refer to section entitled ‘Animal identification in the United States of America’ for definitions of range of data entriesb) these costs were calculated based on the previous two columns and were used as the modes for the Pert distribution described in the text

Determining cost. Step 1: cost of the animalidentification systemThe situations analysed in this paper trace an animal from theslaughterhouse back to the last farm of ownership. Thesituation in Table II describes the type of animal and theendpoint of the traceback. The scenario describes the level ofidentification available to perform the traceback. The data entrynumbers refer to alternative points in the lifetime of the animalwhen information about the animal might be entered into adatabase (29).

Each data entry action is assumed to cost US$0.10. (A clerk isassumed to earn approximately $20,000 per year,approximately $10 per hour or $0.16 per minute; a record canbe entered into a database in approximately 0.5 minutes.)Assuming a maximum of 11 data entry actions per animal, themaximum data entry cost for any animal is US$1.10. Fixedstart-up costs are not included in this analysis because all of theanimal identification levels discussed currently exist in the USA.Given this pre-existing infrastructure, additional start-up costsare assumed to be insignificant in the USA relative to thevariable costs of implementing the various levels of animalidentification improvement. For countries that may bebeginning to implement an animal identification system, thesestart-up costs should be considered as an additional element ofan analysis of this type.

Table V summarises the annual costs for each situation andidentification level. All situations involve tracing to the last farmof ownership. The four situations are defined in Table II.


Determining cost. Step 2: cost distributionassumptionsIncreases in costs associated with increased levels of animalidentification are stochastically modelled as part of the benefit-cost simulation. Figure 2 illustrates the distribution of theannual increase in costs associated with the higher level ofanimal identification (level 1 versus level 4 for swine, level 1versus level 5 for cattle) used in the benefit-cost analysis. Thecalculation of these increases in cost is described in more detailin Table V. A Pert distribution incorporates variability anduncertainty into the estimates of annual cost (16, 28). The Pertdistribution is commonly used when the modeller has littledata other than the mean, minimum and maximum (28). ThePert distribution is often favoured over the more commontriangular distribution when there is reason to believe thatunobserved points between extremes and the mean follow anon-linear pathway. In the absence of data to the contrary(i.e. uncertainty), the authors always favour the non-linear Pertdistribution to the closely related triangular (linear)distribution, because the former is less restrictive.

Figure 2 shows results of the simulation process over 5,000iterations for two of the animal identification situations.Minimum and maximum annual costs are imposed on thedistribution at 50% below and 50% above the most likelyannual cost described in Table V. This range helps to accountfor uncertainty about the costs of data entry due to differencesin systems available on specific farms, economies of size, etc.Furthermore, the number of entries that are made under eachscenario is unknown. The numbers reflected in Table V aremost likely, but individual entries may vary substantially.

The benefit-cost ratio simulationBenefit-cost ratios are simulated over 5,000 iterations in an@Risk procedure using distributions of benefits and costs asdescribed above.

Costs are considered to be incurred yearly, as new animals enterthe respective herds. These costs are expected to be repeatedover the planning horizon of the animal identification systembeing evaluated. This stream of costs is discounted back topresent value.Three planning horizons are considered, namely: 15, 30 and 50years. Any improvement in an animal identification system hasa finite effective life, after which obsolescence occurs. Horizonsare intended to represent the time after which obsolescenceoccurs. Yearly simulated costs for each of the four situations arediscounted back to present value over 15, 30 and 50 years.

Benefits are based on the probability of an FMD outbreakoccurring at some point in the future. Given that a primaryFMD outbreak will occur at some point within a 50-year time

horizon, the probability of the outbreak occurring at variouspoints in time is assumed to follow a uniform distribution. Inother words, it is assumed that this outbreak, given that itoccurs at all, is equally likely to occur in any given year. Oncean FMD outbreak occurs, the benefit of the animalidentification system is derived. Multiple primary outbreaks ofFMD within the planning horizon, or additional primaryoutbreaks of other FADs would be expected to increase themagnitude of the consequences being simulated, thusincreasing the benefits of improved animal identificationbeyond those measured here. Ignoring these additionalpotential benefits is a somewhat conservative approach toevaluating the benefits and costs of these improvements.

The benefits of the improved animal identification system couldbe realised in the first year, should an outbreak occur.Alternatively, the benefits could never be realised, if an outbreakfails to occur within the planning horizon (the useful lifetime ofthe animal identification system). The simulated benefits areallowed to occur at uncertain times in the future. An equalprobability of an outbreak occurring over a 50-year timehorizon is assumed on the benefits side of the simulation. (Theyear in which the first outbreak of FMD occurs is determinedin the benefit-cost simulation for each iteration using thefollowing @Risk formula: RISKUNIFORM (1,50) (16). Asmentioned earlier, this distribution assumes an equalprobability of an outbreak occurring in any year over the next50 years.) Effectively, when the 15-year planning horizonsituations are simulated, at least one outbreak occurs in 30% ofthe 5,000 simulations. Similarly, when the 30-year planninghorizon situations are simulated, at least one outbreak occurs in60% of the 5,000 simulations. When the 50-year planninghorizon situations are simulated, at least one outbreak occurs inall of the 5,000 simulations.

For each of 5,000 iterations, the benefit and cost simulationsare combined to form the representative benefit-cost ratios.This analysis is repeated in a simulation for four situationsacross the three planning horizons. Results of the simulationsare presented in the next section.

ResultsTable VI shows the resulting mean value for the benefit-costratios obtained from the simulation exercise, in addition toprobabilities for benefit-cost ratios being greater than 1. ForSituations 1 and 2, on average, an improvement in animalidentification system from level 1 to level 5 is cost beneficialover all technological planning horizons, with average benefit-cost ratios above 1.0 across all three planning horizons. InSituation 3, the mean ratio is only above 1.0 for the 15-yeartechnology-planning horizon. The mean benefit-cost ratio inSituation 4 is slightly less than 1.0, even with the 15-yeartechnological planning horizon.


Fig. 2A Pert distribution of costs by situation

a) Situation 2

b) Situation 4

Pro

babi

lity

Pro

babi

lity

Cost (US$ millions)

Cost (US$ millions)

These mean results suggest the following:

a) for cattle in situations similar to those found in the USA,improved levels of animal identification may provide sufficienteconomic benefits in terms of reduced FAD consequences tojustify the improvements. This is true even if technologicalchange does not make the systems obsolete for 50 years

b) in swine, results show that improved animal identificationsystems do not provide sufficient economic benefits in terms ofreduced FAD consequences to justify the improvements.

Results from the 15-year planning horizon for Situation 1 showa 75% probability of the benefit-cost ratio being greater than 1.Similarly, simulation results from Situation 2 show an 86%probability of the ratio being greater than 1. Probabilities ofratios greater than 1 are 54% and only 37% for Situations 3 and4, respectively. More detailed simulation results of benefit-costratios are shown in Figure 3 for the 15-year planning horizon.Results for simulated benefit-cost ratios across the planninghorizons are shown in Table VI. More detailed results areshown in Appendix B.


Fig. 3Simulation results: benefit-cost ratios for a 15-year planning horizon

Table VIBenefit-cost ratio results for the simulation exercises over varying time horizons

15 years 30 years 50 yearsSituation Mean Probability Mean Probability Mean Probability

ratio of ratio > 1 ratio of ratio > 1 ratio of ratio > 1

1. Adult cattle at slaughter to last farm of ownership 2.40 0.75 1.54 0.58 1.24 0.48

2. Feedlot steer at slaughter to last farm of ownership 3.15 0.86 2.02 0.71 1.63 0.61

3. Adult swine at slaughter to last farm of ownership 1.44 0.54 0.92 0.34 0.74 0.25

4. Market pig at slaughter to last farm of ownership 0.97 0.37 0.62 0.20 0.50 0.13

a) Situation 1 b) Situation 2

c) Situation 3 d) Situation 4

Pro

babi

lity

Pro

babi

lity

Pro

babi

lity

Pro

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Benefit-cost ratio Benefit-cost ratio

Benefit-cost ratio Benefit-cost ratio

The resulting distributions of simulated benefits by economicstage for Situation 1 are shown in Figure 4. Stage 2 trade lossesare constant and are therefore not displayed. (Stage 2 trade lossis always equal to the OIE standard x daily trade loss, here$1.1 billion for all scenarios and all simulations, therefore netgain in Stage 2 trade is always $0.0.) In all cases, a proportionof the individual simulations resulted in no benefit(consequences of the FAD outbreak were at least as severe with

improved animal identification as were the consequences ofthe FAD outbreak with lesser level 1 animal identification inplace). As intuitively expected, uncertainty and variability (inthe distributions) cause overlap such that consequences canoccasionally be more severe with the improvement in animalidentification system than without. Direct economicconsequence savings are on average just over US$6 million.Estimated losses due to trade are of a much greater magnitude,with savings averaging US$2 billion during the outbreak(Stage 1) and US$1.5 billion after the OIE standard period oftrade restriction has elapsed (Stage 3).

Direct economic consequence savings, Stage 1 trade losssavings and Stage 3 trade loss savings are shown for each of thefour animal identification improvement situations inAppendix C.

Recalling that the difference in economic consequencesbetween the lower and improved level of animal identificationdetermines the ‘benefit’ for the benefit-cost ratio, results ofwhich are described above, an examination of the underlyingdistributions of economic consequences associated with thosebenefits may be of interest to the reader. Distributions of theeconomic consequences for each scenario are presented inAppendix A. The bimodal character of these distributions isinteresting to note. This character may be explained by the‘either/or’ nature of the economic consequences associated withFAD introductions. Either the disease is contained sufficientlyearly to minimise the economic consequences, or the diseaseescapes early containment attempts, leading to a far greaterlevel of consequences. An example of this type of bimodaldistribution occurring in the real world is evident in the FMDepidemic affecting the EU in 2001. Early detection andcontainment efforts in the UK failed at the beginning of thisepidemic. This failure resulted in a very high level of economicconsequences as a result of the FMD introduction. More than1,500 outbreaks have been reported to date in the UK.Conversely, at the time of writing, early containment efforts inFrance appear to have been successful, with only two outbreaksbeing reported.

The simulation results using improved animal identificationsystems are consistent with intuitive expectations about theeffect of these improvements on the bimodal distributions ofeconomic consequences. The second modes of the economicconsequence distributions are far less pronounced, in additionto being shifted to the left, indicating a reduced magnitude ofeconomic consequences. This type of change in thedistributions is consistent with the idea that an improvedanimal identification system results in a lower frequency ofhigh-level economic consequences. The lower frequency ofhigh-level consequences represents the benefits of the system.Whether this reduced frequency of high-level consequences issufficient to warrant implementation of such a system requiresa comparison of these benefits with the costs of the system.


Fig. 4Simulation results: benefits by economic consequence category,for tracing of adult cattle at slaughter to the last farm ofownership (Situation 1)

a) Savings in direct economic consequences

b) Savings in Stage 1 trade loss consequences

c) Savings in Stage 3 trade loss consequences

Pro

babi

lity

Benefits (US$ millions)

Pro

babi

lity


Pro

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lity


LimitationsAs with any evaluation, this analysis of the benefits and costs ofanimal identification systems is subject to certain limitations.The limitations described below represent areas of potentialfuture research and analysis regarding animal identificationsystems.

The benefits of improved animal identification systemscalculated in this study are based on an assumption that a singleprimary FMD outbreak will occur in the USA over a 50-yeartime frame. At present, no risk analysis has been conducted todetermine the actual annual probability of a primary FMDoutbreak occurring in the USA. The 50-year time frame used inthis study is presented for illustrative purposes. Additionaldetailed research would be required to accurately estimate theprobability of FMD occurring in the USA, or in other countriesthat may be considering improvements to national animalidentification systems. The FMD virus could enter the USAthrough many different pathways. The pathways that representthe highest risks include contraband, illegal transhipments,garbage from boats and planes and illegal immigration.Accurate quantification of the probability of FMD virus entrythrough each of these various pathways would be a substantialundertaking that is well beyond the scope of the current study.The purpose of the current study is to present a conceptualmodel, with an example application, of the evaluation of theeconomic usefulness of improved animal identification systemsin the presence of FAD risks.

The current analysis focuses on the avoidance of FMDconsequences as a source of the benefits of improved animalidentification. The benefits of improving the animal healthsituation in the USA with regard to other FADs and endemicdiseases could also be evaluated and would probably contributesubstantially to the estimated benefits of improved animalidentification. However, the trade effects of other diseaseswould not necessarily be cumulative for two reasons. Firstly,trade impacts of other diseases would probably involve thesame trade as that affected by FMD in the current analysis.Secondly, the restrictions imposed by trading partners mightnot be as severe as those imposed for FMD if the disease is oflesser economic consequence, as is the case for many endemicdiseases currently faced in the USA. Other substantial benefitsmay be found in increasing food safety and consumerconfidence in this safety through the ability to rapidly tracesources of disease or contamination. These additional benefitsare not quantified in this analysis.

The analysis uses the gross value of exports to represent tradeloss. Other significant economic aspects of lost exports are notincluded in this measure of trade effects. For example, during adisease outbreak, when exports have been halted, largenumbers of animals or large quantities of product are divertedto the domestic market, causing prices to fall, sometimessignificantly. Lower prices have a positive effect on consumers

and a negative effect on producers. The gross value of exportsdoes not capture these effects.

The analysis uses a singular approach, based on the length ofthe FAD outbreak, to determine stochastically the length oftime required to complete recovery of the previous trade flowfollowing a loss of export markets. In fact, other world-widesupply and demand conditions, such as availability ofcompetitors to fill trade gaps, frequency of disease outbreaks incompeting markets, confidence in the veterinary infrastructuresof all potential suppliers and the ability of a supplier toeffectively regionalise when an outbreak occurs, are allexamples of factors that play an important role in traderecovery. Further empirical research into the various aspects ofmarket recovery is necessary to more accurately estimate thebenefits that would accrue from reduced market recoverytimes.

Beyond the trade effects, the economic picture of a diseaseepidemic is complicated by the decrease in supply resultingfrom eradication of infected and exposed animals in quarantinezones. Even herds with no infected or exposed animals areaffected by the imposition of quarantines while investigationsare conducted as to the extent of disease spread. Thesebystander herds also suffer production losses due to theinability to conduct normal business operations. In addition,consumer demand for livestock products may be negativelyaffected by reports of disease outbreaks in the media. Thisnegative consumer effect may be partially offset by theassurance provided by the improved animal identificationsystem. These effects are not modelled in the current analysis.

A further factor not directly considered in the current analysisas part of the impacts of animal identification is the indirect andinduced losses to the regional and national economies resultingfrom the loss of production and employment in the event ofdisease outbreaks. The gains to these economies resulting fromeradication, vaccination and other employment activities havealso been ignored. One might argue that using the gross valueof exports adequately accounts for losses incurred in theseareas.

Each of these areas is complex and requires additional datacollection and modelling. Each represents important aspects ofthe evaluation of the benefits and costs of improving animalidentification systems and would be valuable supplements tothe current analysis.

ConclusionsRapid tracing of potentially infected animals, herds orcontaminated products is an essential step in the rapid controlof a disease outbreak. Identification and recording systems,when effective, can facilitate rapid control and eradication. Thisanalysis presents a benefit-cost evaluation of traceback and


control of an infectious disease in animals using improvedanimal identification systems.

This analysis suggests that, for cattle in situations similar tothose found in the USA, improved levels of animalidentification may provide sufficient economic benefits in termsof reduced FAD consequences to justify the improvements. Inswine, improved animal identification systems do not providesufficient economic benefits in terms of reduced FADconsequences to justify the improvements. However, additionalbenefits, not quantified in this analysis, may be derived fromother sources, such as the following:

a) savings in the cost of eradicating endemic diseases and otherFADs (e.g. CSF)

b) gains to producers from improved genetics and carcassquality, herd certification and premium prices for products

c) consumer confidence in the national livestock industry.

Market structure is an important factor in the discussion ofanimal identification systems. Vertically integrated industries, inwhich animals have only one owner from birth to slaughter ina closed system, may not require a national system of individualanimal identification for traceback purposes. Typically, theseenterprises internally track individual animal genetics, feeding,care and other environmental factors in the interest ofenhancing profits. Traceback is enhanced by individual animalidentification for other purposes in vertically integratedoperations.

This analysis focused on the benefits and costs of tracebackfrom the slaughter plant where the disease is discovered to thelast farm of ownership. A favourable benefit-cost ratio wasestimated in most of these situations. However, if traceback isrequired to the farm of birth, the complexity of tracebackincreases, the speed of the process slows and the accuracy isreduced. Disease spread becomes potentially greater, tradelosses increase and the benefit-cost ratios would change.

The necessity of traceback to the farm of birth depends on thedisease. For instance, FMD has a short incubation period,spreads rapidly and requires rapid traceback, but probably notto the farm of birth. Other diseases, such as scrapie and bovinespongiform encephalopathy, spread less rapidly and have lessobvious symptoms, possibly creating a greater need totraceback to the farm of birth.

Clearly, a comprehensive evaluation of animal identificationsystems is an extremely complex undertaking. The primarygoal of the current analysis was to establish a framework for thistype of evaluation and begin a discussion on the use of benefit-cost analysis in evaluating improved animal identificationsystems. This framework provides a basis for future researchinto the benefits and costs of animal identification systems. Theauthors hope that this paper will generate useful discussion thatwill result in additional research in this emerging area of animalhealth.

AcknowledgementsThe authors wish to thank M. Schoenbaum, D. Mitchell,K. Cassidy, C. Saylor and B. Trout, of the United StatesDepartment of Agriculture, Animal and Plant Health InspectionService, Centers for Epidemiology and Animal Health, forreviews, comments and technical assistance in preparing thismanuscript.


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Analyse coût-bénéfice de l’identification animale appliquée à laprévention et à la prophylaxie des maladies

W.T. Disney, J.W. Green, K.W. Forsythe, J.F. Wiemers & S. Weber

RésuméL’identification animale revêt une grande importance pour les pays désireuxd’améliorer leurs systèmes de traçage ascendant. Dans leur analyse, les auteursprésentent un cadre conceptuel du rapport coût-bénéfice permettant d’évaluerl’intérêt économique de l’amélioration des systèmes d’identification animale visantà réduire l’impact des maladies animales exotiques. Les résultats obtenus pour lesbovins dans des situations comparables à celle des États-Unis d’Amériquemontrent que l’amélioration du système d’identification animale se justifie par les


Análisis de rentabilidad de la identificación de animales con finesde prevención y control sanitario

W.T. Disney, J.W. Green, K.W. Forsythe, J.F. Wiemers & S. Weber

ResumenLa identificación de cada ejemplar por separado es un aspecto importante paraque muchos países logren perfeccionar sus sistemas de rastreabilidad deanimales. En su análisis, los autores presentan las bases conceptuales paraevaluar la relación costo/beneficio, y por ende la utilidad desde el punto de vistaeconómico, de sistemas de identificación animal más eficaces y concebidos paraatenuar las consecuencias de enfermedades animales exóticas. En el caso debovinos en circunstancias análogas a las que concurren en los Estados Unidos deAmérica, los resultados demuestran que una identificación más exacta puedereportar suficientes beneficios económicos (menor perjuicio causado porenfermedades exóticas) como para justificar la implantación de mejoras. Encambio, los resultados de estudios similares realizados con porcinos demuestranque los beneficios económicos no bastan para justificar la introducción desistemas más eficaces de identificación animal. Quizá los sectores productivosverticalmente integrados, esto es, con sistemas cerrados en los que cada animaltiene un solo propietario desde el nacimiento hasta la muerte, no requieran, aefectos de rastreo, sistemas individuales de identificación animal. Tales sistemaspresentan no obstante otras ventajas complementarias, no cuantificadas en esteanálisis, que podrían invertir el signo de la relación costo/beneficio y hacer que lamejora de los sistemas de identificación resultara rentable en ciertos sectores dela industria porcina.

Palabras claveComercio – Control sanitario – Economía – Identificación de animales –Rastreabilidad – Rastreo – Relación costo/beneficio.

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bénéfices générés par la réduction de ces maladies. En revanche, pour lesporcins, les avantages économiques résultant d’une limitation de l’impact desmaladies porcines exotiques ne suffisent pas à justifier l’amélioration du systèmed’identification. Les systèmes de production dans lesquels les animaux sontmaintenus chez un seul et même propriétaire depuis leur naissance jusqu’àl’abattage, peuvent se passer de l’identification individuelle pour les besoins dutraçage ascendant. Toutefois, l’amélioration de l’identification des porcs pourraitprésenter d’autres avantages, non quantifiés dans cette analyse, et se traduirepar un rapport coût-bénéfice favorable dans certains secteurs de la filièreporcine.

Mots-clésCoût-bénéfice – Échanges – Économie – Identification animale – Prophylaxie –Traçabilité – Traçage ascendant.

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