Biocheck.UGent: A quantitative tool to measure … - A...measures on poultry farms ... the foundation for biosecurity of the entire production ... their associated preventive measures

INTRODUCTION In highly organized and intensive broiler production,

every disease outbreak has a major effect on health and welfare, leading to a decreased technical performance and profitability. Shorter production cycles, through improved genetics and diet, have led to the fact that there is little recovery time for animals after a disease outbreak (Butcher and Miles, 2012). In case of endemic diseases, disease outbreaks will predominantly result in economic losses for individual farmers, whereas in case of epidemic diseases, the entire poultry production sector may be involved through mandatory preventive measures such as quarantine or destruction of poultry (Carey et al., 2005; Tablante, 2008).

It is therefore of great importance for broiler produc-ers to prevent disease outbreaks rather than to cure them. An additional challenge is that because of the

increasing development of antimicrobial resistance in veterinary and human medicine, this prevention should not be achieved through an increased prophylactic use of antibiotics (Eijck and De Wilt, 2009). As a result, bi-osecurity, defined as all measures taken to prevent both the introduction and the spread of infectious agents on the farm (Barcelo and Marco, 1998), is of key impor-tance in the concept of animal disease prevention.

Despite the recognized importance of biosecurity, it is known from practice and research that there are still serious shortcomings in the application of preventive measures on poultry farms (Van Steenwinkel et al., 2011). Moreover, biosecurity at the farm level provides the foundation for biosecurity of the entire production chain (Siekkinen et al., 2012).

In scientific literature, a large number of risk fac-tor studies, related to infectious diseases in poultry, is available. Based on these studies, many risk factors and their associated preventive measures have been identi-fied, but always in the function of one specific disease (Kouwenhoven et al., 1978; Wolgemuth, 1989; Kappe-rud et al., 1993; Liljebjelke et al., 2005; McQuiston et al., 2005; Capua and Marangon, 2006; Hermans and

Biocheck.UGent: A quantitative tool to measure biosecurity at broiler farms and the relationship with technical performances and antimicrobial use

P. Gelaude ,*1 M. Schlepers ,* M. Verlinden ,† M. Laanen ,* and J. Dewulf *

* Unit of Veterinary Epidemiology, Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Ghent University, 9820 Merelbeke, Belgium; and † Department of Pathology,

Bacteriology and Poultry Diseases, Faculty of Veterinary Medicine, Ghent University, 9820 Merelbeke, Belgium

ABSTRACT The Biocheck.UGent scoring system has been developed to measure and quantify the level of biosecurity on broiler farms. This tool is composed of all relevant components of biosecurity on broiler farms and is subdivided into external (purchase of 1-d-old chicks, off-farm movements of live animals, feed and water supply, removal of manure and dead birds, en-trance of visitors and personnel, supply of materials, infrastructure and biological vectors, location of the farm) and internal (disease management, cleaning and disinfection, materials, and measures between compart-ments) biosecurity. The unique feature of this scoring system is that it takes the relative importance of the different biosecurity aspects into account, resulting in a risk-based weighted score. The Biocheck.UGent scoring

system and accompanying questionnaire can be filled in for free at www.Biocheck.UGent.be. The obtained biosecurity scores are provided immediately after com-pletion of the questionnaire, and the scores for each subcategory can be compared with national averages to allow the farmer to benchmark the obtained results to his colleagues. Preliminary results (n = 15) show a huge range in the biosecurity level on broilers farms in Belgium, with internal biosecurity scores ranging from 54/100 to 87/100 and external biosecurity scores rang-ing from 55/100 to 72/100. These first results show that despite the well-known importance of biosecurity, there’s a lack of implementation of many biosecurity measures and room for improvement.

Key words: well-being , biosecurity , quantifying tool , broiler

2014 Poultry Science 93 :2740–2751http://dx.doi.org/ 10.3382/ps.2014-04002

IMMUNOLOGY, HEALTH, AND DISEASE

Received March 2, 2014. Accepted June 29, 2014. 1 Corresponding author: [email protected]

© 2014 Poultry Science Association Inc.

2740Downloaded from https://academic.oup.com/ps/article-abstract/93/11/2740/1573201/Biocheck-UGent-A-quantitative-tool-to-measureby Ghent University useron 07 September 2017

Morgan, 2007). At this time, no quantitative informa-tion is available regarding the reverse analysis, which is based on whether or not certain biosecurity measures are applied and the possible relationship between the biosecurity level at broiler farms and animal health, technical performance, antimicrobial use, and profit-ability of the herd. One of the assumed reasons for the absence of this type of study is the lack of an objective biosecurity quantification system.

The aim of this study was therefore to describe a newly developed risk-based weighted scoring system for the biosecurity level in broiler farms and to describe the use of this system on a pilot group. At the same time data about antimicrobial use and technical per-formances were collected to investigate the possible re-lationship between biosecurity, technical performances, and antimicrobial use.

MATERIALS AND METHODS

Development of a Biosecurity Scoring System

Biosecurity Questionnaire. The Biocheck.UGent-poultry questionnaire aims at describing the complete biosecurity situation at a broiler herd. Questions are asked on each relevant aspect of the biosecurity to de-termine whether a preventive measure is applied or whether a specific situation is present or absent. The questionnaire is a result of a thorough literature study on disease transmission in poultry, from previous ob-tained information during the development of the Bio-check.UGent tool for pigs (Laanen et al., 2013) and the biosecurity questionnaire of the Federal Agency for the Safety of the Food Chain of Belgium.

A thorough literature study was performed by con-sulting present literature about disease transmission in poultry. All possible transmission routes were included such as airborne transmission, food-borne transmis-sion (e.g., Salmonella spp., water hygiene, and so on), vector-borne transmission (e.g., personnel, wild birds, insects, litter, equipment, rodents or pets, and so on), and environment (e.g., cleaning and disinfecting the poultry house, and so on). Information on general bios-ecurity procedures that are equal for every animal spe-cies (e.g., equipping the hygiene lock, hygienic proto-col before entering the stable, and so on) was obtained from the Biocheck.UGent tool for pigs.

Besides a literature study and the Biocheck.UGent tool for pigs, the Federal Agency for the Safety of the Food Chain biosecurity questionnaire was consulted. This questionnaire has to be filled in annually by all professional poultry farmers together with the veteri-narian and aims at monitoring all different pathways and management factors that may lead to the intro-duction of avian influenza and the possibility of spread once infection is present (AFSCA, 2012).

Subsequently, all measures that prevent the intro-duction of pathogens—through blocking the different

pathways, breaking the infection cycle, or both—were filtered from the information sources mentioned above and grouped into several (sub)categories of biosecurity.

The scoring system is separated into 2 main catego-ries, external and internal biosecurity, and comprises 79 questions on different biosecurity measures. The ques-tionnaire has been designed in such a way that the bios-ecurity management of the broiler farm is questioned in detail without having an excessive number of questions. External biosecurity (51 questions) comprises all mea-sures preventing the introduction of off-farm pathogens and is subdivided into 8 subcategories: purchase of 1-d-old chicks, off-farm movement of live animals, feed and water supply, removal of dead animals and manure, en-trance of visitors and personnel, supply of materials, infrastructure and biological vectors, and location of the farm. Internal biosecurity (28 questions) includes all measures that aim at preventing the within-herd spread of pathogens and is subdivided into 3 subcat-egories: disease management, cleaning and disinfection, and materials and measures between compartments. The amount of measures that are taken into account within each subcategory range from 2 to 17.

The questionnaire can be consulted for free on the website http://www.Biocheck.UGent.be.

Prioritization of Different Biosecurity Measures. Given that not every pathway of disease transmission has the same efficiency, biosecurity measures are not all equally important in ensuring the health of farm animals.

It is well known that direct contact between animals [e.g., purchase of live animals, several animal groups (ages) on one poultry farm, possibility of free range of poultry, and so on] poses a higher risk, whereas indirect contacts (e.g., transmission of pathogens by rodents, sharing of material between different farms, and so on) are less efficient in the transmission of pathogens (Amass and Baysinger, 2006). This efficiency in disease transmission has been taken into account in the bios-ecurity scoring system by weighing the different preven-tive measures accordingly.

The prioritization and weighing of the various bi-osecurity measures and (sub)categories has been done by an expert panel consisting of 16 different experts, each with their own area of expertise. Epidemiologists, veterinary practitioners, microbiologists, and hygiene specialists were included to provide a balanced view on the importance of individual measures. The method of Gore (1987) was used to quantify the effect of a specific measure on disease prevention. In accordance to this method, each expert was given a total amount of 100 weight points that had to be distributed over the dif-ferent subcategories in function of their relative impor-tance. Subsequently, the experts had to give a weight, ranging from 0 to 10, to each preventive measure within the associated subcategory. For each question related to a biosecurity measure different answers are possible, and for each answer a score can be obtained ranging from 0 to 10. All results of the experts were combined

2741BIOSECURITY SCORING SYSTEM

Downloaded from https://academic.oup.com/ps/article-abstract/93/11/2740/1573201/Biocheck-UGent-A-quantitative-tool-to-measureby Ghent University useron 07 September 2017

afterward and the averages were calculated and trans-lated into weights of subcategories as well as ques-tions. By doing so, the scoring system is risk-based and weights are included both at the level of the subcatego-ries as well as at the level of the individual questions.

The expert panel considered external biosecurity to have a larger effect on the biosecurity level of a broiler farm than internal biosecurity. Within the category of external biosecurity, the following subcategories and their corresponding preventive measures were consid-ered to be most important: off-farm movements of live animals, entrance of visitors and personnel, and infra-structure and biological vectors. Within the category of internal biosecurity, the subcategory cleaning and disinfection was pointed out as most important for the prevention of diseases.

Besides the efficiency in disease transmission of a spe-cific transmission route, the scoring system also takes into account the frequency that a transmission route occurs (Fèvre et al., 2006). When a specific indirect contact with a relatively small probability in transmis-sion of disease occurs at a high frequency, this trans-mission route will pose a substantial risk (Laanen et al., 2013) and therefore receives a higher estimated effect.

Quantification of the Biosecurity Level. Based upon the different weights given by the expert panel to each biosecurity measure and (sub)category a final weighted and risk-based score is calculated. To obtain this score, each answer to a specific question receives an individual score between 0 (= total absence of preven-tive measure or full presence of risk) and 1 (= full pres-ence of preventive measure or total absence of the risk).

This score is subsequently multiplied by the weight of the specific question to obtain the relative result of the question. Next, all the results of the individual ques-tions within a subcategory are summed up and divided by the maximum score that can be obtained in the sub-category. This proportional result of the subcategory is then multiplied by the weight of the subcategory to ob-tain the subcategory score. The final score of the inter-nal and external biosecurity is the sum of the different subcategory scores. The overall biosecurity score is the sum of the external and internal biosecurity score. Due to the different relative weight, the external biosecurity score counts for 70% and the internal counts for 30% in the total biosecurity score. For the ease of interpreta-tion of the results, category and subcategory scores are recalculated each time to a score on 100 and presented as a percentage in the reports (Figure 1).

To illustrate this scoring system, the external bi-osecurity subcategory location of the farm is selected (Table 1). This subcategory has a relative weight of 7 within the 70 points allocated to the external biosecuri-ty. Within the subcategory there are 4 questions. Some of these only have a yes/no answer translated into 1 or 0 points, whereas other questions (e.g., number 2, distance to nearest poultry farm) have more potential answers resulting in intermediate scores such as 0.5. Assume that in a specific herd the answer to a ques-tion with the subcategory location of the farm (Table 1) = no, on question 2 = 500 to 1 km, on question 3 = sometimes, and on question 4 = never. Then this will be translated into a score of 1*5 + 0.5*10 + 0.3*8 + 1*4 = 16.4 out of a possible maximum score of 27,

Figure 1. Online results after completing the questionnaire. Color version available in the online PDF.

2742 GELAUDE ET AL.


which is 0.61 or 61%. This score is then multiplied by the subcategory weight (0.61*7 = 4.27) to obtain the final share of this specific subcategory in the total bi-osecurity score.

These calculations are automatically performed on-line after filling in the questionnaire on the Biocheck.UGent website.

Reporting of the Biosecurity Level. The question-naire and accompanying scoring system can be filled in online for free at http://www.biocheck.ugent.be. Based on the answers given in the questionnaire, a farmer obtains a score between 0 and 100 for both external and internal biosecurity and the corresponding subcat-egories.

Immediately after completing the questionnaire, which takes between 20 and 30 min, all scores of the different subcategories are calculated online and shown in a table together with the average scores in Belgium (Figure 1). This enables the farmer to benchmark the obtained results against his colleagues. The deviation of an obtained score from 100 also indicates the po-tential range for improvement (Beek, 2008; Laanen et

al., 2010). Through the Biocheck.UGent website, ad-ditional information on the importance of the related preventive measures is obtained through a hyperlink for each subcategory. The obtained results are also dis-played graphically in a spider web graph (Figure 2) al-lowing rapid visual identification of any bottlenecks in the biosecurity management at the farm. The different axes of the spider web graph represent the associated subcategories within external or internal biosecurity. Every score obtained by the farmer for a specific sub-category is plotted on the related axis. Subsequently, all plotted scores are connected with each other, form-ing an orange-colored geometrical shape that represents the magnitude of the external or internal biosecurity level of the farm. The green-shaped geometrical figure represents the average magnitude of external or inter-nal biosecurity of the participating broiler farms.

Evaluation of the Scoring SystemThe scoring system was evaluated at 15 Flemish

broiler farms to check for usefulness of the system and

Table 1. The weight for the category external biosecurity (70), the subcategory location of the farm (7), the weight for the different measures, and the score that can be obtained according to the answers

Question

Weight of the

question

Answer possibilities

Best Score Intermediate Score Worst Score

Is there within a radius of 1 km stagnant or running water?

5 No 1 / / Yes 0

At what distance is the nearest poultry farm located?

10 >1 km 1 500 m to 1 km 0.5 <500m 0

Is manure from other poultry farms spread on neighboring farmlands?

8 Never 1 Sometimes 0.3 Often 0

Do animal transports occur frequently (minimum once a day) on the public road where your farm is located at (e.g., due to the location of a slaughterhouse in the neighborhood)?

4 No 1 / / Yes 0

= 27

Figure 2. Benchmarking of obtained biosecurity scores against the average through a spider web graph. Color version available in the online PDF.



quality and unambiguity of the different questions. The obtained scores were also discussed with the farmer and the veterinarian to evaluate to what extent the findings of this evaluation were in accordance with their per-sonal estimation of the farm situation.

Selection of Broiler Farms. A list of 41 randomly chosen broiler farms was provided by the nonprofit organization Belplume (Brussels, Belgium). Belplume represents all organizations of the broiler production chain and is the driving force behind the quality system within the Belgian broiler production chain.

Subsequently, all 41 poultry farmers were contacted by phone and asked for their cooperation on a voluntary basis. Farmers who declined to take part were asked to explain their reasons for not participating.

Collection of Data. All data of the first Biochek.Ugent audit were collected between May 2012 and January 2013 through a personal interview at the farm. All broiler farms were visited by the same in-vestigator so that interviewer bias could be minimized as much as possible and interfarm comparability was ensured.

After the interview was conducted and the question-naire was filled in, all poultry houses were visited and photographs were taken. The inspection of the different poultry houses was performed to allow a comparison of the answers given by the farmer and the present situation in the flock. An average flock visit took 2 h. If during the inspection it appeared that the given answers on the questionnaire did not match the reality, the poultry farmer was notified and the given answer was changed. During the visit, no comments were made by the investigator on the given answers.

Afterward, a report of the obtained biosecurity scores was made. In this report, the current biosecurity man-agement was described based on the questionnaire and additional information was given about the importance of the biosecurity measures. Bottlenecks of the biosecu-rity management were highlighted by using the spider web graph, and specific advice was given to improve the biosecurity situation of the herd. A second audit was performed within 1 yr after the given advice to evaluate the changes.

Besides information about biosecurity measures, data on technical performance and antimicrobial use was also collected during both audits. During the first audit this data was retrospectively collected of the past year, while during the second audit data was collected of the last 2 production cycles.

By consulting the farmers administration and slaugh-terhouse documents, 5 technical parameters were calcu-lated for every production cycle by using the following formulas:

mortality first weekM S

N=

+%,

1 1100×

where M1 = number of dead animals during the first week, S1 = number of euthanized animals during the first week, n = total number of live animals at d 1.

Total mortalityMt + St

n= %,×100

where Mt = number of dead animals at the end of the production cycle, St = number of euthanized animals at the end of the production cycle, n = number of live animals at d 1.

Average daily growthWpd Npd Wtd Ntd

Npd Dpd=( )+( )

( )× ×

× ++ ( ),

Ntd Dtd×

where Wpd = average weight at partial depopula-tion time, Npd = number of animals that went to the slaughterhouse at partial depopulation time, Dpd = age of the animals at partial depopulation time, Wtd = average weight at the end of the production cycle, Ntd = number of animals that went to the slaughterhouse at the end of the production cycle, and Dtd = age of the animals at the end of the production cycle.

Feed conversionFt

Wpd Wc × Npd + [ Wtd Wc Ntd]

=

( )

( )− − ×

,

where Ft = total feed intake of the flock at the end of the production cycle, Wc = chick weight at d 1, Wpd = average weight at partial depopulation time, Npd = number of animals that went to the slaughterhouse at partial depopulation time, Wtd = average weight at the end of the production cycle, and Ntd = number of animals that went to the slaughterhouse at the end of the production cycle.

Performance index 100 total mortality ADG

10 FCPI( ) =

( )− ×

×,,

where the PI is an economic parameter that quantifies the production efficiency and FC is feed conversion.

To quantify the antimicrobial use (AMU), official veterinary prescription documents were used. The treat-ment incidence (TI) per thousand animal days based on the defined daily dose animal (DDDA) expressed in milligrams per kilogram was calculated according to the method described by Timmerman et al. (2006) for every production cycle to be able to compare the AMU between both audits and farms.

TI =amount of antimicrobials administered (mg)DDDA the p× eeriod "at risk" kg of animal×

×1 000, ,

2744 GELAUDE ET AL.


where the period “at risk” = the total length of the production cycle expressed in days.

Statistical AnalysisDue to the small number of participating broiler

farms and therefore the limited data set, the statisti-cal analysis was narrowed down to descriptive statis-tics. The average, minimum, maximum, and SD were calculated for AMU, technical results, and biosecurity (Tables 2, 3, and 4).

RESULTSAs described above, the biosecurity scoring system

is subdivided in 2 categories (external and internal bi-osecurity) and 11 subcategories. First, the content and relative importance of each of these subcategories is described.

External Biosecurity (70/100)

Purchase of 1-d-Old Chicks (Weight: 8). Besides the possibility of infection at the hatchery, 1-d-old chicks may also be carriers of vertically transmitted (from hen to chick) pathogens such as Mycoplasma spp. (Lister, 2008). It is therefore important to have knowledge of the sanitary status of the broiler breeder farms because each poultry farm has its own risk profile for the intro-duction of pathogens, disease development, and spread of pathogens to other poultry farms (Sims, 2007). To have a homogenic population of birds at the broiler farm, it is advisable to populate all poultry houses with birds from the same hatchery and breeder farm. Several studies have already pointed out that buying animals from different farms entails a greater risk of introduc-tion of disease-causing agents (Hege et al., 2002).

Off-Farm Movement of Live Birds (Weight: 11). Each time the lorry driver, the catching team, and

Table 2. Subcategories of the Biocheck.UGent scoring system and the overall results for a pilot group of broiler herds

(Sub)category WeightAudit (A) Difference

Average score SD Minimum Maximum

External biosecurity 70 A1 64 5 55 72 A2 +5 69 4 61 74

Purchase of 1-d-old chicks 8 A1 65 16 37 90 A2 +8 73 14 37 90

Exports of live animals (slaughterhouses, traders, individuals) 11 A1 58 13 31 78 A2 +7 65 9 51 78

Feed and water supply 8 A1 44 6 40 47 A2 +4 48 7 37 69

Removal of manure and dead animals 7 A1 64 5 48 66 A2 +5 69 8 53 78

Entrance of visitors and personnel 11 A1 75 8 64 84 A2 +6 81 6 70 90

Supply of materials 7 A1 43 25 0 56 A2 +4 47 21 0 56

Infrastructure and biological vectors 11 A1 81 9 57 94 A2 +3 84 6 68 94

Location of the farm 7 A1 74 25 24 100 A2 +1 75 24 24 100

Internal biosecurity 30 A1 73 10 54 87 A2 +4 77 8 62 88

Disease management 10 A1 81 12 58 100 A2 +3 84 10 60 100

Cleaning and disinfection 13 A1 67 8 49 78 A2 +4 71 7 49 78

Materials and measures between compartments 7 A1 72 26 29 100 A2 +8 80 20 53 100

Table 3. The average technical performance of the 13 participating broiler farms during audit 1 and 2

Parameter Audit (A) Difference Average SD Minimum Maximum

Mortality first week A1 1.08 0.47 0.60 2.44A2 +0.19 1.27 0.45 0.62 2.06

Total mortality A1 3.54 1.42 2.03 7.15A2 −0.49 3.05 0.74 1.80 4.37

Average daily growth A1 57 8 39 66A2 +0 57 6 43 64

Feed conversion A1 1.80 0.31 1.64 2.76A2 −0.10 1.70 0.14 1.57 2.00

Performance Index A1 318 73 136 380A2 +14 332 57 212 396



their equipment enter the farm for depopulation of the stables there is a risk of introducing pathogens. Equip-ment such as transport crates has already been associ-ated with spread of disease (Lister, 2008). Therefore, depopulation must be done in as minimum steps as possible and farm-specific clothing and footwear needs to be assigned to the catching teams (McDowell et al., 2008).

Second, the animal transport vehicles can also spread disease-causing agents because they enter many farms. Epidemiological studies have indicated contaminated livestock lorries as the source of infection for many disease-causing agents (Windsor and Simmons, 1981; Fussing et al., 1998; Rajkowski et al., 1998; Fritzemeier et al., 2000; Hege et al., 2002). It is recommended that at least the wheels of the transport vehicle are disin-fected before entering the poultry farm (Lister, 2008).

Birds may only be loaded into vehicles that have been thoroughly cleaned and disinfected, after remov-ing dead animals, litter, and droppings from another flock. If not, pathogens can spread between different poultry farms.

Feed and Water Supply (Weight: 8). Besides lor-ries that can act as a mechanical vector, the feed can also be a source of infection. The feed can be contami-nated with, for example, Salmonella spp., Escherichia coli, Clostridium spp., Aspergillus spp., and mycotox-ins. The contamination of the feed can occur at differ-ent times during the production, storage, or transport (Lister, 2008).

Also, drinking water is an important potential source of disease transmission. It is important that water is stored in a well-closed reservoir to avoid contamina-tion via dust, wild birds, or rodents (Lister, 2008).

The quality of the drinking water is also influenced by the presence or absence of biofilms in the water pipes. Biofilms form a safe haven for bacteria to grow, and therefore regular monitoring of the drinking water and cleaning of the pipes with products that are capable of removing biofilms is recommended.

Removal of Manure and Dead Animals (Weight: 7). Cadavers are always a potential source of infectious material. Animals often die due to an infection and become a source of infectious material. It is therefore strongly advised to remove cadavers as soon as possible from the stables (Meroz and Samberg, 1995) and to store them in a well-insulated and cooled place at suf-ficient distance from the poultry house(s) (Evans and Sayers, 2000).

The cadaver storage room has to be located in such a way that the rendering company can collect the ca-davers without entering the farm because rendering ve-hicles have previously been associated with spread of diseases (McQuiston et al., 2005). After the collection of the cadavers, it is advisable to thoroughly clean and disinfect the cadaver storage room.

Litter can be highly contaminated at the end of the production cycle by all kinds of pathogens; it is there-fore advised not to store litter at the poultry farm (Lister, 2008).

Entrance of Visitors and Personnel (Weight: 11). Humans may also act as mechanical vectors of several different pathogens. Therefore, the number of visitors of the stables should be limited to the necessary (Lister, 2008). Human movements between farms is believed to have been a key factor in the spread of high pathogen avian influenza in the 2003 outbreak in the Netherlands (Thomas et al., 2005; Vieira et al., 2009).

Table 4. Average treatment incidence (TI) per production cycle for each participating broiler farm at the time of audit 1 and 2

Broiler farm Audit (A) Difference Average TI SD Minimum Maximum

1 A1 176 118 89 346A2 +16 192 148 88 297

2 A1 197 100 126 267A2 −72 125 57 85 166

3 A1 157 176 123 482A2 −71 86 67 31 133

4 A1 311 174 137 498A2 −114 197 96 100 292

5 A1 257 147 10 451A2 +66 323 85 262 383

6 A1 213 167 36 701A2 −99 114 74 19 186

7 A1 115 24 77 153A2 +8 123 1 122 123

8 A1 66 65 11 142A2 −61 5 8 0 11

9 A1 337 175 188 648A2 −263 74 81 17 132

10 A1 186 103 23 372A2 −131 55 78 0 110

11 A1 298 128 207 388A2 −25 273 115 82 362

12 A1 166 82 63 257A2 −73 93 132 0 186

13 A1 21 0 21 21A2 + 92 113 126 23 202

2746 GELAUDE ET AL.


Hobby poultry flocks generally have lower biosecurity levels mainly due to the poor infrastructural hygiene and the poor confinement against the outdoor environ-ment (Van Steenwinkel et al., 2011). Therefore, contact should be avoided with persons that interact with (for-eign) backyard poultry.

Not only the number of visitors but also the num-ber of animal caretakers per poultry house should be limited (Refrégier-Petton et al., 2001). Especially when one caretaker is responsible for multiple poultry houses (Kapperud et al., 1993), pathogens can be easily trans-mitted between these houses.

Accordingly to the risk of introducing pathogens into the flock, the use of a hygiene lock for each poultry house is very helpful. The hygiene lock aims to pre-vent the risk of mechanical transmission of pathogens through human beings (Vangroenweghe et al., 2009). Several studies have shown the benefit of taking hy-gienic measures before entering the poultry house (van de Giessen et al., 1998; Evans and Sayers, 2000).

Supply of Materials (Weight: 7). In addition to per-sons and vehicles, instruments can also serve as disease transmission vectors. To prevent the transmission of pathogens from one herd to another, it is wise to use farm or stable-specific instruments.

To prevent contaminated equipment from being brought into the company by contractors (ladders, tools, and so on; Vieira et al., 2009), it is advised that this type of equipment is already present and available for use at the farm (Lister, 2008). Therefore, contrac-tors are able to use farm-specific equipment.

Infrastructure and Biological Vectors (Weight: 11). Pathogens can be introduced on the farm by ro-dents, wild birds, and insects but also via pet animals and other farm animals.

Rodents may serve as biological as well as mechani-cal vectors of pathogens (Amass and Baysinger, 2006). They may spread infections both within and between neighboring farms. It has been clearly demonstrated that rodents are an important vector of Salmonella Ty-phimurium and Salmonella Enteritidis (Liljebjelke et al., 2005; Lister, 2008). No equipment, weeds, or waste should be piled up against the outer stable walls and feed should be stored in a vermin-free place to discour-age rodents from nesting in the vicinity of the stables (Lister, 2008).

Wild birds are associated with numerous pathogens including avian influenza virus, Newcastle Disease vi-rus, Myxoplasma spp., Campylobacter spp., Salmonella spp., Yersinia spp., and Mycobacterium avium. Ven-tilation holes need to be closed with wire mesh and spilled food in the vicinity of the poultry house should be cleaned up. Ponds or lakes in the surrounding of poultry houses need to be covered with a mesh to dis-courage migratory birds (Lister, 2008).

Putting birds on range is strongly discouraged be-cause of the possibility of direct contact with wild birds (Lister, 2008). If this is not possible, an increased dis-ease surveillance is advised.

Insects can act as a vector for a variety of pathogens; for example, litter beetles have been associated with the spread of Gumboro, Campylobacter spp., Salmonel-la spp., and Marek’s disease (Lister, 2008). Flies have been associated with the spread of Campylobacter spp. between poultry houses (Graham et al., 2008). There-fore, biological vectors need to be controlled through insecticides, parasiticides, and so on or other measures need to be taken to control the insect population (e.g., a mesh in front of air inlets). Measures must not only be taken in and around poultry houses, but also in the hygiene lock because Refrégier-Petton et al. (2001) has described an increased risk for Campylobacter spp. in-fection in broiler farms in the presence of litter beetles in the hygiene lock.

Certain pathogens can be transmitted between dif-ferent farm animal species. Keeping pigs in the vicinity of poultry houses has already been associated with the transmission of avian influenza, methicillin-resistant Staphylococcus aureus and Campylobacter jejuni (Peiris et al., 2001; Ninomiya et al., 2002; Boes et al., 2005). The transmission of Campylobacter jejuni has also been described between ruminants and poultry (van de Gies-sen et al., 1996, 1998; Boes et al., 2005). Furthermore, it should be taken into account that also other patho-gens such as Salmonella Typhimurium frequently occur in pigs, poultry, and ruminants (Wall et al., 1995), and transmission between these species cannot be excluded.

Also, housing different types of poultry (e.g., water-fowl and chickens) on the same farm should be strong-ly discouraged given that some pathogens can be low pathogenic for some poultry species but highly patho-genic for others and can cause severe diseases (Tablan-te, 2008).

Location of the Farm (Weight: 7). The farmer has no real control over the location of his poultry farm, and usually cannot change it easily. However, this does not alter the fact that several important pathogens can be transmitted through air (Hartung and Schulz, 2007). Poultry density in the vicinity of the farm is an important factor for those pathogens for which trans-mission is density dependent (Truscott et al., 2007). A good example is Mycoplasma spp., for which it has already been shown that this pathogen can spread via the wind (Bradburry and Morrow, 2008) and under fa-vorable conditions can remain infectious for a long time (Hartung and Schulz, 2007).

To reduce the likelihood of airborne transmission be-tween poultry farms, the distance to the nearest neigh-bor should be at least 500 m and preferably >1 km. When poultry farms are close to each other, attention should be paid to the predominant wind direction. Not only industrial poultry farms but also backyard poultry can pose a risk (Lister, 2008; Van Steenwinkel et al., 2011).

Besides the presence of another poultry farm in the vicinity, animal transport along the public road can also form a risk for the introduction of pathogens via air (Graham et al., 2008; Vieira et al., 2009). In some



cases, litter is spread on nearby arable lands, contain-ing a risk for the spread of many pathogens such as Gumboro disease virus, avian influenza virus, and in-fectious bronchitis virus (Lister, 2008). When spread-ing contaminated litter in the vicinity of a susceptible flock, the risk of infection varies depending on the wind direction, the presence of vermin and wild birds, and the possible spread through executive personnel and used equipment (Vieira et al., 2009).

Internal Biosecurity (30/100)Disease Management (Weight: 10). Disease man-

agement consists of vaccinating susceptible birds, a strict euthanasia policy, removing dead birds from the stables, and controlling the stocking density.

Vaccination is an important control measure for many diseases that are ubiquitously present (Sims, 2007; Cserep, 2008). Besides reduced losses due to mor-bidity and mortality, vaccination also contributes to animal welfare (Morton, 2007; Cserep, 2008).

Morbid animals need to be euthanized. Such animals form a threat for other susceptible poultry due to the continuously spreading of pathogens. Also, because of animal welfare, such animals need to be euthanized.

The poultry stocking density influences the severity of a disease outbreak (Sims, 2007). A high stocking density induces stress, which results in an increased susceptibility to infections and an increased excretion of pathogens. Many infected poultry in a small area en-tail a sharp increase in the infection pressure. Reducing the stocking density is already proved to be an effective measure for the control of infectious proventriculitis in broilers (Kouwenhoven et al., 1978).

In addition to the risk of transmission, stocking den-sity also influences production results. Recent research associated a high stocking density with a reduced qual-ity of bone and muscle formation, which resulted in an increased prevalence of bowed legs and fractures. Foot quality also deteriorates, and a shorter latency-to-lie period and a higher frequency of contact derma-titis such as hock burn has been associated with high stocking densities. At the end of the production cycle, daily weight gain will be less when compared with lower stocking densities (Van Poucke et al., 2010).

Cleaning and Disinfection (Weight: 13). Cleaning and disinfecting is of great importance for the control of diseases in poultry. It should be avoided for chicks to come in contact with litter, dust, feathers, and other debris from the previous flock (Meroz and Samberg, 1995). Some pathogens can survive for a long time in the environment without the presence of poultry (Jef-frey, 1997; Butcher and Miles, 2012). Therefore, the following steps of the complete cleaning and disinfec-tion protocol should be carried out between 2 produc-tion cycles: dry cleaning, wet cleaning, disinfection, va-cancy period, and monitoring the efficacy (Meroz and Samberg, 1995). Not only the interior of the stables (including the drinking and feeding lines) but also the

environment around the stables may form a potential reservoir for several pathogens including Campylobacter spp. (Studer et al., 1999). Therefore, the hardened envi-ronment around the stables need to be cleaned as well. The findings of latter study also show the importance of taking hygienic measures before entering the poultry house (see above).

Materials and Measures Between Compartments (Weight: 7). Stable equipment that is used on the entire herd can also cause the spread of pathogens. A brush and a shovel can easily be contaminated with feces that can contain infectious material. It is therefore recom-mended to use different equipment in different sections and make sure that this equipment is clearly recog-nizable (different colors) to avoid moving equipment from one section of the herd to another. The same rule can be applied to clothing, for exactly the same rea-son. Also, washing and disinfecting the hands between stables reduces the risk of transmission of pathogens.

Preliminary Results of the Scoring SystemOut of 41 broiler farms, 15 farmers (37%) agreed to

participate in this study. During the study, 2 farmers sold their poultry farm and therefore were not audited twice. Reasons for nonparticipation were: not interested (32%), no time (7%), and not willing for several other reasons (24%). The 15 participants were distributed throughout Flanders.

However, the distribution of the participating broiler farms did not match the proportional spread of broil-er farms in Flanders. For example, in the pilot group, only 1/15 broiler farms was situated in West Flanders, whereas according to Viaene (2012) 221/590 broiler farms are situated in this region.

The majority of the questions were easily understood by the farmers, and only some minor vocabulary ad-justments were made to improve the clarity of the ques-tions.

On average, the external biosecurity score (64/100) was lower than the internal biosecurity score (73/100) during the first biosecurity audit (Table 2). Within the category of external biosecurity, the following 3 sub-categories had the lowest average scores: supply of ma-terials (43/100), feed and water supply (44/100), and off-farm movement of live animals (58/100). In the subcategories of the external biosecurity, infrastructure and biological vectors (81/100), entrance of visitors and personnel (75/100), and location of the farm (74/100) obtained the highest average scores. Within internal biosecurity, disease management (81/100) obtained the highest score, whereas cleaning and disinfection (67/100) had the lowest score.

The implementation of extra biosecurity measures based on the given advice after audit 1 resulted in an overall improvement of the biosecurity scores during audit 2 (Table 2). Although the external biosecurity score improved on average by 5 points (69/100), it re-mained lower than the internal biosecurity score, which

2748 GELAUDE ET AL.


improved on average by 4 points (77/100). The high-est increase in biosecurity scores was found for the fol-lowing subcategories: purchase of 1-d-old chicks and materials and measures between compartments. Both subcategories gained 8 points.

Technical Performance and Antimicrobial Use

During the study 2 out of the 15 participating broiler farms did not complete the entire study; therefore, only the results of the 13 remaining broiler farms were taken into account. The data on technical performance during the 2 audits are presented in Table 3.

At the time of the second audit, the mortality dur-ing the first week had risen from 1.08 to 1.27%, but the total mortality decreased from 3.54 to 3.05%. The average daily growth remained the same between the 2 audits (57 g/d), but the feed conversion decreased by 0.1 points. Consequently, the economical production ef-ficiency or PI increased by 14 points.

Also for AMU differences were found between the 2 audits. During the first audit, a large variation was found between the different broiler farms with regard to AMU. The lowest TI was seen on broiler farm 13 (TI = 21), whereas broiler farm number 9 had the highest AMU (TI = 337). The average TI at the time of the first audit was 192, this means that on average 192 out of 1,000 animals received one daily dose of antimi-crobial drugs. Another way to interpret the TI is that 19.2% of the total production time all birds were medi-cated. At the time of the second audit the AMU was reduced on 9 farms, resulting in an average TI equal to 136. This means that there was an average reduction of AMU with 29% (Table 4).

DISCUSSION

This study has attempted to develop a risk-based quantitative tool to measure the biosecurity level at broiler farms in a standardized and reproducible man-ner. The Biocheck.UGent scoring system enables us for the first time to quantify the biosecurity at herd level, taking into account all relevant aspects of biosecurity. In contrast to other biosecurity questionnaires in which no weights were given to the different measures, it is now possible to differentiate between high and low bios-ecurity farms based on the type of preventive measures that are applied and not only upon the amount of mea-sures. At the same time, the Biocheck.UGent scoring system can be used as a motivational and didactic tool for the farmer. Bottlenecks in the biosecurity manage-ment are highlighted, and by comparing the results of the farm to the national averages a farmer can bench-mark his situation. Benchmarking of results has already proven to increase the awareness of social issues (e.g., antimicrobial use in livestock) and to stimulate farm-ers to improve the current farm situation on their farm

(Onis E., 2013). Besides the possibility of benchmark-ing results, the website contains a lot of information concerning the different (sub)categories.

Despite the fact that the Biocheck.UGent scoring sys-tem and the associated weights are based on a thorough literature study, previous comparable exercises in pig production (Laanen et al., 2013), and the opinion of an expert panel, the attributed weights remain a subjec-tive estimation of the importance of the different pre-ventive measures. However, the scoring system can be seen as a valuable tool to monitor the biosecurity level of broiler farms over time. Different poultry farms can easily be compared with one another and each farm can be followed up in time when the same scoring system is used. If the biosecurity scoring system is used through-out the country, the biosecurity level could be mapped out and high risk areas for the spread of diseases iden-tified. This may be helpful in case of epidemic disease outbreaks and makes target surveillance possible.

The results obtained from the pilot group cannot be easily extrapolated to the region of Flanders because the pilot group only consists of 15 broiler farms. In addition, the distribution of the participating broiler farms do not match the proportional spread of broiler farms in Flanders. Therefore, a larger number of herds should be scored before good estimations of the average situations can be obtained. This effort will certainly be done in the near future for Belgium and likely also for other European countries.

Although broiler farms were selected on a voluntary basis, a large variation was found between the biosecu-rity scores of the different farms, showing that, despite the fact that the poultry production sector is some-times perceived as one of the most advanced sectors of animal production in relation to biosecurity, there is still a lot of improvement possible (Table 2). Similar results were found in the study of Van Steenwinkel et al. (2011). In general, the internal biosecurity scores was higher than the external biosecurity scores, con-trary to the porcine livestock industry where external biosecurity scores (65/100) are on average higher than the internal biosecurity scores (52/100; Laanen et al., 2013). For poultry, this difference between the external and internal biosecurity scores can be partly explained by the fact that there are less preventive measures for internal biosecurity in comparison with the external bi-osecurity. Therefore, high scores reaching the maximum score of 100/100 can be more easily obtained for inter-nal biosecurity.

This innovative tool allows us to study, in a quan-titative manner, the relationship between biosecurity, health, and production characteristics, as has recently also been done for pig production (Laanen et al., 2013). This type of study is of great importance to be able to demonstrate in an objective and quantitative manner the importance of biosecurity measures in preserving the health of animals. During this study, a substantial AMU reduction of 29% was obtained without having negative effects on the technical production results. The



technical results even improved because PI increased by 14 points. Although this improvement of production results and the reduction of AMU were obtained after optimizing biosecurity at the broiler farms, this does not mean that statistically significant relationships were found between biosecurity, health, and production characteristics. Due to the limited data set caused by the small number of participating broiler farms, only descriptive statistics were performed. However, the preliminary results shows a promising trend between biosecurity and AMU, and further research should be performed to investigate whether biosecurity can have a large effect on AMU or not.

REFERENCESAFSCA. 2012. AFSCA questionnaire. Accessed Jul. 2, 2013. http://

www.afsca.be/dierengezondheid/vogelgriep/_documents/vragen-lijstbioveiligheidtoelichting-nl-20120820.pdf.

Amass, S. F., and A. Baysinger. 2006. Swine disease transmission and prevention. Pages 1075–1098 in Diseases of Swine. 9th ed. B. E. Straw, J. J. Zimmerman, S. D’Allaire, and D. J. Taylor, ed. Blackwell Publishing Ltd., Oxford, UK.

Barcelo, J., and E. Marco. 1998. On farm biosecurity. Pages 129–133 in Proceedings of the 15th IPVS Congress, Birmingham, UK.

Beek, J. 2008. Biosecurity at pig farms, an attempt to quantify through a scoring system. Thesis. Faculty of Veterinary Medi-cine, Ghent, Belgium.

Boes, J., L. Nersting, E. M. Nielsen, S. Kranker, C. Ene, H. C. Wachmann, and D. L. Baggesen. 2005. Prevalence and diversity of Campylobacter jejuni in pig herds on farms with and without cattle or poultry. J. Food Prot. 68:722–727.

Bradburry, J. M., and C. Morrow. 2008. Avian Mycoplasmas. M. Patisson, P. F. McMullin, J. M. Bradburry, and D. J. Alexander, ed. Pages 220–234 in Poultry Diseases, 6th ed. Saunders Elsevier, Beijing, China.

Butcher, G. D., and R. D. Miles. 2012. Disease prevention in com-mercial poultry (CR1079). University of Florida IFAS Exten-sion. Accessed Jul. 2, 2013. http://edis.ifas.ufl.edu/pdffiles/VM/VM01100.pdf.

Capua, I., and S. Marangon. 2006. Control of avian influenza in poultry. Emerg. Infect. Dis. 12:1319–1324.

Carey, J. B., J. F. Prochaska, and J. S. Jeffrey. 2005. Poultry Facility Biosecurity (L-5182). AgriLife Extension. Accessed Jul. 2, 2013. http://repository.tamu.edu/bitstream/handle/1969.1/87791/pdf_823.pdf?sequence=1.

Cserep, T. 2008. Vaccines and vaccination. Page 66 in Poultry Dis-eases. 6th ed. M. Patisson, P. F. McMullin, J. M. Bradburry, and D. J. Alexander, ed. Saunders Elsevier, Beijing, China.

Eijck, I., and J. De Wilt. 2009. Co-innovation program farm ani-mals and reduction of antimicrobial usage. Accessed Feb. 7, 2013. http://www.innovatienetwerk.org/nl/bibliotheek/rap-porten/438/CoinnovatieprogrammaLandbouwhuisdierenenAnti-bioticaReductieCLEAR.

Evans, S. J., and A. R. Sayers. 2000. A longitudinal study of Cam-pylobacter infection of broiler flock in Great Britain. Prev. Vet. Med. 46:209–223.

Fèvre, E. M., B. M. C. Bronsvoort, K. A. Hamilton, and S. Cleave-land. 2006. Animal movements and the spread of infectious dis-eases. Trends Microbiol. 14:125–131.

Fritzemeier, J., J. Teuffert, I. Greiser-Wilke, Ch. Staubach, H. Schlüter, and V. Moennig. 2000. Epidemiology of classical swine fever in Germany in the 1990s. Vet. Microbiol. 77:29–41.

Fussing, V., K. Barfod, R. Nielsen, K. Møller, J. P. Nielsen, H. C. Wegener, and M. Bisgaard. 1998. Evaluation and application of ribotyping for epidemiological studies of Actinobacillus pleuro-pneumoniae in Denmark. Vet. Microbiol. 62:145–162.

Gore, S. M. 1987. Biostatistics and the Medical Research Council. MRC News 35:19–20.

Graham, J. P., J. H. Leibler, L. B. Price, J. M. Otte, D. U. Pfeiffer, T. Tiensin, and E. K. Silbergeld. 2008. The animal-human inter-face and infectious disease in industrial food animal production: Rethinking biosecurity and biocontainment. Public Health Rep. 123:282–299.

Hartung, J., and J. Schulz. 2007. Risks caused by bio-aerosols in poultry houses. International Conference: Poultry in the 21st century, avian influenza and beyond, Bangkok. Accessed Jul. 2, 2013. http://www.fao.org/AG/AGAINFO/home/events/bang-kok2007/docs/part2/2_10.pdf.

Hege, R., W. Zimmermann, R. Scheidegger, and K. D. C. Stärk. 2002. Incidence of reinfections with Mycoplasma hyopneumoniae and Actinobaillus pleuropneumoniae in pig farms located in re-spiratory-disease-free regions of Switzerland—Identification and quantification of risk factors. Acta Vet. Scand. 43:145–156.

Hermans, P. G., and K. L. Morgan. 2007. Prevalence and associated risk factors of necrotic enteritis on broiler farms in the United Kingdom; a cross-sectional survey. Avian Pathol. 36:43–51.

Jeffrey, J. S. 1997. Biosecurity for poultry flocks. Poultry fact sheet N°26. Accessed Jul. 2, 2013. http://animalscience.ucdavis.edu/avian/pfs26.htm.

Kapperud, G., E. Skjerve, E. Vik, K. Hauge, A. Lysaker, I. Aalmen, S. M. Ostroff, and M. Potter. 1993. Epidemiology investigation of risk factors for Campylobacter colonization in Norwegian broiler flocks. Epidemiol. Infect. 111:245–255.

Kouwenhoven, B., F. G. Davelaar, and J. Van Walsum. 1978. Infec-tous proventriculitis causing runting in broilers. Avian Pathol. 7:183–187.

Laanen, M., J. Beek, S. Ribben, F. Vangroenweghe, D. Maes, and J. Dewulf. 2010. Bioveiligheid op varkensbedrijven: Ontwikkel-ing van een online scoresysteem en de resultaten van de eerste 99 deelnemende bedrijven. Vlaams Diergeneeskundig Tijdschrift 79:302–306. (In Dutch).

Laanen, M., D. Persoons, S. Ribben, E. de Jong, B. Callens, M. Strubbe, D. Maes, and J. Dewulf. 2013. Relationship between bi-osecurity and production/antimicrobial treatment characteristics in pig herds. Vet. J. 198:508–512.

Liljebjelke, K. A., C. L. Hofacre, T. Liu, D. G. White, S. Ayers, S. Young, and J. J. Maurere. 2005. Vertical and horizontal trans-mission of Salmonella within integrated broiler production sys-tem. Foodborne Pathog. Dis. 2:90–102.

Lister, S. A. 2008. Biosecurity in poultry management. M. Patisson, P. F. McMullin, J. M. Bradburry, and D. J. Alexander, ed. Pages 48–65 in Poultry Diseases. 6th ed. Saunders Elsevier, Beijing, China.

McDowell, S. W. J., F. D. Menzies, S. H. McBride, A. N. Oza, J. P. McKenna, A. W. Gordon, and S. D. Neill. 2008. Campylobacter spp. in conventional broiler flocks in Northern Ireland: Epidemi-ology and risk factors. Prev. Vet. Med. 84:261–276.

McQuiston, J. H., L. P. Garber, B. A. Porter-Spalding, F. W. Hahn, S. H. Pierson, S. H. Wainwright, D. A. Senne, T. J. Brignole, B. L. Akey, and T. J. Holt. 2005. Evaluation of risk factors for the spread of low pathogenicity H7N2 avian influenza virus among commercial poultry farms. J. Am. Vet. Med. Assoc. 226:767–772.

Meroz, M. and Y. Samberg. 1995. Disinfecting poultry production premises. Revue scientifique et technique (Office International des Epizooties) 14:273–291.

Morton, B. 2007. Vaccines and animal welfare. Revue scientifique et technique (Office International des Epizooties) 26:157–163.

Ninomiya, A., A. Takada, A. Okazaki, K. F. Shortridge, and H. Kida. 2002. Seroepidemiological evidence of avian H4, H5 en H9 influenza A virus transmission to pigs in southeastern China. Vet. Microbiol. 88:107–114.

Onis, E. 2013. Reduction of antimicrobial use in the broiler industry. GD Pluimvee 52:5–7. (In Dutch).

Peiris, J. S., Y. Guan, D. Markwell, P. Ghose, R. G. Webster, and K. F. Shortridge. 2001. Cocirculation of avian H9N2 and contem-porary “human” H3N2 influenza A viruses in pigs in southeastern China: Potential for genetic reassortment? J. Virol. 75:9679–9686.

Rajkowski, K. T., S. Eblen, and C. Laubauch. 1998. Efficacy of washing and sanitizing trailers used for swine transport in reduc-tion of Salmonella and Escherichia coli. J. Food Prot. 61:31–35.

2750 GELAUDE ET AL.


Refrégier-Petton, J., N. Rose, M. Denis, and G. Salvat. 2001. Risk factors for Campylobacter spp. Contamination in French broiler-chicken flocks at the end of the rearing period. Prev. Vet. Med. 50:89–100.

Siekkinen, K. M., J. Heikkilä, N. Tammiranta, and H. Rosengren. 2012. Measuring the costs of biosecurity on poultry farms: A case study in broiler production in Finland. Acta Vet. Scand. 54:12.

Sims, L. D. 2007. Risks associated with poultry production systems. International Conference: Poultry in the 21st century, avian influ-enza and beyond, Bangkok. Accessed 2/7/2013.http://www.fao.org/AG/againfo/home/events/bangkok2007/docs/part2/2_1.pdf.

Studer, E., J. Luthy, and P. Hübner. 1999. Study of the presence of Campylobacter jejuni and C. coli in sand samples from four Swiss chicken farms. Res. Microbiol. 150:213–219.

Tablante, N. L. 2008. Biosecurity: A vital key to poultry disease prevention. Poultry Perspectives 8:2–4.

Thomas, M. E., A. Bouma, H. M. Ekker, A. J. M. Fonken, J. A. Stegeman, and M. Nielen. 2005. Risk factors for the introduction of high pathogenicity Avian Influenza virus into poultry farms during the epidemic in the Netherlands in 2003. Prev. Vet. Med. 69:1–11.

Timmerman, T., J. Dewulf, B. Catry, B. Feyen, G. Opsomer, A. de Kruif, and D. Maes. 2006. Quantification and evaluation of antimicrobial drug use in group treatments for fattening pigs in Belgium. Prev. Vet. Med. 74:251–263.

Truscott, J., T. Garske, I. Chis-ster, J. Guitain, D. Pfeiffer, L. Snow, J. Wilesmith, N. M. Ferguson, and C. Ghani. 2007. Control of highly pathogenic H5N1 avian influenza outbreak in the GB poultry flock. Proceedings of the Royal Society: Biological Sci-ence 274:2287–2295.

van de Giessen, A. W., B. P. M. Bloemberg, W. S. Ritmeester, and J. J. H. C. Tilburg. 1996. Epidemiological study on risk factors and risk reducing measures for campylobacter infections in Dutch broiler flocks. Epidemiol. Infect. 117:245–250.

van de Giessen, A. W., J. J. H. C. Tilburg, W. S. Ritsmeester, and J. Van der Plas. 1998. Reduction of Campylobacter infections in broiler flocks by application of hygiene measures. Epidemiol. Infect. 121:57–66.

Van Poucke, E., S. Buijs, F. Tuyttens, L. Maertens, A. Verspecht, F. Vanhonacker, G. Van Huylenbroeck, W. Verbeke, C. Vangestel, and L. Lens. 2010. ILVO Eindverslag: Optimale bezettingsdich-theid van landbouwhuisdieren gehuisvest in groep, in relatie tot ruimtelijke behoeften, bedrijfsrendabiliteit en maatschappelijke acceptatie. (In Dutch). Accessed Jul. 2, 2013. http://www.ilvo.vlaanderen.be/NL/Onderzoek/Veehouderijendierenwelzijn/Kle-inveehouderij/Optimalebezettingsdichtheid/tabid/464/dnnprint-mode/true/language/nl-BE/Default.aspx?SkinSrc=%5BL%5DSkins%2FDier%2Fprint&containerSrc=%5BL%5DContainers%2FDier%2Filvo.

Van Steenwinkel, S., S. Ribbens, E. Ducheyne, E. Goossens, and J. Dewulf. 2011. Assessing biosecurity practices, movements and densities of poultry sites across Belgium, resulting in different farm risk-groups for infectious disease introduction and spread. Prev. Vet. Med. 98:259–270.

Vangroenweghe, F., S. Ribbens, T. Vandersmissen, J. Beek, J. Dewulf, D. Maes, and F. Castryck. 2009. Hygiene protocol–Hy-giene lock (In Dutch). Pages 115–116 in Keeping Pigs Healthy. 1st ed. F. Vangroenweghe, ed. DCL Print & Signs, Zelzate, Bel-gium.

Viaene, J. 2012. Overzicht van de Vlaamse pluimvee-en konijnen-houderij in 2010–2011. Accessed Jul. 2, 2013. http://www.age-con.ugent.be/vepek/overzicht2010_2011.pdf.

Vieira, A. R., C. L. Hofacre, J. A. Smith, and D. Cole. 2009. Hu-man contacts and potential pathways of disease introduction on Georgia poultry farms. Avian Dis. 53:55–62.

Wall, P. G., D. Morgan, K. Lamden, M. Griffin, E. J. Threlfall, L. R. Ward, and B. Rowe. 1995. Transmission of multi-resistant strains of Salmonella typhimurium from cattle to man. Vet. Rec. 136:591–592.

Windsor, R. S., and J. R. Simmons. 1981. Investigation into the spread of swine dysentery in 25 herds in East Anglia and as-sessment of its economic significance in five herds. Vet. Rec. 109:482–484.

Wolgemuth, R. 1989. Control of mealworm (Alphitobius diaperinus Panz) in poultry housing. Pages 18–20 in Proc. Jubilee Interna-tional Symposium. Stockholm, Sweden.



Documents

Biocheck.UGent: A quantitative tool to measure … - A...measures on poultry farms ... the foundation for biosecurity of the entire production ... their associated preventive measures