Joint effects between biosecurity, productivity, vaccine and antimicrobial use

Amanda Brinch Kruse1 amanda@sund.ku.dk

Liza Rosenbaum Nielsen1, Lis Alban2

1Department of Veterinary and Animal Sciences

University of Copenhagen

2Danish Agriculture & Food Council

CPH Pig Seminar

Tuesday 30 January 2018

Background

Two major challenges for the Danish pig production• Future challenge: keep up production while reducing antimicrobial

use (AMU) without zinc oxide

• Retain high standards for biosecurity to avoid introduction of ASF

Possible solution: Prevention is better than cure • More focus on biosecurity

• Improved and targeted vaccination

Previous studies have looked for associations between AMU, productivity, biosecurity and vaccination

• Using traditional statistical methods, e.g. multivariable models

• These data are expected to be multi-correlated

• How are the different variables interrelated?

2

Objectives

• To explore the joint effects between AMU, productivity, biosecurity and vaccination in the Danish pig production using factor analysis

• To characterise different types of herds based on discussion of the results in collaboration with two pig veterinarians

3

Herds and herd information

Conventional sow herds registered in CHR (>100 sows)

• Productivity data available from SEGES in 2014

• 364 sow herds fulfilled the enrolment criteria

• Either farrow-to-weaner or farrow-to-finisher herds

Additional information about each herd:

• SPF enrolment (SPF or non-SPF herds)

• Export of weaners (yes/no)

• Age of buildings

• Number of employees

• Foreign employees

4

Herd-level data available

Biosecurity (N = 160)• Evaluated using Biocheck

• Questionnaire covering internal and external biosecurity

• Added country-specific questions

• Telephone interview of farmers in 2015

Productivity• Weaned piglets per sow per year

Antimicrobial use (N = 152)• Antimicrobial prescription for sows and weaners from VetStat

• Measured in ADD/100 animals/day

Vaccination• Purchase of vaccines against M. hyopneumoniae, Porcine

Circovirus Type II (PCV2), A. pleuropneumoniae, Porcine Reproductive and Respiratory Syndrome virus (PRRS) and Lawsonia intracellularis

5

Data analysis: Factor analysis

• Explorative, multivariate method

• Factor analysis uses the correlations among many variables to sort related variables into fewer underlying factors

• Interpretation of factors based on the variables included

• Each herd has a score on each factor – can also be used in the interpretation of results

6

Factor

V V V V

Results7

Factor 1: Herd type

Factor 2: Biosecurity

Factor 3: Foreign

employees

Factor 4: Vaccines and herd health

status

No. of animals

Age of buildings

Productivity

AMU

Preventing food from foreign countries

Preventing Swill-feeding Vac. against

MYC

Type of production

Vac. against PRRS

SPF

Vac. against PCV2

Vac. against APP

Washing hands

Registration of visitors

Handling of foreign materials

Handling of diseased pigs

Cleaning and disinfection

Changing boots

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Interpretation of factors – joint effects

Factor 1: Herd type

• High-scoring herds had many sows and weaners, were farrow-to-weaner herds, with newer farm buildings, higher productivity and higher AMU

• Low-scoring herds had few sows and weaners, were farrow-to-finisher herds, with older farm buildings, lower productivity and lower AMU

• Explanation: Treatment strategy/threshold, maybe a higher use of group treatment

Factor 2: Biosecurity

• In high-scoring herds several biosecurity measures were in place

• Low-scoring herds did not have these biosecurity measures in place

• Explanation: A farmer with focus on internal biosecurity is likely to also have focus on external biosecurity

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Interpretation of factors – joint effects

Factor 3: Foreign employees

• Farmers from high-scoring herds said they try to prevent that employees would bring food back from foreign countries and feed pigs food leftovers

• Farmers from low-scoring herds did not have this focus

Factor 4: Vaccination and herd health status

• High-scoring herds were non-SPF and used many vaccines

• Low-scoring herds were enrolled in SPF and did not use many vaccines

• Explanation: Herds with several diseases has a lower herd health and therefore a higher use of vaccines. It makes less sense to be part of the SPF system.

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Combination of factors - Identification of herd types

Herdtype

Biosecurity

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Combination of factors - Identification of herd types

Vaccination and herd health status

Herdtype

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Discussion and conclusion

Important with country-specific studies and identification of herd types

• Use this for setting up health strategies

• Denmark already has high standards for biosecurity and a general low AMU

• Therefore, the need for vaccines may be minimal in most herds

• Though, there is still room for improvement - Both in larger and smaller herds!!!

Can we reduce AMU further without jeopardizing productivity?

• AMU was weakly correlated with higher productivity, so it may be difficult

• Neither AMU nor productivity were correlated with vaccination and biosecurity

• We need new ways to ensure future sustainable pig production

• Look at feed quality and weaning weight

Acknowledgement

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University of Copenhagen and the UC-care project (funding)

The Danish Agriculture and Food Council (economic support)

SEGES Pig Research Centre (productivity and SPF data)

DVFA (Vetstat and CHR data)

DTU-Vet (Vetstat and CHR data)

Special thanks to:

• The pig farmers for their willingness to participate

• Gitte Blach Nielsen and Sif Holmgaard Carlsen for providing input to the identification of herd types

Thank you for your attention

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