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ANIMAL IDENTIFICATION AND ANIMAL IDENTIFICATION AND RECORDING FOR ANIMAL DISEASE RECORDING FOR ANIMAL DISEASE PREVENTION AND CONTROL PREVENTION AND CONTROL Paolo Calistri Paolo Calistri National Reference Centre for Veterinary Epidemiology, Programming, Information and Risk Analysis (COVEPI), Istituto Zooprofilattico sperimentale dell’Abruzzo e del Molise “G. Caporale”, Teramo (Italy) [email protected]
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Page 1: ANIMAL IDENTIFICATION AND RECORDING FOR ANIMAL … · National Reference Centre for Veterinary Epidemiology, ... epidemiological data, in order to generate ... I&R) system as well

ANIMAL IDENTIFICATION AND ANIMAL IDENTIFICATION AND  RECORDING FOR ANIMAL DISEASE RECORDING FOR ANIMAL DISEASE 

PREVENTION AND CONTROLPREVENTION AND CONTROL

Paolo CalistriPaolo CalistriNational Reference Centre for Veterinary Epidemiology, 

Programming, Information and Risk Analysis (COVEPI),Istituto Zooprofilattico sperimentale dell’Abruzzo e del Molise “G. 

Caporale”, Teramo (Italy)

[email protected]

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Contents

• I&R system and AHIS• Objectives of AHIS• Inputs and outputs of an AHIS• Key points for AHIS development• Systems interoperability (Examples)

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Foreword

• Any strategy for animal disease prevention  and/or control requires the establishment of 

an animal health information system (AHISAHIS)• An effective AHIS should be able to collect, 

manage

and systematically analyse

relevant  epidemiological data, in order to generate 

appropriate information for policy‐makers

and  other stakeholders

along livestock food value 

chains.

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I&R system and AHISThe presence of a fully operative animal identification 

and registration (I&RI&R) system as well as the existence of  an animal traceability (ATAT) system are pre‐requisites for  the establishment of an effective and fully integrated 

AHIS.

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I&R and AHISChoices made in I&R influence AHIS performances

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I&R and AHISChoices made in I&R influence AHIS performances

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I&R and AHIS

•• Not only depending on identification meansNot only depending on identification meansBut also for example:But also for example:

•• Epidemiological unit choice (holding vs herd Epidemiological unit choice (holding vs herd  vs village, pastures codificationvs village, pastures codification…….).)

•• Data collected for each premise / group of Data collected for each premise / group of  animal / individual animal (for examples animal / individual animal (for examples 

geographic coordinates)geographic coordinates)•• Rules for movements notification (movements Rules for movements notification (movements 

to pastures, nomadic herds, to pastures, nomadic herds, ……))

Choices made in I&R influence AHIS performances

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AHIS Objectives

•• International obligationsInternational obligations•• International credibilityInternational credibility

•• Efficacy of interventionsEfficacy of interventions•• Reduction of consequencesReduction of consequences

Objectives

Benefits

•• Free of disease demonstrationFree of disease demonstration•• Health status and certificationHealth status and certification

•• Import / Export risk assessmentImport / Export risk assessment•• Support zoning / regionalization / Support zoning / regionalization / 

compartmentalization strategiescompartmentalization strategies•• Support to decisionSupport to decision‐‐making processmaking process

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Inputs and output of a AHIS

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Key points for AHIS development

• AHIS must be based on clear rules clear rules and proceduresprocedures,  specifying the responsibilities and tasks of all “actors”

• Data should be validatedvalidated

by those who have  produced them

• Respect of the organizational structureorganizational structure, the legal  competencies and tasks of the institutions involved

• Integration of different data sources requires data  and procedures standardization procedures standardization and the 

implementation of common dictionaries common dictionaries and  common coding systemscommon coding systems

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11SAMPLINGSAMPLING

Animalsamples

Samples form 

with a unique 

sampling code

Foodsamples

22SAMPLING DATASAMPLING DATA

Results of 

laboratory tests

33LABORATORYLABORATORY

44TEST RESULTSTEST RESULTS

Example of integration of I&R and LIMS

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11SAMPLES REGISTRATIONSAMPLES REGISTRATION

Sampling data are 

automatically 

retrieved

Sampling code

Samples 

labelling

22SAMPLES TESTINGSAMPLES TESTING

Test results

Scanner 33DIGITAL DIGITAL 

SIGNATURESIGNATURE

Example of integration of I&R and LIMS

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An example of LIMS integration in African countries

• LIMS web application called  “SILAB for Africa”

(SILABFA)

• Interoperability with I&R already  in place in Botswana and ongoing  in Namibia

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Example of integration with I&R for  diseases management: Web GIS

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Example of integration with AT for  diseases management: SNA & tracing tools

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Example of integration with AT for diseases  management: SNA & tracing tools

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In‐field applications

• Smartphones• Tablets

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