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Participatory and quantitative systems modelling approach to animal health economics
The document presents a participatory and quantitative systems modelling approach to animal health economics, as proposed by Kanar Dizyee, focusing on case studies related to foot-and-mouth disease in Botswana, African swine fever in Uganda, and food safety in Vietnam. It highlights the limitations of traditional farm-level economic impact assessments and advocates for a more integrated approach that captures the broader socio-economic and health impacts of animal diseases. Future research directions include developing quantitative models and participatory approaches to better understand the interactions between animal health, human health, and ecosystem health.
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Participatory and quantitative systems modelling approach to animal health economics
- 1. Better lives throughlivestock Participatory and quantitative systems modelling approach to animal health economics Authors: Kanar Dizyee Position: Scientist: Value chain impact assessment modeler, PIL/ILRI Presented to the French Agricultural Research Centre for International Development (CIRAD) on the proposed Participatory and quantitative systems modelling approach, 15 February 2021, Nairobi, Kenya: ILRI.
- 2. Case studies: examples Appliedparticipatory and quantitative system modelling on: • The impact of Foot-and-Mouth Disease (FMD) on market access for beef in Botswana; • The impact of African Swine Fever (ASF) in Uganda; and • Food safety and animal health issues in the pig sector in Viet Nam
- 3. Research direction In thepast decades, various methodologies have been used to model the epidemiology and economics of animal diseases (e.g., cost-benefit analysis, partial budget analysis, input-output, linear programming, etc). However, most of these studies have focused on farm level impacts that provide policy and decision makers with a tool to assess: • Benefit-cost estimates of disease control • Direct and indirect costs of animal diseases Despite the virtues of each of these models, how applicable these in integrated animal health economics given the complex interaction between the epidemiology and economics of disease and the existing feedback mechanisms that can influence the success of disease control interventions and their cost-effectiveness. Source: Dijkhuizen et al. (1995); Rushton (1999); Rich et al. (2005); Hamza et al. (2014); Truong et al. (2018)
- 4. Recent developments inthe field of integrated approach to animal health economics Source: adapted from Hamza et al. (2014) • Farm level animal health economic impact assessment approaches focuses on linear (e.g., partial budget and cost-benefit analysis – e.g., Truong et al. (2018) – or non-linear approaches – e.g., Hamza et al. (2014)).
- 5. Example: Cost-benefit analysisof FMD control in Vietnam Source: Truong et al. (2018)
- 6. Recent advances inanimal health economics impact assessment (using participatory and systems modelling approaches) • Despite the virtues of animal health economic assessment at farm level, how effective are these methods to capture the broader economic impact of animal health at farm level and beyond? Livestock production Livestock collection Livestock wholesaling Livestock processing Livestock trade Intervention Chain impacts (economic gains/losses, employment, service provision, gender, hh nutrition and food safety) Nodal impacts – direct and feedback effects, often with delays (market, institutional, strategic choice) Source: Dizyee et al. (2016); Ouma et al. (2017); Rich et al. (2018) E.g., FMD vaccination; ASF biosecurity measures Disruptions E.g., Trade ban due to FMD outbreaks; Panic sale and trade ban due to ASF outbreaks
- 7. Example 1: FMDcontrol in Beef sector in Botswana (Profit performance) Source: Dizyee et al. (2017) Run 1: Business as usual; Run 2: Market liberalization; Run 3: Business as usual + FMD freedom; Run 4: Market liberalization + FMD freedom.
- 8. Example 2: Africanswine fever control and market integration in pig sector in Uganda Source: Ouma et al. (2018)
- 9. What is next?Future research direction Human Health Animal Health Ecosystems Health • Quantitative systems models (predictive modelling and what-if-scenarios) • Available quantitative data and knowledge • Participatory approaches to engage with stakeholder to gather qualitative knowledge and construct adaptive and resilient decision tools Socio-economic impact of animal health Source: Constructed based on information from Duboz et al. (2018)
- 10. Future research direction •Can we develop a more integrated approach to animal health that not only captures the economic impact of animal health at farm and beyond farm gate but also at human and ecosystem health level? • Can we move Integrated Approach to Animal Health from conceptual models to more formal and quantitative models? • Can participatory systems approach and systems modelling approach play a role in advancing the existing framework to Integrated Approach to Health?
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- 12. References • Dijkhuizen, A.A., Huirne, R. B. M., and Jalvingh, A. W. 1995. Economic analysis of animal diseases and their control. Preventive Veterinary Medicine, 25(2), 135-149. • Dizyee, K., Baker, D., Rich, K. M., Fleming, E., and Burrow, H. 2016. Applying system dynamics to value chain analysis(No. 235242). Australian Agricultural and Resource Economics Society. • Dizyee, K., Baker, D., and Rich, K. M. 2017. A quantitative value chain analysis of policy options for the beef sector in Botswana. Agricultural Systems, 156, 13-24. • Duboz, R., Echaubard, P., Promburom, P., Kilvington, M., Ross, H., Allen, W., ... And Binot, A. 2018. Systems Thinking in Practice: Participatory Modeling as a Foundation for Integrated Approaches to Health. Frontiers in veterinary science, 5. • Hamza, K., Rich, K. M., and Wheat, I. D. 2014. A system dynamics approach to sea lice control in Norway. Aquaculture Economics & Management, 18(4), 344-368. • Ouma, E., Dione, M., Birungi, R., Lule, P., Mayega, L., and Dizyee, K. 2018. African swine fever control and market integration in Ugandan peri-urban smallholder pig value chains: An ex-ante impact assessment of interventions and their interaction. Preventive veterinary medicine, 151, 29-39. • Rich, K. M., Miller, G. Y., and Winter-Nelson, A. 2005. A review of economic tools for the assessment of animal disease outbreaks. Revue Scientifique Et Technique-Office International Des Epizooties, 24(3), 833. • Rich, K. M., Dizyee, K., Nguyen, T. H., Duong, N. H., Pham, V. H., Nguyen, T. N., ... and Lapar, M. L. 2018. Quantitative value chain approaches for animal health and food safety. Food microbiology, 75, 103-113. • Rushton J, Thornton PK, Otte MJ. Methods of economic impact assessment. Rev Sci Tech (1999) 18:315–42. doi:10.20506/rst.18.2.1172 • Truong, D. B., Goutard, F. L., Bertagnoli, S., Delabouglise, A., Grosbois, V., and Peyre, M. 2018. Benefit–cost analysis of Foot-and-Mouth Disease Vaccination at the Farm-level in south Vietnam. Frontiers in veterinary science, 5, 26.
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Editor's Notes
- #8 BMC stands for Botswana Meat Commission (in charge of processing and exporting beef to export market. BMC has monopoly power over beef export from Botswana to export markets) Results: Cumulative results over 15 years time horizon. Run Key assumptions Run 1: Business as usual A representation of normal market and production conditions and unchanged policy. FMD outbreaks (large enough in scale to interrupt export marketing) were projected to occur randomly once each 7 years (based on historical data) (BIDPA, 2006, Mapitse, 2008). The reported simulation introduced an FMD outbreak in late 2016 (week 350). The actual 2011 (week 60) FMD outbreak was included to ensure replication of past events. During FMD outbreaks, exports to the EEA (over 50% of export market share) are blocked for two years (OIE: Terrestrial Animal Health Code – Article 8.8.3). Thus, we assume that demand from the export market declines by over 50% for two years based on lost access to the EEA markets, and then returns to normal. Run 2: Market liberalization. A partial market liberalization, allowing export of weaners to South Africa. We evaluate the effect of exporting about 2,000 weaners per week starting from 2017 (week 364) (2,000 is a random initial value; the model endogenously develops weaner prices and demand – on average, only 55% of 2000 weaners per week are exported due to limited supply). This scenario is motivated by the policy debate in Botswana on the positive and negative effects of reducing or removing BMC’s market power in the beef industry (BOPA, 2011, BOPA, 2013). Run 3: Business as usual + FMD freedom. An FMD-free scenario for cattle production and marketing, which features an uninterrupted flow of cattle to the export market. This scenario is motivated by the fact that large scale FMD outbreaks, and outbreaks in the EU export zones in Botswana - unlike small regional outbreaks - do not occur as frequently as outbreaks in FMD-endemic and FMD-vaccinated zones (Mapitse, 2008, BIDPA, 2006). We assume a two-round FMD vaccination each year for all cattle located in FMD ones in Northern Botswana. Vaccination (funded by the Government of Botswana) is assumed to generate the FMD-free scenario. Run 4: Market liberalization + FMD freedom. In this scenario, we assess how FMD freedom combined with market liberalization will influence market dynamics within the beef value chain.
- #9 3.3 Model simulation scenarios The constructed value chain model was used to run four scenarios through simulations over a 15 year and 30 year period to predict changes in pig mortalities and gross margins accruing to pig farmers and other value chain actors as a result of the ASF and pig business hub interventions relative to the current baseline situation. The details of the four scenarios are as follows: 3.3.1 Baseline scenario The baseline scenario presents the status quo of peri-urban pig value chains in Masaka district. In the baseline scenario, the model is parameterised based on data from the pig value chain assessment survey. The results of the baseline scenario is used as a benchmark to compare alternative scenarios. Tables 1 – A, Table 1 – B and 2 show the parameters, per cent product flow through different channels, and initial values used in the production and trading sectors, respectively. 3.3.2 Implementation of ASF biosecurity interventions in the production sector to control ASF outbreaks In this scenario, we look at the effect of implementation of biosecurity interventions in the production sector to control ASF outbreaks. The target is to reduce mortality rates due to ASF from the current 20.8% to zero (Dione et al. 2014). The effects of ASF in the value chain are introduced through increased mortality, home slaughter and panic selling. The biosecurity practices are in line with FAO (2010) recommendations and have been adapted for smallholder piggery settings in Uganda (Nantima et al. 2015b). These include: Erection of fence and gate, control and monitoring of physical barrier, enforcement of change of footwear and clothing, and restricting the entry of vehicles or dipping of tyres in case of necessary entrance Daily sweeping, routine washing of the pen with copious amount of water, thorough washing with soap, water and brush to ensure that no visible dirt is seen on the surface of building and materials, dry cleaning of all material that are not water resistant. Usage of appropriate disinfectant to sanitize washed and dry-cleaned materials. Reporting to the veterinary office in case of disease outbreak Quarantine and prompt disposal of dead animals Regular deworming of pigs Boiling of swill before feeding to pigs The cost of the biosecurity practices is estimated at Uganda Shillings 2,625 per grower (pig ready for slaughter with a weight of about 30Kg carcass weight) per week. The biosecurity estimates are provided in Table 3-A. With improved biosecurity implementation, the pigs have better body condition and farmers are able to bargain for about 5% higher price. 3.3.3 Implementation of the pig business hub model to enhance linkages to input and output markets for better pig incomes The pig business hub model links pig producer collectives to dedicated input suppliers and output markets. This scenario assesses the effect of the pig business hub model on ASF control and pig incomes. The pigs are marketed collectively and collected by traders from pig collection centres. This has an effect of minimising ASF outbreaks and spread as traders are not allowed to collect pigs on-farm. The farmers are also able to negotiate with input suppliers and pig traders for better input and pig prices due to bulk sales and purchases. At baseline, the average producer price per grower is about 150,000 Uganda Shillings. With the pig business hub the farmers are able to bargain for a 24% higher price. The cost parameters associated with the pig business hub model include land rate payment to the municipal council associated with the pig collection centre, ante-mortem pig inspection fees and pig loading into transport equipment. The cost is estimated at 68,540 Uganda Shillings per week. The detailed cost breakdown are provided in Table 3-B. 3.3.4 Implementation of ASF biosecurity and pig business hub model In this scenario, we look at the effects of implementing both biosecurity interventions to control ASF and the pig business hub model to better link pig producer collectives to input suppliers and pig markets. With combined biosecurity and the pig business hub, farmers are able to bargain for 30% higher pig price.