Biosecurity and risk factors for production diseases in pigs and poultry

Transcription

1 Biosecurity and risk factors for production diseases in pigs and poultry Tommy Van Limbergen, Ilias Chantziaras Jeroen Dewulf, Marlijn Klinkenberg, Dominiek Maes Unit Porcine Health Management Faculty of Veterinary Medicine Ghent University Belgium Tommy Van Limbergen - Ghent University 28/11/2018 1

2 Outline of presentation Introduction Aims Study 1: Assess biosecurity levels in European poultry and pig farms Study 2: Factors associated with health, welfare and reproductive performance indicators Study set up Results Study set up Results Conclusions Tommy Van Limbergen - Ghent University 28/11/2018 2

3 INTRODUCTION WP1 deliverables 1.3 and 1.4: To quantify biosecurity and risk factors in pigs and poultry in a standardized way in diverse EU systems in 7 EU countries regarding: - Health, - Welfare and - Performance Tommy Van Limbergen - Ghent University 28/11/2018 3

4 Aims Assess biosecurity levels in European pig and poultry farms Identify risk and protective factors associated with: Health, welfare & performance parameters Tommy Van Limbergen - Ghent University 28/11/2018 4

5 Study 1: How to score biosecurity and management on pig and poultry farms? Webbased tool: Based on: Scientific literature Poultry Experts opinion In-house experience FREE ACCESS => 3 versions: pigs, broilers and laying hens Tommy Van Limbergen - Ghent University 28/11/2018 5

6 How to score biosecurity and management on pig and poultry farms? Risk based scoring tool 12 subcategories 2-11 questions per subcategory (n=109 in total) Max. score = 100 (perfect biosecurity) Min. score = 0 (absence of biosecurity) Weighted scores Weight factor for each subcategory/question Based on scientific research and expert opinion Tommy Van Limbergen - Ghent University 28/11/2018 6

7 How to score biosecurity and management on pig and poultry farms? Webbased tool: Takes only +/- 20 minutes Full multiple choice (easy) Instant 2 page report! => clear advices: How to improve!!! Tommy Van Limbergen - Ghent University 28/11/2018 7

8 How to score biosecurity and management on pig and poultry farms? Webbased tool: Own results (red) Database average (green) Create a log in! => Do it again and check your improvements!!! Tommy Van Limbergen - Ghent University 28/11/2018 8

9 Biosecurity and management in broiler farms Tommy Van Limbergen - Ghent University 28/11/2018 9

10 Biosecurity in broiler and layer farms Summary Internal >>>> external Larger farms => lower internal biosecurity and management Best category: Disease management 87.9% Worst category: Entrance of visitors and personnel 55.1% = easy to improve!!!! Tommy Van Limbergen - Ghent University 28/11/

11 Biosecurity in sow farms External biosecurity score: 76.3% Internal biosecurity score: 56.9% Tommy Van Limbergen - Ghent University 28/11/

12 Biosecurity in fattening pig farms External biosecurity score: 67.4% Internal biosecurity score: 59.2% Tommy Van Limbergen - Ghent University 28/11/

13 Biosecurity in pig farms (sows and fatteners) Scores of external biosecurity were higher than internal biosecurity Large variation: between countries, between farms room for improvement Benchmarking biosecurity levels motivates the farmer make targeted actions! Tommy Van Limbergen - Ghent University 28/11/

14 MATERIAL & METHODS Study 2: 1) Specific questionnaires (50 farms/country) 2) Collection of farm data (50 farms/country) 3) Statistical analysis Tommy Van Limbergen - Ghent University 28/11/

15 MATERIAL & METHODS Specific questionnaire: - Developed in 2014 together with PROHEALTH-consortium - A total of 67 questions - Six categories: General information Housing Feed and water supply Treatment / diseases Animal details Production management Tommy Van Limbergen - Ghent University 28/11/

16 MATERIAL & METHODS Collection of farm data broilers: Collected on a flock basis (at least 6 successive flocks) Standardized parameters: Average age (days) Dead on arrival to slaughterhouse (%) Average weight (kg) Condemnation rate (%) Overall mortality (%) Feed conversion rate First week mortality (%) Daily gain (gram/day) Tommy Van Limbergen - Ghent University 28/11/

17 MATERIAL & METHODS Statistical analysis: Eight linear mixed models (SAS): 1) Overall mortality 5) Condemnation rate 2) First week mortality 6) Feed conversion rate (FCR) 3) Mortality after 7 days 7) Daily growth 4) Dead on arrival 8) European production index (EPI) Multivariable linear regression model => stepwise forward model building procedure Random country effect Tommy Van Limbergen - Ghent University 28/11/

18 RESULTS Descriptive results: - 7 EU member states conventional broiler farms - 77%: only activity = broiler production - 78,5%: Part of a quality assurance scheme - 51,8%: Part of an integrated system Tommy Van Limbergen - Ghent University 28/11/

19 RESULTS Risk-factor analysis: First week mortality Floor quality: cracked floors => higher first week mortality Ventilation type: higher in tunnel or roof ventilated houses Professional activities: higher when farmer has multiple activities Neonatal E.coli infection Tommy Van Limbergen - Ghent University 28/11/

20 RESULTS Risk-factor analysis: Mortality after 7 days Floor quality: cracked floors => higher first week mortality Feed conversion rate (FCR) Daily growth Coccidiosis infections: no problems with coccidiosis => higher daily growth Tommy Van Limbergen - Ghent University 28/11/

21 RESULTS Risk-factor analysis: Dead on arrival Type of light adaptation: red lights => higher DOA Drinking system: nipple drinking system => lower DOA Daily growth: higher DG => higher DOA Tommy Van Limbergen - Ghent University 28/11/

22 RESULTS Risk-factor analysis: Drinking system: Daily growth: Condemnation rate cup system => lower condem. rate higher DG => higher condem. rate Feed withdrawal time: shorter feed withdrawal times => higher condem. rate Ventilation: No recirculator vents => higher condem. rate (lower in crossventilated houses)? House size: Higher capacity => higher condem. rate E.coli after 7 days Type of feed: concentrate + wheat => lower condem. rate Tommy Van Limbergen - Ghent University 28/11/

23 RESULTS Risk-factor analysis: Feed conversion rate (FCR) Daily growth Light intensity adaptation: if possible => lower FCR Ventilation: Roof < Cross < Cross x Tunnel Necrotic enteritis problems: if present => higher FCR Tommy Van Limbergen - Ghent University 28/11/

24 RESULTS Risk-factor analysis: European production index (EPI) Sex of DOC: only males => higher EPI; only females => lower EPI Dysbacteriosis problems: if present => lower EPI Comparison of daily results with previous batches: if performed => higher EPI Daily check of drinking and feeding system: if performed => higher EPI Type of drinking system: round drinkers => lower EPI Type of feed (if no dysbacteriosis): complete compound => higher EPI Tommy Van Limbergen - Ghent University 28/11/

25 CONCLUSIONS BROILERS Clear risk factors were found: Housing: floor quality; ventilation; type of light at loading and intensity of light Infectious: E.coli; coccidiosis and dysbacteriosis Management: level of professionalism; feed withdrawal time and light adaptations Adaptations of management, housing and health programs are beneficial Tommy Van Limbergen - Ghent University 28/11/

26 Study 2: risk factors in pig farms 169 farms from 8 EU countries (collected during ) 2 sets of data Questionnaire focusing on farm (management, housing) Farm production data After refinement, 130 farms from 5 EU countries were further selected for the analyses Tommy Van Limbergen - Ghent University 28/11/

27 Study 2: risk factors in pig farms Farm production data 8 parameters were collected 4 related to sow reproductive performance Litters/sow/year Replacement rate Re-inseminations rate Weaning to 1 st mating interval Piglets born alive per litter 4 related to litter/piglet health performance Piglets born dead per litter Preweaning mortality Weaned piglets per litter Tommy Van Limbergen - Ghent University 28/11/

28 Study 2: statistical analyses risk factors in pigs National level Multivariable model structure 2-step process Univariable models Supranational level Step 1: Univariable analysis Criterion for inclusion: P < 0.2/8 Univariable models Multivariable models Step 2: Multivariable analysis Criterion for inclusion: P < 0.05/8 Tommy Van Limbergen - Ghent University 28/11/

29 Study 2: results for risk factors in pig farms Note: Text in green: positive association Text in red: negative association sow reproductive performance Litters/sow/year weaning age of piglets separate housing for sows to be inseminated (after weaning) Repeat-breading % PRRS SPF farm farrowing induction separate housing for sows to be inseminated (after weaning) Replacement % Gilts bred (raised) on the farm PRRS SPF farm Weaning to first mating interval Tommy Van Limbergen - Ghent University 28/11/ Chantziaras et al., Prev Vet Med 2018

30 Study 2: results for risk factors in pig farms Note: Text in green: positive association Text in red: negative association litter/piglet health performance Preweaning mortality Gilts bred (raised) on the farm PRRS SPF farm Piglets born dead per litter Piglets fattened on the farm Piglets born alive per litter age (building) of farrowing unit Mechanical ventilation in gestation unit Weaned piglets per litter Mechanical ventilation in gestation unit Open box group housing system for pregnant sows Tommy Van Limbergen - Ghent University 28/11/ Chantziaras et al., Prev Vet Med 2018

31 Conclusions for pig farms At a supranational level, several factors relating to: interventions (e.g. PRRS free farms), management (e.g. weaning age) and housing (e.g. ventilation) have a significant effect on various performance parameters (e.g. litter index, weaned litters per litter). Further research is needed! Tommy Van Limbergen - Ghent University 28/11/

32 Overall conclusions Biosecurity and management Do the basic things properly and consistently every day challenge, also during weekend, holidays * sensitizing, benchmarking, evolution over time Targeted investments, holistic management Farmers and advisors mostly know the correct solution, but do not always practice it * A chain is only as strong as its weakest link Tommy Van Limbergen - Ghent University 28/11/

33 Thank you for your attention! Tommy Van Limbergen - Ghent University 28/11/