Economic consequences of a scrapie outbreak in Australia Ahmed Hafi, Jenny Eather and Graeme Garner

Research by the Australian Bureau of Agricultural and Resource Economics and Sciences

Research report 17.10 September 2017

© Commonwealth of Australia 2017

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Inquiries about the licence and any use of this document should be emailed to copyright@agriculture.gov.au.

Cataloguing data Hafi, A, Eather, J & Garner, G 2017, Economic consequences of a scrapie outbreak in Australia, ABARES research report 17.10, Canberra, September. CC BY 4.0.

ISSN 1447–8358

ISBN 978–1–74323–360–3

ABARES research report no. 17.10

ABARES project 43609

Internet This publication is available at agriculture.gov.au/abares/publications.

Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES) Postal address GPO Box 858 Canberra ACT 2601 Switchboard +61 2 6272 3933 Email info.abares@agriculture.gov.au Web agriculture.gov.au/abares

Disclaimer The Australian Government acting through the Department of Agriculture and Water Resources, represented by the Australian Bureau of Agricultural and Resource Economics and Sciences, has exercised due care and skill in preparing and compiling the information and data in this publication. Notwithstanding, the Department of Agriculture and Water Resources, ABARES, its employees and advisers disclaim all liability, including for negligence and for any loss, damage, injury, expense or cost incurred by any person as a result of accessing, using or relying on information or data in this publication to the maximum extent permitted by law.

Acknowledgements The authors would like to thank Department of Agriculture and Water Resources staff for their comments and advice, in particular Jonathan Taylor, Andrew Moss, Kerri Clark, Gregory Bryant, Rikki Ciolik and George Perry (Biosecurity Animal Division), and John Ryan, Rob Atkinson, Josie Holmes, Anna Somerville, Alexandra McLaran and Mary Shuttleworth (Exports Division).

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Contents Summary 3

Approach 4

Disease spread scenarios 5

Biosecurity measures costs and benefits 6

Study limitations 7

Introduction 8

1 Modelling the spread of a disease outbreak 12

Background 12

Eradicable scrapie epidemic 13

Spread model and assumptions 13

2 Spread modelling results 18

Spread of scrapie under the eradication campaign 18

Key results of the eradication campaign 19

Distribution of key indicators of the eradication campaign 20

3 Potential market closures 22

Developing export ban scenarios 22

Export ban scenarios 25

4 Economic impact of a scrapie epidemic—an eradication scenario 26

Eradicable scrapie epidemic 26

Control costs 26

Direct economic impacts of export ban 30

5 The economic impact of a scrapie endemic—living with scrapie 35

Background 35

Modelling spread 35

Economic cost 37

6 Framework for policy evaluation 43

Conclusions 46

Appendix A: One-year export ban 47

Appendix B: Extended export ban 50

Appendix C: Incidence of scrapie worldwide 53

Appendix D: Export certification requirements 55

Appendix E: ABARES partial equilibrium model 58

Appendix F: Overseas experience of scrapie 59

Glossary 61

References 62

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Summary In this report, ABARES estimates the economic impact of a hypothetical outbreak of scrapie in Australia’s sheep and goat population and the benefits of control measures—eradication, and slowing the spread if eradication is unsuccessful. Information on the likely impacts of a disease outbreak helps Australian policymakers assess the consequences of an incursion and ensures that the biosecurity risk to Australia is maintained at an acceptable level.

Scrapie is a progressive neurodegenerative disease affecting sheep and goats. It belongs to the group of conditions known as transmissible spongiform encephalopathies (TSEs), which also includes bovine spongiform encephalopathy (BSE or mad cow disease) in cattle.

Australia is one of the few major sheep-producing countries that is free of scrapie. To protect Australia’s scrapie-free status, Australia only allows imports of live sheep from New Zealand (which Australia recognises as scrapie-free). Australia allows importation of ovine (sheep) and caprine (goat) genetic material from Canada, the European Union, New Zealand, and the United States under rigorous conditions.

Scrapie typically transmits from ewes to lambs at or soon after birth. Infected sheep do not show clinical signs of disease for several years after infection. The disease is always fatal, but the long incubation period means that many infected sheep and lambs are slaughtered before the onset of clinical signs.

It is difficult to estimate the spread of the disease because mechanisms of transmission and incubation of scrapie are not well understood. In this study, ABARES addressed uncertainty around predicting spread by simulating an outbreak 1,000 times. Each time ABARES used parameter values chosen randomly from their probability distributions.

Scrapie (unlike BSE) is not associated with any known human health risks when meat from infected animals is eaten. World Organisation for Animal Health (OIE) guidelines recommend that importing countries do not impose scrapie-related import conditions on sheep meat or wool but do so on high-risk products such as live sheep, ovine semen and sheep and goat by-products intended for ruminant feed. However, the fact that scrapie belongs to the same group of diseases as BSE may influence food safety perceptions.

Approach In this report, ABARES estimates the economic impacts of scrapie for three disease spread scenarios:

1. eradicable epidemic 2. managed spread 3. uncontrolled spread.

Control costs are estimated for each disease spread scenario. ABARES models export losses for three export ban scenarios:

1. three-month export ban

- sheep meat only - sheep meat and beef

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2. one-year export ban

- sheep meat only - sheep meat and beef

3. extended export ban (15 years average)

- sheep meat only.

In chapter 4, ABARES estimates the outcomes of an eradicable epidemic combined with a three-month export ban. In chapter 5, the outcomes of a managed spread and an uncontrolled spread are estimated. ABARES estimates the export losses for a one-year export ban and an extended export ban in Appendix A and Appendix B respectively.

The extent of export market disruptions likely to result from an outbreak of scrapie in Australia is uncertain. Many of Australia’s trading partners would be expected to follow OIE guidelines and allow trade to continue largely uninterrupted. However, some of Australia’s largest markets—China, Japan and the Republic of Korea—have been sensitive to outbreaks of notifiable livestock diseases in the recent past. These countries may be more likely to impose bans on Australian commodities over and above OIE guidelines. However, bans would most likely be short-lived because of limited alternative supply.

ABARES modelled the trade impacts of a three-month ban on Australian sheep meat imports by China and Japan. In this scenario, Australia would negotiate a resumption of trade with these countries by offering assurances that meat would be sourced from unaffected farms. ABARES also modelled a Korean ban on Australian beef imports. This is based on existing agreed certification with Korea requiring Australian exporters to include an attestation that Australia is free of scrapie on export certificates for a range of beef and sheep meat products.

Two additional scenarios are presented in Appendix A and Appendix B. In Appendix A, negotiations lead to a resumption of trade after one year. In Appendix B, China and Japan maintain a ban on Australian sheep meat products until Australia can regain negligible-risk status for scrapie under OIE guidelines. These scenarios address potential uncertainties about trading partners’ reactions to a scrapie outbreak in Australia but are considered less likely than the three-month ban modelled in the main report.

In the managed and uncontrolled endemic scenarios, scrapie continues to spread despite eradication efforts and becomes endemic to Australia. ABARES estimates the economic impact of these two scenarios. For managed spread, control measures that slow the spread are assumed to be adopted while industry adjusts to living with the disease. ABARES modelled uncontrolled spread to compare costs to the other scenarios and assess the economic benefit of managing scrapie.

Disease spread scenarios Eradicable scrapie epidemic The economic impacts of a scrapie epidemic comprise control costs (costs of controlling and eradicating the disease) and lost income resulting largely from export market closures and movement restrictions.

ABARES estimated that eradication would likely be achieved an average of eight years after detection of the first case (based on 1,000 simulations of the disease spread model). The OIE requires an additional seven years of surveillance after eradication to regain negligible-risk

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status. Therefore, Australia would likely regain its negligible-risk status after around 15 years on average. Most outbreaks would likely be eradicated within a decade, but they could last up to 50 years.

Lost revenue resulting from export market closures accounted for most of the economic impact for this scenario.

Under a three-month sheep meat and beef ban, the cost to livestock industries of a scrapie outbreak was estimated to be $75 million in present value terms. This comprised $5 million in control costs and $70 million as a result of trade disruptions.

A longer market ban (although less likely) could have more significant impacts. For example, the cost of scrapie to trade was estimated at:

• $152 million for a year-long sheep meat ban and $323 million for a year-long sheep meat and beef ban

• $2.2 billion for a sheep meat ban extended until Australia regained negligible-risk status (15 years average).

Managed spread The economic impacts of this scenario includes lost income resulting from increased animal mortality and reduced productivity—in addition to losses from potential export market closures. Additional income losses would arise from movement restrictions and the costs of complying with government control programs. Government costs include implementing control programs and paying compensation to producers for culled infected and susceptible animals. ABARES estimated these losses at between $49 million and $80 million in present value terms. However, losses for this scenario would likely be lower than for an uncontrolled spread.

Uncontrolled spread The economic impacts of uncontrolled spread would include higher animal mortality and lower productivity—estimated at an $83 million in income losses in present value terms. This is $3 million to $34 million higher than the losses in the managed spread scenario—depending on the effectiveness of management measures and the genetic susceptibility of the animals. These impacts would be in addition to export ban impacts. Without management measures in place, Australia would not be able to ensure exports were sourced from unaffected farms, and so the export bans could be more severe than the scenarios estimated in this report.

Biosecurity measures costs and benefits ABARES estimated the economic returns from investing in control measures using estimated avoided losses (benefits) for eradication and managed spread. Successful eradication would result in avoidance of losses associated with managed spread. Comparison of costs and income losses for eradication (including the estimated $8 million cost of running an average eight-year eradication campaign) with additional losses associated with managed spread shows that investment in eradication would likely yield a benefit–cost ratio between 5:1 and 10:1.

The benefit of managing and slowing disease spread is in avoided losses associated with uncontrolled spread over and above losses associated with managed spread. For example, if a total program cost of $50 million over 75 years is assumed, management measures would be expected to yield a benefit–cost ratio of approximately 6:1. The study also estimated that the

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cost of prevention should be limited to about $750,000 for each percentage point reduction in the likelihood of a scrapie epidemic.

Study limitations Uncertainty around key disease spread parameters and the likely reaction of trading partners to a scrapie outbreak in Australia limited ABARES ability to provide accurate estimates of the economic impact of an outbreak. ABARES modelled only one outbreak scenario (caused by infected genetic material) in one farm in New South Wales or Victoria and the disease going undetected for 10 years. However, a more severe situation could result from multiple farms being infected by genetic material from the same donor. In this case, the length of the outbreak and eradication costs would likely be much greater. Analysis was further limited by lack of data on the costs of running local scrapie control centres, the proportion of the Australian sheep population susceptible to scrapie and the distribution of the Australian goat (including feral goat) population. Despite these limitations, the results indicate that Australia benefits significantly from remaining free of scrapie. In the event of an outbreak, it would likely benefit from implementing measures to control its spread.

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Introduction This study estimates the economic impact of a hypothetical outbreak of scrapie in Australia’s sheep and goat population.

Scrapie is a progressive neurodegenerative disease affecting sheep and goats. It belongs to the group of conditions known as transmissible spongiform encephalopathies (TSEs), which also includes bovine spongiform encephalopathy (BSE or mad cow disease) in cattle, chronic wasting disease in deer and variant Creutzfeldt-Jakob disease in humans.

Signs of scrapie are generally visible two to five years after infection. The disease is always fatal, killing the animal within about six months of the onset of clinical signs. Signs of scrapie include nervousness and aggression, scratching and rubbing, lack of coordination, tremors, weight loss without loss of appetite, head pressing and ‘star-gazing’.

In sheep, different breeds have varied genetic susceptibility to the disease. Suffolk and other black-faced breeds are particularly susceptible to scrapie. The annual mortality rate in an infected flock is typically around 3 to 5 per cent but can be up to 20 per cent in a severely infected flock.

Australia is one of the few sheep-producing countries that is free of scrapie. Scrapie was first observed in Europe (including the United Kingdom) over 250 years ago and has been reported in countries across Europe, the Americas, the Middle East, Africa and parts of Asia. Table C1 lists countries that reported the presence of the disease to the World Organisation for Animal Health (OIE) in the decade to 2016.

Australia recognises the scrapie-free status of New Zealand and South Africa. Rigorous conditions allow for the importation of ovine (sheep) and caprine (goat) genetic material from Canada, the European Union, New Zealand and the United States, but live sheep imports are only permitted from New Zealand. The genetics trade with South Africa remains suspended due to foot-and-mouth disease outbreaks in 2011. To further protect Australia's TSE-free status, Australia prohibits the importation of animal-derived meat and bone meal from all countries except for New Zealand, and has banned feeding animal-derived meals to ruminants (Animal Health Australia 2017).

Scrapie (unlike BSE) is not associated with any known human health risks when meat or non-meat animal products (such as the spinal cord or brain) from infected sheep are eaten. However, a scrapie outbreak could affect the Australian sheep and goat industry significantly. Costs would include eradication, revenue losses from movement restrictions on farms in affected areas and a likely loss of access to some overseas markets (at least in the short term).

Estimates provided in this report will help the Department of Agriculture and Water Resources assess the risk of a scrapie incursion. The department estimates risk by combining the likelihood of disease introduction and establishment with expected economic consequences. It must limit risk to very low (not zero) to ensure that Australia maintains its appropriate level of protection.

Value of the sheep meat and wool industry The sheep and goat industries are worth around $6 billion annually to Australian agriculture and account for around 20 per cent of Australia’s livestock production by value.

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In 2015–16 the gross value of sheep and sheep meat production (including live exports) in Australia was around $3.5 billion, and the gross value of wool production was around $3.0 billion (ABARES 2017). In 2015–16 total Australian wool exports were valued at $3.3 billion.

The Australian sheep and wool industry is highly dependent on export markets. In 2015–16 almost three-quarters of Australian wool exports by value went to China. Exports to India, Italy, the Republic of Korea and the Czech Republic accounted for a further 19 per cent (Figure 1).

Figure 1 Value of Australian wool exports, by market, 2015–16

Source: ABS 2017b

In 2015–16 Australian exports of lamb and mutton were valued at $2.5 billion. The key markets for sheep meat were the United States, China, the United Arab Emirates, the European Union, Malaysia, Qatar and Japan (Figure 2). Australian live sheep exports were valued at $227 million. Most went to Middle Eastern countries such as Kuwait, Qatar and the United Arab Emirates, with the remainder going to smaller markets in Asia and Africa.

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Figure 2 Value of Australian sheep meat exports, by market, 2015–16 a

a Excluding live exports. Source: ABS 2017b

Value of the goat industry The Australian goat industry is small but growing rapidly. Goat meat accounts for most of the industry’s gross value of production. Other goat industry sectors (dairy, cashmere and mohair) are less significant economically.

Feral goats account for most of Australia’s goat meat production (DSEWPaC 2011), but specialist goat meat breeds such as Boer goats and Kalahari red goats are becoming increasingly common (Foster 2014).

In 2015–16, 2.2 million goats were slaughtered in Australia, mostly for export (Figure 3). An additional 80,000 live goats were exported (Department of Agriculture and Water Resources 2017). Goat meat (fresh and frozen) and live goat exports were valued at $237 million in total (ABS 2017b). The United States is the most important export market for goat meat, accounting for almost two-thirds by value. Other important markets include Taiwan, Republic of Korea, Canada, Trinidad and Tobago and Malaysia.

Total $2.5bUnited States

China

United Arab Emirates

European Union

Malaysia

Qatar

Japan

Other

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Figure 3 Goat production and value of goat exports, Australia, 2008–09 to 2015–16 a

a Value of exports includes goat meat (fresh and frozen) and live animals. Sources: Department of Agriculture and Water Resources Levies Data (2017), Australian Bureau of Statistics (2017b)

Value of other ovine- or caprine-based industries Australia’s TSE-free status benefits industries such as biopharmaceuticals and ovine meat and meal for animal feed.

The biopharmaceutical industry uses bovine and ovine materials as inputs for some products. Manufacturers worldwide have responded to outbreaks of BSE in the United Kingdom and other parts of the world by sourcing secure supplies of clean biological raw materials from Australia and New Zealand. In the mid-1990s the New Zealand biopharmaceuticals industry was valued at around NZ$150 million a year (MacDiarmid 1996).

The Australian biopharmaceuticals industry would no longer benefit from Australia’s TSE-free status if scrapie became established in Australia. The significance of an outbreak would depend on the extent of the industry’s reliance on ruminant products as a source of raw materials. Little information is available on the size of the Australian biopharmaceuticals industry and its reliance on ovine products. As a result, ABARES has not estimated the economic impacts of a scrapie outbreak on the biopharmaceuticals industry.

The United States ovine meal market is a niche but rapidly growing market for Australian exporters. The United States imports Australian ovine meat and meal for manufacture into pet food, and pays a price premium because of Australia's TSE-free status. In 2015–16 Australia produced almost 42,000 tonnes of ovine meat and bone meal, most of which was exported.

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1 Modelling the spread of a disease outbreak

Background Scrapie is a transmissible spongiform encephalopathy (TSE) caused by unconventional disease agents known as prions. An animal’s genotype influences susceptibility and expression of the disease (McIntyre et al. 2006), but the mechanisms of transmission and incubation are not well understood.

Infected sheep and goats do not show clinical signs of the disease for several years after infection. Scrapie typically transmits from ewes to lambs or from does to kids at or soon after birth. Transmission is most common with exposure to foetal membranes and fluids. Transmission can also occur through direct contact within or between sheep flocks and goat herds. In sheep, the mean age of onset of clinical disease is around two to six years depending on genotype (Animal Health Australia 2009; McIntyre et al. 2008). Infected animals (even without symptoms) remain infectious for life.

Movement of infected animals is an important route of transmission between farms. Animal movement patterns resulting from farmer buying and selling activities have been identified as the most important determinant in acquiring scrapie (McLean et al. 1999).

Scrapie is always fatal, but the rate of new infections (incidence of the disease) among sheep and goats is variable. The annual mortality rate in an infected sheep flock is typically 3 per cent to 5 per cent and can be up to 20 per cent in a severely infected flock. Without control, scrapie can persist in a herd or flock for long periods.

Stringer, Hunter and Woolhouse (1998) used a mathematical model to simulate the dynamics of scrapie in a sheep flock. They reported long durations of on-farm outbreaks (more than 25 years). Prevalence (the proportion of the population infected at a given time) peaked at 36 per cent at around 10 years before declining to 0.5 per cent by 27 years. In a study focusing on Great Britain, Gubbins (2005) found the median duration of an outbreak within a flock was 7.5 years but that an outbreak could last more than 40 years.

The role of genetic material in the transmission of scrapie is contentious (AQIS 2000). The scrapie agent has been detected in semen, but transmission by semen has not been confirmed in controlled studies. For example, Rubenstein et al. (2012) found that scrapie is likely transmissible through semen. In contrast, the International Embryo Transfer Society (IETS) concluded that—provided sheep embryos are properly handled between collection and transfer—the risk of transmission was negligible (Thibier 2011). The IETS has stated that it cannot draw conclusions on the transmission risk for goats (IETS 2017). The Australian Government Department of Agriculture and Water Resources does not support the IETS findings on sheep.

In 2010 the European Food Safety Authority (EFSA 2010) concluded that the likelihood of TSE transmission associated with semen and embryos collected from scrapie-incubating sheep and goats ranges from low to negligible. However, hundreds of doses of semen can be collected from each stud animal daily and the genetic material is then distributed Australia-wide, so even a small likelihood of infection from each dose could still pose a significant risk to the sheep and goat industries.

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Eradicable scrapie epidemic ABARES modelled the potential for scrapie to establish and spread in Australia’s sheep and goat populations. ABARES assumed that scrapie was introduced into Australia through infected genetic material, resulting in one eastern Australian (NSW or Victorian) sheep and goat farm being infected. The disease remained undetected for 10 years. Following detection, an eradication program was implemented and resulted in the eventual eradication of the disease. ABARES assumed that a further seven years of surveillance reporting nil detections was achieved, so Australia could declare itself ‘negligible-risk’ for scrapie under World Organisation for Animal Health (OIE) guidelines (Animal Health Australia 2009; OIE 2016).

Spread model and assumptions ABARES developed a modified version of the AusSpread foot-and-mouth disease (FMD) model (Garner and Beckett 2005) to simulate the spread of scrapie. The model was adjusted to incorporate scrapie epidemiology. ABARES used a different approach to simulating disease transmission and a yearly (rather than daily) time step because of scrapie’s longer incubation period.

ABARES also adapted Gubbins’ (2005) and Gubbins and Webb’s (2005) approaches to modelling scrapie transmission for this study. Gubbins (2005) incorporated scrapie dynamics by applying two probabilities: a sheep flock acquires an infected animal and an outbreak occurs in a flock after exposure. The probability of a flock becoming infected depends on contact rates and buying and selling patterns.

For clinical outbreaks, a key assumption of the model is that the susceptibility of the Australian sheep flocks to prion protein (PrP) is similar to that of British sheep in a UK control study (see Hunter & Cairns 1998).

After the assumed introduction of scrapie to one farm through infected genetic material, the disease is spread within the flock and between flocks through sheep trade.

The simulation of disease spread also incorporates a series of control measures aimed at eradicating the outbreak once scrapie has been detected. Australian Veterinary Emergency Plan–AUSVETPLAN (Animal Health Australia 2009) would be implemented and disease spread would be controlled until eventual eradication. Control measures would comprise:

• surveillance

• tracing

• movement controls

• culling and sanitary disposal of infected and high-risk animals

• grazing management plans for infected farms.

Figure 4 shows a diagram of the scrapie spread model used in this study.

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Figure 4 Scrapie spread model

Key model features Within-flock spread Once the disease has been detected, the probability of an outbreak occurring and the duration of that outbreak would depend on:

• within-flock basic reproductive number (R0), representing the expected number of susceptible animals infected from a single infected animal

• genetic predisposition to scrapie (measured by the PrP genotype profile of the flock)

• number of animals in the flock

• incubation period.

Animals within a flock are divided into three groups—unaffected, exposed (latent) and infected—reflecting disease spread within a flock. Table 1 provides specific parameters governing within and between-flock spread and their assumed values.

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Table 1 Within and between flock spread parameter assumptions, spread model

Parameter Parameter value or range

Within-flock spread

Basic reproductive number (R0) a 2.5–14 a year

Incubation period 1.6–5.9 years

Flock-level susceptibility b 0.002–0.14

Minimum time taken by a newly exposed flock before spreading to other flocks 12 months

Minimum time before showing clinical symptoms 2 years

Between-flock spread

Between-flock reproductive number R0 (uniform distribution) c 1.1–1.5

Median within-flock outbreak duration 7.5 years

Expected new infections per infected flock per time period d 0.13–0.227 a year a Expected average number of secondary cases generated from a single primary case in a fully susceptible population. b A flock level average measure representing relative risk of each PrP genotype weighted by its share in the population in the flock. c Based on Gubbins, Touzeau and Haganaars (2010) and Kao, Gravenor and McLean (2001). d Expected new infections per infected flock per time period estimated as the ratio of between-flock reproductive number to median within-flock outbreak duration.

Between-flock spread The probability that a susceptible flock will become infected with scrapie depends on the probability of spread following contact with infected animals from another farm. This will depend on farmers’ sheep buying and selling patterns.

Between-flock spread is modelled using a between-flock basic reproductive number (R0). The values of parameters governing between-flock spread (Table 1) are based on overseas data. It is possible to model the movements of animals between Australian sheep farms but difficult to estimate the probability of infection being established in the recipient flock under Australian conditions.

Disease control Once scrapie is detected, Australia would seek to control and eradicate the disease as quickly as possible using a combination of strategies:

• surveillance and tracing to determine the source and extent of infection

• quarantine and movement controls

• culling and sanitary disposal of infected and high risk animals

• assessment to identify risk and to define further strategies

• grazing management plans (Animal Health Australia 2009).

Surveillance The model incorporates active surveillance by flock owners and tests carried out by abattoir operators under targeted surveillance programs. Flock owners report suspected clinical cases (subject to their ability to recognise scrapie and willingness to report) and abattoir operators test sheep carcases and downer sheep (those that cannot stand without assistance).

Reporting by flock owners is assumed to increase over time as they find more infected animals. A background level of false reports was also modelled. Specific parameters defined to simulate the effect of surveillance measures and their assumed values are given in Table 2.

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Table 2 Parameter assumptions, control measures, spread model

Control measures Parameter value or range

Surveillance

Probability that a farm that has been infected for more than two years will report a 0.16 a year

Increase in the reporting probability over time, that is, in year t b 1-(1–0.16)^t c

Probability of being detected through abattoir and fallen stock surveillance d 0.09

Number of false reports 2–10 a year

Tracing

Length of tracing period 5 years

Tracing effectiveness 80 per cent

Minimum period of infection of traced premises before being confirmed as infected 2 years

Number of animals falsely traced onto and off-farm 4–12 a year

Movement controls

Reduction in transmission risk for farms under movement restrictions 90 per cent

Movement restriction period for infected premises 5 years

Movement restriction period for suspect premises 1 year

Movement restriction period for traced premises if not scrapie confirmed Betapert(1,3,5) e

Culling and sanitary disposal of infected and high risk animals

Culling of clinically affected, exposed and equivalent-risk animals in infected farms 10–25 per cent a Based on values reported by Truscott and Ferguson (2009). b Assumed to follow a binomial progression. c Where t denotes time period in years. d Based on values reported by Hopp, Webb and Jarp (2003). e Drawn randomly from the Beta-pert distribution with a minimum of one year, most likely value of three years and maximum of five years.

Tracing The model traces animal movements on and off infected farms over the previous five years. It is assumed that tracing is effective in tracking 80 per cent of all movements and allows for the likelihood that some animals traced could have been false traces. The 80 per cent tracing effectiveness assumption is consistent with estimates by the Centre for International Economics (2010). A more recent ABARES report (2014) assumed average tracing effectiveness of 90 per cent, but noted that lifetime traceability—which would be required due to scrapie's long incubation period—is more likely to be hindered by information gaps or inaccuracies. Specific parameters defined to simulate the effect of surveillance measures and their assumed values are given in Table 2.

Movement controls Infected, traced and suspect flocks are subject to movement controls to contain the spread of disease. Movement of animals in and out of premises is restricted over five years for infected premises, between one and five years (randomly drawn) for traced premises and one year for suspect premises. These assumptions are detailed in Table 2.

Culling and sanitary disposal of infected and high risk animals A variable proportion (10 to 25 per cent) of clinically affected, exposed and equivalent-risk animals on an infected farm is assumed to be culled.

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Incorporating uncertainty into the model Parameter value uncertainty The model incorporates uncertainty around the values of most of the parameters. The model result depends on the set of parameter values chosen, so the model was run 1,000 times to generate a distribution of stochastic realisations of the spread and impact of control measures. Each time the model is run, it randomly chooses a value for each parameter from a pre-specified probability distribution.

Dynamic disease transmission The model addresses the dynamics of disease transmission by incorporating a time lag before a newly exposed animal starts spreading infection to other animals and before clinically affected animals are likely to be observed. For each time period, and each new infection, a candidate flock is randomly selected based on regional sheep movement patterns. Each stochastic model run continues for several years until no exposed or infectious animals remain in the infected flocks.

Data assumptions The model uses the existing national herd dataset to represent the spatial distribution of sheep and mixed sheep herd types based on ABS agricultural census data. Limited goat herd data is available, so ABARES assumed that the sheep farm dataset was also representative of the spatial distribution of goats.

The model incorporates movement patterns (frequencies and distance distributions) for sheep from datasets previously used in Australian FMD modelling studies (Bradhurst et al. 2015; Roche et al. 2013).

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2 Spread modelling results Spread of scrapie under the eradication campaign The extent of the spread of scrapie following its introduction into a sheep flock in New South Wales or Victoria was considered according to:

• total number of infected premises

• number of animals culled before scrapie is eradicated

• duration of the outbreak.

In addition to farms initially found to be infected, tracing animal movements onto and off infected farms in the five years before detection results in the identification of traced premises. Reporting of animals with suspect scrapie results in the identification of suspect premises. Movement controls are put in place to prevent or restrict movement of animals into and out of the three groups of affected farms (infected, traced and suspected), with costs being incurred as a result of these restrictions. Given the uncertainty around spread parameters and the efficacy of control measures, the number of farms affected, the number of animals culled and outbreak duration can vary between stochastic realisations.

ABARES ran the model to produce 1,000 stochastic realisations of the outbreak. Each stochastic model run continued for several years until no infected flock had exposed or infectious animals (Figure 5).

Figure 5 Outbreak duration and number of infected farms

Note: Modelling assumes that the first case of scrapie is not detected until 10 years after its introduction to Australia. This means that year 1 of control corresponds to year 11 of the incursion. Source: ABARES model output, modified version of Garner and Beckett’s (2005) AusSpread model

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The left-hand side of Figure 5 presents results for the first 100 stochastic realisations of the outbreak, showing for each realisation, how the cumulative number of farms infected increased over time until scrapie was eradicated. The coordinates corresponding to the end point of each line plotted show the duration of the outbreak (horizontal axis) and the number of farms diagnosed as infected (vertical axis). The right hand side of Figure 5 shows a scatter plot of the duration of control measures (in years) and the corresponding number of farms infected for all stochastic realisations. Table 3 provides summary statistics for affected farms, animals culled and outbreak duration.

Table 3 Statistical variability in affected farm types, animals and outbreak duration across 1,000 stochastic realisations

Key indicators

Unit Minimum 25th percentile

a

Median b Average 75th percentile c

Maximum

Infected farms d

No 0 2 6 9 13 74

Infected farms

Farm-years e 0 10 30 46 65 370

Traced farms

Farm-years e 0 9 22 33 48 216

Suspect farms

Farm-years e 0 12 45 59 86 296

All restricted farms

Farm-years e 0 42 103 143 207 853

Sheep culled No. 0 579 1,545 2,560 3,676 21,634

Outbreak duration

Years 0 1 6 8 12 47

a Value below which 25 per cent of the observations are found. b Value at the midpoint of the observed values arranged in ascending or descending order. c Value below which 75 per cent of observations are found. d Cumulative number of infected farms over time measured when the outbreak is finally declared eradicated. e Farm years is the number of farms affected multiplied by the average number of years each farm is affected. One same farm could be an infected, traced or suspect farm for more than a year so infected, traced, suspect and all restricted farms are appropriately measured in farm years.

Key results of the eradication campaign The scrapie spread modelling yielded these key results:

• Around three-quarters of outbreaks were estimated to be eradicated within 12 years and infected fewer than 13 farms.

• Eradication would take an average of eight years after detection of the first case. The OIE requires seven years of surveillance after initial eradication, so Australia would regain its ‘negligible-risk’ status after an average of 15 years.

• The chance of Australia regaining full market access within 19 (12 plus 7) years is estimated at 75 per cent. This factors into the model uncertainty around the spread parameter values and assumes that importing countries follow OIE guidelines.

• An outbreak would result in an average of nine infected farms, 33 traced farm-years (the number of farms in this category multiplied by the average number of years each farm is affected), 59 suspect farm-years and a total of 143 restricted farm-years.

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• The chance that the farm impacts would be limited to 13 infected farms, 48 traced farm-years, 86 suspect farm-years and 207 restricted farm-years in total is 75 per cent. This factors in uncertainty around the spread parameter values.

• On average 2,560 sheep and goats would need to be culled. The chance that this number would not exceed 3,680 is 75 per cent.

Distribution of key indicators of the eradication campaign The median values of the outbreak length and number of farms affected are smaller than the averages (mean). The distribution is characterised by mostly shorter outbreaks associated with a smaller number of infected farms and a much smaller number of longer and more severe outbreaks. In other words, the frequency distributions of spread measures exhibit long tails to the right (Figure 6 and Figure 7) suggesting that the use of mean values alone could lead to an overestimation of the most likely impact.

Figure 6 Control duration, number of infected farms and animals culled

Note: Graphs a to c show the results from 1,000 stochastic runs of the disease spread model. For example, graph a shows that in over 100 runs of the model the outbreak failed to become established and died out before it was detected, while in a further 200 runs of the model, the outbreak was eradicated after two years of control measures. The probability of much longer outbreaks is small. The colours in the graphs indicate the frequency of different values, with red indicating the most frequent values and the greener shades indicating less frequent values. Source: ABARES model results

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Figure 7 Number of farms affected by implementation of control measures

Farm-years is the number of farms affected multiplied by the average number of years each farm is affected. Notes: Graphs a to c show the results from 1,000 runs of the disease spread model. The colours in the graphs indicate the frequency of different values, with red indicating the most frequent values and the greener shades indicating less frequent values. Source: ABARES model results

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3 Potential market closures The Australian sheep and goat industries are largely export oriented, so the economic impact of a scrapie outbreak in Australia would depend on the severity of trade restrictions imposed on Australia by major importing countries.

The extent of export market disruptions likely to result from an outbreak of scrapie in Australia is uncertain. Spread modelling showed that Australia would regain its ‘negligible-risk’ status following the detection of scrapie after about 15 years on average. However, World Organisation for Animal Health (OIE 2016) guidelines recommend that importing countries not impose scrapie-related conditions on the import of sheep meat or wool other than for some high-risk products such as live sheep, ovine semen and sheep and goat by-products intended for ruminant feed. ABARES assumes that many countries would follow OIE guidelines and allow trade to continue largely uninterrupted.

It is expected that only those importing countries that are either free of scrapie or sensitive to scrapie regardless of its presence in their own countries would impose bans on Australian exports. Some of Australia’s largest markets for livestock products, such as China, Japan and the Republic of Korea, have in the recent past been sensitive to outbreaks of notifiable livestock diseases and imposed restrictions in excess of OIE recommendations.

The extent of trade restrictions is difficult to predict, and could depend on a variety of factors, including:

• scrapie status of the importing country at the time of the outbreak

• whether the importing country requires Australia to declare freedom from scrapie on export certificates

• other recent disease outbreaks or public health scares in the importing country or elsewhere

• ability of importing countries to source sheep and goat products from other scrapie-free countries

• media and public response to changed scrapie status of Australian produce (the public may perceive scrapie-infected meat as high risk despite lack of evidence for these concerns)

• characteristics of the outbreak (severity and areas affected)

• strength of trading and diplomatic relations (which may be affected by Australian responses to similar incursions in that country in the past).

Developing export ban scenarios To develop plausible export ban scenarios, ABARES collated information for individual countries including whether export certificates require attestation on scrapie freedom and how countries have responded to notifiable animal disease outbreaks in Australia and other exporting countries in the past.

The largest markets for Australian sheep and goat meat (China, the United States and the United Arab Emirates) generally do not require an assurance of scrapie freedom on export certificates except for some specific livestock products of minor importance such as lamb for re-export to Mexico and calf lungs for biopharmaceutical purposes to the United States (Table 4).

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The countries that require attestations on a broader range of products are not major export markets for Australian sheep and goat meat. However, in some cases the same export certificate is used for multiple species and includes attestations relevant to each species. For example, current agreed certification of meat from cloven hoofed animals (including cattle, sheep, goats and pigs) to the Republic of Korea requires attestation of scrapie freedom. Korea is not a major export destination for sheep meat products but is one of the most important markets for Australian beef. If scrapie were detected in Australia, exports of Australian beef to Korea would be expected to cease immediately—at least until new export certification requirements could be negotiated.

Table 4 Scrapie related export certification requirements for selected importing countries

Country Commodities that require attestation of scrapie freedom

Iran Beef/sheep meat and inedible tallow

United States Lamb to be on-shipped to Mexico after entering the United States and calf lungs for pharmacological purposes

Republic of Korea A range of meat products and edible offal originating from beef, sheep, goat and deer, beef casings, sheep and pig casings, wool, skin and hides and edible tallow.

Note: Appendix D provides a list of countries that require attestations of scrapie freedom on export certificates. Information correct as of June 2017. Source: Department of Agriculture and Water Resources

China China is Australia’s most important market for sheep products. In 2015–16 China imported Australian wool to the value of $2.4 billion and lamb and mutton products to the value of $238 million.

China does not require attestations of scrapie freedom on export certificates of Australian sheep meat products. However, it has generally implemented strict import restrictions after detection of a notifiable livestock disease in a trading partner. For example, after outbreaks of highly pathogenic avian influenza in Australia in 2012 and 2013, China imposed import restrictions on all Australian commodities derived from poultry. As at mid 2017 these restrictions stand, three and a half years after Australia’s disease-free status was re-established. This suggests that China might restrict imports of Australian sheep meat products if scrapie was detected in Australia.

However, China would be expected to consider its ability to source sheep and goat products from other markets in responding to an outbreak in Australia. In 2016 China sourced its imports of sheep and goat meat (fresh or frozen) almost exclusively from New Zealand (68 per cent by value) and Australia (30 per cent). Uruguay, Chile and Mongolia provided less than 1 per cent each (UN Statistics Division 2017). The relatively high market share of Australian sheep meat exports in the Chinese market and the fact that only a few countries have the capacity to produce scrapie-free meat may mitigate the risk of an extended ban on Australian exports. Chinese consumers would have to pay higher prices or substitute to other meat products if China did not allow imports of Australian sheep meat products. Therefore, China may be willing to allow exports from disease-free areas to resume once the outbreak was contained.

Australia is the world’s largest producer and exporter of wool. In 2016, 67 per cent of Chinese raw wool imports were sourced from Australia (UN Statistics Division 2017). Australian wool, particularly superfine wool, is important to the Chinese textile industry so it is unlikely that this trade would be disrupted.

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Japan In 2015–16 Japan imported $107 million of sheep meat products and $22 million of wool from Australia (ABS 2017b). In 2016, 68 per cent of Japan’s imports of sheep and goat meat (fresh, frozen or chilled) by value was sourced from Australia and 31 per cent from New Zealand. It imported smaller amounts from Iceland and Hungary (UN Statistics Division 2017).

Japan does not require scrapie-related attestations on its export certificates. However, the way Japan has responded to previous outbreaks of notifiable animal diseases in trading partners suggests that it might impose restrictions on Australian sheep meat products following an outbreak. In previous disease outbreaks, Japan’s animal health legislation has prevented countries that have had outbreaks gaining recognition of disease-free zones and this has increased the duration of export bans.

Republic of Korea Korea is not a major importer of Australian sheep meat products. However, its imports of Australian beef and veal (valued at $1.3 billion in 2015–16) would be disrupted by a scrapie outbreak. Korea’s export certification requirements specify that imports of a range of Australian livestock products (Table D1 ) would be suspended following a scrapie outbreak. This would continue at least until new export certification requirements could be negotiated.

In 2016, 50 per cent of Korea’s imports of fresh, chilled and frozen beef came from Australia, with 44 per cent from the United States, 4 per cent from New Zealand and 1 per cent from Canada. Small amounts were also imported from Chile, China, Finland, Mexico and Uruguay (UN Statistics Division 2017). Scrapie is present in the national flocks of the United States and Canada, so it is likely that Korea would negotiate a revised protocol with Australia if it could be assured that the beef would be sourced from scrapie-free areas.

Other markets The market access implications of a scrapie outbreak are expected to be limited for other major trading partners. Australian exports of sheep meat products to the United States account for almost 20 per cent of Australian exports by value and are unlikely to be affected except for products such as ovine meat and meal for animal feed. The United States generally follows OIE guidelines in its response to livestock disease outbreaks in exporting countries. Therefore, any disruption to US market access is likely to be minimal.

Trade to the European Union (EU) is also unlikely to be significantly affected because EU countries follow animal health requirements on export certificates for specific products. For most countries, these do not include scrapie-related clauses. Exceptions are Latvia and Romania. Latvia requires freedom from scrapie for sheep and goat meat certificates and Romania freedom from transmissible spongiform encephalopathies (including scrapie) on certification for pork, beef and sheep meat.

Other major markets such as Malaysia, India, the United Arab Emirates and Qatar have generally not taken overly strict approaches to exotic disease detections in Australia so might be flexible in allowing the continuation of trade.

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Export ban scenarios ABARES modelled export losses following an outbreak of scrapie in Australia for three export ban scenarios:

• three-month export ban

- China and Japan immediately ban all sheep meat products from Australia. Market access is restored after three months, following an agreement on import protocols to source sheep meat products from scrapie-free areas in Australia. It is assumed that the outbreak can be contained and the scrapie-free status of particular zones is recognised by the two countries.

- Korea immediately bans all Australian beef imports for three months at the same time as the three-month ban on sheep meet products by China and Japan. Beef exports to Korea would be disrupted in the short term until new export protocols could be agreed and market access is restored after three months.

• one-year export ban

- Australia takes one year to renegotiate access to Chinese, Japanese and Korean markets. Modelling results are presented for a ban on sheep meat products by China and Japan with and without the Korean ban on beef.

• extended export ban (15 years average)

- China and Japan ban Australian sheep meat products until Australia regains scrapie-free status under OIE guidelines. This means a ban for the duration of the outbreak plus seven years. This scenario is plausible but is less likely than scenarios 1 or 2.

A one-year or extended ban on sheep meat products by China and Japan is less likely. Results for the three-month ban are presented in chapter 4, a one-year ban in Appendix A and an extended ban in Appendix B.

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4 Economic impact of a scrapie epidemic—an eradication scenario

Eradicable scrapie epidemic In this chapter, ABARES estimates the economic impact of an eradicable scrapie outbreak in sheep and goats, including trade losses associated with a three-month export ban. See chapter 5 for cost estimates of a non-eradicable outbreak, and Appendix A and B for more severe export ban scenarios.

The economic impact of a scrapie epidemic comprises control costs (for controlling and eradicating the disease) and lost income resulting from export market bans and movement restrictions.

Control costs ABARES estimated costs incurred by infected farms only. ABARES did not estimate Australian and state/territory government costs for running control centres due to limited availability of information. Costs incurred by infected farms would include:

• forgone farm gross margins (gross farm income less variable costs) resulting from quarantine measures and livestock movement controls that affect the normal business activities of farms

• cost of culling and disposing of infected or exposed sheep, goats and other high-risk animals

• replacement value of culled animals

• decontamination costs.

Farm-level control costs were estimated for each of the 1,000 stochastic realisations of the simulated outbreak until scrapie eradication (Chapter 2).

ABARES used NSW Department of Primary Industries (2016) enterprise budgets for specialist wool (merino ewes, merino rams) and lamb (dorper ewes, dorper rams) farms. These budgets were scaled to reflect the profiles of average wool and lamb specialist farms constructed from ABARES farm survey data (Table 5). ABARES constructed a representative enterprise budget for sheep studs by drawing on the sheep enterprise budgets and the profile of an average sheep stud constructed from ABARES farm survey data. Herd structure, selling and purchase prices of different types of animals and variable costs assumed in the farm budgets were retained.

In this scenario, the government places quarantine restrictions and movement controls on all restricted farms reported in Table 3. ABARES assumed that these restrictions would result in a reduction in saleyard prices for animals and income losses. It assumed a 10 per cent price discount for wool and lamb specialist farms, following the assumptions made by Topp and Bailey (2001) when estimating similar losses for Johne’s disease. For sheep studs under quarantine, rams were assumed to sell at the average price for an adult sheep for slaughter ($77 a head) instead of the stud ram price ($611 a head). Average gross margins for wool were estimated to be reduced by $32,000 a year, for lamb $20,400 and for specialist stud farms $93,100.

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Table 5 Profile of average Australian sheep farms a

Category Unit Lamb Wool Stud

Rams no. 64 98 131

Ewes no. 2,792 3,892 2,779

Wethers no. 405 1,590 247

Ewes mated % 88 85 88

Lambs marked % 90 75 96

Price of lambs sold $/head 92 69 95

Price of rams sold $/head 91 61 611

Price of adult sheep sold $/head 77 59 155

Receipts from sheep activities $/farm 313,819 240,576 321,867

Total receipts $/farm 959,428 459,430 1,320,532

Total cash costs $/farm 698,574 356,518 1,019,320

Total farm cash income $/farm 260,854 102,912 301,212 a Three-year average to 2015. Source: ABARES

Abdalla et al. (2005) estimated the cost of slaughter and sanitary disposal of affected and at-risk stock—at $15,000 a farm (based on a stocking rate of 4,000 a farm). ABARES adopted this value for this study after adjusting for inflation to 2016 prices and differences in estimated size of affected farms.

ABARES also assumed that only 10 per cent to 25 per cent of animals on reported farms were culled. Farmers would be compensated for the cost of culled animals at market prices, as specified in the Government and livestock industry cost-sharing deed in respect of emergency animal disease responses (Animal Health Australia 2016). ABARES used the prices in the NSW DPI enterprise budgets to approximate the market value.

The cost of decontamination was based on an estimate of $45,700 a farm. This was the figure reported by Garner, Roche and Wicks (2012), adjusted for inflation between 2012 and 2016. Rams and 18-month-old maiden ewes were assumed to be purchased for restocking the farm. This cost is calculated using the average size of the farm. Information on selling prices and the mix of rams and ewes was assumed in the enterprise budget (Table 5).

ABARES estimated total income losses from movement controls and control costs of culling, decontamination and restocking for all affected farms for each stochastic realisation of the simulated outbreak and for each year until scrapie is eradicated. For each stochastic realisation, the resulting income loss and cost series were discounted to estimate the present value over the period until scrapie is eradicated. This ranged from one to 47 years across 1,000 stochastic realisations. A 7 per cent discount rate was adopted, as recommended by the Australian Government (2007, 2016). See Box 1 for discussion.

Average total cost to the Australian sheep and goat industries (total for all affected farms before compensation) of controlling an outbreak was estimated to be $4.7 million (median $3.2 million) (Table 6). Costs for movement restrictions ($2.8 million) and restocking (1.5 million) represent the bulk of this. Cost for inputs and other resources used in culling, sanitary disposal and decontamination were estimated to be relatively small (just over $400,000 in total).

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The cost of the epidemic to industry would be slightly lower (average $127,000 per affected farm) when compensation for culled animals is included.

Table 6 Summary statistics for scrapie control cost for all affected farms

Cost item 25th percentile a

($’000)

Median b ($’000)

Average c ($’000)

75th percentile d

($’000)

Movement restrictions 616 2 ,142 2,816 4,372

Culling and sanitary disposal of stock

33 81 115 173

Decontamination 93 226 321 482

Restocking 421 1,019 1,448 2,174

Total 1,163 3,268 4,700 7,201

Compensation for culled animals 33 88 127 184

Cost to industry (net of compensation)

1,130 3,180 4,573 7,017

a 25 per cent of the 1,000 realisations had control costs equal to or lower than these amounts. b 50 per cent of observations had control costs equal to or lower than the median and 50 per cent were higher. c Refers to the average (mean) cost across all realisations. Mean value is higher than median value because of a small number of realisations with very high control costs. d 25 per cent of realisations were equal to or above these amounts. This implies that the chance that control costs would be below these values is 75 per cent. Source: ABARES

Outbreak control costs (Table 6) were calculated using estimates for an average Australian lamb, wool and stud farm. However, these costs would vary between individual farms. Control costs for an infected stud farm would be much higher because the value of culled breeding animals would be much higher and movement restrictions would prevent the sale of breeding stock.

Like other key indicators of the eradication campaign, (see Figure 6, Figure 7), total control costs had a frequency count with a large number of small values, and a small number of much larger values (Figure 8). The likelihood that the total control cost could be around $20 million is small, but the chance that it would not exceed $7.0 million in present value terms is 75 per cent (Table 6 and Figure 8).

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Box 1 Rationale for using a 7 per cent discount rate to calculate present values

This report presents the economic impacts of a hypothetical scrapie incursion in present value terms, using a discount rate of 7 per cent a year. It is necessary to discount costs and benefits received in the future because a dollar received today can be invested and earn a return. Therefore a dollar received today is worth more than a dollar received in the future.

The choice of discount rate is important as it can affect whether an investment yields a positive net present value (a benefit-cost ratio greater than one). It can also influence the relative profitability of alternative response strategies in a biosecurity investment project and of different projects when costs and benefits occur over different time frames. A higher discount rate favours eradication strategies that yield benefits in early years over others that yield benefits in later years. For example, the red imported fire ant could take 70 years to spread across the Australian continent, with most damage likely to be realised towards the end of this time horizon (Hafi et al. 2013). Therefore, a high discount rate would heavily discount the impact in this case.

Harrison (2010) identified two options for choosing a discount rate: a descriptive approach and a prescriptive or normative approach. Adopting the descriptive approach means choosing a discount rate based on the opportunity cost of funds sourced from the private sector. This recognises that market rates reflect the opportunity cost of investing in public projects as well. The prescriptive approach involves considering various ethical issues (such as intergenerational equity) and therefore favours lower discount rates to balance equity and efficiency. However, using low discount rates when market rates of return are relatively high could make future generations worse off. Harrison (2010) found that the marginal return to capital over the four decades to 2010 averaged approximately 9 per cent in real terms.

Harrison (2010) recommended a real discount rate of 8 per cent for use with sensitivity tests done at 3 per cent and 10 per cent. The Australian Government (2007) Best practice regulation handbook recommends a real discount rate of 7 per cent for use with sensitivity tests done at 3 per cent and 11 per cent. In its Cost-benefit analysis guidance note, the Australian Government (2016) largely maintained its 2007 recommendation but reduced the upper bound discount rate for sensitivity tests to 10 per cent. Consistent with these recommendations, ABARES adopted a real discount rate of 7 per cent.

The default discount rate recommended by the Australian Government (2016) and Harrison (2010) is an average discount rate based on the weighted average of long-term marginal rates of return to capital. Market rates of return include a market risk premium. Therefore, a discount rate based on the weighted average market rate of return is appropriate for a publicly funded biosecurity investment project because the risk level is generally similar to that of the average private sector investment. Harrison (2010) recommends that the practitioners conduct sensitivity analysis at lower and higher discount rates because of the considerable imprecision in estimated weighted average market rate of returns. This is a result of lack of clarity on appropriate risk premium and weights to be used (Harrison 2010). The low discount rates are based on the average rate of return for risk-free assets and the high discount rates for riskier assets (Harrison 2010).

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Figure 8 Frequency distribution of control costs by affected farms

Note: Graph (a) shows the number of simulations (out of 1,000) for each value of control costs, and graph (b) shows the same information, but presented as the estimated probability that control costs will be equal to or lower than each amount shown on the horizontal axis. The colours in graph (a) indicate the frequency of different values, with red indicating the most frequent values and the greener shades indicating less frequent values. Source: ABARES

Direct economic impacts of export ban ABARES used its partial equilibrium model of markets for key agricultural commodities produced in Australia to simulate the market impacts for the three disease spread scenarios: eradication, managed spread and uncontrolled spread. See Appendix E for a summary of the key features of the model and Thorpe and Klijn (2002) for full documentation of the model.

ABARES incorporated market impacts into the model by taking into account estimated reductions in export demand from China, Japan and the Republic of Korea and estimated duration of export bans (see Chapter 3). The model also allows for flow-on impacts to other agriculture sectors—namely, broadacre industries not directly affected by scrapie—through the reallocation of land away from sheep enterprises.

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Three-month export ban Sheep meat products only The model projects that in the first year of a scrapie outbreak (compared to baseline of no scrapie outbreak) prices would fall as a result of Chinese and Japanese markets closing to Australian sheep meat (Figure 9). The consequences would be:

• Farmers would respond to lower prices by withdrawing animals from sale. This would lead to an increase in herd numbers and a corresponding fall in production in that year.

• Sheep meat prices would start to recover as exports to China and Japan resume in the second year. This would result in a run-down of herd numbers and an increase in slaughter and meat production.

• Meat production would increase to higher than baseline by the end of the second year.

• Sheep meat production would then decline as stock run-down slows. It would remain above the baseline level until the fifth year before converging to baseline stock levels. Prices would also converge around the same time.

• In the first four years, herd numbers would remain above the baseline level.

• Prices would remain at the baseline level in the third and fourth year. Prices would decrease slightly (by 0.2 per cent) in the fifth year. This is not consistent with the movement of herd numbers, slaughter and production and has been ignored.

• As a result of higher animal numbers, wool production would remain above the baseline level for the first three years. Consequently, wool prices would be lower than baseline.

Figure 9 Effect of three-month ban on sheep meat—percentage change from baseline

Note: Shows the percentage difference between a three-month export ban on sheep meat products to Japan and China compared to baseline of no scrapie outbreak. Trade in wool products is not disrupted. Changes in wool price and production are result of changes in sheep meat production profitability. Source: ABARES

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Sheep meat and beef products The model projects that in the first year of a scrapie outbreak (compared to baseline of no scrapie outbreak) prices for beef would fall as a result of the Korean market closing at the same time as Chinese and Japanese markets closed to Australian sheep meat (Figure 10). The consequences would be:

• Beef prices would fall in the first year following the closure of the Korean market.

• Farmers would respond to lower prices by withdrawing animals from sale. This would lead to a build-up of herd numbers and a fall in production in that year.

• Beef prices would start to recover as exports to Korea resume in the second year. This would lead to a run-down of herd numbers and an increase in slaughter and beef production above baseline level.

• Beef production would then decline as herd run-down slowed. It would remain above the baseline level until the fifth year before converging to baseline stock levels. Prices would also converge around the same time. During the first five years, herd numbers would also remain above baseline level before converging.

ABARES modelling found that Korea’s ban on Australian beef imports did not have significant flow-on effects to the sheep industry. Consequences for the sheep meat industry were similar in modelling for the sheep meat only ban and the sheep meat and beef ban.

Figure 10 Effect of three-month ban on sheep meat and a Korean ban on beef—percentage changes from baseline

Note: Shows percentage difference between a three-month export ban on sheep meat products to Japan and China and beef products to Republic of Korea compared to baseline of no scrapie outbreak. Trade in wool products is not disrupted. Changes in wool price and production are result of changes in profitability of sheep meat production. Source: ABARES

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A ban of three months was estimated to result in sheep meat prices falling by about 1.2 per cent and beef prices by 0.5 per cent in the first year. Revenue losses in the first year would be partly offset by revenue increases in subsequent years. Second-year revenue would be higher because lower prices would be more than offset by increased production volumes (Figure 11).

Figure 11 Changes in industry revenue—three month ban scenario

Note: Shows difference in annual industry revenue between a three-month export ban on sheep meat products to Japan and China and a three-month export ban on beef products to Republic of Korea compared to the baseline of no scrapie outbreak. Source: ABARES

Present value of revenue losses Three-month export ban ABARES estimated the present value of the trade impact to be $35 million over 10 years (Table 7) for the three-month export ban by China and Japan on sheep meat only. This estimate rises to $70 million over 10 years when this is combined with an export ban by Korea on beef. Exports for sheep meat and beef would resume on the assurance that sheep meat and beef products were sourced from accredited scrapie-free areas, that the outbreak was contained and that Australia had commenced eradication. The market ban would end after three months, regardless of how long it would take Australia to be free of scrapie.

One-year export ban Export bans on sheep meat of one year would increase the potential impact to an estimated $152 million over 10 years and on sheep meat and beef to $323 million over 10 years (see Appendix A).

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Extended export ban An extended ban (see Appendix B) on sheep meat products by China and Japan is less likely. However, if these markets imposed export bans until Australia regained ‘negligible-risk’ status under OIE guidelines, the potential impact could rise to $2.2 billion over 50 years (Table 7).

Table 7 Estimated present value of trade impacts following a scrapie outbreak

Scenario Sheep meat market Beef market Total

($ million) ($ million) ($ million)

Three-month ban—sheep meat only a 35 0 35

Three-month ban—sheep meat and beef b 34 36 70

Year-long ban—sheep meat only c 152 0 152

Year-long ban—sheep meat and beef d 158 165 323

Extended ban—sheep meat only e 2,234 0 2,234 a Exports to China and Japan only. b Sheep meat exports to China and Japan and beef to Republic of Korea. c Exports to China and Japan for one year. See also Appendix A. d Sheep meat exports to China and Japan and beef to Republic of Korea for one year. See also Appendix A. e Sheep meat exports to China and Japan average 15 years. See also Appendix B. Note: Present value calculated based on a discount factor of 7 per cent.

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5 The economic impact of a scrapie endemic—living with scrapie

Background In this chapter, ABARES estimates the direct economic costs to Australia’s livestock industries if scrapie could not be eradicated and became endemic in Australia’s sheep and goat populations.

In Chapter 2, the results of 1,000 stochastic realisations of the epidemic modelling showed that even the longest outbreak (50 years) was successfully eradicated. However, given the insidious nature of the disease, scrapie in sheep may not be detected until it is too widespread to be eradicable. Further, if scrapie became established in Australia’s feral goat population, eradication would likely be infeasible.

Key markets for Australian sheep meat products such as China and Japan might ban imports of Australian products indefinitely if scrapie became endemic. However, it is more likely that these two countries would ban imports for a shorter period (Chapter 3)—until Australia negotiated market access for products from certified disease-free areas or farms. A three month ban would limit the trade impact to an estimated $70 million (Chapter 4).

The economic impact of scrapie becoming endemic to Australia would not be limited to control costs and trade impacts. Scrapie-related productivity losses arising from mortality and reduced animal productivity would also need to be considered. Productivity impacts would vary depending on the proportion of the Australian sheep and goat populations with susceptible genotypes and disease prevalence and mortality rates among susceptible flocks. Production losses would increase as the disease spread through Australia’s genetically susceptible sheep and goat populations.

In countries with endemic scrapie, the spread has been very slow and prevalence rates low. In the United States, scrapie was detected in 1947 but by 2003 prevalence in sheep was estimated at only 0.2 per cent. Scrapie has been present in Great Britain for over two centuries but only about 1.7 per cent of the sheep flock is affected. This is projected to reach 4 per cent by 2100 (Gubbins 2005). These reported prevalence rates are indicative of disease spread under current control programs. Rates are likely to be higher in the absence of appropriate control measures and taking into account possible under-reporting or non-detection of scrapie by farmers.

Modelling spread To model disease spread in the endemic scenario, ABARES used the epidemic model (Chapter 1) without control measures aimed at eradication. This model assumes a 10-year gap between disease introduction and first reporting. It also assumed that control measures are implemented after first detection so that scrapie would not continue to spread uncontrolled throughout the population. ABARES assumed that the distribution of the Australian goat population was the same as the distribution of sheep population (because goat data were unavailable). This study assumes that control is limited to:

• statutory reporting of disease by farmers

• limited movement control on reported flocks

• compulsory slaughter of animals found to be infected

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• compulsory replacement of animals of susceptible genotypes in reported farms with resistant genotypes—similar to the UK Compulsory Scrapie Flocks Scheme (see Appendix F)

• surveillance—including non-slaughter surveillance (testing on reported and traced farms), slaughter-based surveillance (testing of apparently healthy animals at time of slaughter) and testing of samples taken from dead and fallen animals on-farm

• voluntary scrapie-free flock certification program, enabling farms to sell certified scrapie-free animals to markets—similar to the US Scrapie Free Flock Certification Program (see Appendix F)

• supporting regulatory measures—may include identifying individual animals using ear tags to facilitate tracing of animals that have been in contact with animals that have tested positive.

ABARES assumed three different levels of management effectiveness (due to limited availability of data on effectiveness of management actions) to model spread trajectories. ABARES also modelled a baseline scenario without management measures in place. Management measures were assumed to result in a 25 per cent, 50 per cent or 75 per cent reduction in within-flock and between-flock transmissions. These were modelled through the basic reproductive number parameter Ro (see Table 1) from the levels assumed for uncontrolled spread.

Initial results all showed an exponential growth in disease prevalence regardless of the assumed level of reduction in transmission incorporated into the model. This was different from the patterns observed in Great Britain and the United States—where the prevalence rate approached an upper limit. This is because although the alternative spread scenarios with management assume lower base rates of transmission, the likely impact of management on reducing the transmission rate over time is not incorporated in the model.

Transmission rates would be expected fall over time as producers better manage scrapie risk and replace animals with susceptible genotypes with resistant genotypes through natural selection and breeding programs. This suggests that an S-shaped (logistic) curve rather than an exponential growth curve would better simulate the long-term spread of scrapie. In the absence of a model incorporating complex epidemiological relationships that would have produced a more realistic spread time trajectory, the prevalence rates with management measures in place—estimated with the simple spread model—were capped once the percentage of flocks reported as infected reached 1.6 per cent (Figure 12) (based on Gubbins 2005). This abrupt prevalence rate capping did not result in a significant overestimation of impacts realised in years around the 50th year (when spread is expected to continue decreasing rather than increasing as modelled), because they are discounted heavily to obtain present values.

The spread of scrapie across the national flock is expected to result in new exposed (latent) and infected flocks each year. Not all infected flocks are likely to be reported (despite the statutory requirement). Therefore, ABARES has assumed that reported prevalence rates in any year are lower than the percentage of flocks infected.

Figure 12 shows time trajectories of the percentage of flocks categorised as latent or infected, infected, infected and reported, and infected with no control measures (baseline). The percentage of flocks affected by scrapie increases exponentially to around 50 years with management measures in place. The greater the reduction in transmission brought about by management measures, the slower the spread of disease and the longer the time taken to reach the maximum rate. Without management measures in place, scrapie would be expected to spread to all Australian sheep and goat flocks in 75 years.

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Figure 12 Spread of scrapie under endemic scenario

Notes: The disease spread model has three categories of flocks: unaffected, latent (that is, exposed to the disease) and infected. Not all cases of scrapie are reported, so the percentage of reported flocks is likely to be lower than actual infected flock numbers. When management measures are in place, the prevalence of scrapie is capped once the percentage of flocks reporting the disease reaches 1.6 per cent—this reflects the experience of other scrapie-endemic countries including the United States and the United Kingdom. In the absence of scrapie-management measures (Figure d), the spread of scrapie continues exponentially. Source: ABARES

Economic cost The economic cost of endemic scrapie would have private and public costs. Private costs include:

• income losses from increased livestock mortality

• income losses from quarantine measures and movement controls affecting selling activities of reported farms

• government control program compliance costs: surveillance measures, scrapie-free flock certification programs, compulsory replacement of animals and supporting regulatory measures

• contributions to research and development on breeding resistant genotypes through Australian Wool Innovation and Meat & Livestock Australia.

Public costs include:

• compensation to farmers for removal of scrapie-susceptible and scrapie-positive animals on reported farms

• implementation of surveillance measures, a scrapie-free flock certification program, compulsory replacement of animals and supporting regulatory measures

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• government-funded selection and breeding of resistant genotypes and related research.

Given the similarity to Johne’s disease, which started spreading uncontrolled across Australia’s national sheep flock in 1996, the department expects an initiative similar to the National Johne’s Disease Project would be developed if efforts to eradicate scrapie failed. A national project to manage scrapie spread would most likely be developed to coordinate government and industry activities in market assurance (a scrapie-free flock certification program), disease management, genotype testing and removal of susceptible animals, selection and breeding of resistant genotypes, and related research.

This study estimated the income losses associated with increased mortality and quarantine measures (private costs) and compensation paid to farmers for animals removed (public cost) for managed spread. For uncontrolled spread, ABARES estimated income losses associated with increased mortality only.

Private costs: income losses from increased mortality and quarantine Annual losses per affected farm The annual mortality rate attributed to scrapie in an infected sheep flock could typically be 3 per cent to 5 per cent and as high as 20 per cent in a severely-infected flock. ABARES estimated associated income losses by assuming the mortality rate to be randomly distributed with a minimum value (3 per cent), a most likely value (4 per cent) and a maximum value (20 per cent). This distribution is based on the Beta-pert probability distribution, traditionally used when knowledge of underlying parameters is limited. The effect of increased mortality on farm-level gross margins was estimated by taking 10,000 random draws from the mortality distribution and calculating the effect on farm income for each draw using farm profiles shown in Table 5.

Quarantine restrictions and movement controls would be placed on infected flocks only after scrapie has been reported. Farms with infected flocks would incur additional losses because of restrictions imposed on sale of infected animals. ABARES modelled income losses from these restrictions by assuming a reduction in saleyard prices. ABARES assumed a 10 per cent price discount for wool and lamb specialist farms (similar to eradication, Chapter 4), following the assumptions of Topp and Bailey (2001) in their study on estimating similar losses for Johne’s disease. For sheep studs under quarantine, rams were assumed to sell at the average price of an adult sheep for slaughter ($77 per head) instead of the usual price received for healthy stud rams ($611 per head).

Figure 13 shows frequency distributions of gross margin losses for infected flocks (reported and unreported). Gross margins for wool farms reported to have scrapie are estimated to be reduced by an average of $51,300 a year, for lamb farms $57,600 and for stud specialist farms $113,300. Annual reductions in gross margins for farms with unreported infected flocks were estimated to be $21,400 for wool farms, $41,800 for lamb farms and $26,200 for stud specialist farms. The comparatively large increase in losses for reported stud farms would largely be explained by the heavy discounting of the price of stud rams when sold as sheep for slaughter.

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Figure 13 Reduction in gross margins for scrapie infected sheep flocks a

a Reduction in gross margin includes costs of increased mortality and quarantine measures. Note: Costs are higher for farms that report scrapie because of additional cost of quarantine measures, which restrict the sale and movement of animals. The colours in the graphs indicate the frequency of different values, with red indicating the most frequent values and the greener shades indicating less frequent values. Source: ABARES

Present value of income losses for industry ABARES estimated aggregate income losses for each year by multiplying the number of infected flocks for each farm type (lamb, wool and stud specialist) by the corresponding farm level gross margin losses shown in Figure 13. The resulting time trajectories of income losses closely followed those of growth in infected flocks under controlled spread (Figure 12). These time trajectories of income losses (undiscounted) were then discounted using a 7 per cent discount rate and summed over 75 years to estimate the present value of income losses to the industry. See Figure 14 for present value of income losses estimated this way.

Present value of income losses with control measures in place ranged from $29 million to $41 million in 2016 dollars (Figure 14). Present value of losses over 75 years for uncontrolled spread were estimated to be $83 million. Therefore, control measures led to savings (avoided losses) ranging from $42 million with 25 per cent reduction in transmission to $54 million with 75 per cent reduction in transmission.

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Figure 14 Present value of income losses over 75 years

Note: Present value based on a 7 per cent discount rate. Values between the black horizontal lines are the middle 50 per cent of the distribution. Income losses for reported flocks (Figure b) are the sum of losses from increased mortality and quarantine restrictions. Unreported flocks are not subject to quarantine restrictions so losses are from increased mortality only (Figure a). Source: ABARES estimates

Public costs: compensation for culled animals ABARES assumed that reporting of an infected flock would lead to any animals testing positive for scrapie being slaughtered and compensation paid to affected farmers. Scrapie tests conducted on live sheep are not fully reliable so authorities may decide to test genotypes in reported flocks to isolate all susceptible animals. Susceptible animals would then be slaughtered and the farmer paid compensation at market value, as specified in the Government and livestock industry cost-sharing deed in respect of emergency animal disease responses (Animal Health Australia 2016).

The market value of culled infected animals was estimated assuming an average of 284 animals testing positive for each farm (as for the eradication scenario, chapter 4). Market value of culled animals in this group was estimated assuming the proportion of susceptible animals in a flock at 20 per cent, 30 per cent and 40 per cent.

Present value of compensation costs for industry Time trajectories for annual compensation costs to cull infected or susceptible animals follow a similar pattern to those of growth in infected or reported flocks under controlled spread (Figure 12).

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ABARES estimated aggregate compensation costs to cull infected and susceptible animals for each year by multiplying the number of infected flocks (for transmission rates of 25 per cent, 50 per cent and 75 per cent) by the estimated compensation cost paid to each farm. Resulting time trajectories for compensation costs for infected and susceptible animals were then discounted using a 7 per cent discount rate and summed over 75 years to estimate the present value of compensation costs to the industry.

Figure 15 shows present value of industry compensation costs for removal of infected animals. Total industry compensation costs for infected animals ranged from $6 million to $8 million and the total including all genetically susceptible animals ranged from $20 million to $39 million. These estimates varied according to the effectiveness of management measures (percentage reduction in transmission rates achieved) and the proportion of susceptible animals in the Australian flock.

Figure 15 Present value of compensation costs

Notes: Present value calculated based on a 7 per cent discount rate. Because of uncertainty about effectiveness of control measures in achieving a reduction in transmission rates, and in the percentage of genetically susceptible animals in the Australian flock, compensation costs were calculated for three different levels of transmission reduction (25, 50 and 75 per cent), and three different percentages of genetically susceptible animals (20, 30 and 40 per cent). Compensation is paid for culled animals, which includes infected animals, and genetically susceptible animals in affected flocks. Source: ABARES

Overall costs and benefits for managed spread Figure 16 shows present value of total costs over 75 years (excluding trade losses, calculated separately in Chapter 4). Costs are calculated for the three genetic susceptibility levels (20 per cent, 30 per cent and 40 per cent of the Australian sheep flock), three assumptions about management measure effectiveness in reducing the rate of transmission (25 per cent,

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50 per cent and 75 per cent) and for uncontrolled spread (0 per cent reduction in transmission). Present value of losses over 75 years ranged from $49 million to $80 million (Figure 16).

Figure 16 Overall cost of endemic scrapie by percentage of susceptible animals a

a Does not include trade losses. See Chapter 4. Note: Present value estimated over 75 years based on a 7 per cent discount rate. Overall impact includes mortality increases, lost income from quarantine measures and compensation for culled livestock. Values between the black horizontal lines are the middle 50 per cent of the distribution. Source: ABARES

In present value terms over 75 years, uncontrolled spread of scrapie was estimated to cost $83 million to the industry. This figure is higher than estimated total costs for controlled spread for all assumed levels of management effectiveness and genetic susceptibility. Therefore, an investment in slowing the spread of scrapie would yield positive net benefits to the industry—ranging from $3 million (when genetic susceptibility is high and management effectiveness is low) to $34 million (when genetic susceptibility is low and management effectiveness is high) in present value terms.

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6 Framework for policy evaluation This chapter illustrates how the Australian Government could use modelling results from this study to evaluate expected benefits of investing in biosecurity measures.

Prevention, eradication and slowing the spread of scrapie can be viewed as a set of sequential response measures along the biosecurity continuum (pre-border, at the border and post-border). This framework represents the costs and potential losses estimated in this study to inform policy decision-making (Figure 17). Scrapie could be managed to avoid costs through:

• prevention—avoided eradication costs including post-border detection costs and production and trade losses associated with eradication of infected and susceptible stock

• eradication—avoided program costs and production and trade losses associated with slowing the spread of scrapie

• containment—avoided losses associated with uncontrolled spread of scrapie.

Potential costs of implementing these measures include:

• prevention—pre-border and border biosecurity costs

• eradication—eradication program cost including post-border detection cost, and production and trade losses resulting from an epidemic

• containment—control program cost and any residual production and trade losses.

Figure 17 Prevention, eradication and slowing the spread

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Figure 17 shows the potential costs and benefits of investment in the three biosecurity activities: prevention, eradication and slowing the spread. They are shown as a sequential set of response measures where the control measure in any of the inner boxes (eradication or slowing the spread) only become necessary if the measure in the outer box (prevention or eradication, respectively) fails. This means that the benefits of successfully implementing the measure in the outer box (prevention or eradication) can be measured in terms of avoided losses associated with the inner measure (eradication or slowing the spread, respectively).

Eradication follows failed prevention, so potential costs associated with eradication also equate to the benefit from investment in prevention. Likewise, costs of managing the spread of scrapie equate to the benefits from investment in eradication. Slowing the spread (in the case of failed eradication) is beneficial if potential losses from uncontrolled spread are larger than potential losses from managing the spread.

Benefits and costs associated with prevention, eradication and managing the spread differ. This section presents benefit-cost ratio estimates for investment in each response measure.

Table 8 shows key modelling results for benefits (avoided costs and losses) and costs associated with prevention, eradication and management. Note that Table 8 does not list the costs of implementing eradication and the management programs, as the relevant information was not available.

Table 8 Summary of costs and benefits estimated for epidemic and endemic scenarios

Item Eradication (epidemic scenario)

($m)

Managed spread (endemic scenario)

($m)

Uncontrolled spread (no

management) ($m)

Costs from lost income

Movement control and productivity 3 29–41 83

Trade losses 70 70 >323

Costs of control

Compensation for culled animals – 20–39 –

Culling, sanitary disposal, decontamination and restocking

2 – –

Program cost na na na

Total costs 75 119–150 >406

Net benefits relative to managed spread 44–75 na na

Net benefits relative to uncontrolled spread na >256 na

na not applicable Source: ABARES

Eradication Benefits of successful eradication were estimated at between $44 million and $75 million. This would be equal to total losses avoided with managed spread ($119 million to $150 million) over and above losses associated with eradication ($75 million). Benefits are the difference between net costs for management and eradication, noting that trade effects cancel out. This assumes probability of success for management is 100 per cent. ABARES assumed (due to absence of data) a cost of $3 million to run epidemic control centres, so total eradication cost was $8 million

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($3 million plus $5 million in other non-trade related costs). See Table 8. Investment in eradication is likely to yield a benefit-cost ratio ranging from 5:1 to 10:1.

Managed spread Management measures would be expected to avoid potential losses of uncontrolled spread over and above losses associated with slower spread. Incremental losses have two components: movement control costs plus productivity losses estimated at between $42 million and $54 million ($83 million less $29 million to 41 million) and trade losses associated with uncontrolled spread over and above an estimated $70 million losses for the three-month export ban.

Trade losses in the uncontrolled spread scenario would likely be higher than under eradication or managed spread, as Australia would not be able to provide assurances that exports were coming from unaffected farms. If the trade losses under the uncontrolled spread scenario are assumed to be equal to trade losses of $323 million estimated for the year-long ban scenario, then the potential trade losses over and above slower spread scenario are estimated to be $253 million ($323 million less $70 million). This estimate is based on the assumption that Australia would find alternative markets within one year and that these markets would purchase excess Australian supply from year 2 onwards at the same price as offered by China, Japan and Republic of Korea. Estimated total avoided losses range from $295 million to $307 million ($253 million plus $42 million to $54 million) when management and trade loss impacts are combined.

A management program to slow the spread would include replacement of susceptible animals and several other activities such as surveillance, scrapie-free flock certification and enforcement of supporting regulatory measures (animal identification). Therefore, it could cost more than the $20 million to $39 million estimated in compensation for culled animals only. Management measures to slow the spread are expected to yield a benefit-cost ratio of approximately 6:1 if a total cost of $50 million is assumed.

Prevention Information about the cost and effectiveness of biosecurity activities aimed at preventing the entry of scrapie to Australia can be combined with estimates in this report to evaluate the cost effectiveness of prevention activities. The estimated cost associated with a scrapie epidemic ($75 million) assumes a 100 per cent probability of entry and a 100 per cent probability of success in eradication. Uncertainty of entry could be incorporated into the evaluation process by comparing costs of prevention with expected benefit—estimated avoided losses plus the eradication cost associated with the epidemic—weighted by the probability of entry.

Decision-makers could calculate a break-even or threshold probability that equates the expected benefit with cost if probability of entry is unknown. Awareness of potential benefits could also help the department to estimate the maximum investment in prevention at different probabilities of entry. For investment in scrapie prevention to be economically feasible, prevention activities should not cost more than the estimated impact of an epidemic multiplied by the reduction in the probability of entry. For example, were proposed new measures expected to reduce the probability of entry by one percentage point a year, they must cost less than an estimated $750,000 a year (1 per cent of $75 million) to be cost effective, assuming that scrapie is detected and eradicated each time it enters.

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Conclusion The results indicate that Australia would likely benefit from preventing the entry of scrapie and detecting it early if it enters. Early detection would increase the likelihood of eradication being both successful and cost effective. If detected within 10 years of entry, ABARES estimates that scrapie could, on average, be eradicated within eight years at a total cost of $75 million under the most likely scenario: an eradicable scrapie epidemic that involved 3-month export bans on beef and sheep meat (scenario 1).

The total cost under this eradication scenario is likely to be less than the cost of slowing the spread if eradication failed, which is estimated to be in the range $119 million to $150 million. Hence, early detection is vital. International experience shows that scrapie is very difficult to eradicate once it becomes established. Countries such as the United Kingdom and the United States have not been able to eradicate scrapie, despite significant effort (see Appendix F).

If a scrapie outbreak was detected late and deemed ineradicable, it would likely be cost effective for Australia to implement measures to slow the spread. ABARES estimates the cost of an uncontrolled spread to exceed $406 million.

Thus, maintaining strong prevention measures is likely to be cost effective, especially as there is no evidence that scrapie has entered Australia. Were government to propose additional measures, ABARES modelling indicates that it would be economically feasible to spend up to $750,000 for each percentage point reduction in the likelihood of a scrapie epidemic.

Accurately estimating the economic impact of a scrapie outbreak in Australia was challenging because of high uncertainty around key disease spread parameters and the reaction of trading partners. Spread modelling was limited to one scenario of one farm in New South Wales or Victoria becoming infected through genetic material, with the disease going undetected for 10 years. Were genetic material from the same donor to infect multiple farms, the length of the outbreak and eradication costs would likely be much higher. The analysis was further limited by a lack of data for other key parameters, namely: the costs to operate local control centres; the proportion of the Australian sheep population susceptible to scrapie; and the distribution of the Australian goat population. Despite these limitations, the results indicate that there are likely to be significant benefits to Australia from remaining scrapie free.

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Appendix A: One-year export ban ABARES modelled the trade impacts of a one-year ban on Australian sheep meat imports by China and Japan. In this scenario, Australia negotiates a resumption of trade with these countries by offering assurances that meat would be sourced from unaffected farms. ABARES also modelled an interruption of beef exports to the Republic of Korea. This is based on the requirement that Australian exporters include an attestation that Australia is free of scrapie on export certificates for a range of beef and sheep meat products to Korea.

Sheep meat only Under this scenario, a scrapie outbreak in Australia would lead to closure of the Chinese and Japanese markets for Australian sheep meat. In the first year, domestic sheep meat prices would fall (Figure A1) and Australian farmers would respond by withdrawing animals from sale. This would lead to a build-up of herd numbers and a fall in production in that year.

Figure A1 One-year export ban on Australian sheep meat, effect on industry

percentage change from baseline

Note: Shows percentage difference between baseline scenario (no scrapie outbreak) and year-long ban scenario, where a scrapie outbreak in Australia would result in China and Japan banning sheep meat products for one year. Source: ABARES

In the second year, domestic sheep meat prices would start to recover as exports to China and Japan resumed. As a result, farmers would reduce herd numbers and slaughter and meat production would increase above the baseline level by the end of the second year. As stock run-

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down slowed, sheep meat production would decline, gradually converging to the baseline level. After the fifth year, prices would converge back to the baseline.

During the first four years, herd numbers would remain above the baseline level, before gradually converging. During this period, higher animal numbers would result in wool production remaining above the baseline level. Consequently, prices of wool would be lower than they would have been without the ban on sheep meat.

The present value of revenue losses under this scenario would be $152 million.

Sheep meat and beef Under this scenario, a scrapie outbreak in Australia would lead to closure of the:

• Chinese and Japanese markets for Australian sheep meat

• Korean market for Australian beef.

In the first year, domestic beef prices would fall (Figure A2) and Australian farmers would respond by withdrawing animals from sale. This would lead to a build-up of herd numbers and a fall in production in that year.

In the second year, domestic beef prices would start to recover as exports to Korea resumed. As a result, farmers would reduce herd numbers and beef production would increase above the baseline level. As stock run-down slowed, beef production would decline. Production would remain above the baseline level before converging in the fifth year and prices would converge at around the same time.

During the first five years, herd numbers would also remain above the baseline level.

The present value of revenue losses under this scenario would be $323 million. The Korean ban on Australian beef would comprise $165 million of that total.

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Figure A2 One-year export ban on Australian sheep meat and beef, effect on industry

percentage change from baseline

Note: Shows percentage difference between baseline scenario (no scrapie outbreak) and one-year ban scenario, where a scrapie outbreak in Australia would result in China and Japan banning sheep meat products and the Republic of Korea banning beef for one year. Source: ABARES

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Appendix B: Extended export ban Under this scenario, China and Japan would ban imports of Australian sheep meat products until Australia regained its negligible-risk status for scrapie (under OIE guidelines)—15 years on average according to disease spread modelling (Chapter 2).

In the first year, domestic prices of sheep meat would fall (Figure B1a). Producers would anticipate ongoing trade disruptions and resulting lower prices by reducing stock numbers. This would lead to higher sheep turn-off and more meat being produced despite significantly lower prices.

From the second year, production of sheep meat would start to fall below the baseline and prices would improve but remain below the baseline level. Lower prices for sheep meat would result in a long-term reduction in sheep numbers of around 3 per cent. This would reduce the supply of wool and contribute to an increase in the wool price in future years (Figure B1b).

Figure B1 Extended export ban on Australian sheep meat, effect on industry

percentage change from baseline

Note: Shows percentage difference between baseline scenario (no scrapie outbreak) and extended export ban scenario, where a scrapie outbreak in Australia would result in China and Japan banning sheep meat products for up to 15 years. Source: ABARES

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Impacts on industry revenue Under this scenario, the Australian sheep meat and wool industry would lose an estimated $300 million a year (Figure B2). Sheep meat industry revenue would decline. However, wool industry revenue would remain relatively unchanged over the 15-year projection period because the decline in revenue from reduced wool production would be largely offset by increased wool prices.

Figure B2 Impacts on industry revenue

Note: Shows percentage difference between baseline scenario (no scrapie outbreak) and the three export ban scenarios: an extended export ban on sheep meat by China and Korea until Australia regains negligible-risk status for scrapie under OIE guidelines (average 15 years), and a year-long ban scenario, where a scrapie outbreak in Australia would result in China and Japan banning sheep meat products and the Republic of Korea banning beef for one year. Source: ABARES

Present value of revenue losses under extended export ban scenario The present value of annual losses varies between stochastic simulations, depending on the length of the market ban—which ranges from eight to 55 years (the length of the outbreak plus seven years negative surveillance).

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The model projects market variables and annual revenues for the next 10 years only, but most stochastic realisations had market bans extending beyond 10 years. Annual revenue losses from the 11th year onward are assumed to be equal to the 10th year because sheep meat prices and production levels appear to steady at around that time. Figure B3 shows that under the extended export scenario, a scrapie outbreak would cost on average an estimated $2.2 billion (with a 75 per cent chance that the impact would be under $3.2 billion).

Figure B3 Extended export ban scenario, frequency distribution of revenue losses (present value)

Note: Under this scenario, a scrapie outbreak in Australia would result in China and Japan banning sheep meat products for up to 15 years. The colours in the graphs indicate the frequency of different values, with red indicating the most frequent values and the greener shades indicating less frequent values. Source: ABARES

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Appendix C: Incidence of scrapie worldwide

Table C1 Scrapie status, as reported to the World Organisation for Animal Health, 2005–2016

Country Years reported

Belgium 2005–2007

Brazil 2005–2013, 2016

Bulgaria 2008–2010

Canada 2005–2016

Cyprus 2005–2016

Czech Republic 2005, 2007, 2008, 2014

Finland 2005–2007, 2009, 2010, 2012

France 2005–2013 a

Germany 2005–2008, 2010–2016

Greece 2005–2015 b

Hungary 2006–2014 a

Iceland 2005–2010,2012, 2014–2016 a

Ireland 2005–2016

Israel 2007, 2008, 2012–2016 a,c

Italy 2005–2016

Japan 2005, 2011, 2012, 2016 a

Libya 2014–2015 a

Netherlands 2005–2012

Norway 2005–2016

Palestinian Autonomous Territories 2005, 2007–2009, 2012–2016 a

Portugal 2008–2013, 2016

Romania 2005–2016 a

Russian Federation 2005 a

Sierra Leone 2013–2014 a, c

Slovakia 2005–2016

Slovenia 2005–2010

Somalia 2015

Spain 2005–2016 a

Switzerland 2005

Tajikistan 2005

Tanzania 2005–2007 a, c, d

Timor Leste 2016

United Kingdom 2005–2016

United States 2005–2016

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a Scrapie limited to one or more zones in latest report. b No status reports submitted in 2016. c Scrapie suspected but not confirmed in latest report. d No status reports submitted since 2007. Note: Not all countries have scrapie surveillance programs in place, so not all scrapie outbreaks are reported to the World Organisation for Animal Health. Source: World Organisation for Animal Health (OIE 2017)

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Appendix D: Export certification requirements

Table D1 Markets and commodities requiring scrapie-free certification, as at June 2017

Market Commodity

Algeria Casings

American Samoa Lamb to be on-shipped to Mexico after entering the United States Calf lungs for pharmacological purposes

Argentina Runners Frozen green sheep runners for pharmacological purposes

Belarus Beef meat and edible offal Sheep/goat meat and edible offal Venison and edible offal Skins and hides Pet meat and pet food

Bosnia Skins and hides

Brazil Sheep/goat meat and edible offal Runners exported as dried casings

Cameroon Beef/sheep/goat meat and edible offal

Egypt Calf vells

French Polynesia Meat and edible offal; meat carcase; chilled meat Canned meat Rabbit meat and edible offal Casings Pet food and stockfeed Organic fertiliser of animal origin Rendered feed for non-ruminants destined for human consumption

Guam Lamb to be on-shipped to Mexico after entering the United States Calf lungs for pharmacological purposes

Hong Kong Deer tails, tendons and pizzles

Indonesia Meat and bone meal, poultry meal, feather meal

Iran Beef/sheep meat Ship stores Runners Inedible tallow

Israel Blood products from all species for laboratory use

Kazakhstan Beef meat and edible offal Sheep meat and edible offal Venison and edible offal Skins and hides Pet food

Latvia Sheep and goat meat

Mexico Meat and edible offal

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Market Commodity

New Caledonia Meat and bone meal

Northern Mariana Islands Lamb to be on-shipped to Mexico after entering the United States Collagen splits

Papua New Guinea Mammalian meat and bone meals including blood meal and stockfeeds containing mammalian rendered products Non-mammalian meals, including stockfeeds containing non-mammalian products

Philippines Meat and bone meal

Puerto Rico Lamb to be on-shipped to Mexico after entering the United States Calf lungs for pharmacological purposes

Romania Bovine, ovine and porcine meat and meat products

Russian Federation Beef meat and edible offal Sheep/goat meat and edible offal Venison and edible offal Skins and hides Raw pet meat and heat treated processed pet food Mechanically recovered meat Meat fractions Casings Domestic sourced sheep runners further processed as casings in an export registered establishment Gelatine Spray-dried blood plasma for processing into pet food Canned pet food Dried pet food Ram or bull testes for pharmacological purposes Inedible tallow Meat and bone meal, including carcase meal and poultry Fertiliser containing meat and bone meal

Republic of Korea Frozen beef meat, meat products and edible offal Chilled beef meat, meat products and edible offal Unrefrigerated beef meat products Sheep meat, meat products and edible offal Bone-in goat carcases from domesticated goats Deer meat, meat products and edible offal (including blood) Meat, meat products and edible offal (excluding beef, sheep, goat and deer) Beef casings Sheep and pig casings Edible tallow Wool (including greasy wool) Skins and hides (excluding deer, kangaroo and ostrich) Deer skins and hides Ostrich hides Raw pet meat and processed pet food

Trinidad and Tobago Sheep meat, meat products and edible offal

Tunisia Sheep meat

Turkey Casings

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Market Commodity Carry-on packs, personal consignments and trade samples Green runners Processed pet food

Ukraine Beef meat and edible offal Sheep meat and edible offal Skins and hides

United States Lamb to be on-shipped to Mexico after entering the United States Calf lungs for pharmacological purposes

US Minor Outlying Islands Lamb to be on-shipped to Mexico after entering the United States Calf lungs for pharmacological purposes

Uzbekistan Beef meat, meat products and edible offal

Vietnam Animal by-products (containing ruminant material) for animal feed production Animal by-products (excluding ruminant material) for animal feed production

Virgin Islands Lamb to be on-shipped to Mexico after entering the United States Calf lungs for pharmacological purposes

Wallis and Futuna Islands Meat and bone meal or stockfeeds containing meat and bone meal Source: Department of Agriculture and Water Resources

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Appendix E: ABARES partial equilibrium model

The ABARES partial equilibrium model (Thorpe & Klijn 2002) can be used to project the annual volume of agricultural commodities produced and consumed domestically and the excess supply exported to the rest of the world. Being a forward-looking partial equilibrium model, it also projects agricultural commodity prices that clear the markets by equating domestic production to the sum of domestic and export demands.

The model contains supply and demand equations for 15 agricultural commodities—including beef from grass-fed and feedlot cattle, beef and dairy products from dairy cattle, sheep meat and wool from sheep enterprises, pig meat, poultry and broadacre crop products. For livestock commodities, the model also incorporates the relationship between animal inventory and slaughter and how they are affected by changes in the price of meat products. Cropping and grazing activities in broadacre agriculture a subject to a land resource constraint.

For each commodity, domestic demand is a function of income (real gross domestic product) and price. The marginal cost of producing a commodity is a function of the quantity produced and the opportunity cost of land. The quantity produced is determined at the point where the price equals the marginal cost of production.

The model's forward-looking feature allows for early adjustments in livestock herd numbers to meet long-run equilibrium conditions. This feature assumes that producers have perfect information regarding future states of the agricultural production environment and the behaviour of their trading partners. This allows producers to make decisions each year that help maximise profits in the long run.

For example, following a scrapie outbreak, producers observe that the restrictions on exports are going to last one year—they have no option other than to sell the excess supply in the first year in the domestic market despite its price-depressing effect. When prices are low, maximising profits in the long run requires that producers keep animals by delaying their slaughter until they foresee higher prices.

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Appendix F: Overseas experience of scrapie

United Kingdom Scrapie has been present in UK sheep flocks for almost 300 years and has been a notifiable disease since 1993. Eradication of scrapie from national flocks became a priority in the late 1990s with the discovery of a link between Bovine spongiform encephalopathy (BSE) in cows and variant Creutzfeldt-Jakob disease in humans. UK authorities became concerned that scrapie, with its similar symptoms, could mask the possible existence of BSE in sheep (Boden et al. 2010).

In 2001 the National Scrapie Plan was introduced to eradicate scrapie by identifying existing cases and increasing the genetic resistance of the national flock. Active surveillance for scrapie began in 2002, with surveys of slaughtered stock and of fallen stock on-farm.

The UK Government’s 2004 Compulsory Scrapie Flocks Scheme (CSFS) provided for two disease control options for flocks with confirmed cases of scrapie:

• genotyping and a selective cull of susceptible genotypes

• culling of the entire flock.

The CSFS reduced the incidence of scrapie but costs were high, involving the slaughter and disposal of many apparently healthy sheep. Changes in EU requirements for transmissible spongiform encephalopathy (TSE) management in 2011 allowed the United Kingdom to implement measures that it considered more ‘proportionate to risk’, and that did not place an unnecessary burden on government and industry (DEFRA 2012).

In line with the EU changes, the UK Department for Environment, Food and Rural Affairs (DEFRA) moved away from genotyping and selective culling as the default option for scrapie-affected flocks towards a less costly monitoring approach. Under the monitoring approach, affected flocks are subject to movement restrictions and enhanced surveillance until no animal tests positive for two years. Animals can be slaughtered for human consumption, but those over 18 months of age must test negative for TSEs before entering the food chain. Government assistance is still available for genotyping and there are restrictions on animals that can be used for breeding.

According to DEFRA (2014), the annual cost of implementing a sampling program of 20,000 sheep and 500 goats is almost £600,000. The cost to government of the CSFS in an average year was estimated at £131,624, including culling infected and high-risk animals (transport, slaughter, incineration and compensation payments) and testing for TSEs and susceptible genotypes (DEFRA 2012). In contrast, the monitoring option would cost government an estimated £23,856—a saving of £107,768. (DEFRA 2012).

If Australia implemented similar programs, costs would probably be higher because the Australian sheep flock is larger—around 70 million animals in Australia, compared with around 33 million in the United Kingdom (ABS 2017a; DEFRA 2016).

Australian policymakers would have to factor in the additional cost of carcase splitting—where the spinal cords of sheep over 12 months of age are removed at the time of slaughter to prevent

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transmission of TSEs. The UK National Sheep Association estimated that carcase splitting costs their industry £23 million annually (NSA 2014).

United States Scrapie was discovered in the United States in 1947. Eradication efforts began with the introduction of the National Scrapie Eradication Program (NSEP) in 1952. Concerns about human health impacts of TSEs led to the introduction in 2001 of an accelerated version of the NSEP. This aimed to eradicate scrapie in the United States by 2018 and meet negligible-risk status for scrapie (under OIE guidelines). The NSEP plans to eradicate scrapie through:

• education and compliance education for producers and industry

• identification monitoring and compliance

• slaughter and non-slaughter based surveillance

• trace investigations

• flock monitoring for occurrence or recurrence of scrapie

• genetic testing and culling of exposed, genetically susceptible animals (with compensation paid at market prices for culled animals)

• voluntary participation in the scrapie-free flock certification system.

The voluntary scrapie-free flock certification system was introduced in 1992. Under this system, program participants commit to:

• reporting all suspect animals for testing

• monitoring flocks for signs of scrapie

• individual animal identification

• keeping accurate records

• testing a specified number of animals.

Benefits to participating producers include reduced risk of scrapie and increased export opportunities.

The NSEP sets annual sheep and goat sampling minimums in each state, with most sampling occurring through the Regulatory Scrapie Slaughter Surveillance program. The program targets mature sheep and goats with particular risk factors (including face colour and age) at the time of slaughter. The NSEP is targeting areas where sheep flocks have not been tested.

The NSEP has reduced the prevalence of scrapie in the United States. From 2002–03 to 2013–14, the prevalence of scrapie among culled sheep at slaughter (with data adjusted for differences in face colour of sheep sampled) declined by 88 per cent to 0.02 per cent (US Department of Agriculture 2015).

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Glossary Term Definition

attestation written assurances on export certificates that the goods being exported meet requirements of the importing country—for example, that Australia is free of scrapie

beta-pert distribution used to model a probability distribution when information is limited; useful when using expert opinion because it requires only minimum, maximum and most likely values

bovine spongiform encephalopathy

transmissible and fatal neurodegenerative disease of cattle that causes a spongiform degeneration of the brain and spinal cord. Variant Creutzfeldt-Jakob disease (vCJD) in humans thought to be a result of transmission of BSE.

caprine relating to goats

clinical disease disease that has recognisable signs and symptoms; scrapie can be asymptomatic for years before clinical signs emerge

export certificate export documentation issued by the Department of Agriculture and Water Resources to verify that commodity meets requirements of the Export Control Act 1982 and of the authorities of the importing country; the Manual of Importing Country Requirements (MICoR) provides guidance on requirements of importing countries

gross margin gross income from an enterprise less the variable costs incurred in achieving it; does not include fixed or overhead costs such as depreciation, interest payments, rates or permanent labour

notifiable livestock disease livestock disease that must be reported at the time of diagnosis because it is potentially dangerous to animal or human health

ovine relating to sheep

present value acknowledges that a dollar received today can be invested and earn a return; therefore a dollar received today is worth more than a dollar received in the future; in this study, future costs or benefits are discounted at the rate of 7 per cent a year

PrP (prion protein) potentially infectious agents composed entirely of protein material, which can fold in multiple, structurally distinct ways and lead to disease spread that resembles viral infections; thought to be causative agent in TSEs such as BSE and scrapie in animals and Creutzfeldt–Jakob disease in humans

ruminant any animal of the Artiodactyl suborder Ruminantia, which comprises the various cloven-hoofed and cud-chewing quadrupeds, as cattle, bison, buffalo, sheep, goats, chamois, deer, antelopes, giraffes, chevrotains

scrapie Fatal, degenerative disease affecting the nervous systems of sheep and goats. One of several TSEs—not considered transmissible to humans

stochastic process includes a random element, so the result cannot be predicted precisely; however, the probability of different outcomes can be analysed statistically

transmisible spongiform encephalopathies (TSEs)

A group of progressive and often fatal conditions affecting the brain and nervous system of many animals, including humans

turn-off number of livestock produced and available for market

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