You Are An Analyst At The Animal Health Agency AHA Must Make

You An Analyst At The Animal Health Agency Aha Must Make Areco

You, an analyst at the Animal Health Agency (AHA), must make a recommendation whether or not to ban imported pigs due to a risk of importing a disease, porcine hoof blister (PHB), or to require that imported pigs be tested for the disease. With no ban, the probability of an outbreak is known with 90% confidence to be in the range [0.2%, 5%], and the cost of dealing with an outbreak is known to be $1,000,000 (ultimately paid by the consumer). With a ban, there will be a 0% probability of transmission, but the industry will experience increased costs estimated with 90% confidence to be in the range of [$1,000, $50,000], also paid by the consumer. Alternatively, requiring a test reduces the outbreak probability to [0.02%, 0.5%] with 90% confidence, but incurs additional costs of $10,000, plus $1,000,000 if an outbreak occurs. The agency’s goal is to reduce the overall cost to the consumer.

Paper For Above instruction

The decision regarding whether to ban imported pigs, require testing, or take no action involves evaluating the costs and risks associated with each strategy to minimize overall expenses borne by consumers. This analysis applies a probabilistic risk assessment and cost-benefit framework to identify the most economically efficient approach aligned with the agency’s goal of cost reduction.

First, evaluating the scenario with no ban involves considering the risk of disease outbreak and its associated costs. The probability of an outbreak, with 90% confidence, ranges from 0.2% to 5%. The expected cost of an outbreak can be estimated by multiplying the probability by the cost of managing an outbreak, set at $1,000,000. Since this is a range, the expected outbreak costs vary accordingly:

  • Lower bound: 0.2% (0.002) probability × $1,000,000 = $2,000.
  • Upper bound: 5% (0.05) probability × $1,000,000 = $50,000.

The expected cost of disease outbreaks under the no-ban scenario thus ranges between $2,000 and $50,000, depending on the true underlying probability. The associated risk must be balanced against other policies.

Implementing a complete ban effectively eliminates the risk of disease importation, but incurs increased industry costs ranging from $1,000 to $50,000, with 90% confidence. This range represents the additional costs that consumers ultimately bear, regardless of whether disease transmission occurs or not. The expected cost of the ban, therefore, spans from:

  • Lower bound: $1,000
  • Upper bound: $50,000

Given this, the ban guarantees zero risk of disease transmission but imposes a certain additional cost on the industry, and consequently consumers.

The testing approach aims to strike a balance between the two. Conducting tests reduces the outbreak probability to a range of [0.02%, 0.5%] (90% confidence). This reduced probability translates to expected outbreak costs as follows:

  • Lower bound: 0.02% (0.0002) × $1,000,000 = $200
  • Upper bound: 0.5% (0.005) × $1,000,000 = $5,000

However, the testing incurs an additional cost of $10,000, plus a potential outbreak cost of $1,000,000 if an outbreak occurs despite testing. To compute the expected total costs of testing, the probability of outbreak post-testing must be considered, along with the additional fixed testing cost:

Expected outbreak costs after testing are:

  • Lower bound: 0.0002 (0.02%) probability × $1,000,000 = $200
  • Upper bound: 0.005 (0.5%) probability × $1,000,000 = $5,000

Total expected costs for testing will therefore be:

  • Minimum: $10,000 (testing cost) + $200 (expected outbreak cost) = $10,200
  • Maximum: $10,000 + $5,000 = $15,000

In addition, should an outbreak occur, the cost of $1,000,000 is covered, but since the expected outbreak cost already accounts for probability, these calculations include it probabilistically.

The overall goal is to compare these expected costs to identify the most cost-effective strategy. Considering the low range of expected outbreak costs with no ban ($2,000 to $50,000) and the relatively predictable costs of the ban ($1,000 to $50,000), it appears that the no-ban scenario may be more economical when the outbreak probability is at its lower end (closer to 0.2%). But, given the lower probabilities achieved through testing, testing might further reduce expected costs, especially around the upper estimation of outbreak probability.

In conclusion, the testing strategy offers a significant reduction in disease transmission risk while adding a manageable, fixed testing cost. When comparing expected costs:

  • Without intervention, expected outbreak costs vary considerably but can be minimized if actual outbreak probability is near its lower estimate.
  • With a ban, the costs are predictable but higher, especially at the upper range.
  • Testing provides a middle ground, reducing outbreak risk substantially at an incremental cost of approximately $10,000, which may be justified given the potential to lower expected outbreak costs below the upper bounds of the no-ban scenario.

Therefore, based on the analysis of expected costs and the goal of minimizing total costs to consumers, the recommended approach would be to implement a testing protocol for imported pigs. This strategy effectively balances the low probability of disease transmission, the costs of testing, and the potential costs of outbreaks, ultimately reducing the overall financial burden on consumers.

References

  • Allen, L. J. S. (2017). An Introduction to Stochastic Processes with Applications to Biology. Chapman and Hall/CRC.
  • Gordon, A., & Pakes, A. (2020). Cost-Benefit Analysis of Disease Control Strategies. Journal of Agricultural Economics, 71(2), 283-298.
  • Kwon, H. Y., & Kim, H. (2018). Economic implications of disease management in livestock industries. Veterinary Research Communications, 42(3), 123-137.
  • Levy, A., & Williams, N. (2019). Evaluating disease outbreak risks in trade policies. Risk Analysis, 39(5), 1043-1055.
  • Smith, R. D., & Keogh, D. (2016). Infectious disease models and their implications for policy. Infection Ecology & Epidemiology, 6, 30588.
  • Thompson, D., & Smith, P. (2019). Cost-effectiveness of biosecurity measures in animal importation. Preventive Veterinary Medicine, 171, 104766.
  • World Organisation for Animal Health (OIE). (2020). Standards for the Control of Animal Diseases. OIE Scientific and Technical Review.
  • Yeates, P., & Wilkinson, P. (2015). Risk assessment methods in veterinary epidemiology. Preventive Veterinary Medicine, 122(4), 418-425.
  • Zhou, X., & Cheng, H. (2021). Modeling and analysis of disease transmission in livestock populations. Computers and Electronics in Agriculture, 188, 106290.
  • Zhao, Y., & Zhou, J. (2018). Economic evaluation of intervention strategies for infectious diseases. Journal of Veterinary Science, 19(4), e37.

Related Assignments