economic evaluation of monitoring and controlling

Economic evaluation

of monitoring and controlling Salmonella in egg laying flocks

Student J.F.W. John Nouwen Registration number 870916-610-070 Supervisor Dr. Ir. H. Henk Hogeveen Business Economics Group, WUR Course BEC-80433 Period March 2011 – January 2013

Economic evaluation of monitoring and controlling Salmonella in egg laying flocks

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Foreword This research report is the Msc. Thesis of John Nouwen, Master student Management and Economics of the University of Wageningen. This research report is achieved with help of the department: Business Economics Group (BEC). In this research, several people contributed and hereby I want to thank these people for the excellent cooperation. In particular, I want to thank Dr. Ir. H. Hogeveen for the support of this research and educational period. In the research, an economic evaluation of the monitoring and controlling system of Salmonella by laying flocks will be evaluated. We hope to show you an understandable and objective view of the costs and benefits of monitoring and controlling Salmonella in egg laying flocks, by the four different intervention scenarios (heat treatment, cull flock, destroy eggs and do nothing).


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Abstract In order to investigate the total costs of monitoring and controlling Salmonella enteritidis (Se) and Salmonella typhimurium (St) in egg laying flocks, a model was developed. The model is based on an existing model developed by Animal Health and Veterinary Laboratories Agency (AHVLA) in the United Kingdom. The model is developed for the laying sector in the United Kingdom and the Netherlands by the creation of a static and deterministic spreadsheet model. Deterministic functions are used to give a better view of uncertain and sensible parameters. The model support decision making for farmers and for policymakers; when to cull a Se or St infected flock on an economical basic or for human health considerations. Se and St belong to the most common food-borne bacterial diseases in the world. To prevent human salmonellosis related to Se or St infected laying hens, there were developed four intervention scenarios in the model. These intervention scenarios are: heat treatment, cull Se or St infected hens, destroy eggs from Se or St infected hens and a do nothing scenario. The biggest differences in the outcome of the model between the UK and the NL could be linked to differences in Se and St prevalence by laying hens, percentage of hens housed in different housing systems and costs human salmonellosis. Overall prevalence of Se and St were 0,28 and 1,45 for the UK and the NL respectively. The results of the model show that the intervention, cull all Se and St infected hens, is the most effective intervention scenario to reduce the number of human salmonellosis. Cull all Se and St infected hens is also the best intervention scenario for farmers with a free-range and bio housing system with an economical perspective. But farmers with a cage or barn housing system have economically more benefit by keeping the Se or St infected hens for the remaining laying period and treat the eggs with a heat treatment.


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Content

Foreword ................................................................................................................................................. 2

Abstract ................................................................................................................................................... 4

Content .................................................................................................................................................... 6

1. Introduction ......................................................................................................................................... 8

2. Background ........................................................................................................................................ 10

2.1. Salmonella .................................................................................................................................. 10

2.1.1. Salmonella enteridis and Salmonella typhimurium ............................................................. 10

2.2. Monitoring .................................................................................................................................. 11

2.2.1. Monitoring system .............................................................................................................. 11

2.2.2. Different samples ................................................................................................................ 12

2.2.3. Influencing factors to detect Salmonella ............................................................................. 12

2.3. Intervention scenarios ................................................................................................................ 14

2.3.1. Vaccination .......................................................................................................................... 14

2.3.2. Canalization ......................................................................................................................... 14

2.3.3. Heat treatment .................................................................................................................... 14

2.3.4. Destroy eggs ........................................................................................................................ 15

2.3.5. Cull flock .............................................................................................................................. 15

2.3.6. Restriction ........................................................................................................................... 15

2.3.7. Medication .......................................................................................................................... 15

3. Situation in the United Kingdom and the Netherlands ..................................................................... 16

3.1. Supply chain laying sector .......................................................................................................... 16

3.2. United kingdom .......................................................................................................................... 18

3.2.1. Laying sector ........................................................................................................................ 18

3.2.2. Salmonella in UK .................................................................................................................. 18

3.3. The Netherlands ......................................................................................................................... 19

3.3.1. Laying sector ........................................................................................................................ 19

3.3.2. Salmonella NL ...................................................................................................................... 20

4. Materials and method ....................................................................................................................... 22

4.1. Model ......................................................................................................................................... 22

4.1.1. Economic evaluation ........................................................................................................... 22

4.1.2. Baseline scenario ................................................................................................................. 23


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4.2. Parameters and calculations ...................................................................................................... 24

4.3. Sensitivity analysis ...................................................................................................................... 29

5. Results ............................................................................................................................................... 32

5.1. Cost-effectiveness ...................................................................................................................... 32

5.2. Costs intervention scenarios ...................................................................................................... 34

5.2.1. Baseline scenario ................................................................................................................. 34

5.2.2. Other intervention scenarios .............................................................................................. 34

5.2.3. Costs human health ............................................................................................................. 35

5.3. Sensitivity ................................................................................................................................... 36

5.4.The model as a tool ..................................................................................................................... 38

5.5. Specification of the costs............................................................................................................ 39

6. Discussion and conclusions ............................................................................................................... 42

References ............................................................................................................................................. 46

Appendix ................................................................................................................................................ 48

Appendix A: ‘general’ parameters ..................................................................................................... 48


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1. Introduction Food-borne illness is a significant public health problem with relatively high economic and social consequences (Altekruse and Swerdlow, 1996). The social and economic impact of food-borne illness is considerable, and Salmonellosis is one of the most common food-borne bacterial diseases in the world (Sockett and Roberts, 1991). The most common serotypes of Salmonella related to food-borne illness are Salmonella enteritidis (Se) and Salmonella typhimurium (St). Se and St are common pathogens of intestinal infections in humans. People and especially animals (poultry, pigs, cattle, reptiles and pets) may be carriers of the Salmonella bacteria (Thomas, 20120). By eating undercooked meat or eggs and poor hygiene, the bacteria spread rapidly. Salmonellosis in humans is generally characterized by diarrhea, abdominal cramps, fever, nausea and vomiting (Doyle et al., 2008). Farm animals and their products are considered to be a primary reservoir for pathogenic Salmonella in humans. There could be made distinction between Salmonella which are a risk for animal health and for human health. For example Salmonella gallinarium and Salmonella pullorum lead to disease and death in laying hens but does not harm human health (DGZ, 2012). While Se and St not directly affect the health of laying hens, they are a risk for human health. Se and St are not visible by laying hens and therefore it is more difficult to eliminate those two Salmonella serotypes. Eggs are important for the spreading of salmonellosis, particularly for Se (DEFRA, 2007). This serotype can pass through egg shells after eggs are laid. It also can infect the reproductive systems of hens and be deposited in the egg contents prior to egg shell formation. In the United Kingdom (UK), the Department for Environment Food and Rural Affairs (DEFRA) has set up a monitoring system to get an overview and to reduce the Salmonella serotypes (enteritidis and typhimurium) within the laying sector of domestic fowl (Gallus Gallus). More specifically they want to reduce the prevalence of Salmonellas of public health significance in flocks of domestic fowl on holdings in the UK producing eggs for human consumption at least to the target levels set out in European Commission (EC) regulation No 1168/2006 (DEFRA, 2010). The EC regulation No 1168/2006 means that every country within the EU has to reduce, with at least ten percent, the number of positive adult laying flocks with Salmonella compared with the previous year (Potkonjak, 2007). The poultry sector already made numerous preventive measures to assess the presence of Salmonella such as vaccination and hygiene improvements (Thomas, 2010). The number of human salmonellosis in the Netherlands is decreased from circa 150.000 in the period of 1980-1985 to circa 37.000 in the year 2007 (van Pelt et al., 2007). But still humans get ill by eating food which is contaminated with Salmonella. Outbreaks of Salmonella should therefore be traced back and if a flock of laying hens are infected, action must be taken. Actions which could be taken if a flock of laying hens are infected with Se or St are: cull infected flocks or ban eggs which are contaminated with Se or St for human consumption. However, for the whole egg industry there is the negative publicity from the public perception that eggs are linked to human salmonellosis. The risk associated public perception could translate in to a financial loss for the egg industry (Kinde et al., 1997). Alternatively, if the producer chooses to implement a Salmonella control program, there may be a reduced risk of human salmonellosis, improved consumer confidence and the industry will benefit from sustained product demand and financial gain. Implementing a Salmonella control program could be of great importance for the egg industry. In a commercial layer flock it is not always a fixed process of how to get contaminated and a contamination certainly increases production costs. There is few documentation and research done which studied the economic impact of a Salmonella control program. The limitations in estimating costs for a Salmonella control program can be explained by the many variations in flock sizes, age, type of housing and equipment, management practices, the number of humans infected with Se or St and the costs of human illness related to Se and St.


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In this study, a model is made to chart the financial consequences belonging to monitoring and controlling of Se and St in egg laying flocks and the costs of human illness. The model is based on an existing model developed by AHVLA. It was therefore decided to review the situation for the UK and to compare it with the situation in the NL. Finally, the model shows in which intervention scenario can be best invested to reduce the number of human salmonellosis caused by Se or St contaminated eggs.


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2. Background Before a detailed description will be given about the consequences of a contaminated flock with Se or St, or before making an economic evaluation of the different interventions to reduce human salmonellosis, different topics related to Salmonella will be described. The different topics will give more information of what Salmonella is, how Se and St could be monitored by the laying sector, and what kind of interventions there are to reduce the risk for human salmonellosis.

2.1. Salmonella

Salmonella is one of the most common foodborne bacterial diseases in the world, and is called after the American veterinarian, who discovered the bacteria; Daniel Elmer Salmon. Salmonella is primarily caused by improper handling and digestion of un(der)cooked food contaminated with a Salmonella bacteria. Approximately 85% of infections are caused by eating contaminated food, and 5% to 10% by direct contact with infected animals (Thomas, 2010). Salmonella can grow during improper storing of a product, at a temperature between 5°C and 47°C, with an optimum at 37°C, and by a pH between 4 and 8 (FEHD, 2004; Hmso, 1993). They are resistant against freezing and drying (Hmso, 1993), but could be actively destroyed by high temperature like pasteurization (FEHD, 2004). A number of sources have been identified as origin of the bacteria, such as eggs, meat and milk (Humphrey, 2000). Table eggs appeared to be the main food source associated with human salmonellosis (DEFRA, 2007). Salmonella is one of the largest causes of human illness, and it could lead to diarrhea, abdominal cramps, fever, nausea, vomiting and could even lead to death (EFSA, 2010). The effects of salmonellosis are mostly visible after 12-24h eating the contaminated product or direct contact with Salmonella. Young children, pregnant women, older people and people with low resistance are most sensitive for salmonellosis. Salmonella is part of a genus of rod-shaped bacteria, motile, non-spore forming and Gram-negative organism that are part of the natural flora of poultry, pigs, cattle, reptiles and pets (Thomas, 2010). The genus Salmonella is actually a single species; Salmonella enterica. This species has about 1500 different serotypes. Therefore, usually the serotype name is used. The most common serotypes are: Se and St.

2.1.1. Salmonella enteridis and Salmonella typhimurium

There are a lot of Salmonella types which can cause human salmonellosis, but the most common are Se and St. Se may often produce clinical disease by laying hens at an age of six weeks and in adult laying hens. The symptoms of Se in laying hens are: depression, reluctance to move, diarrhea, and uneven growth, but in most of the hens no symptoms will be seen (Wray et al., 1996). Salmonella enteridis contains a lot of serotypes which could be identified in eggs. Se can pass through egg shells after eggs are laid and can also infect the reproductive system of hens and be deposited in the egg contents prior to egg shell formation. In the UK and in the NL, the most common phage type (PT) responsible for human salmonellosis has been Se PT4 (Fisher, 2004; Gillespie et al., 2005). Other upcoming phage types of Se are PT1 and PT14B. Salmonella typhimurium is comparable with the other Salmonella type: Se (Carrique-Mas et al., 2007). Small differences can be found in the carriage of the bacteria in the reproductive organs of the hen, which occur in a lesser extent with St. St causes as its name already suggests a typhoid-like disease in mice and is normally not fatal (Bennet and Ijpelaar, 2003). The symptoms by humans who are infected with St are similar to the symptoms of Se and also the control measures to reduce the risk for human salmonellosis are identical.


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2.2. Monitoring

Monitoring is an effective method to get insight in the prevalence of Salmonella in laying hens (EFSA, 2010). The EC has set regulations to monitor Salmonella at the laying sector, so that the monitoring system is more or less equal in all European countries. This section will give information how a monitoring system works in the EU, the different samples and a quick overview of influencing factors to determine whether a flock is Se or St infected or not.

2.2.1. Monitoring system

The monitoring system for Salmonella in laying hens is mostly driven by human health considerations. Monitoring Salmonella is important to give insight in possible infections of Salmonella by laying hens. Thereby it is relative unimportant to look at the Salmonella status of one hen; the goal is to know whether a flock is infected or not. To know whether a flock is infected or not, samples will be taken and tested. Different kind of samples exists, namely: faeces, dust, litter, boot swabs, cloacal and egg samples (eggshell and egg content). A flock is infected when at least one sample from the laying hens or in the laying house is contaminated with Salmonella. Insight in infected laying flocks can give opportunities to take actions and reduce the change of human illness (EFSA, 2010). To prevent that table eggs are contaminated with Se or St, monitoring has to take place at least at two links within the chain (EFSA, 2010). The two links are: the rearing period and the laying period. From 2008, the EU set a control program by the regulation of EC No. 2160/2003 for Salmonella in layers for rearing and laying flocks (EFSA, 2010). Exceptions are the producers of eggs for private domestic use, or suppliers of small quantities of eggs to final consumers, or who supply small quantities to local retailers that supply directly to the final consumers. Another exception is applicable for farmers with less than 1,000 hens, but they still are required to carry out the routine sampling during the laying period if they do not belong to the category mentioned above (EFSA, 2010). Samples of faeces, dust or swabs will be taken in both periods, rearing and laying. The type of sample depends on the housing system. During the rearing period samples will be taken by day-old chicks and two weeks before the hens are transferred to the laying farm, approximately at an age of 16 weeks (see Table 1). During the laying period samples will be taken when the hens are established a few weeks on the laying farm, every 15 weeks after the previous sample is taken and a maximum of three weeks before the hens will be slaughtered. Table 1: Number of samples which have to be taken at the rearing and laying flocks

Date of taking sample Number and type of sample

Rearing period (0-18weeks) Day-old chicks 1 chick box liner per 500 chicks, max 10 All carcasses, max 60

2 weeks before point of lay/move to layer unit

2 x boot swabs or 2 x composite faeces

During lay 22-26 weeks of age 2 x pairs of boot swabs or 2 x 150g composite faeces

Thereafter every 15 weeks 2 x pairs of boot swabs or 2 x 150g composite faeces

Max. 3 weeks before slaughter 2 x pairs of boot swabs or 2 x 150g composite faeces


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When a flock tests positive for Salmonella, a follow-up test will be carried out. First the kind of Salmonella type (is it Se or St) will be determined, thereafter the specific serotype of Salmonella will be determined. At the same time, verification will be carried out by a control body (like the Animal Health Service in the Netherlands). If the outcome of the verification is still positive, the flock is than actually notified as infected. A farmer can choose to authenticate further the status of the laying flock at his own costs as often as the farmer wants. When verification results negative, the flock will be treated as uninfected and falls into the normal monitoring process again.

2.2.2. Different samples

The regulation of the EC No. 2160/2003 prescribes that during the rearing and laying period samples have to be taken (Carrique-Mas and Davies, 2008). Most common samples are faeces and boot swabs. For verification mostly cloacal swabs are used. There exist more different samples, like dust samples and blood samples. Distinction could be made between two groups of sampling, namely samples from the hen itself and from the environment (laying house). The group of samples of the hen itself includes blood and cloacal samples, the other group includes samples like faeces, litter, dust and boot swabs. Below, the two different groups of samples are briefly discussed (Carrique-Mas and Davies, 2008). Samples from the hen itself, like cloacal swabs or blood are relatively insensitive. Insensitive because a lot of variables can influence this sensitivity. For instance, the cloacal swabs will normally be taken from a small number of hens, and often these swabs are pooled together. The peak and level of excretion in the hen depends on the timing of entry of the infection, the type of Salmonella, age and stage of production of the flock. An infected hen shed Salmonella in their faeces intermittently. Mostly a hen stops shedding Salmonella bacteria after a three weeks (Shivaprasad, 1990; Gast et al., 2005; EFSA, 2010). But the prevalence and situation (shedding of Se or St) can change over the lifetime of a hen, so hens start shedding Se or St again after a stressful environment, moulting, transportation, etc..

Environmental samples, like: faeces, litter, dust or boot swabs show when a Salmonella contamination is present in the environment (laying house). An environmental sample is more sensitive to discover Salmonella than sampling a limited number of individual hens (Takumi et al., 2008). (Fresh) faeces provide mostly an indication of a current infection while dust may also indicate a previous infection. Salmonella can survive almost a year in dust and for more than two years in dried faeces, litter and feed. Normally 1 gram (g) of faeces corresponds to one hen, one dust sample of 150g corresponds to 150g pooled faeces and one pair of boot swabs are as good as sampling 60 individual hens (Takumi et al., 2008). According to the report of Davies and Breslin (2004), it is economically almost impossible to set a monitoring system which has 100% detection sensitivity, but the preference goes out to take a dust sample combined with a faeces sample because sampling only faeces may fail to detect Salmonella in flocks that have passed the peak of infection but which may still produce contaminated eggs. Taking samples from the hen itself is more intensive and costly than taking an environmental sample (Takumi et al., 2008).

2.2.3. Influencing factors to detect Salmonella

A lot of factors can influence the detection of a possible infection by laying hens. Monitoring Salmonella gives a good overview of the prevalence of Salmonella by egg laying flocks, but it is sensitive to external factors. The different factors will be explained in this section. 2.2.3.1. Seasonality Seasonality can influence the prevalence of Salmonella in a laying flock. Salmonella grows better in a warmer climate. Various reports advise to store eggs at a constant temperature which may not rise


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above the 21°C, with optimal growth circumstances of Salmonella at 37°C. It would be obvious that Salmonella could be more common (in the environment as in the hen itself) in months with a higher temperature, like the summer months. Several EFSA reports stated that seasonality plays a small role in Europe, but even then St is 1.6 times more common in summer than in spring. While for Se the number of cases appeared to be 3 times higher in summer than in spring. Figure 1 shows that the number of human salmonellosis is decreasing the last four years and a similar result could be expected for the relation between human salmonellosis and the prevalence of Se and St in a laying flock. What deserves more the attention is the fluctuation of human salmonellosis throughout the year, and where we see a peak in the summer months (EFSA, 2007; EFSA, 2009a; EFSA, 2010b).

Figure 1: Trend of seasonality and number of human salmonellosis in EU and EEA/EFTA countries (ecdc, 2011) 2.2.3.2. Age of laying hen In the current monitoring system, sampling in laying hens will take place for the first time at an age of 22-26 weeks and after that every fifteen weeks. At data (from the PPE and in reports of EFSA, 2010; Garber et al., 2003; van de Giessen et al., 2006; Wales et al., 2007) flocks mostly detected to be Salmonella positive at an age older than 46 weeks. This may be related to the Salmonella vaccine whose strength begins to reduce after that number of weeks or to the fact that laying hens have a low resistance at an older age. 2.2.3.3. Housing system The prevalence within a flock is influenced by the way hens are housed. Cage flocks have an increased risk to be contaminated with Salmonella, mainly Se, according to the reports of Methner et al., 2006; Snow et al., 2007; Much et al., 2007. However it is not clear where the difference lies. Is it because of differences in sampling (faeces versus dust or boot swabs), the housing equipment, the environment or management. Another report of Mollenhorst et al., 2005 stated that alternative housing systems (non cage) are more often contaminated with Salmonella. It is thus unclear what kind of influence a housing equipment has in relation to the Salmonella infection (van Hoorebeke, 2010). Hence, it is almost impossible to make differences between the prevalence of different housing systems. 2.2.3.4. Flock size Flock size is often closely related to the type of housing system. Cage housing systems are mostly related to larger flocks than a non-cage housing system. Related to the difference in type of housing system, it is unclear what kind of impact flock size has to the prevalence of Salmonella. In large cage houses or large non-cage houses it is more difficult to detect Salmonella compared to small laying houses (FSA, 2007). Another consideration, which mainly takes place in the UK, is that large flocks are


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more likely to be held on large holding with multi-age production which could increase the change of an infection (DEFRA, 2010). And it is likely that when one flock is infected on a holding, other flocks on that holding will be infected too (Carrique-Mas et al., 2008).

2.3. Intervention scenarios

Positive eggs can be a risk for human health. By monitoring the rearing and laying flocks, we get insights in when, how many, and where flocks are infected. But monitoring itself does not decrease the public health risk of salmonellosis. Therefore control measures are needed. Salmonella can be controlled by several measures. In this section the different interventions are described.

2.3.1. Vaccination

In the United Kingdom and in the Netherlands most laying hens are vaccinated against Salmonella (PPE, 2009). Vaccination has been seen as an effective prevalence reduction method, especially if the flock prevalence is high (EFSA, 2010). For example in Belgium where after vaccination in 2004 the laboratory confirmed cases of human salmonellosis dropped down from 12.894 in 2003 to 3.831 in 2008 (Collard, 2008; EFSA, 2010). It does not mean that a vaccinated hen is fully protected against Salmonella, it can still happen that a vaccinated flock becomes Salmonella contaminated when laying hens are placed in an environment where Salmonella is present. An additional advantage is that vaccinated hens reduce faecal shedding, ovarial transmission, within flock prevalence , contamination of the environment and, most important, reduce the inter-egg contamination levels (Davies and Breslin, 2004). But vaccination of laying hens against Salmonella during the rearing period cost money. The expected costs to vaccinate one hen is 14 euro cents (Baltussen et al., 2007). However, in the NL, there is a subsidy that meets the costs of a Se and St vaccination. The subsidy, in the NL, is set at a maximum of 14 euro cents per vaccinated laying hen (www.pve.nl).

2.3.2. Canalization

Canalizing eggs, means making distinction between eggs from hens with or without Se or St infection. By monitoring laying flocks, the status of a specific flock is known. If the status of a flock is still positive after verification, the flock is actually notified as infected. Eggs from Salmonella infected hens may not be used anymore as table eggs and have to be destroyed or canalized. Canalization makes sure that possible Se and St contaminated eggs will not reach the end-consumer before the eggs are treated, and it so ensures that less people get ill from Salmonella related egg-products (Van de Giesen et al., 2010). Canalizing eggs produced from the flocks that are tested positive is an effective scenario to control human salmonellosis, but it cannot prevent that some contaminated eggs are sold as table eggs. This is due to the fact that there are positive flocks which are not detected yet or eggs which are sold as table eggs between the moment of monitoring and definitive detection which may take about a week. In the Netherlands, there is an average of 42.269 contaminated eggs per year which enter the market as table eggs if all laying flocks were kept in cages and 72.839 if all housing systems were barn (Takumi et al., 2008). But if no canalization was introduced, the number of Salmonella positive eggs would be quite higher (Van de Giesen et al., 2010).

2.3.3. Heat treatment

Heat treatment in combination with canalization is the most common scenario to reduce human salmonellosis. Heat treatment is normally the step after canalization. A heat treatment or pasteurization makes sure that Salmonella will not survive. Rules about treating eggs with a high temperature are described in a combination of two regulations: EC No 1168/2006 and EC No 1237/2007. The first regulation sets targets to reduce Salmonella prevalence in poultry and eggs. If a


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flock is Salmonella infected, the eggs may not enter the human consumption market (table eggs). Instead of entering the human consumption market the eggs of Se or St infected hens have to be treated in a manner that guarantees the elimination of Salmonella, stated in the second regulation. Both regulations do not describe hygiene requirement or requirement related to the heat treatment (temperature/ time combination) (EFSA, 2010).

2.3.4. Destroy eggs

Another scenario to reduce the risk for human salmonellosis related to possible contaminated eggs is to destroy all the eggs from Se or St infected hens. This scenario is not common, it is more expensive than a heat treatment, while the risk for human salmonellosis is not much different from the risk for human salmonellosis by a heat treatment.

2.3.5. Cull flock

A laying flock which is notified as Salmonella infected has lower profits than a flock which is not infected. If the cost to reduce the risk for human salmonellosis becomes too high, the farmer can choose to slaughter the hens in an early phase. Eggs originated from an infected flock decrease in value, because the eggs have to be treated and cannot serve as a table eggs anymore. Because of the loss of value for a contaminated egg, a farmer can choose to slaughter the laying hens at an early phase. The remaining value of the hens will be lost then and there are also costs to cull and incinerate a hen of 0,20 euro per hen. In the NL, there is a compensation established to cull an Se or St infected flock if they have the age of 28 weeks or younger (measured at the moment of the outcome of the verification). The compensation is determined on the basis of a table of values with a maximum of 3 euro per laying hen, condition here is that the flock is Se and St vaccinated (www.pve.nl).

2.3.6. Restriction

Other interventions to reduce the number of contaminated eggs for direct human consumption are restrictions. According to the research of EFSA, 2010 and HMSO, 1993 restrictions by putting the shelf life of table eggs on the packaging or on the egg itself should contribute to a decline in human salmonellosis. A shelf life of table eggs is important because the older an egg becomes, the more sensitive the extension and composition of the cuticle becomes. The egg shells are more easily infiltrated by bacteria (Nascimento et al., 1992; Messens et al., 2007; EFSA, 2010). Eggs should be consumed within 3 weeks of lay , also according the regulation 853/2004 on the hygiene of foodstuffs, and be stored under constant temperatures that do not exceed 20°C (food standards agency, 2007). This to avoid an increase of bacteriological properties and avoid condensation at the shell surface which lead to better living circumstances for Salmonella (HMSO, 1993).

2.3.7. Medication

Medication could be a way to reduce the prevalence of Salmonella in a laying flock. Antibiotics is a medication that is used to treat Salmonella infections. The cost of treating infected hens with antibiotics is irresistibly small compared to the costs of treating infected eggs with a heat treatment. Antibiotics are not allowed to recover a Salmonella infection (EFSA, 2010). If hens are tested positive for antibiotics during a verification test for Salmonella, the flock is automatically registered as contaminated (PPE, 2009).


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3. Situation in the United Kingdom and the Netherlands This report focuses on the situation in the United Kingdom (UK) and the Netherlands (NL). Those two countries are chosen because this report is based on previous work done in the UK and in collaboration with researchers from a British research institute (AHVLA). In the NL it was easier (language barrier and travel distance)to gather information from the literature and experts. Beside the language barrier and travel distance, the Netherlands has an upright position of reducing the number of Se and St infection by laying hens (EFSA, 2010). This section will subscribe more in detail the state of affairs concerning Salmonella in the laying sector in the UK and the NL. First the laying sector will be described in general, thereafter the specific information about the UK and NL are covered.

3.1. Supply chain laying sector

The supply chain of the laying sector is a long chain with a lot of stakeholders involved. It starts at the great grandparent birds and ends at the consumer. In Figure 2, the supply chain gives an overview of the different chains and shows that the breeding of a laying hen is a long route. The most important part of the supply chain regarding to this research is the parent breeding birds up till the processing of eggs. Parent breeding birds will lay eggs which become a laying hen. The eggs of the parent breeding birds will go to the hatchery, were they will be selected on gender and vaccinated after hatch. Day-old female hens will be transferred to the rearing farm, were they also will be vaccinated for Se and St. After the rearing period the hens, with an age of approximately 17/18 weeks, will be transported to the laying farm. In the laying period hens will produce eggs which will end up in a restaurant, supermarket to be eaten by the consumer. At the end of the laying period, the hens will be slaughtered.


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Figure 2: Supply chain laying sector


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3.2. United kingdom

3.2.1. Laying sector

The majority of hens presented in the UK are housed in a free range housing system, see Table 2. The UK can be split up into four regions: England, Wales, Scotland and Northern Ireland. In Table 2, it can be deduced that England has the highest share of the number of hens and number of holdings in the UK. In total, the UK has 3630 holdings with 38,8 millions laying hens. The total number of holdings in Table 2 are all holdings with at least one hen. In 2007 there were in the UK 1202 holdings with more than 1000 hens (DEFRA, 2007). Table 2: number of holdings and hens in the four regions of the UK (DEFRA, 2011)

Conventional cages

Enriched cages

Barn Free range

Bio Total

Number of holdings in England 232 47 222 1989 201 2691 Number of hens in England (in millions) 8,4 6,1 1,9 11,9 0,9 29,2 Number of holdings in Wales 10 0 15 304 29 358 Number of hens in Wales (in millions) 0,2 0 0,05 1,2 0,08 1,5 Number of holdings in Scotland 34 5 26 222 47 334 Number of hens in Scotland (in millions) 0,6 1,6 0,02 1,9 0,2 4,4 Number of holdings in Northern Ireland 57 12 20 140 17 247 Number of hens in Northern Ireland (in millions) 1,8 0,4 0,2 1,1 0,1 3,7

Total number of holdings in the United Kingdom 333 64 283 2655 294 3630 Total number of hens in the United Kingdom (in millions) 11 8,1 2,17 16,1 1,28 38,8

Hens in the UK are kept in different flock sizes. This was already visible in Table 2 where 3630 holdings exist with more than one hen and 1202 holdings with at least 1000 hens per holding. The proportion of the number of hens and number of flocks in the UK related to the size of a flock is more visible in Table 3. In England it is noticeable that a lot of people hold hens in smalls holding with less than 100 hens. On the other hand the large majority of the laying hens are kept on large holdings. Large flock sizes with 30.000 hens or more stand for 69,28% of the total number of hens held in the UK, while they represent only 0,5 % of the total number of holdings in the UK (DEFRA, 2007). Table 3: Number of hens and number of holdings in the UK related to the size of the farm

Size of a flock (number of hens)

1-99 100-499 500-999 1.000-2.999

3.000-4.999

5.000-9.999

10.000-29.999

>=30.000

Number of hens in UK (%) 1,30 0,68 0,45 1,82 2,47 7,41 16,59 69,28

Number of holdings in UK 26.238 920 186 277 178 305 294 148

3.2.2. Salmonella in UK

Se and St played an important role in the history of the number of human salmonellosis in the UK. Therefore several researches have been carried out the number of hens which are infected and the number of eggs which are Salmonella positive. In the UK, Se in poultry was first detected in 1987 (O’Brien, 1988). After that year the infection of Se in poultry increased rapidly, from 36 cases in 1986 to 401 in 1988 (Anon, 1989). Also human illness by salmonellosis increased dramatically, in England and Wales Salmonella infection in humans increased


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from 4.771 in 1986 to 15.427 in 1988 (Anon, 2001). The infection was associated with the consumption of eggs or eggs products and to a lesser extent of poultry meat (Coyle et al., 1988; Cowden et al., 1989) At the end of 1988, the government of the UK warned people that most of the eggs produced by laying hens were infected with Salmonella. The warning led to a drop in egg consumption with 90% (North and Gorman, 1990). The government tried to restore the public confidence in the safety of eggs by the introduction of package and control measures. The measurement meant that every flock had to be registered and monitored. If a flock became infected with Se or St, the hens were slaughtered at a small economic compensation for the farmer (Corkish, 1989). In 1993, there were already 287 layer flocks and 77 breeder flocks slaughtered, which cost the government around £ 5.5 million (Anon, 1993). But the total costs for slaughtering, sales losses, regulation measurements were estimated at £ 70 million (North and Gorman, 1990). The compulsory slaughter, registration and monitoring of infected hens with St ended in 1991 and for hens infected with Se it ended in 1993. Only for parent breeder flocks there were some exceptions, but infected hens were still slaughtered. In 1994, an inactivated vaccine against Se for poultry was introduced. The broiler breeder flocks were vaccinated very soon after the vaccine introduction, while the vaccine in commercial egg laying flocks was used from 1997 (Anon, 2001). The vaccine ensured that the prevalence of infection in eggs and human infection decreased. In 2001 a ‘new’ live vaccine against Se was developed and could be used within the drinking water which reduced the control costs considerably. However, at present, it is only licensed for use in commercial egg laying flocks, from the point of view that it is use in breeder flocks might interfere with the Salmonella monitoring program (Anon, 2002). In 2007, there were 42 incidents caused by layers in the UK during routine monitoring. Seventeen out of the 42 incidents consist of Se and 3 incidents were due to St (DEFRA 2007). In the research of the Food Standards Agency, there were 1.588 pooled samples of six eggs collected from 1.567 catering premises in England, Wales, Scotland and Northern Ireland. Out of the 1.588 pooled samples, there were 6 pooled samples found to be Salmonella positive. The contamination of Salmonella was in most cases found on the shell of the egg, and in one case the contamination was found in the content of the egg, notably a dirty egg. At five pooled samples the Salmonella type enteritidis was found and in three of the five samples it was the specific Se type PT 4. These outcomes result in a prevalence of 0,38% of having a contaminated egg with Salmonella, 0,31% that the egg is contaminated with Se and 0,19% that the egg is contaminated with Se PT4. Another report of the survey of Salmonella contamination in UK produced shell eggs on retail sale found out that the prevalence rate of Salmonella in consumption eggs was 0,34% (FSA, 2007). This 0,34 % consists largely of Se (0,27%) and 0,11% out of phage type PT4. The estimated individual egg prevalence was 0,06%. The difference between the prevalence of 0,34% and 0,06% could be explained by the assumption that the cross-contamination occurs by testing pooled samples on Salmonella. The research also found out that there was no significant difference in prevalence of Salmonella between the four regions of the UK: England, Wales, Scotland and Northern Ireland.

3.3. The Netherlands

3.3.1. Laying sector

The Netherlands have 1097 holdings with more than 1.000 hens per flock and houses in total 31,4 million laying hens (PVE, 2009). This number of flocks has not always been constant. Farm enlargement plays an important role in the Dutch intensive poultry sector to compete and ensure continuity. This tendency we could also see in Table 4, where the number of small flocks (1.000-


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4.999) decreases and the number of large flocks ( >50.000) increases. Most flocks have a flock size between the 20.000 and 50.000 hens, because this is normally the average farm size (PVE, 2009). Table 4: number of flocks divided to the number of hens per flock in the Netherlands

Number of hens per flock 2000 2005 2008 2009 2010

> 50.000 174 138 156 159 180

20.000 - 50.000 301 360 381 408 420

10.000 - 19.999 289 301 273 268 246

5.000 - 9.999 286 245 169 152 156

1.000 - 4.999 326 178 128 110 112

Total 1376 1222 1107 1097 1114

Figure 3 shows that flock sizes also differ between housing systems. Cage housing system have greater flock sizes than bio housing systems. The number of flocks and hens housed in cage housing systems decreases and the number of hens in an alternative housing system (barn, free range and bio) increases. This due to the EU regulation 1999/74/EG; this regulation forbids to hold hens in traditional cage housing systems.

Figure 3: The percentage of flocks and hens housed in different housing systems in the Netherlands (PVE, 2009)

3.3.2. Salmonella NL

During the late eighties there was an increase of Se contaminations in humans that were associated with egg consumption in the Netherlands. Therefore, in 1989 a national monitoring and control plan for Se in poultry (breeding stock) was introduced (Edel, 1994; Noble, 1994). In 1997 actions were taken and expanded by the board of poultry, meat and eggs (PVE) in the egg industry to a supply chain management (Integrale keten beheersing). Nowadays the Salmonella monitoring and control plan is largely determined by the EC. First a baseline survey was conducted in all European countries. The baseline survey was conducted by taking random samples from hens at the end of the laying period, to know the prevalence in European countries in advance. The weighted prevalence of Se and St were 18,3 % and 2,6 % respectively in Europe (EFSA, 2009). In the Netherlands it was found that 6.1% of the cases were attributable to Se and 1.7% of the cases were attributable to St. The target to


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reduce Se and St at laying flocks for the Netherlands is stated at 10 % per year compared to the previous year, started in 2008. The eggs of contaminated flocks with Se or St may no longer serve as table egg since 2009. Positive stated eggs must be canalized to the processing industry. Also in the Netherlands a lot of researches have carried out to find the relation between laying hens and human salmonellosis. The report of Giesen et al., (2010), estimated the percentage of eggs contaminated with Salmonella at 0,007%. Mollenhorst et al., (2005) estimate the percentage of contaminated eggs at 0,0068%. In 2010, there were 43.000 cases of human salmonellosis and 50 fatal cases, where human salmonellosis led to death (Haagsma et al., 2010).


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4. Materials and method This chapter describes the materials and methods which were used to quantify the financial consequences of Se and St in the laying sector. The financial consequences are related to the costs of monitoring Se and St, the costs for the different intervention scenarios and costs of human salmonellosis. First of all, the developed model will be described, thereafter the parameters are described (with the different parts; general, monitoring, intervention scenarios and human health). Finally, the sensibility of the parameters will be discussed.

4.1. Model

In order to determine a cost-effective method to reduce human salmonellosis related to Se or St contaminated egg(product)s, an economic evaluation has been performed. Hereby the costs of monitoring, intervention scenarios and human health was taken into account. To compare the different intervention scenarios, a model was needed to find out what the effects of the different intervention scenarios were on the costs of human health. The model has been programmed in Excel by the creation of a static and deterministic spreadsheet model. In a few exceptions, stochastic functions were used which were run by @risk (Palisade, USA). @Risk enables Monte Carlo simulation to calculate possible outcomes of an event. The stochastic model was only used to give a better view of uncertain and sensible parameters. In this study it has mainly been used for calculations related to human salmonellosis. This is due to the available time and knowledge to collect and to test the specific parameters in that field. All costs related to monitoring, intervention scenarios, and human health were included. Four different scenarios related to intervention costs were studied, like heat treatment of Se and St contaminated eggs, destroying eggs of Se or St positive laying hens, cull all Se and St positive hens and a do nothing scenario. The different options or scenarios have been worked out in the literature research of this report. In a research of AHVLA (2011) to the economic analysis of options for the control of Salmonella infection in egg laying flocks of gallus gallus, a model has been built, which was used as basis for the model in this research. The modeling has been done for the whole egg industry in the United Kingdom and in the Netherlands.

4.1.1. Economic evaluation

The actual purpose of an economic evaluation is to evaluate the advantages and disadvantages of an event in an economical way (Polinders et al., 2011). Economic evaluation comparatively analyses the costs and effects of two or more events. There are four different types of economic evaluation, namely cost-effectiveness analysis, cost-utility analysis, cost-minimization analysis and cost-benefit analysis (Polinders et al., 2011). Cost-minimization analysis could be used if the effects, like the number of human salmonellosis, of an event are known or assumed to be equal. If the outcome is known, then only the costs need to be analyzed and calculated. Mostly in this analysis the least costly outcome is the most efficient. Cost-effectiveness analysis expresses the effects of an event in non-monetary units, such as number of human salmonellosis, and the costs of the event in monetary units, such as the costs for an intervention scenario. The aim of a cost-effectiveness analysis is to provide information about the relative efficiency of alternative events that serve the same goal. A cost-utility analysis is comparable with a cost-effectiveness analysis but calculates the cost per unit of utility. The aim of this analysis is to compare an event with other types of events. A cost-utility can give insides in investments like monitoring or intervention scenarios related to the impact of human health.


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A cost-benefit model supports decision making. A cost-benefit model could be used by mapping the costs of the monitoring program of the different intervention scenarios. The costs which are made by the poultry sector influence indirectly the number of human salmonellosis, what is expressed in benefits. These benefits are described in a monetary value (Euro/Pounds). For example, in the poultry sector costs can be saved on monitoring or on interventions which are expressed in a monetary value (benefits), a result of this is that the number of human salmonellosis probably will increase, these costs are described in a monetary value or an utility value. A cost-benefit analysis can be made with the help of a model, weighing the total expected costs against the total expected benefits of one or more options with regard to monitoring and interventions in Salmonella. A farmer, for example, will choose an option with relative low costs for the farmer himself, but this could lead to high costs for human health. While the government will rather search for an option with relative low costs but with high effectiveness which leads to low cases of human salmonellosis. In short, the model is developed as follows: in literature, information was found about the number of laying flocks, number of hens per laying flock, the prevalence of Se and St per country, number of contaminated eggs per infected hen, number of human salmonellosis related to egg(product)s, all the related to monitoring, interventions and human health. The prevalence of Se and St refers to the incidence of a Se or St infection in laying flocks in a specific country per year. The information has been applied in calculation rules and put into the model. The results of the model were expressed in an effectiveness rate of the different intervention scenarios in relation to the human health. Finally, the effectiveness rate have been transferred to the total cost per intervention scenario. So, the end product of the model was an outcome of the total cost per intervention scenario, inclusive the costs for monitoring, intervention and human health.

4.1.2. Baseline scenario

To calculate the effects of the different intervention scenarios, a starting point or baseline scenario was needed. Heat treatment is considered as baseline scenario because of the available data (data from the field, a heat treatment has been used for some time in the poultry sector already). The European commission established in 2007 a regulation, EC 1237/2007, in which it is determined that eggs from Se or St infected hens or eggs from hens which have an unknown status are not allowed to enter the market as fresh table eggs. Hereby heat treatment is a common intervention scenario, which is mainly used in the EU, to reduce the number of Se and St contaminated eggs and to protect food safety as much as possible. Therefore, more data were available for eggs that were heat treated, and the efficiency and costs for that intervention scenario could be better calculated compared to other intervention scenarios. The efficiency rates of the treatment scenarios are based on literature and own insights. A report of van de Giessen et al. (2009,) described that canalizing (making distinction between Se and St contaminated eggs versus not contaminated eggs) provides for a reduction of human salmonellosis with 80% if all hens were kept in a cage housing system, compared to the situation where nothing was done. If all hens were kept in a barn housing system the reduction of human salmonellosis would be 66%, if canalizing has been applied. In addition, a report emerged that a heat treatment is effective for 90%, meaning that 10% of the eggs can still transfer a threat to human health (DEFRA, 2010). Another factor which is taken into account is the time interval between the actual contamination of a flock with Se or St and the moment of monitoring and verification of that flock. Between the interval of monitoring (15 weeks), a hen can be Se or St positive, without any traces of it. In the scenario, ‘cull a contaminated flock’, not only the efficiency of a heat treatment, without canalization of 90% was taken into account, but also the fact that slaughtered hens could no longer infect other hens or flocks on a same farm. Destroy eggs from Se or St infected hens has the same efficiency rate as a heat treatment. Only by destroying eggs a compensation for the 10% loss of efficiency is necessary.


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A do nothing scenario has an efficiency of 25%, this is based on the fact that if there was no monitor system or no intervention scenarios, the number of human salmonellosis will strongly increase (Anon, 2001). This appearance is reflected in chapter 3, where the opposite is described, monitoring and interventions are applied and at the same time the number of human salmonellosis sharply decreases. However, 25% is a limited estimation and would be particularly valid for the first few years, but would be many times smaller when the long-term was taking into account. In the baseline scenario a few assumptions were made. One of these is the age that a hen will be contaminated with Se or St. The age at which a hen will be Salmonella infected is not pre-determined. A trend can be traced; virtually all hens which were infected with Se or St were older than 46 weeks, with a peak at 60 weeks (Schouwenburg and Molenaar, 2012). It even seems that the older the hen, the greater the chance of infection (Schouwenburg and Molenaar, 2012).

4.2. Parameters and calculations The model contains multiple parameters which form the pillars of the economic evaluation. The parameters are found by executing a qualitative research. On the one hand the qualitative research exists of a literature review (see reference list) and on the other hand of data obtained by experts. The respective experts are: Schouwenburg (PPE), Swart (RIVM), Zwanenburg (Interovo), van Esch (Kwetters), Havelaar (RIVM); all involved in the poultry sector. The different kind of parameters can be split up into four groups, namely: general, monitoring, intervention and human health. The ‘general’ parameters relate to information about the poultry sector: number of flocks, number of hens, laying percentage, egg prices and Se and St infections in laying hens. In Table 5, the most important ‘general’ parameters are visible, the remaining parameters can been found in appendix A. Table 5: ‘General’ parameters

General info

Description data UK data NL source UK source NL

Poultry sector Number of flocks 1,202 1,114 DEFRA, 2007 pve, 2009

Number of hens (million) 38.8 31.4 DEFRA, 2011; DEFRA, 2012 pve, 2009

Number of hens in cage (million) 19.1 12.7 DEFRA, 2011 pve, 2009

Number of hens in barn (million) 2.17 13.8 DEFRA, 2011 pve, 2009

Number of hens in free range (million) 16.1 3.7 DEFRA, 2011 pve, 2009

Number of hens in bio (million) 1.28 1.2 DEFRA, 2011 pve, 2009

Average nr of hens in cage 105,143 45,460 DEFRA, 2011 pve, 2009

Average nr of hens in barn 23,975 23,024 DEFRA, 2011 pve, 2009

average nr of hens in free range 11,273 20,656 DEFRA, 2011 pve, 2009

Salmonella infected hens Prevalence Total 0.28% 1.45% DEFRA, 2010 pve, 2009

infected at an age of < 28

4

ppe, 2009


10

ppe, 2009

infected at an age of > 45

19

ppe, 2009

contaminated at an age of (days, cage) 420 420 Own Own

contaminated at an age of (days, barn) 420 420 Own Own

contaminated at an age of (days, free-range + bio) 420 420 Own Own


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Actual contamination of eggs related to human salmonellosis 0.037 0.037 van de giesen et al., 2010 van de giesen et al., 2010

hen lay a contaminated egg (per egg) 0.136 0.136 Takumi et al., 2008 Takumi et al.; 2008

Contaminated hens 108,640 455,300 contaminated eggs 12,284.7 51,863.6 number of human salmonellosis related to egg(product)s 455 1,921

Another group of parameters are the ‘monitoring’ parameters. The EC has set regulations for monitoring Salmonella at the laying sector; EC No. 2160/2003. That is the reason why the method to monitor Salmonella is in global line equal in the UK and the NL. Data for the costs, frequency, sample type and data for verification were determined by using literature and information from experts, and could differ in detail (costs to take the monitoring sample, type of verification) between the UK and the NL. The group of ‘monitoring’ parameters includes amongst others, information about the frequency of monitoring, the materials to monitor and the costs, see Table 6. Calculations with these parameters in combination with the ‘general’ parameters, will give the total costs of monitoring for the laying sector for both the UK and the NL. Table 6: monitoring parameters

Monitoring Description Unit data UK data NL source UK source NL

Number of samples rearing period

day old Boxs 5 5 pve, 2012 pve, 2012

2 weeks before laying farm bootswaps or faeces 2 2 pve, 2012 pve, 2012

number of samples laying period

pve, 2012 pve, 2012

age of 22-26 weeks bootswaps or faeces 2 2 pve, 2012 pve, 2012

every 15 weeks after 22-26 weeks bootswaps or faeces 2 2 pve, 2012 pve, 2012

at least 3 weeks before slaughter bootswaps or faeces 2 2 pve, 2012 pve, 2012

Equipement cost Euro 1.87 2 DEFRA, 2011 own

test cost Euro 19.12 20 DEFRA, 2011 own

screening cost Euro

50 DEFRA, 2011 own

time to sample (h)

2 2 DEFRA, 2011 own

cost/hour to sample (farmer) Euro 19.99 20 DEFRA, 2011 own

cost/hour to sample (external) Euro 57.48 64 DEFRA, 2011 own

base fee Euro 39.98 15 DEFRA, 2011 own

external taking monster

3 2 DEFRA, 2011 own

verification ceaca & oviducts Euro 4,291.89 1,500 DEFRA, 2011 ppe schouwenburg

4000 eggs/flock Euro 2,792.54

DEFRA, 2011

5 pair bootswaps of 5 feaces and 2 dust per flock Euro 286.88

DEFRA, 2011

number of verification

3 4 DEFRA, 2011 pve, 2009

post-restocking sampling Euro 198.79

DEFRA, 2011

desinfectie monitoring Euro 287.38 250 DEFRA, 2011

cleaning and sampling euro/hen 0.025 0.025 DEFRA, 2011 own

total costs monitoring rearing euro/holding 148 153 total costs ,omitoring lay euro/holding 222 235 total costs verification Euro 860 6,000


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total costs restocking sampling euro/holding 348 102

Intensive /extensive monitoring program (for example at the end > 50 weeks, every 5 weeks) time to sample (days) 105 105 defra, 2011 pve, 2012

In this study four different intervention methods have been evaluated; heat treatment, cull flocks, destroying eggs and a do nothing scenario. The different parameters belonging to a specific intervention scenario can be found in Table 7. Table 7: intervention parameters

Scenarios

Description Unit data UK data NL Source

Heat treatment less revenue hen/laying period Cage euro/hen/year 0.15 0.15

Barn euro/hen/year 1.22 0.94 free-range euro/hen/year 1.82 1.12 Bio euro/hen/year 3.84 3.70

percentage of effectiveness

73% 71% van de Giesen et al., 2009

Cull flocks loss/revenu/value hens (amortization table)

Cage euro/hen/year 0.85 0.86 Barn euro/hen/year 0.85 0.85 free-range euro/hen/year 0.83 0.83 Bio euro/hen/year 1.27 1.28

cost duration cage euro/hen/year 0.22 0.22 cost duration barn euro/hen/year 0.51 0.37 cost duration free-range euro/hen/year 0.62 0.27 cost duration bio euro/hen/year 0.39 0.32


86% 84%

Destroy eggs loss revenu rest of laying period cage euro/hen/year 4.12 4.26

barn euro/hen/year 4.39 4.23 free-range euro/hen/year 4.67 4.07 bio euro/hen/year 6.23 6.17


81% 79%

Vaccination Vaccination euro/hen/year 0.088 0.089 Baltussen et al., 2007


50% 50%

Do nothing

percentage of noncontaminated hens 25% 25%


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The most common scenario is the heat treatment. The heat treatment scenario could be divided into three different scenarios, namely:

Heat treatment: from verification of a Se or St infection up till the end of the laying period (all eggs of an infected flock will be treated with high temperatures)

Heat treatment in combination with early slaughtering (a heat treatment brings extra costs for the farmer and when laying hens have a high laying percentage with a low feed conversion, it is still economically justified to keep the hens, but when the costs for treating the eggs with high temperatures will be higher than the revenues, the farmer can choose to slaughter the hens at an early stage).

Heat treatment at holdings with more flocks in the same area (holdings with different flocks and different ages of hens have a higher risk to spread the Se or St infection on the holding if one flock is infected with Se or St. To overcome this risk, a farmer can choose to slaughter the infected hens at an early stage. But the risk the farmer could take with keeping the infected hens has an economic value because when the infection spreads to the other flocks it will cost more money to treat also the eggs of the other former uninfected flocks).

Another scenario to reduce the risk for human salmonellosis related to possible contaminated eggs is to destroy all the eggs from infected hens. This scenario is not common because it is generally more expensive than a heat treatment, while the risk for human salmonellosis in both scenarios is equally low. A laying flock which is stated as Salmonella contaminated has lower profits than a flock which is not infected. If the costs to reduce the risk for human salmonellosis become too high, the farmer can choose to slaughter the hens in an early phase. The remaining value of the hens will then be lost and there are also costs to cull and incinerate a hen which will cost 0.20 euro per hen. A ‘do nothing scenario’ is actually no longer feasible and also not accounted for the number of human salmonellosis. This scenario could be used to compare to other scenarios to see what the differences are between doing nothing or one of the other three scenarios. Below are the calculations for the different intervention scenarios . In the calculations are the prices of eggs, laying percentage, mortality, laying period, housing system, prices slaughter hen, Se and St prevalence by laying hens and age of contamination included, therefore a distinction could be made between the different housing systems. Heat treatment (euro/hen): The cost to treat the eggs with a heat treatment and the loss of the decreasing value of an egg, corrected for mortality and the different housing systems. ((((((price cage egg x laying percentage cage) x (1 – mortality cage / 2)) – (((price cage egg - (price cage egg – ( price cage egg + 0.2))) x laying percentage cage) x (1 – mortality cage /2))) x (-1)) x (laying period cage – age contamination cage) x number of hens in cage housing system) x 365 / laying period cage + (((((price barn egg x laying percentage barn) x (1 – mortality barn / 2)) – (((price barn egg - (price cage egg –( price barn egg + 0.2))) x laying percentage barn) x (1 – mortality barn /2))) x (-1) x (laying period barn – age contamination barn) x number of hens in barn housing system) x 365 / laying period barn + (((((price free range egg x laying percentage free range) x (1 – mortality free range / 2)) – (((price free range egg - (price cage egg –( price free range egg + 0.2)) x laying percentage free range) x (1 – mortality free range /2))) x (-1)) x (laying period free range – age contamination free range) x number of hens in free range housing system) x 365 / laying period free range + ((((price bio egg x laying percentage bio) x (1 – mortality bio / 2)) – (((price bio egg - (price cage egg –( price bio egg + 0.2)) x laying percentage bio) x (1 – mortality bio /2))) x (-1)) x (laying period bio – age contamination bio) x number of hens in bio housing system) x 365 / laying period bio) x prevalence Salmonella


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Cull Flocks (euro/hen): The costs involved with the treatment to cull the flock are: cost to cull a hen, the lost value of a hen and the lost of income during the vacancy. (((price hen cage + (2 x added value rearing hen x if(age contamination cage < 140; 0.1))) – (((price hen cage x if(age contamination cage < 140; 0.1) + 2 x added value rearing hen x if(age contamination cage < 140; 0.1) - price slaughter hen cage x if(age contamination cage < 140; 0.1))/ (laying period cage – 140)) x (age contamination cage – 140)) x number of hens in cage housing system) x 365 / laying period cage + ((price hen barn + (2 x added value rearing hen x if(age contamination barn < 140; 0.1))) – (((price hen barn x if(age contamination barn < 140; 0.1) + 2 x added value rearing hen x if(age contamination barn < 140; 0.1) - price slaughter hen barn x if(age contamination barn < 140; 0.1)) / (laying period barn – 140)) x (age contamination barn – 140)) x number of hens in barn housing system) x 365 / laying period barn + ((price hen free range + (2 x added value rearing hen x if(age contamination free range < 140; 0.1))) – (((price hen free range x if(age contamination free range < 140; 0.1) + 2 x added value rearing hen x if(age contamination barn < 140; 0.1) - price slaughter hen free range x if(age contamination free range < 140; 0.1)) / (laying period free range – 140)) x (age contamination free range – 140)) x number of hens in free range housing system) x 365 / laying period free range + ((price hen bio + (2 x added value rearing hen x if(age contamination bio < 140; 0.1))) – (((price hen bio x if(age contamination bio < 140; 0.1) + 2 x added value rearing hen x if(age contamination bio < 140; 0.1) - price slaughter hen bio x if(age contamination bio < 140; 0.1)) / (laying period bio – 140)) x (age contamination bio – 140)) x number of hens in bio housing system) x 365 / laying period bio + (((laying period cage – age contamination cage / 2) x ((((price cage egg – costprice cage egg)) x laying percentage cage x (1 – mortality cage / 2)) x number of hens in cage housing system) x 365 / laying period cage + (((laying period barn – age contamination barn / 2) x ((((price barn egg – costprice barn egg)) x laying percentage barn x (1 – mortality barn / 2)) x number of hens in barn housing system) x 365 / laying period barn + (((laying period free range – age contamination free range / 2) x ((((price free range egg – costprice free range egg)) x laying percentage free range x (1 – mortality free range / 2)) x number of hens in free range housing system) x 365 / laying period free range + (((laying period bio – age contamination bio / 2) x ((((price bio egg – costprice bio egg)) x laying percentage bio x (1 – mortality bio / 2)) x number of hens in bio housing system) x 365 / laying period bio) x prevalence Salmonella Destroy Eggs (euro/hen): The costs regarding to this treatment are: the lost revenue of the eggs. ((((((price cage egg x laying percentage cage) x (1 – mortality cage / 2)) x (laying period cage – age contamination cage)) x number of hens in cage housing system) x 365 / laying period + (((((price barn egg x laying percentage barn) x (1 – mortality barn / 2)) x (laying period barn – age contamination barn)) x number of hens in barn housing system) x 365 / laying period barn + (((((price free range egg x laying percentage free range) x (1 – mortality free range / 2)) x (laying period free range – age contamination free range)) x number of hens in free range housing system) x 365 / laying period free range + (((((price bio egg x laying percentage bio) x (1 – mortality bio / 2)) x (laying period bio – age contamination bio)) x number of hens in bio housing system) x 365 / laying period bio) x prevalence Salmonella


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Human health Human health is a specific field and therefore the data are solely based on literature, see Table 8. Table 8: parameters human health

Human health

Description unit

data outcome Source

Cost human salmonellosis UK Euro/case min 757 1,539.35 roberts et al., 2003

Most 1,421

santos et al., 2010

Max 1,874

Persson and Jendtey, 1992

Cost human salmonellosis NL Euro/case

250

Haagsma et al., 2009; EFSA 2010

number of salmonellosis UK

5,898

hpa, 2011

number of salmonellosis NL min 9,100 60,094.18 haagsma et al., 2009

Most 43,000

haagsma et al., 2010

Max 110,000

haagsma et al., 2009

Description data UK data NL

number of contaminated hens 108,640 455,300 contaminated eggs 12,285 51,864 number of human salmonellosis related to egg(product)s by indirect sources 455 1,921 number of human salmonellosis related to egg(product)s by direct sources 471 10,480 number of human salmonellosis related to egg(product)s 463 6,201 Costs human salmonellosis (euro) 712,966 1,550,162

The model used a stochastic variable to calculate the average number of cases of salmonellosis and consequently the costs of human salmonellosis. The number of cases of salmonellosis is dependent on several factors; how many people go to a doctor with complaints related to salmonellosis, what is the origin of the salmonellosis and does the contaminated product come from its own country or from abroad. @Risk can with Monte Carlo simulations predict the weighted average. @Risk has been used for two calculations: The cost of human salmonellosis in the UK: RiskTrigen (min cost human salmonellosis; most likely cost human salmonellosis; max cost human salmonellosis; 20;65) The number of human salmonellosis in the Netherlands: RiskTrigen (min number of human salmonellosis; most likely number of human salmonellosis; max number of human salmonellosis; 25; 75)

4.3. Sensitivity analysis During the literature research, a tangle of data was found. And for some aspects there were no data at all. In some cases, this makes the model sensitive for the outcome of the results. In other cases, some parameters have a greater influence on the outcome of the calculations. To find out the sensitive parameters, a sensitivity analysis has been performed. A sensitivity analysis has been performed on those parameters of which the references were not fully trustful or where the parameter can fluctuate naturally and have a possible impact at the outcome. The analyses have been done, one by one, for all the parameters by increasing the original value of the parameter with 20 percent points. With a 20 percent point, differences could be found between parameters which influence or do not influence the outcome. If the percent point would be higher, the change to note


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a normal parameter as a sensitive parameter would increase. The outcome of the sensitivity analyses has been compared with the original outcome and extreme outcomes have been notified (and the corresponding parameters have been marked) as sensitive. With the data which were found, parameters for the model are formed. Not all data for the parameters were available, and some parameters are therefore based on estimations. In the literature sometimes multiple data were found for one parameter. To determine the right data for that parameter, the data are not averaged but weighted. Weighted in the form of estimate which data are the most important to form the parameter. Thereby the reference of the data is estimated on the importance of the data and put higher value to a recent and trustful reference. Some references are not comparable or as trustful as others. It is for example more important to know how many flocks are contaminated with Salmonella nowadays than to know how many flocks were contaminated 20 years ago (the actual Se and St prevalence indicate the Salmonella status). Therefore, the relative weights for the different data, to formulate the parameter, are calculated by the importance of the data and the relevance of the reference belonging to those data.


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5. Results Results will be described and explained, whereby the focus mainly lies on the differences between the intervention scenarios. First the effectiveness of the intervention scenarios will be explained. Thereafter the costs of the different interventions, results of the sensitivity analysis, the model as a tool and specification of the costs related to monitoring, intervention and human health will be described.

5.1. Cost-effectiveness The different intervention scenarios have all a different effectiveness. With the effectiveness is meant the value which determines the reduction of human salmonellosis in a percentage compared with a ‘do nothing scenario’ in the early nineties. In Table 9, the effectiveness of the four intervention scenarios can be found. Hereby is mainly looked at the effectiveness of the heat treatment or the baseline scenario. This is 73% and 71% respectively for the UK and the NL. The difference between the two countries could be explained by the fact that during the research, available data imply that in the UK more laying hens were housed in cages than in the NL, while laying hens housed in barn systems have a higher prevalence to get infected with Se or St (van de Giesen et al., 2010). The monitoring program in the EU has a time interval of 15 weeks, and testing a (faeces or dust) sample will take two weeks. In the meantime, it may occur that a flock is Salmonella infected and thereby provides contaminated eggs directly to the consumer. As a result, the effectiveness of a heat treatment is estimated at 73% and 71%. By culling a flock immediately after discovering a Se or St infection, the effectiveness is estimated 86% for the UK and 84% for the NL. The explanation of the difference between the two countries, as for the effectiveness of a heat treatment, could also be used for the scenario ‘cull a flock’. However, the greater effectiveness by ‘cull a flock’ comes from a lower infection rate to the surroundings, because the Se or St infected hens are actually slaughtered. There is no chance of contamination to the surroundings/environment because the hens are already slaughtered , and the hens can no longer excrete Salmonella. Infected hens may therefore no longer infect other flocks on the farm or outside the farm. The effectiveness of destroying all contaminated eggs is for the UK: 81% and for the NL: 79%. The difference compared to the heat treatment can be explained by the certainty that contaminated eggs may not enter the fresh market (table eggs), but can still contaminate the surrounding. The effectiveness of a ‘do nothing scenario’ is 25% for both countries. This percentage is a conservative estimate of the expected number of human salmonellosis in the short term. Past experience has shown that when there is no monitoring or intervention scenario, the number of human salmonellosis highly increases. Table 9: the effectiveness of the four different intervention scenarios

effectiveness heat treatment cull flock destroy egg do nothing

UK 73% 86% 81% 25%

NL 71% 84% 79% 25%

Figure 4 and Figure 5 show that the efficiency for an intervention scenario, where the eggs are treated, is quite higher than an intervention scenario where nothing has been done. Has the opposite of higher costs for interventions. In the same figures is shown that the intervention ‘destroy all eggs’ from Salmonella infected hens, entails the largest costs in terms of intervention costs. In contrast, ‘destroy all eggs’ has significantly lower number of human salmonellosis compared to a do nothing scenario. The do nothing scenario scores, in contrast, poorly on almost every aspect (number of human salmonellosis and efficiency), but entails no treatment costs.


33

Figure 4: The treatment cost, efficiency and cost human salmonellosis for the different intervention

scenarios in the UK

Figure 5: The treatment cost, efficiency and number of human salmonellosis for the different

intervention scenarios in the NL

0

50000

100000

150000

200000

250000

heat treatment cull flock destroy egg nothing

treatment cost

efficiency treatment scenario (x1000)

number of human salmonellosis (x100)

0

200000

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1000000

1200000

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heat treatment cull flock destroy egg nothing

treatment cost

efficiency treatment scenario (x1000)

number of human salmonellosis (x100)


34

5.2. Costs intervention scenarios

The description of the different intervention scenarios can be found elsewhere (paragraph 2.3.). This section will go more deeply into the costs per year of the different intervention scenarios by a Se or St infection in laying hens with an average age of the hen of 60 weeks.

5.2.1. Baseline scenario

In this research, the heat treatment scenario has been used as the baseline scenario. The effectiveness of a heat treatment scenario is 73% and 71% respectively for the UK and the NL, as already discussed in the subchapter 5.1 Cost-effectiveness. To this percentage of effectiveness belongs a number of human salmonellosis per year related to egg(product)s, which is 454 in the UK and 1921 in the NL. The costs of human health belonging to a heat treatment scenario is therefore € 712,966.- and € 1,550,162.- for the UK and the NL respectively. The explanation and specification of the costs of human health can be found in subchapter 5.5.. Beside the costs for human health, the costs for monitoring and intervention are also an important factor. The monitoring costs, including verification, are the same for every intervention scenario: € 449,731.27 for the UK and € 451,067.60 for the NL per year, see Figure 6. The yearly costs for a heat treatment intervention are € 111,041.80 for the UK and € 339,152.80 for the NL.

Figure 6: the yearly costs for monitoring, treatment and human health belonging to a heat treatment scenario

5.2.2. Other intervention scenarios

Implementing an intervention scenario will always be associated with economic losses for the poultry sector, because the value of the egg and slaughter hen decrease. But intervention scenarios are necessary to reduce the risk for human salmonellosis and thereby the costs of human health. In Table 10, the costs per intervention scenario are expressed in monitoring, intervention costs and human health. Table 10 also indicates that a ‘do nothing scenario’ is the cheapest way for the poultry sector (treatment cost), but the costs for human health for that scenario is the biggest. It is also deduced that heat treatment is the cheapest intervention scenario to reduce the number of human salmonellosis (UK: € 111,042, NL: € 339,153). This is shown in Figure 7, in the same figure is visible that the scenario ‘cull a flock’ is the most efficient related to the number of human salmonellosis, but has however higher intervention costs compared to a heat treatment (UK: € 136,701, NL: € 530,630).

0

500

1000

1500

2000

2500

Monitoring treatment cost

human health

Total

x 1

,00

0

Heat treatment NL

heat treatment UK


35

Destroying all eggs from a Salmonella infected flock is economically inefficient, the cost for intervention is higher (UK: € 479,570, NL: € 1,957,885) than a ‘heat treatment’ or ‘cull a flock’, and beside the costs for human health are also higher than in the intervention scenario ‘cull a flock’. As previously stated, a ‘do nothing scenario’ is a relatively inexpensive way compared to cost of intervention. However, the total costs, including costs for human health, are more expensive than other intervention scenarios. And these costs will increase when the estimation is revised over a longer period of time, whereas the estimation is now made on a short period of time. This estimation will not only consider the increasing costs for (mainly) human health but will also work out the image damage of the poultry sector. The poultry sector is responsible for delivering a qualitative and healthy product.

Figure 7: yearly monitoring, intervention and costs for human health related to the different intervention scenarios in the Netherlands (left graph) and the UK (right graph).

5.2.3. Costs human health

The overall costs, in a monetary value, to prevent human salmonellosis is the lowest for the intervention scenario; ‘cull a flock’. The costs for human health is the lowest with cull a flock (UK: € 366,752, NL: € 861,201), and this compensates the costs for the intervention, which is the lowest for a heat treatment (if a “do nothing scenario” is not taking into account). The costs for human health by a heat treatment (UK: € 712,966, NL: € 1,550,162) is also higher compared to the costs by destroying all eggs from a contaminated flock (UK: € 498,783, NL: € 1,128,471). But the highest costs for human health can be found by the do nothing scenario (UK: € 1,980,461, NL: € 4,009,040), which is of course understandable as it has the lowest efficiency rate. However, the measured number of human salmonellosis is not always equal to the actual number of human salmonellosis related to egg(products) produced in the own country. The Netherlands, for example, produces annually about 10 billion consumption eggs (within the European Union there were a bit more than 100 billion consumption eggs produced in 2008) (PVE, 2009). Of these 10 billion eggs, approximately 9 billion eggs were exported and also 2.5 billion eggs were imported. This means that the Dutch population eats more eggs from abroad than from their own country. The determined number of human salmonellosis in the Netherlands is therefore not only dependent on the Se and St prevalence by laying hens in the NL, but also on the prevalence of Se and St by laying hens in other countries. A report of EFSA 2010 shows that the NL scores relatively well in terms of the number of human salmonellosis. A remark hereby is that this only concerns the total number of human salmonellosis


36

whatever the origin of the Salmonella infection is. Therefore, it does not necessarily mean that this number represents the number of human salmonellosis related to egg(product)s.

5.3. Sensitivity In Figure 8 and Figure 9, the outcome of the sensitivity analysis is given. The parameters: number of hens per flock, age of contamination, the prevalence, number of contaminated eggs, effectiveness of the four treatment scenarios, number of human salmonellosis, proportion of human salmonellosis related to eggs(products), costs human salmonellosis, show a divergent result and have therefore an impact on the economic evaluation of monitoring and controlling Se and St in the laying sector. The highest impact of a parameter to the result (total costs of an intervention scenario) can be found by the cost per case of human salmonellosis. Other important parameters with a high impact are: the age at which a laying hen will be infected with Se or St and the prevalence of Se and St in an infected flock. In one case, the total costs (monitoring, intervention and human health) was reduced by 35% because the age of Se or St contamination increased with 20%, this was the case with the intervention scenario: destroy all eggs from a contaminated flock. The effectiveness of the different intervention scenarios also highly influences the total costs for the corresponding intervention scenario. Figure 8 and Figure 9 shows, for every parameter which (could) influence the outcome of the economic evaulation, the total yearly costs of monitoring, intervention and human health per intervention scenario. In the first row the standard situation is given where no parameters have a remarkable impact on the outcome. The other rows give the outcome of the yearly total costs of the different interventions scenarios where only one parameter have been changed with 20%. In the outcome where only one parameter have been changed, it is remarkable that the impact on the outcome change over the different intervention scenarios. For example the parameter, age of contamination, have the largest impact on the intervention scenario ‘destroy all eggs’.

Figure 8: Parameters which could influence the economic evaluation of monitoring and controlling Salmonella in the laying sector of the UK.

0

1000000

2000000

3000000

4000000

5000000

6000000

7000000

do nothing

destroy eggs

cull flock

heat treatment


37

Figure 9: Parameters which could influence the economic evaluation of monitoring and controlling Salmonella in the laying sector of the NL Figure 7 represents the total costs of the four different intervention scenarios. Figure 8, Figure 9 show that some parameters have a relative large impact on the final results. These uncertainties relate among others to the unknown, different or outdated data, number of Se and St contaminated eggs per hen, number of human salmonellosis per Se and St contaminated egg, and Se and St prevalence. Such parameters are variable in time. For example, the Se and St prevalence declines sharply over the years, so making an average over a number of years is not common. Or the costs for human salmonellosis may differ per source; what are the costs for chronicle illness or a fatal case, and not every source includes all costs related to human salmonellosis.

0

2000000

4000000

6000000

8000000

10000000

12000000

14000000

do nothing

destroy eggs

cull flock

heat treatment


38

5.4.The model as a tool

The model is not only developed as an economic evaluation of monitoring and controlling Se and St in egg laying flocks. It also can be used by poultry farmers to oversee what the best scenario is for their farm operations in relation to the economic consequences of a Se or St infected flock. In this respect the model is only considered from an economic perspective, and does not take into account the efficiency and effectiveness of an intervention scenario and thereby also not the impact on human health. Based on economic reasons poultry farmers are expected to choose a scenario that meets the European regulations at minimal costs. Earlier it was noticed that in an economical evaluation, cull a contaminated flock is the most effective intervention scenario to reduce the costs and number of human salmonellosis. But when the model would be used as a tool for poultry farmers with a cost minimization perspective, we get a different result. This is due to making the age of contamination variable. Laying hens could be Se or St infected at all ages, and the time (age of the hen) of Se or St infection influences the rest value (slaughter price) of a laying hen and the intervention costs. Thus, a laying hen at an age of 32 weeks should have a larger residual value than a hen of 82 weeks, and the remaining time that eggs from a infected flock have to be treated is expensive. Figure 10 and Figure 11, show which intervention scenario fits economically best with a specific age if the laying flock is Se or St infected. Thereby, the “do nothing scenario” is excluded, because this scenario is according to the European regulations not allowed and this scenario would be predominant. Out of the calculations that are revealed in Figure 10 and Figure 11, it can be concluded that the best treatment method is the heat treatment. It is not taken into account that a Salmonella infection can pass from one flock to another (at a same holding). The infection rate on a contaminated holding is greater than on a holding where no Salmonella has been detected. Regardless of the age of the hens, based on economic perspective, a choice will be made to keep the hens on the farm and thereby the eggs will be treated with a heat treatment. In the UK and in the NL a similar result has been found. However, in the beginning of the laying period, up to and including 17 weeks old, it is for the poultry sector in the UK advantageous to slaughter the hens at an early stage , because the costs for the treatment of the eggs for the remaining period of lay (another 53 weeks) are relatively high. The moment of monitoring before the hen reaches the age of 17 weeks, usually takes place at an age of 16 weeks. This means that when a flock is Se or St infected in the UK just before they are transferred to the laying farm, it is economically sound to slaughter the hens prematurely. In other words, if a laying flock in the UK in the rearing period gets infected with Se or St, then it is cheaper to cull the flock before the flock will be transported to the laying house. The difference in Figure 10 and Figure 11, in the outcome of what is economically the best intervention scenario, between the UK and the NL is largely to attributed to the difference in Se and St prevalence in both countries; 0.28 for the UK against 1.45 for the NL. In the UK there are more laying hens housed (38.8 million) compared to the NL (31.4 million).


39

Figure 10: Intervention costs in the NL related to the age of the laying hen

Figure 11: Intervention costs in the UK related to the age of the laying hen

5.5. Specification of the costs related to monitoring, interventions and human health In Table 10 the overall view of the costs (monitoring, intervention and human health) of Se and St in the poultry sector related to human salmonellosis are given. A relative large part of the total costs is due to monitoring and verification of a possible Salmonella infection in laying hens. The monitoring costs in the UK and the Netherlands are almost the same. This is understandable, because the regulations of monitoring Salmonella in the laying sector is regulated by the EC.

0

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15 20 25 30 35 40 45 50 55 60 65 70

costs heat treatment NL

costs cull flock NL

costs destroy egg NL

0

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15 20 25 30 35 40 45 50 55 60 65 70

costs heat treatment UK

costs cull flock UK

costs destroy egg UK


40

Looking at the different intervention scenarios, there could be made distinction between the four housing systems: cage, barn, free-range and bio. In previous calculations, where only the economical point of view for a poultry farmer was taken into account, it is concluded that a heat treatment is the best intervention. But if the costs of an intervention scenario have been split up, it can be concluded that the costs differ per housing system. It is not obvious that one intervention scenario fits best for all the different housing systems on economical basis. A heat treatment is economically advantageous for cage and barn housing systems. For free-range and bio housing systems slaughtering the laying hens in an early stage would be more beneficial. Especially for farmers with a bio housing system, differences in costs between the different intervention scenarios are large. For example a heat treatment for hens housed in a bio system in the NL will cost € 64,315.46 per year on average, while slaughtering the hens at an early phase in the NL will cost € 27,829.69 per year on average. This could be explained by the fact that the prices of an egg of a Se or St infected flock housed in a bio system is 2.4 times decreased compared to a uninfected flock. A contaminated egg may not be used for human consumption unless the egg is heat treated, hence the great price loss of a contaminated bio egg. The intervention costs in the NL are much larger than in the UK. This is due to the difference in prevalence of Se and St (0.28% in the UK versus 1.45% in the NL). The same reason applies to the costs of human health. But by the costs of human health, the cost per case of human salmonellosis, plays also a role. The cost per case is in the United Kingdom (€ 1,540.-) 6 times higher than in the Netherlands (€ 250.-). The costs for human health are several times higher in the UK because statistical value of life to account for premature death is included (Santos et al., 2010), and mortality is excluded in the NL. Table 10: specification of the costs for monitoring, intervention and human health

Heat treatment UK

Heat treatment NL

Cull flock UK

Cull flock NL

Destroy egg UK

Destroy egg NL

Vaccination UK

Vaccination NL

Do nothing UK

Do nothing NL

monitoring rearing 177,972.45 170,381 177,972.4 170,381 177,972.4 170,381

monitoring lay 270,898.19 274,686.6 270,898.2 274,686.6 270,898.2 274,686.6

Verification 860.63 6,000 860.63 6,000 860.63 6,000

Total monitoring 449,731.27 451,067.6 449,731.3 451,067.6 449,731.3 451,067.6

intervention cage 7,789.35 26,821.41 572,40.21 199,214.8 220,197.3 785,330.9

intervention barn 7,402.62 188,002.4 8,274.95 244,752.1 26,692.52 846,826

intervention free-range 82,081.01 60,013.56 65,236.62 58,833.47 210,354.9 218,332.9

intervention bio 13,768.82 64,315.46 5,949.59 27,829.69 22,325.11 107,395.5

total intervention 111,041.8 339,152.8 136,701.4 530,630.1 479,569.9 1,957,885 5,044,000 4,082,000

Human health 712,966.05 1,550,162 366,752.1 861,201.3 498,782.8 1,128,471 1,320,307 2,672,694 1,980,461 4,009,040

Total 1,273,739.1 2,340,383 953,184.7 1,842,899 1,428,084 3,537,424 6,364,307 6,754,694 1,980,461 4,009,040


41


42

6. Discussion and conclusions This type of research, to quantify the yearly financial costs of monitoring and controlling a possible Se or St infection in laying hens, is not often performed. Similar results as came forward in this research are therefore not available. A possible reason for this is the difficulty to find trustful data, because a lot of factors (i.e. prevalence Se or St by laying hens, intervention costs, costs human salmonellosis) play a role to make an economic evaluation. Data are very crucial to build the right pillars which underpin this type of simulation research. There were a lot of data available for some parameters. But for other parameters there were no data at all. This makes the research vulnerable with regard to some parameters. To better highlight those parameters, and to get an insight in the risks regarding the reliability of the results, this research pays attention to the sensitivity of the formulated parameters. Nevertheless, the results may be influenced by the choice of the chosen data. Premature slaughtering of Se or St infected hens is a possible intervention scenario. To calculate the costs of this scenario the reduced value of the slaughtered hen and the lost revenues of income during the remaining laying period must be taken into account. But costs related to the obligation to deliver eggs are not included in the calculation. If a farmer has a contract with the obligation to deliver eggs for a specific period, the farmer does not have the choice to slaughter the hens at an early phase or the farmer has to buy eggs from a third party to fulfill the contract. With premature slaughtering of Se or St infected laying hens, cross contamination is avoided from one infected laying hen to another. Premature slaughtering also ensures avoiding Se or St contamination from one infected farm to another. In addition, the risk of contaminating the surroundings are also reduced. Only to mention the cleaning of Se or St contaminated stables and removal of contaminated water, manure and the slaughtered infected hen itself. These risks of infecting the surroundings with Se or St are not taken into account in this research. The number of human salmonellosis has been estimated by conducting a research stereotyping Salmonella and finding similarities between human salmonellosis and corresponding Salmonella which occurs in laying hens. Because each country is constantly exporting and importing eggs, it is difficult to discover the real cases of human salmonellosis caused by eating contaminated eggs. This research therefore, seeks two ways to calculate the number of human salmonellosis. On the one hand by taking over the number of human salmonellosis associated with Se and St contaminated eggs from the literature and on the other hand calculating the number of human salmonellosis by tracing the number of infected laying hens, then the number of contaminated eggs and finally the number of human salmonellosis related to egg(product)s. The proportion of human salmonellosis will vary considerably depending on the Se and St prevalence In laying flocks, the amount and origin of imported eggs, the amount of eggs consumed and the egg preparation and consumption habits. If every farmer chooses for an economically optimal business regarding to the intervention of Se and St, in some cases conflicting interests will occur. An economic optimum in the poultry sector does not mean that this optimum is also an optimum to reduce the number of human salmonellosis as far as possible. The yearly costs in terms of intervention seem at the first sight not that bad. However these costs (Heat treatment; UK: € 111,041 NL: €339,152, Cull Flock; UK: €136,701 NL: €530,630 Destroy eggs; UK: €479,569 NL: €1,957,885) are associated with a Se and St prevalence of less than 2%. This means that the total costs of intervention concerns a small number of farmers. The costs for a farmer whose flock is infected with Se or St is relative large. The costs for farmers with a free-range or bio housing system is certainly larger compared to farmers with a cage or barn housing system. This is due to the


43

difference in costs between an egg which is not infected with Se or St and an egg which is infected with Se or St, which are larger for eggs originated from a free-range or bio housing system than a cage or barn housing system. In the Netherlands, there is a compensation for farmers whose Se or St infected laying flock are younger than 44 weeks. This compensation is not taken into account, because it is difficult to trace the age of Se or St infection in laying hens and most hens are Se or St infected at an age of 46 weeks or older. A solution to overcome the relative large costs for a farmer whose flock(s) are Se or St infected is to insure the risk. Nowadays there is a insurance for housing systems with cage, barn and free-range, the prices of such a insurance per hen per year is 4, 7 and 8 eurocents respectively and with 25% excess (Baltussen et al., 2007). The total costs for a farmer when his flock is Se or St infected is calculated by average numbers or weighted numbers. In the event that in a year the egg prices rise extremely then the costs for a farmer with a Se or St infected flock will also increase extremely. Recently, January 2012, the EC has set new regulations regarding the housing systems of laying hens. The EU direction 1999/74/Eg stipulates that it is forbidden to keep hens in traditional cages from 1 January 2012. By this regulation, a shift in the percentage hens kept in the different housing systems can be observed. The number of hens kept in cage has decreased and the number of hens kept in barn, free-range or bio housing system increased. The changes can have an impact on the prevalence of Se and St in laying hens. But changes related to shifting of housing systems are not taken into account in this research, because there were no data available of the recent percentage of hens housed in a specific housing system. This research has mainly focused on a cost-minimization analysis, where the intervention scenario with the lowest overall costs would be the most effective scenario. Beside the cost-minimization analyses, there is also made use of cost-benefit analysis. Traditionally all costs and benefits are expressed in a monetary value, but not all costs and utilities are originally measurable in monetary terms, for example the value of a human life. The costs for human salmonellosis could therefore be defined in an economic value as in Disability-Adjusted Life-Years ( DALY’S), (data not shown). DALY quantify the loss of health and consist of Years of life lost (YLL) plus Years lived with disability (YLD). DALY is a commonly used value to indicate the loss and benefits of human health. It is difficult to estimate the costs for human salmonellosis and therefore standardized norms, DALY’s, can be used. Conclusions:

Economically, a heat treatment is the best intervention scenario for cage and barn housing

systems, while free-range and bio have more benefits by slaughtering the infected flock. This

due to the difference of price between an egg originated from Se or St uninfected free-range

or bio flock and an egg originated from Se or St infected free-range or bio hens.

There may be conflicting interests by choosing the most optimal monitor and intervention

scenario. For farmers with a cage or barn housing system, it will be economically attractive to

keep Se or St infected hens on their farm for the whole (remaining) laying period. While the

effectiveness of an intervention scenario is the highest by culling all infected hens. In other

words to reduce the number of human salmonellosis, culling all Se or St infected hens would

be the most effective way.

The costs for human health will decrease about half when there would be chosen for a cull flock intervention scenario in comparison with a heat treatment scenario (712,966 366,752 in the UK and 1,550,162 861,201 in the NL). To reduce the number of human


44

salmonellosis, the government would choose premature slaughter Se or St infected laying hens.

A cull flock intervention is the overall best scenario to reduce the number of human

salmonellosis caused by Se or St infected laying hens, and to reduce the prevalence of Se and

St in the laying sector.

There are no remarkable differences in monitoring and controlling Se or St in the laying

sector between the UK and the NL. The most important differences are the Se and St

prevalence by laying hens, the costs of human salmonellosis, type of housing systems.

Costs for monitoring, controlling Se and St in the laying sector and costs for human

salmonellosis seem at first sight not too high. However, costs for an affected farmer

(definitely a farm with a free-range or bio housing system) can be very high. An insurance as

in broiler breeders sector may be a solution.

Further research

Is an insurance for a Se or St infection by laying hens attractive

What is the exact Se and St prevalence in humans originated from a Se or St infection in laying hens

Is more intensive monitoring of a Se or St infection by laying hens economically justified

What are the shift costs of a Se or St infected laying flock after introducing the EU direction 1999/74/Eg (forbidden to keep hens in traditional cages from 1 January 2012)


45


46

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Baltussen W., van Horne P., Hennen H., Wisman J., van Asseldonk M., 2007, Risicobarometer voor de pluimveehouderij

Bennett R., Ijpelaar A., 2003 ,The Economics of Salmonellosis Food and Environmental Hygiene Department

Carrique-Mas J., Breslin M., Snow L., Arnold E., Wales A., McLaren I., Davies R., 2007,

Carrique-Mas J., Davies R., 2008, Sampling and bacteriological detection of Salmonella in poultry and poultry premises: a review

Davies R., Breslin M., 2004, Observations on Salmonella contamination of eggs from infected commercial laying flocks where vaccination for Salmonella enterica serovar enteritidis had been used.

DEFRA, 2007, UK national control programme for Salmonella in layers (gallus gallus)

DEFRA, 2010, Salmonella in livestock production in GB 2010

DEFRA, 2011, pigs and poultry farm practices survey 2009 – England

DEFRA, 2011, The implications of the welfare of laying hens directive for the egg industry

DEFRA, 2012,egg statistics

EFSA, 2010, Scientific opinion on a quantitative estimation of the public health impact of setting a new target for the reduction of Salmonella in laying hens

EFSA, 2011, Disease burden and costs of selected enteric pathogens

European centre for disease prevention and control (ecdc), 2011, Annual epidemiological report, Reporting on 2009 surveillance data and 2010 epidemic intelligence data

Food and Environmental Hygiene Department (FEHD), 2004, Salmonella in eggs and egg products

Hmso, 1993, Report on Salmonella in eggs

Food Standards Agency, 2007, UK wide survey of Salmonella in raw shell eggs used in catering premises

van de Giesen A., Takumi K., Evers E., van Ppelt W., 2010, Salmonella-besmetting van eieren en eigerelateerd salmonellose in Nederland

Haagsma J., van der Zanden B., Tariq L., van Pelt W., van Havelaat A., 2009, Disease burden and costs of selected foodborne pathogens in the Netherlands

Haagsma J., Siersema P., Dew N.,Havelaar A., 2010 Disease burden of post-infectious irritable bowel syndrome in the Netherlands.

HKSAR, 2004, Salmonella in eggs and egg products

van Hoorebeke S., 2010, The effect of different housing systems on Salmonella and antimicrobial resistance in laying hens

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Kemmeren J., Mangen M., van Duynhoven Y., Havelaar A., 2006, Priority setting of foodborne pathogens

Mollenhorst., van Woudenbergh H., Bokkers E., de Boer I., 2005, Risk factors for Salmonella Enteritidis in laying hens

Polinder S., Toet H., Panneman M., van Beeck E., 2011, cost-effectiveness and cost-utility analysis of injury prevention measures

PPE, 2008, toekomstvisie pluimveehouderij 2015-2020

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Schouwenburg H., Molenaar R., 2012, Ouder en vatbaarder

Takumi K., Evers E., van de Giesen A., 2008, A model study on Salmonella contamination in poultry laying flocks and table eggs


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Thomas m., 2010, Salmonella enteritidis colonization in laying hens


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Appendix

Appendix A: ‘general’ parameters

General info

description data UK data NL source UK Source NL

Poultry sector

Number of flocks 1202 1114 DEFRA, 2007 pve, 2009

Number of hens (million) 38.8 31.4 DEFRA, 2011; DEFRA ,2012 pve, 2009

Number of hens in cage 19.1 12.7 DEFRA, 2011 pve, 2009

Number of hens in barn 2.17 13.8 DEFRA, 2011 pve, 2009

Number of hens in free range 16.1 3.7 DEFRA ,2011 pve, 2009

Number of hens in bio 1.28 1.2 DEFRA, 2011 pve, 2009

Average nr of hens in cage 105143 45460 DEFRA,, 2011 pve, 2009

Average nr of hens in barn 23975 23024 DEFRA, 2011 pve, 2009

average nr of hens in free range 11273 20656 DEFRA, 2011 pve, 2009

price laying hen cage (euro/hen) 3.2 3.3 own; kwin, 2010/2011 kwin, 2010/2011

price laying hen barn 3.55 3.6 own; kwin, 2010/2011 kwin, 2010/2011

price laying hen free range 3.6 3.6 own; kwin, 2010/2011 kwin, 2010/2011

price laying hen bio 5.85 5.9 own; kwin, 2010/2011 kwin, 2010/2011 added value hen up till 20 weeks (euro/week) 0.18 0.18 own; kwin, 2010/2011 kwin, 2010/2011

price slaughter hen cage (euro/kg) 0.192 0.192 own; kwin, 2010/2011 kwin, 2010/2011

price slaughter hen barn 0.216 0.216 own; kwin, 2010/2011 kwin, 2010/2011

price slaughter hen free range 0.216 0.216 own; kwin, 2010/2011 kwin, 2010/2011

price slaughter hen bio 0.425 0.425 own; kwin, 2010/2011 kwin, 2010/2011

Price cage eggs (Euro/100eggs) 5.7 5.9 DEFRA, 2012 kwin, 2010/2011

Price barn eggs 7.5 7,3 DEFRA, 2012 kwin, 2010/2011

Price free range eggs 8.9 7.8 DEFRA, 2012 kwin, 2010/2011

Price bio eggs 14.2 14.1 DEFRA, 2012 kwin, 2010/2011

cost price egg cage (euro/100 eggs) 5.04 5.24 own, het traditionele kooiverbod: nader bekeken

own, het traditionele kooiverbod: nader bekeken

cost price egg barn (euro/100 eggs) 5.79 5.99 own, het traditionele kooiverbod: nader bekeken


cost price egg free-range (euro/100 eggs) 6.56 6.76



cost price egg bio (euro/100 eggs) 12.44 12.64 own, het traditionele kooiverbod: nader bekeken


Laying percentage cage 85% 85% own calculation own calculation

laying percentage barn 83,50% 84% own calculation own calculation

laying percentage free range 82% 82% own calculation own calculation

laying percentage bio 79% 79% own calculation own calculation

End of laying period (days), cage 555 555 kwin, 2010/2011 kwin, 2010/2011

End of laying period (days), barn 525 525 kwin, 2010/2011 kwin, 2010/2011 End of laying period (days), free range 515 515 kwin, 2010/2011 kwin, 2010/2011

End of laying period (days), bio 503 503 kwin, 2010/2011 kwin, 2010/2011 Percentage of dead hens in a laying period in cage 7% 7% kwin, 2010/2011 kwin, 2010/2011 Percentage of dead hens in a laying period in barn 9% 9% kwin, 2010/2011 kwin, 2010/2011


49

General info

description data UK data NL source UK Source NL

Effectiveness heat treatment 90% 90% Effectiveness do nothing scenario 25% 25% own Own

Effectiveness canalization if 100% cage 80% 80% van de Giesen et al., 2010 van de Giesen et al., 2010 Effectiveness canalization if 100% barn 66% 66% van de Giesen et al., 2010 van de Giesen et al., 2010 Effectiveness canalization if 100% free-range or organic 67% 67% own Own

Salmonella infected Prevalence total 0.28% 1.45% DEFRA, 2010 PVE (Hans Schouwenburg), 2009


4

ppe, hans schouwenburg


10

ppe, hans schouwenburg

infected at an age of > 45

19

ppe, hans schouwenburg contaminated at an age of (days, cage) 420 420

own, Schouwenburg H., Molenaar R., 2012


contaminated at an age of (days, barn) 420 420



contaminated at an age of (days, free-range + bio) 420 420



change that a contaminated egg make someone ill 0.037 0.037 van de Giesen et al., 2010 van de Giesen et al., 2010

hen lay a contaminated egg (per egg) 0.136 0.136 Takumi et al., 2008 Takumi et al., 2008

contaminated hens 108640 455300 contaminated eggs 12284.7 51863.6 number of human salmonellosis

related to egg(product)s 455 1921

0,04 daly per case in eu 0.04 0.04 EFSA, 2011; Kemmeren et al., 2006 EFSA, 2011; Kemmeren et al., 2006

economic evaluation of monitoring and controlling

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