Cost-benefit Model Research Articles

Reducing recidivism and encouraging desistance: a social entrepreneurial approach

PurposeThis paper, which is both case study and conceptual in nature, presents a relative cost-benefit model to explain why people engage in criminal activity. It then uses the model to motivate a discussion of the major policy approaches to recidivism reduction and desistance, or decreasing the frequency and severity of criminal activity, a more nuanced measure of harm reduction than the binary concept of recidivism typically used to evaluate program success. Several private programs have successfully reduced recidivism and improved measures of desistance but remain applicable only to those who self-select into them. Changed policies and incentives, however, could stimulate social entrepreneurs to search for programs applicable to additional segments of the prison population.Design/methodology/approachThis paper describes case studies informed by economic theories of crime and incentive alignment. Most approaches to recidivism reduction/desistance have failed, but several programs, including the DOE Fund and PEP, have proven extremely effective: the first by employing former convicts in starter jobs and the latter by teaching inmates about entrepreneurship and general business skills and mentoring them after release.FindingsSuccessful cases cannot simply be scaled up because inmates self-select into the programs. Instead, policymakers should encourage further competition and innovation in the field by paying NGOs each week they manage to keep the formerly imprisoned persons in their charge alive and out of the criminal justice system.Research limitations/implicationsCase study and theoretical. Not yet tried in the real world.Practical implicationsLower recidivism, more desistance for the same budget.Social implicationsHumans will be better treated than currently.Originality/valueInstead of offering a specific recidivism reduction panacea, this paper suggests that incentive alignment and competition for funding will encourage nonprofit NGOs to discover which programs work best for different types of inmates.

Combined 18F-FDG and 11C-acetate positron emission tomography/computed tomography in staging and treatment decision in patients with hepatocellular carcinoma: A cost-effectiveness analysis.

e16176 Background: Dual-tracer positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose and 11C-acetate is increasingly used in the management of hepatocellular carcinoma (HCC). However, considering the high cost of dual-tracer PET/CT, there is a need to assess its value by considering both the efficacy and cost. Methods: In this retrospective cohort study, 223 dual-tracer PET/CT scans were performed in 206 patients between 2014 and 2020 for tumor staging for radiologically or histologically confirmed HCC. New lesion detection rate, changes in the Barcelona Clinic Liver Cancer (BCLC) classification, and changes in treatment allocation based on dual-tracer PET/CT were evaluated. Validation was performed on a cohort of staging patients from another institution (n = 48). A cost-benefit analysis model was built for the incurred costs and the impact of dual-tracer PET/CT findings on treatment strategy over conventional imaging was studied. Results: Of the 223 patients that underwent dual-tracer PET/CT for staging, new lesions were detected in 33 (14.8%) patients, resulting in BCLC upstaging in 26 (11.6%) and treatment modification in 16 (7.2%) cases. The external staging cohort showed similar findings where dual-tracer PET/CT resulted in 12.5% (6/48) BCLC upstaging and 10.4% (5/48) treatment modifications (concordance-index: 0.85; 95% CI: 0.82-0.88). In subgroup analysis of 200 patients performed for pre-treatment metastatic screening, dual-tracer PET/CT detected extra-hepatic metastasis in 11, 10, and 16 patients, respectively, and led to treatment modifications in all of these patients. Sixteen locoregional therapies (8%) were avoided (8 resections, 3 transplantations, and 5 TACEs), with an estimated cost saving of US$161,665 (US$808 / patient) from the use of dual-tracer PET/CT. Sensitivity analyses suggested that dual-tracer PET/CT is consistently more cost-saving than conventional imaging, irrespective of the changes in the cost of imaging, procedures, and the duration of hospital stay (range: US$112,945-210,385). The cost of PET/CT had the greatest influence on the cost savings. Conclusions: Comparing to conventional imaging, dual-tracer PET/CT improves tumor staging, alters treatment allocation and is cost-saving in patients undergoing pre-treatment metastatic screening. Our results demonstrated that the use of dual-tracer PET/CT provides additional value and improves patient care.

Cognitive control, motivation and fatigue: A cognitive neuroscience perspective

The present article provides a unified systematic account of the role of cognitive control, motivation and dopamine pathways in relation to the development of fatigue. Since cognitive fatigue is considered to be one aspect of the general control system that manages goal activity in the service of motivational requirements (Hockey, 2011), our focus is also broader than fatigue itself.The paper shall therefore first focus on the motivation-control interactions at the level of networks of the brain. A motivational control network is argued to play a critical role in shaping goal-directed behavior, in conjunction with dopamine systems that energize the network. Furthermore, motivation-control interactions as implemented in networks of the brain provide an important element to elucidate how decision making weighs both the anticipated benefits and costs of control operations, in optimal and suboptimal conditions such as mental fatigue.The paper further sketches how fatigue affects the connectivity of large-scale networks in the brain during effortful exercition, in particular the high-cost long striatal-cortical pathways, leading to a global reduction of integration in the brain’s network architecture. The resulting neural state within these networks then enters as interoceptive information to systems in the brain that perform cost-benefit calculations.Based on these notions we propose a unifying cost-benefit model, inspired by influential insights from the current neuroscience literature of how fatigue changes the motivation to perform. The model specifies how the reward value, effort costs and fatigue aspects of task performance converge in the medial prefrontal cortex to calculate the net motivation value of stimuli and select the appropriate actions.

Evaluation and Improvement of the Comprehensive Cost-Benefit of Investment and Operation of New Energy Heating System

The on-spot consumption scheme of new energy can improve the utilization efficiency of energy and provide references for the transformation from the conventional regional coal heating mode to the more efficient electric heating mode. To figure out the economic benefit brought by the new energy heating mode, it’s necessary to evaluate its cost-benefit and construct reasonable model to study the dynamic market response. Therefore, this paper aims to evaluate the comprehensive cost benefit of the investment and operation of new energy heating (NEH) system and find ways to improve the said cost benefit. At first, this paper built an investment and operation model for the said NEH system, and constructed an objective function with the minimization of new energy disuse rate as the objective in the commissioned operation scheme for new energy on-spot consumption system connected with large electric heating boiler and large-capacity heat accumulator. Then, the paper gave the structure of the NEH system, and analyzed the main participants, investment and operation modes, and economic benefit of the NEH system. At last, corresponding experimental results and analysis results of an example case were given, which had verified the effectiveness of the proposed model.

An integrated techno-economic analysis on wastewater reclamation in Hong Kong: A comprehensive cost – Benefit analysis with life cycle assessment

Wastewater reclamation and reuse projects have been gaining significant attention as ways to secure sustainable water resources while preventing environmental degradation. However, traditional cost-benefit analyses do not reflect the true net benefits of these processes as they do not consider all externalities, particularly due to the difficulties in monetizing environmental impacts, thereby leading to underutilization. In this study, we conducted a hybrid cost-benefit analysis with an integrated environmental externality approach to evaluate the true net benefit of wastewater treatment and reclamation with explicit and implicit costs and estimated benefits. Firstly, we developed a cost-benefit analysis model based on the Drainage Service Department's statistical data from the Shek Wu Hui plant in Hong Kong from 2014 to 2018. Next, we estimated the external environmental benefits from pollutant abatement based on the shadow price of each pollutant by adopting a distance frontier function. We then conducted a life-cycle assessment to investigate the potential environmental impacts of the process using SimaPro 8.5.2.0 software and the EcoInvent 3 database, utilizing Stepwise2006 methodology for full monetization. A sensitivity analysis was applied to control for uncertainties as a robustness check. Our results show that aggregate cost, shadow price, and monetized environmental impact are estimated to be 4.47, 4.75, and 1.23 HKD per m3 of treated water respectively. Based on these results, our study illustrates that the true benefit is noticeably higher than the unit cost of wastewater reclamation, dependent upon a scale, and represents a breakeven point of 63,769 m3 of water reclamation per day. Our study further demonstrates that wastewater reclamation is viable from both social and economic perspectives and will increase the government budget by 81 million HKD. Therefore, this study can provide a basic guideline for developing a more complete economic valuation of wastewater treatment and reclamation projects.

A Systems Framework for Infrastructure Business Models for Resilient and Sustainable Urban Areas

Sustainable Development Goal 11 calls for inclusive, safe, resilient and sustainable cities. Urban areas comprise interconnected infrastructure systems that deliver services that support all aspects of daily life. Despite their important contribution to modern life current infrastructure business models typically under-estimate the long-term economic, social and environmental benefits of infrastructure. Therefore, new infrastructure business models are required that: (i) target urban areas or regions at a local scale where there is the greatest scope for innovation, (ii) target specific challenges or needs (i.e., where there is a clear driver for innovation), and (iii) tackle the issue of the flawed economic cost-benefit model for assessing the viability of infrastructure investments. This paper presents a framework that promotes multiple stakeholders to working together, and by focusing on outcomes to develop alternative infrastructure solutions and business models that deliver multiple values to multiple stakeholders. By explicitly mapping these values over time and space, the interdependencies between infrastructures are revealed, along with an expanded perception of the value being brought about by that infrastructure. Moreover, the broader consideration of value also increases the number of stakeholders beneficiaries, the value network, and subsequently identify how they can support the infrastructure intervention by formulating alternative funding and financing mechanisms. A series of case studies to achieve resilience, sustainability and regeneration outcomes are used to show how the framework can be utilized to unlock investment in infrastructure in situations where traditional approaches have failed.

Investigating and modeling the dynamics of long ties

Long ties, the social ties that bridge different communities, are widely believed to play crucial roles in spreading novel information in social networks. However, some existing network theories and prediction models indicate that long ties might dissolve quickly or eventually become redundant, thus putting into question the long-term value of long ties. Our empirical analysis of real-world dynamic networks shows that contrary to such reasoning, long ties are more likely to persist than other social ties, and that many of them constantly function as social bridges without being embedded in local networks. Using a cost-benefit analysis model combined with machine learning, we show that long ties are highly beneficial, which instinctively motivates people to expend extra effort to maintain them. This partly explains why long ties are more persistent than what has been suggested by many existing theories and models. Overall, our study suggests the need for social interventions that can promote the formation of long ties, such as mixing people with diverse backgrounds.

Comparative profitability and relative risk of adopting climate-smart soil practices among farmers. A cost-benefit analysis of six agricultural practices

The adoption of climate-smart soil (CSS) practices among farmers have the potential to rehabilitate and protect the soil. Proponents have not fully addressed factors such as; profitability and the relative risk that farmers face during the adoption and implementation of these CSS practices. These factors determine the adoption and sustainability of these practices. This study assessed the comparative profitability and relative risk of implementing CSS practices among farmers in Kakamega, Siaya, and Bungoma counties in Western Kenya. The prioritization of these CSS practices (agroforestry, intercropping, liming, organic manure use, inorganic fertilizer, and improved hybrid seeds) was based on the climate-smart agriculture (CSA) pillars (production, adaptation, and mitigation) and their benefits. A deterministic cost-benefit analysis model that incorporates sensitivity and scenario analysis assessed these factors. The findings showed that agroforestry was the most profitable having a net present value of US$ 16,071 ha−1, followed by intercropping (US$ 10,487 ha−1), and the use of improved hybrid seeds was the least profitable (US$ 881 ha−1). In terms of relative risk, all the practices were more sensitive to the product price and output than the lifespan, discount rate, and labour cost. The result implies that exposure of these practices to climatic and economic shocks will result in high-profit risk. Therefore, national and county governments should place micro-credit loans with minimum interest, input subsidies, and skilled personnel to promote increased adoption of agroforestry and intercropping. Agricultural extension officers should also demystify farmers' mentality that improved hybrid seeds can guarantee increased productivity.

Spatial variations of PM2.5 emissions and social welfare induced by clean heating transition: A gridded cost-benefit analysis

Clean heating (CH) is regard as a key strategy to address the serious air pollution problem in northern China. A “one-fit-all” CH strategy will harm social welfare and engender resistance, due to the differences in heating habits and residents' income between urban and rural areas. To solve this problem, a 5 km × 5 km gridded cost-benefit analysis model for CH is build. Taking the case city as an example, an improved CH solution integrating multiple heat sources is proposed. By utilizing ISH resources, which are low-cost and low-emission-intensity, the improved solution reduces heating-induced PM2.5 emissions to one-fifth, and achieves higher net social benefits than existing CH strategies. Moreover, the spatial distributions of PM2.5 emission reductions and indoor and outdoor health benefits induced by CH strategy, including coal-to-gas/electricity and the improved strategy we propose, are simulated; revealing that the spillover effects of pollutants make CH will somewhat inevitably bring about a transfer of social welfare from rural areas to urban areas, but this can be compensated by opposite direction subsidies.

Digital Forensic Readiness of Information Systems: A cost-benefit variable analysis

Despite the increasing amount of research on the pre-incident side within a digital forensic investigation, little steps have been taken towards assessing the effectiveness of such a plan in terms of cost effectiveness. This research paper lays the foundations of a cost-benefit variable analysis within a digital forensic readiness context by defining a cost-benefit relationship effect model. We collect novel, primary data from organisations and institutions that implement a digital forensic readiness plan to identify cost variables of each measure and threat, and benefit variables of each measure to be taken. We conduct data analysis to portray that specific cost variables have a significant effect on specific benefit variables and present the results of the data collection process amongst organisations and institutions applying a digital forensic readiness plan. Lastly, we produce hypotheses testing results and determine the validity between each cost-benefit relationship.

Valuing the cross-sector benefits from improving youth health to drive investment in place-based preventive interventions in the US: A simulation modeling study

Healthcare payment reform has not produced incentives for investing in place-based, or population-level, upstream preventive interventions. This article uses economic modeling to estimate the long-term benefits to different sectors associated with improvements in population health indicators in childhood. This information can motivate policymakers to invest in prevention and provide guidance for cross-sector contracting to align incentives for implementing place-based preventive interventions. A benefit-cost model developed by the Washington State Institute for Public Policy was used to estimate total and sector-specific benefits expected from improvements to nine different population health indicators at ages 17 and 18. The magnitudes of improvement used in the model were comparable to those that could be achieved by high-quality implementation of evidence-based population-level preventive interventions. Benefits accruing throughout the lifecycle and over a ten-year time horizon were modelled. Intervention effect sizes of 0.10 and 0.20 demonstrated substantial long-term benefits for eight of the nine outcomes measured. At an effect size of 0.10, the median lifecycle benefit per participant across the ten indicators was $3080 (ranged: $93 to $14,220). The median over a 10-year time horizon was $242 (range: $14 to $1357). Benefits at effect sizes of 0.20 were approximately double. Policymakers may be able to build will for additional investment based on these cross-sector returns and communities may be able to capture these cross-sector benefits through contracting to better align incentives for implementing and sustaining place-based preventive interventions.

An Investigation of Multimodal Transport for Last Mile Delivery in Rural Areas

High distribution costs constitute one of the major obstacles to the sustainable development of rural logistics. In order to effectively reduce the distribution costs of last mile delivery in rural areas, based on three typical transport modes (local logistics providers, public transport, and crowdsourcing logistics), this study first proposes a multimodal transport design for last mile delivery in rural areas. Then, a cost–benefit model for multimodal transport is proposed which uses genetic algorithms (GA) to solve the logistical problems faced. Finally, Shapley value is used to fairly allocate profits and represent the marginal contribution of each mode in multimodal transport. The numerical results show that multimodal transport can effectively reduce the distribution costs of last mile delivery in rural areas. When the order demand of each node tends to be stable, the marginal contribution of crowdsourcing logistics is often greater than that of the other two distribution modes. The marginal contribution of public transport is highest only when the number of orders per node is very small.

Risk-based flood adaptation assessment for large-scale buildings in coastal cities using cloud computing

• A risk-based flood adaptation model was developed and investigated in the cloud computing system • Both global and local sensitivity analysis were conducted to show sensitivity of model parameters • Adaptation scenarios were designed to incorporate life-cycle cost and benefits of adaptation, social vulnerability, and public adaptation policies • Public adaptation with seawall and enforced building elevation policy within flood zones could substantially reduce building damages Flood risk management (FRM) in coastal cities is a challenging task due to uncertain climate hazards under sea-level rise (SLR) and large-scale vulnerable buildings within in the floodplain. This study presents a building-level adaptation framework to evaluate alternative community adaptation strategies relying on cloud computing. We incorporated multiple sources of model uncertainties and randomly generated storm surges in each year of simulation using the extreme value distribution (GEV) theory. Based on a case study in Miami-Dade County, Florida, four adaptation scenarios were designed to evaluate their effectiveness in adaptation. Our sensitivity analysis suggested a positive linear relationship between community flood risk reduction and total community adaptation costs in the life-cycle cost-benefit (LCCB) model. Our results showed that uncertainties of the total community damage based on the LCCB model ranges from $ 221 million to $ 2.75 billion. However, when considering social vulnerability, the total community damage increased substantially, ranging from $ 244 million to $ 3.44 billion. Nevertheless, a 6ft public seawall based on the upper bound of the GEV distribution with the enforced building elevation policy in flood zones could substantially reduce community flood damage under uncertain sea-level rises.

Progressive Entity Matching via Cost Benefit Analysis

Entity matching (EM) is a fundamental problem in data preprocessing, and is a long running topic in big data analytics and mining communities. In big data era, (nearly) real-time data applications become popular, and call for progressive EM, which produces as many match pairs as possible in very limited time. Previous progressive EM focus on memory based solutions, but disk based solutions are necessary when dirty datasets cannot be fully loaded into memory. To this end, we propose a cost benefit analysis based progressive EM approach, which partitions data according to coarse clustering results and then iteratively schedules data partitions in a greedy way for high progressive resolution. At first, based on estimated record pair similarities, records are fast coarsely clustered; then, record clusters with near average similarities are greedily distributed to the same partitions, and data partitions are cached. After that, cost model is defined with time and space constrains, and benefit model is defined with expected resolution results. On the basis of the cost benefit model, a greedy approximate method is proposed to effectively schedule data for high progressiveness of EM. Finally, we implement extensive experiments over several datasets to evaluate our approach, and show its advantages over existing works.

Optimisation method of network level pavement maintenance planning based on benefit maximisation subject to budget constraints and a case study

ABSTRACT Considering that the decision-making and planning of large-scale highway network under the condition of limited funds, there are some problems such as complex algorithm of feasible solution of maintenance scheme and low efficiency of optimisation process, a heuristic maintenance planning optimisation algorithm based on budget is introduced. This paper focuses on the performance prediction, the determination of treatment measures and the optimisation of the optimal scheme. Firstly, through the analysis of the technical process of prediction and treatment measures, the pavement performance degradation models of pavement condition index, riding quality index and rut depth index based on treatment level are established. Then, based on the characteristics of pavement performance degradation in China, the concept of maintenance benefit based on pavement performance index is proposed, and the cost-benefit optimisation model of highway asphalt pavement is established. A budget-based heuristic algorithm is proposed to solve the optimisation model for maintenance planning with budget constraints. Finally, taking Lian-Xu highway network in a case study, the optimal scheme of treatment measures and fund allocation for the maintenance section of the large-scale highway network is realised under the condition of limited funds, so as to verify the feasibility of the optimisation model.

Toward a More Strategic National Shortage

The COVID–19 pandemic exposed major deficiencies in the United States’ approach to stockpiling for emergencies. States, cities, and hospitals across the country had meager inventories of critical medical items on hand when the pandemic first reached U.S. soil, and the federal government’s Strategic National Stockpile proved far too small to serve the country’s needs in the first several months of the crisis. As nationwide shortages spread, many state governments were compelled to bid against each other to procure scarce medical supplies—a distribution approach that disadvantaged low-income and minority communities and left countless healthcare professionals and staff ill-equipped to protect themselves against a deadly virus. These severe supply shortages, which hindered the country’s early pandemic response, have since generated an unprecedented push to reform the nation’s stockpiling policy structure. This Article uses a simple cost-benefit model to highlight shortcomings in the existing U.S. stockpiling policy regime and to identify specific avenues for addressing them. Among other things, U.S. stockpiling policies need to better account for important differences in the rotatability of supplies and should incentivize more private stockpiling of the most rotatable emergency items. Targeted reforms of commandeering laws and price-gouging restrictions could further strengthen private incentives to stockpile and may even help to clarify how states and the federal government share responsibilities in the nation’s stockpiling effort. And much more federal support is needed to incentivize the build-out and maintenance of domestic supply chains for the least-rotatable emergency goods. Such tailoring of policies and programs to better fit the unique attributes of stockpiling activities can help ensure the nation is far better equipped to respond the next time disaster strikes.

DEVELOPMENT OF A METHOD FOR MONITORING THE QUALITY OF SERVICE OF DISTRIBUTION NETWORKS IN CAMEROON

ENEO Cameroon and the Government of Cameroon decided to set up new standards for the quality of service and a new methodology to monitor the quality of service of distribution networks in Cameroon. This methodology includes the definition of a cost-benefit model to monitor the link between investment level, quality of service indicators and its impact on the average tariff required to be applied to the customers. The objective of this quality of service-investments model is to define the investment level that provides the most adequate cost-benefit for both the distribution operator and the customers, meeting minimum standards agreed with the Regulator, ARSEL. An analysis of distribution network planned investments is carried out and a methodology to evaluate their effects on the indicators is developed. The results are used as input in the quality of service-investments model to derive an investment plan. The added value is illustrated in this article via different use cases developed upon that methodology.

Benefit Analysis of Low-Carbon Policy Mix Innovation Based on Consumer Perspective in Smart City

In the construction of smart city, the carbon emission reduction problem of road traffic needs to be solved urgently. It is of great significance to introduce reasonable low-carbon policies. Based on urban private cars trajectory data, this study, respectively, establishes the genetic algorithm-back propagation neural network model (GA-BP) and back propagation-adaptive boosting algorithm neural network model (BP-AdaBoost) to predict the carbon emissions of private cars. By comparing the two neural network models, the GA-BP neural network model has better prediction results. Next, this study establishes the cost-benefit model for consumers and compares consumers’ participation willingness, emission reduction effect, and social benefits of consumers from the perspective of six kinds of low-carbon policies. The results show that the overall effect of the low-carbon policy mix of free quota is better than that of paid quota. In addition, different low-carbon policy mixes innovations have different policy implementation effects under different indicators. Overall, the low-carbon policy mix of carbon trading and emission reduction subsidy is better in the short term, and the low-carbon policy mix of carbon tax and emission reduction subsidy is better in the long term.

Las ecotecnias como factor de sustentabilidad. El caso de las biopiscinas municipales en la ciudad de Guadalajara

Ecotechnics constitute one of the fundamental elements for the construction of conditions for sustainability since they represent a viable option to successfully face the social, economic and environmental problems that characterize contemporary society. The article that is presented analyzes the case of biopools in the city of Guadalajara and has the objective of demonstrating, in the case study, their socio-environmental and economic viability. In particular, the economic and socio-environmental benefit is calculated, not only for the users of the swimming pool service, but also for the population, environmental health and government management. With the theoretical framework of ecological economics, we adapt the traditional cost-benefit model, incorporating non-market variables that allow a socio-environmental assessment of the implementation of eco-technology. The results obtained, the annual savings of $ 17,660,498 pesos and the consequent elimination of chemical contamination in the pools, allow us to conclude that, if applied, the proposed eco-technology would bring benefits not only for the users, but also for the population and the municipal government.

Cost-benefit and feasibility analysis for establishing a foot-and-mouth disease free zone in Rukwa region in Tanzania

Tanzania has the second largest livestock population in Africa and livestock keeping is an integral part of most people’s livelihoods. Foot-and-mouth disease (FMD) is a transboundary disease, affecting cloven-hoofed animals, that is currently endemic in Tanzania. The Tanzania Development Vision 2025 aspires to make the livestock sector more competitive. Part of this plan foresees establishing a FMD-free zone in the Rukwa region to be able to increase the export of animals and animal products. The aim of this study was to assess the economic efficiency and feasibility of establishing such an FMD-free zone and to advise policy makers on the profitability of the investment.A stochastic benefit-cost model, set-up in Palisade @Risk for Excel for a time frame of ten years, was developed to assess whether the benefits of establishing a FMD-free zone would outweigh the costs. Data were collated from reviewing literature, government statistics, and key informant interviews with farmers, traders and veterinarians in Tanzania, and complemented by informed assumptions and expert opinion. Moreover, feasibility aspects including underlying infrastructure, market structures and resource availability were discussed based on key informant interviews, literature review and historical analyses. The net present value for the establishment of a FMD-free zone was negative and the benefit-cost ratio was below one (mean 0.09, min 0.05 - max 0.15 in the scenario considering vaccination of all susceptible domestic animals, and mean 0.11, min 0.06 - max 0.20 when considering vaccinating cattle only), excluding potential benefits from trade. The sensitivity analysis showed that variables related to the cost of vaccination had the largest negative impact on the net present value. The proposed FMD-free zone in Rukwa region is unlikely to be cost-effective with the current FMD status and export trade prospects in Tanzania. Interviews with stakeholders revealed that vaccine availability, funding, farmers’ willingness to participate, and lack of staff continuity in key roles were the main barriers to establish a reliable FMD control programme in the country. Recommendations towards FMD control and potential short and middle term strategies are discussed.