Economic evaluation of monitoring and controlling Salmonella in egg laying flocks

Transcription

1 Economic evaluation of monitoring and controlling Salmonella in egg laying flocks Student J.F.W. John Nouwen Registration number Supervisor Dr. Ir. H. Henk Hogeveen Business Economics Group, WUR Course BEC Period March 2011 January 2013

2 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). 2

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4 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. 4

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6 Content Foreword... 2 Abstract... 4 Content Introduction Background Salmonella Salmonella enteridis and Salmonella typhimurium Monitoring Monitoring system Different samples Influencing factors to detect Salmonella Intervention scenarios Vaccination Canalization Heat treatment Destroy eggs Cull flock Restriction Medication Situation in the United Kingdom and the Netherlands Supply chain laying sector United kingdom Laying sector Salmonella in UK The Netherlands Laying sector Salmonella NL Materials and method Model Economic evaluation Baseline scenario

7 4.2. Parameters and calculations Sensitivity analysis Results Cost-effectiveness Costs intervention scenarios Baseline scenario Other intervention scenarios Costs human health Sensitivity The model as a tool Specification of the costs Discussion and conclusions References Appendix Appendix A: general parameters

8 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 in the period of to circa 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. 8

9 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. 9

10 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 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 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. 10

11 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 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 weeks of age 2 x pairs of boot swabs or 2 x 150g composite faeces Thereafter every 15 weeks Max. 3 weeks before slaughter 2 x pairs of boot swabs or 2 x 150g composite faeces 2 x pairs of boot swabs or 2 x 150g composite faeces 11

12 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 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) 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 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 12

13 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) Age of laying hen In the current monitoring system, sampling in laying hens will take place for the first time at an age of 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 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., 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 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 13

14 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) 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 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 in 2003 to 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 ( 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 contaminated eggs per year which enter the market as table eggs if all laying flocks were kept in cages and 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) 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 14

15 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) 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 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 ( 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) 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). 15

16 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 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. 16

17 Figure 2: Supply chain laying sector 17

18 3.2. United kingdom 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 Number of holdings in England Number of hens in England (in millions) 8,4 6,1 1,9 11,9 0,9 29,2 Number of holdings in Wales Number of hens in Wales (in millions) 0,2 0 0,05 1,2 0,08 1,5 Number of holdings in Scotland 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 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 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 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) Bio Total >= 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 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 18

19 from in 1986 to 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 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 pooled samples of six eggs collected from catering premises in England, Wales, Scotland and Northern Ireland. Out of the 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 The Netherlands Laying sector The Netherlands have 1097 holdings with more than 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 (

20 4.999) decreases and the number of large flocks ( >50.000) increases. Most flocks have a flock size between the and 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 > Total 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) 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 20

21 reduce Se and St at laying flocks for the Netherlands is stated at 10 % per year compared to the previous year, started in The eggs of contaminated flocks with Se or St may no longer serve as table egg since 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 cases of human salmonellosis and 50 fatal cases, where human salmonellosis led to death (Haagsma et al., 2010). 21

22 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 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 (Palisade, 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 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. 22

23 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 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. 23

24 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) 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) DEFRA, 2011; DEFRA, 2012 pve, 2009 Number of hens in cage (million) DEFRA, 2011 pve, 2009 Number of hens in barn (million) DEFRA, 2011 pve, 2009 Number of hens in free range (million) DEFRA, 2011 pve, 2009 Number of hens in bio (million) 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 infected at an age of < ppe, 2009 infected at an age of > ppe, 2009 contaminated at an age of (days, cage) Own Own contaminated at an age of (days, barn) Own Own contaminated at an age of (days, free-range + bio) Own Own 24

25 Actual contamination of eggs related to human salmonellosis van de giesen et al., 2010 van de giesen et al., 2010 hen lay a contaminated egg (per egg) Takumi et al., 2008 Takumi et al.; 2008 Contaminated hens 108, ,300 contaminated eggs 12, ,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, weeks before laying farm bootswaps or faeces 2 2 pve, 2012 pve, 2012 number of samples laying period pve, 2012 pve, 2012 age of weeks bootswaps or faeces 2 2 pve, 2012 pve, 2012 every 15 weeks after 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 DEFRA, 2011 own test cost Euro 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 DEFRA, 2011 own cost/hour to sample (external) Euro DEFRA, 2011 own base fee Euro DEFRA, 2011 own external taking monster 3 2 DEFRA, 2011 own verification ceaca & oviducts Euro 4, ,500 DEFRA, 2011 ppe schouwenburg 4000 eggs/flock Euro 2, DEFRA, pair bootswaps of 5 feaces and 2 dust per flock Euro DEFRA, 2011 number of verification 3 4 DEFRA, 2011 pve, 2009 post-restocking sampling Euro DEFRA, 2011 desinfectie monitoring Euro DEFRA, 2011 cleaning and sampling euro/hen DEFRA, 2011 own total costs monitoring rearing euro/holding total costs,omitoring lay euro/holding total costs verification Euro 860 6,000 25

26 total costs restocking sampling euro/holding Intensive /extensive monitoring program (for example at the end > 50 weeks, every 5 weeks) time to sample (days) 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 Barn euro/hen/year free-range euro/hen/year Bio euro/hen/year percentage of effectiveness 73% 71% van de Giesen et al., 2009 Cull flocks loss/revenu/value hens (amortization table) Cage euro/hen/year Barn euro/hen/year free-range euro/hen/year Bio euro/hen/year cost duration cage euro/hen/year cost duration barn euro/hen/year cost duration free-range euro/hen/year cost duration bio euro/hen/year percentage of effectiveness 86% 84% Destroy eggs loss revenu rest of laying period cage euro/hen/year barn euro/hen/year free-range euro/hen/year bio euro/hen/year percentage of effectiveness 81% 79% Vaccination Vaccination euro/hen/year Baltussen et al., 2007 percentage of effectiveness 50% 50% Do nothing percentage of noncontaminated hens 25% 25% 26

27 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 27

28 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 28

29 Human health 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 Description unit data outcome Source Cost human salmonellosis UK Euro/case min 757 1, roberts et al., 2003 Most 1,421 santos et al., 2010 Max 1,874 Persson and Jendtey, 1992 Haagsma et al., 2009; Cost human salmonellosis NL Euro/case 250 EFSA 2010 number of salmonellosis UK 5,898 hpa, 2011 number of salmonellosis NL min 9,100 60, 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, ,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 ,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 can with Monte Carlo simulations predict the weighted 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 29

30 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. 30

31 31

32 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 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. 32

33 treatment cost efficiency treatment scenario (x1000) number of human salmonellosis (x100) 0 heat treatment cull flock destroy egg nothing Figure 4: The treatment cost, efficiency and cost human salmonellosis for the different intervention scenarios in the UK treatment cost efficiency treatment scenario (x1000) number of human salmonellosis (x100) heat treatment cull flock destroy egg nothing Figure 5: The treatment cost, efficiency and number of human salmonellosis for the different intervention scenarios in the NL 33

34 x 1,000 Economic evaluation of monitoring and controlling Salmonella in egg laying flocks 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 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 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, for the UK and 451, for the NL per year, see Figure 6. The yearly costs for a heat treatment intervention are 111, for the UK and 339, for the NL Heat treatment NL heat treatment UK Monitoring treatment cost human health Total Figure 6: the yearly costs for monitoring, treatment and human health belonging to a heat treatment scenario 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). 34

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) 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 35