Small-scale pig farming is highly important to the economic and social status of households in Timor-Leste. The presence of an African Swine Fever (ASF) outbreak in Timor-Leste was confirmed in 2019, a major concern given that around 70% of agricultural households practice pig farming. This research used a virtual spatial group model building process to construct a concept model to better understand the main feedback loops that determine the socio-economic and livelihood impacts of the ASF outbreak. After discussing the interaction of reinforcing and balancing feedback loops in the concept model, potential leverage points for intervention are suggested that could reduce the impacts of ASF within socio-economic spheres. These include building trust between small-scale farmers and veterinary technicians, strengthening government veterinary services, and the provision of credit conditional on biosecurity investments to help restock the industry. This conceptual model serves as a starting point for further research and the future development of a quantitative system dynamics (SD) model which would allow ex-ante scenario-testing of various policy and technical mitigation strategies of ASF outbreaks in Timor-Leste and beyond. Lessons learned from the blended offline/online approach to training and workshop facilitation are also explored in the paper.

Recent research has highlighted the valuable contributions that participatory processes contribute in developing system dynamics models of value chains with stakeholders. A new participatory process known as spatial group model building (SGMB) expands these insights, using maps and GIS concepts to improve the facilitation and modelling process. This practical note provides an overview of SGMB, its recent applications in informing development interventions, and proposed innovations to expand its use and dissemination.

CONTEXT: Myanmar has made rapid economic progress since the country began its transition to a more integrated market economy in the late 2000s. Although these gains are led by positive developments in the agricultural sector, agricultural productivity and profitability are among the lowest in Asia with high rates of poverty especially in rural areas. Small-scale farms dominate rural livelihoods in Myanmar, especially for the 87% of Myanmar's poor who live in rural areas. Hence, these small-scale farms are critical development leverage points as they are an important source of rural incomes to both farm and non-farm households. OBJECTIVE: This study is part of a larger, five-year agricultural research and development project intended to upgrade pork and rice value chains and strengthen rural livelihoods in southern Myanmar's Tanintharyi Region. We evaluated producer-focused interventions to upgrade the pork value chain using tools that consider the dynamic , complex nature of the chain. METHODS: This research used systems thinking and participatory methods to develop a system dynamics model of the pork value chain in southern Myanmar. The model integrated modules of animal production, marketing, investment, finance , collective action. Scenario analysis with the model guided recommendations for pro -poor interventions for implementation within the five-year development project. RESULTS , CONCLUSIONS: Simulation results indicated that a mix of technical interventions implemented by functional producer groups showed promise in delivering sustained financial benefits to the target community and outperformed the short-term gains generated by these interventions in the absence of collective action. The model also highlighted specific interventions, such as improved financial services, animal health workers, and training that enabled poorer households to benefit from pig livelihoods while reducing risks from environmental and economic shocks. Within complex agri-food systems such as the pork value chain in Tanintharyi, a multi -pronged intervention strategy is recommended to address problems faced by small-scale agribusiness value chain participants. SIGNIFICANCE: Development interventions tend to be implemented in complex environments, often with scarce data to inform decision-making. This research shows how system dynamics tools and spatial group model building processes could help overcome these inherent challenges by creating virtual laboratories where plau-sible project interventions can be tested and modified, bringing increased confidence to implementation choices.