Multidimensional sustainability assessment of smallholder dairy cattle farming systems post-foot and mouth disease outbreak in East Java, Indonesia: a Rapdairy approach

2.1 Research location and design

This research was conducted in Malang Regency, East Java Province, Indonesia, during July–August 2024. Data collection was timed to coincide with the peak impact of the renewed Foot and Mouth Disease (FMD) outbreak in the study area. This approach enabled direct observation of farmers’ real-time responses, including adjustments in management, strengthening of biosecurity, and adoption of economic coping strategies. Conducting the survey during this critical phase ensured that the sustainability assessment reflected authentic post-outbreak conditions rather than retrospective accounts. The selected period represented an active recovery stage, with evident institutional interventions, market disruptions, and production risks. Aligning the fieldwork with these conditions enhanced the empirical robustness of the Rapdairy analysis in assessing resilience, vulnerability, and adaptive capacity within smallholder dairy systems under acute disease-related stress. Malang Regency was selected due to its significant role in regional dairy cattle production, with approximately 83.880 cattle heads recorded in 2024 [9], and its experience with FMD outbreak management challenges [10], 11]. The region demonstrates high density of smallholder dairy farmers and diverse cattle farming practices, representing ideal conditions for sustainability assessment research in post-disease outbreak contexts. Figure 1 illustrates the geographical distribution of research sites highlighted in green located in Malang Regency.

Figure 1:

Map of research locations in Malang Regency, East Java, Indonesia. The map was created by the authors using ArcGIS software for visualization of the study sites.

Three sub-districts were purposively selected based on dairy cattle farming system typology: breeding systems (Kalipare), fattening systems (Bantur), and mixed breeding-fattening systems (Gondanglegi). These locations represent strategic geographic areas characterized by lowland conditions below 400 m above sea level and established dairy production centers and experience with disease outbreak management within Malang Regency.

2.2 Sampling methodology

The research employed multistage sampling procedures consisting of four hierarchical selection stages. The first three stages utilized purposive sampling methods (Figure 2) to ensure representation of areas with highest dairy cattle populations and milk production. East Java Province was selected due to its significant contribution to national dairy cattle population (51.93 %) and milk production (56.36 %), followed by Malang Regency with the largest provincial dairy cattle population [4].

Figure 2:

Sampling framework for respondent selection.

The fourth stage employed stratified random sampling to select respondents from dairy farmer populations meeting inclusion criteria: ownership of minimum two lactating cattle units, minimum two years farming experience, and membership in farmer group organizations. Stratification was conducted based on predetermined strata to control population variation and enhance estimation precision [1].

Expert consultation involved focus group discussions with six purposively selected stakeholders representing animal husbandry and veterinary services, livestock unit heads, farmer group leaders, cooperative leaders, and dairy industry representatives. Expert selection criteria included: relevant experience and competence in studied fields; established reputation, position, and credibility as subject matter experts; commitment to studied issues; and neutrality with willingness to accept other respondents’ opinions [12].

The final sample size of 287 respondents was determined based on the total number of active smallholder dairy farmers registered in the selected sub-districts. The sample size exceeded the minimum requirement established through a statistical power test using G*Power 3.1 software, which considered an effect size of 0.25, confidence level of 95 %, and power (1–β) of 0.80. The test confirmed that a minimum of 210 samples was sufficient to achieve representativeness; therefore, the final number of 287 respondents ensured robust statistical validity and representation of the study population.

2.3 Research variables

This study examines six main variables with 42 total attributes across six dimensions of sustainability assessment (Table 1). Each dimension captures specific aspects of dairy farming sustainability relevant to smallholder operations in tropical lowland environments.

2.4 Dependent variables

The sustainability assessment framework employs three dependent variables representing different sustainability outcomes measured through specific indicators relevant to dairy farming performance and impact (Table 2).

2.5 Data analysis methods

Sustainability analysis employed Multidimensional Scaling (MDS) techniques using adapted RAPFISH software termed Rapdairy, a tailored analytical tool derived from the Rapid Appraisal for Fisheries (RAPFISH) framework, modified to capture the multidimensional sustainability of smallholder dairy farming systems. This approach simultaneously evaluates sustainability status across multiple fields by considering ecological and human dimensions [1], 2].

The Rapdairy analysis follows systematic procedures including attribute identification and determination, scoring and value assignment, ordination processes, rotation procedures, sustainability index scaling, leverage analysis, Monte Carlo analysis, and participatory prospective analysis. Attribute scoring utilized 0–3 scale systems, where scores represent conditions ranging from poor (0) to excellent (3) (Table 3). The scoring criteria for each attribute were developed through expert consultation and literature review to ensure contextual relevance and consistency. A score of 0 was assigned when an attribute indicated a completely unsustainable or poor condition (e.g., absence of technology adoption or lack of waste management), while a score of 1 represented a less sustainable condition with limited implementation. A score of 2 reflected a moderate or partially sustainable state where improvements were evident but not optimal. A score of 3 denoted full sustainability performance, demonstrating best practices aligned with established technical and environmental standards. This scoring approach followed the standardized procedure of RAPFISH-based sustainability assessments adapted to the dairy sector.

The risk probability and impact matrix presented in Table 4 provides critical insights into risk prioritization. Production risks consistently demonstrate both high probability (“Always Happens”) and very large impact, positioning them in the highest priority quadrant. This empirical evidence supports the allocation of primary resources toward production risk mitigation. Financial risks similarly occupy a high-priority position with frequent occurrence and large impacts, reflecting the severe economic constraints faced by smallholder farmers during disease recovery periods. Table 4 further illustrates these risk dynamics, visualizing the distribution of risk categories across probability-impact dimensions and confirming that production and financial risks require immediate and sustained intervention efforts.

2.6 Ethical approval

This research was conducted with full adherence to established ethical standards and received formal approval from the Health Research Ethics Committee at the Faculty of Medicine, Universitas Brawijaya (Ethical Clearance No. 205/UN10/KERIs/07/2025). Although data collection activities were conducted between July and August 2024, the ethical clearance was formally issued in July 2025 as a retrospective approval. The committee verified that all research procedures had been implemented according to ethical principles, particularly voluntary participation, informed consent, and confidentiality assurance, and did not involve any medical or high-risk interventions. Therefore, the approval confirmed the compliance of all prior activities with the Declaration of Helsinki’s ethical standards.

2.7 Ethical consent statement

Prior to participation in this study, all smallholder dairy farmers received comprehensive information regarding the research objectives, methodology, data collection procedures, and confidentiality measures. Informed verbal consent was obtained from each participant following a thorough explanation of their rights, including the voluntary nature of participation and the right to withdraw at any time without consequences. The consent process was conducted in accordance with the ethical guidelines approved under clearance number Ethical Clearance No. 205/UN10/KERIs/07/2025. Strict confidentiality protocols were maintained throughout the research process, ensuring that no personally identifiable information was recorded or disclosed.

3.1 Foot and mouth disease context and prevention strategies

Foot and Mouth Disease (FMD) represents a critical biosecurity threat to dairy farming sustainability, with profound socio-economic implications for smallholder farmers in the study areas. The disease, caused by an RNA virus from the genus Aphthovirus, family Picornaviridae, demonstrates exceptional contagiousness affecting cloven-hoofed animals including cattle, goats, sheep, pigs, and buffalo [5]. The complexity of FMD management is compounded by the existence of seven major serotypes (O, A, C, Asia 1, SAT 1, SAT 2, SAT 3), each containing multiple antigenic subtypes that necessitate serotype-specific vaccination strategies, as cross-protection between serotypes is limited [14].

Clinical manifestations, as illustrated in Figure 3, include high fever (up to 41 °C), excessive salivation, and vesicle formation on the mouth, tongue, and interdigital spaces. The visual documentation in Figure 3 demonstrates the severity of lesions that directly impact animal welfare and productivity. The rupture of these vesicles creates painful open wounds that significantly impair feeding and mobility, leading to substantial weight loss and productivity decline. In dairy cattle, milk production can decrease by 50–80 % within days of infection, representing a catastrophic economic loss for resource-constrained smallholder farmers [14]. Young calves face vulnerability, with mortality rates elevated due to complications such as myocarditis, further threatening herd sustainability and future production capacity.

Figure 3:

Clinical signs of FMD in dairy cattle (authors collection based on survey).

Field observations and farmer interviews confirmed that Foot and Mouth Disease (FMD) remained a major threat to dairy production in Malang Regency during the 2024 outbreak. Approximately 64 % of surveyed farmers reported infection cases within their herds, resulting in an average milk yield reduction of 55–70 % during the peak infection period. Farmers also reported economic losses due to treatment costs and temporary cessation of milk sales.

Recovery efforts were primarily focused on improving biosecurity practices, including footbath installations, vaccination campaigns, and stricter animal movement control. However, 42 % of respondents indicated challenges in accessing vaccines and disinfectants during the early phase of the outbreak.

Local veterinary officers and farmer cooperatives played a key role in coordinating vaccination and information dissemination. Despite this, only 37 % of farmers had formal records of disease treatment and recovery, reflecting limited adoption of farm documentation systems. These findings underscore the need for institutional support and capacity-building initiatives to strengthen FMD prevention and rapid response frameworks within smallholder systems.

3.2 Risk assessment and management framework

The comprehensive risk assessment framework developed through this study identifies five interconnected risk categories that threaten dairy farming sustainability in post-FMD contexts: production, market, financial, institutional, and environmental risks (Table 5) this multi-dimensional approach aligns with contemporary risk management frameworks in agricultural systems [15], 16].

Production risks emerge as the most immediate and severe threat, directly impacting farmers’ livelihoods through animal health deterioration and reproductive disruption. The analysis reveals that FMD-induced health declines trigger cascading effects throughout the production system, reducing milk yields and disrupting reproductive cycles essential for maintaining productive herd demographics [14]. Consumer confidence erosion following disease outbreaks compounds production challenges by dampening market demand, creating a dual pressure on farm viability [17]. This finding corroborates previous research demonstrating that disease outbreaks fundamentally alter consumer perceptions of product safety, necessitating comprehensive risk communication strategies [16]. The risk probability and impact matrix presented in provides critical insights into risk prioritization. Production risks consistently demonstrate both high probability (“Always Happens”) and very large impact, positioning them in the highest priority quadrant. This empirical evidence supports the allocation of primary resources toward production risk mitigation. Financial risks similarly occupy a high-priority position with frequent occurrence and large impacts, reflecting the severe economic constraints faced by smallholder farmers during disease recovery periods. Increased barn waste and waste from sick animals can worsen environmental quality if not properly managed 3.6758. 10 % further illustrates these risk dynamics, visualizing the distribution of risk categories across probability-impact dimensions and confirming that production and financial risks require immediate and sustained intervention efforts.

Market risks, while serious, tend to manifest after the production risks, largely due to fluctuations in milk prices. Price instability often follows reduced supply due to livestock health issues or transport disruptions caused by regulatory measures imposed during outbreaks [18]. Supply chain disruptions, exacerbated by movement restrictions and quarantine measures, further isolate farmers from markets and essential inputs [15]. These findings emphasize the need for resilient market linkages and alternative distribution channels that can maintain functionality during disease emergencies.

Financial risks represent a critical constraint to post-outbreak recovery, as farmers face simultaneously increased operational costs and reduced revenues. The financial burden includes elevated veterinary expenses, premium feed costs due to supply disruptions, and investments in biosecurity infrastructure [19]. Limited access to formal credit compounds these challenges, as financial institutions often perceive disease-affected farms as high-risk borrowers, creating a capital constraint that impedes recovery efforts [16]. This financial vulnerability underscores the importance of targeted financial support mechanisms and risk-sharing instruments for smallholder dairy systems.

Institutional risks manifest through coordination failures and regulatory weaknesses that delay effective disease response and recovery support. The lack of inter-agency coordination results in fragmented assistance delivery and contradictory policy directives that confuse farmers and reduce intervention effectiveness [15]. Weak regulatory enforcement regarding animal health standards and movement controls facilitates disease persistence and re-emergence, undermining long-term sustainability efforts [20]. These institutional challenges highlight the need for integrated governance frameworks that align stakeholder actions toward common disease management objectives.

Environmental risks associated with FMD outbreaks extend beyond immediate disease impacts to encompass broader ecological concerns. The accumulation of cattle carcasses and increased biological waste from infected animals poses significant environmental health risks, potentially contaminating soil and water resources critical for agricultural production [21]. Improper disposal of infectious materials can create disease reservoirs that threaten future outbreak cycles, emphasizing the importance of environmentally sound waste management protocols in disease response strategies.

3.3 Sustainability assessment results

The multi-dimensional sustainability assessment reveals differentiated performance across the three study locations, with Kalipare achieving the highest overall sustainability index (88.84), followed by Bantur (84.93) and Gondanglegi (81.03). While all locations fall within the “excellent” sustainability category, the variations highlight important differences in resilience factors and recovery capacities that inform targeted intervention strategies.

These findings align with established sustainability assessment frameworks that recognize the multi-faceted nature of agricultural sustainability [21]. The superior performance of Kalipare suggests the presence of enabling factors – potentially including stronger social capital, better market access, or more effective institutional support – that enhance overall system resilience. Understanding these location-specific advantages is crucial for designing context-appropriate interventions that build on existing strengths while addressing identified weaknesses.

3.4 Ecological dimension sustainability

The ecological sustainability assessment demonstrates robust performance across all locations, with indices ranging from 81.03 to 84.93, indicating that environmental management practices generally support sustainable production. Figure 4 presents the RAPFISH ordination plot and leverage analysis, revealing the critical importance of microclimate management and spatial planning in tropical dairy systems. The leverage analysis identifies “Air Temperature and Humidity” as the most influential ecological factor (5.09), followed by “Distance from Settlements” (3.94) and “Forage Feed Availability” (3.39).

Figure 4:

Ecological sustainability analysis results and leverage analysis.

The dominance of temperature and humidity in the leverage analysis (Figure 4) underscores a fundamental challenge in tropical lowland dairy systems, where heat stress significantly impacts animal welfare and productivity. High temperature-humidity indices characteristic of the study areas creates physiological stress that reduces feed intake, impairs reproductive performance, and compromises immune function, thereby increasing disease susceptibility [22]. This finding underscores the importance of climate-adaptive infrastructure and management practices, including strategic shade provision, ventilation systems, and adjusted feeding schedules that minimize heat stress impacts on production and health outcomes.

Spatial planning considerations, reflected in the high leverage of “Distance from Settlements,” highlight the complex interface between livestock production and human habitation in densely populated rural areas. Appropriate separation between dairy operations and residential areas serves dual purposes: minimizing zoonotic disease transmission risks while facilitating beneficial nutrient cycling through proper manure management [23]. This spatial dimension becomes particularly critical during disease outbreaks when movement restrictions and quarantine measures require clear demarcation between production and living spaces.

Forage availability constraints reflect the fundamental challenge of feed security in smallholder systems dependent on natural resources and crop residues. The traditional cut-and-carry feeding system, while labor-intensive, represents an adaptation to land constraints and communal grazing restrictions [24]. However, seasonal variations in forage quality and quantity create nutritional stress periods that compromise animal health and increase disease vulnerability, emphasizing the need for feed conservation technologies and alternative feed resource development.

3.5 Economic dimension performance

The economic sustainability analysis reveals substantial disparities among locations, with Kalipare’s superior performance (88.84) contrasting sharply with Gondanglegi’s moderate score (68.82). This variation reflects differential access to productive resources, market opportunities, and support services that fundamentally shape farm economic viability in post-FMD recovery contexts. Figure 5 illustrates the RAPFISH ordination plot for the economic dimension, with the accompanying leverage analysis providing crucial insights into intervention priorities.

Figure 5:

Economic sustainability analysis results and leverage analysis.

As shown in Figure 5, “Average Milk Production” emerges as the primary economic determinant (4.97), confirming the direct relationship between technical efficiency and economic sustainability in smallholder dairy systems. This finding aligns with previous research demonstrating that productivity improvements generate disproportionate economic benefits for resource-constrained farmers [25]. The high leverage value suggests that targeted interventions to enhance production efficiency – through improved genetics, nutrition, and health management – can catalyze significant economic improvements. In post-FMD contexts, production recovery strategies must balance immediate output restoration with long-term productivity enhancement through systematic herd improvement programs.

Government subsidies demonstrate substantial influence on economic sustainability (4.72), highlighting the critical role of public support in maintaining farm viability during crisis periods. Effective subsidy programs can address multiple constraints simultaneously, providing inputs, veterinary services, and infrastructure improvements that individual farmers cannot afford [26]. However, the design and implementation of subsidy programs significantly impact their effectiveness, with poorly targeted or inconsistently delivered support potentially creating dependency rather than building resilience. The findings suggest that subsidy programs should prioritize productivity-enhancing investments and capacity building rather than simple income support.

Business capital access (3.77) represents a fundamental constraint to sustainable intensification and disease resilience in smallholder systems. Limited capital restricts farmers’ ability to invest in improved housing, biosecurity infrastructure, and productivity-enhancing technologies essential for competitive dairy production [27]. The capital constraint is particularly acute during post-outbreak recovery when simultaneous investments in herd rebuilding, infrastructure improvement, and biosecurity enhancement strain limited financial resources. This finding emphasizes the need for innovative financing mechanisms, including value chain financing and group-based credit systems, that address the specific needs and constraints of smallholder dairy farmers.

3.6 Social-cultural sustainability assessment

The social-cultural dimension demonstrates strong performance across locations, with scores ranging from 71.33 to 88.97, reflecting the robust social fabric underlying smallholder dairy systems. Figure 6 presents the RAPFISH ordination plot and leverage analysis for the social-cultural dimension, revealing “Social Participation” as the dominant factor (6.61), followed by “Community Protests or Objections” (4.96) and “Farmer Age” (4.36). These findings emphasize the critical importance of collective action and community engagement in sustainable dairy development.

Figure 6:

Social-cultural sustainability analysis results and leverage analysis.

The exceptional leverage value of social participation shown in Figure 7 indicates that investments in social capital development can generate transformative impacts on system sustainability. Social participation through farmer organizations, cooperatives, and community groups creates multiple pathways for sustainability enhancement. These collective structures facilitate knowledge sharing, enable bulk input procurement, strengthen market negotiation power, and provide platforms for coordinated disease prevention efforts [28]. In the context of FMD management, strong social networks enable rapid information dissemination, coordinated biosecurity measures, and collective resource mobilization essential for effective outbreak response [29].

Figure 7:

Technological sustainability analysis results and leverage analysis.

Community acceptance, reflected in the “Community Protests or Objections” factor (4.96), highlights the importance of maintaining social license for dairy farming operations. Potential conflicts may arise from environmental concerns, particularly related to waste management and water resource competition, or from disease-related fears during outbreaks [30]. Managing these social dynamics requires proactive engagement, transparent communication, and benefit-sharing mechanisms that ensure dairy farming contributes positively to community wellbeing. The findings suggest that sustainable dairy development must explicitly address community concerns and demonstrate tangible local benefits beyond individual farm profits.

The influence of farmer age (4.36) on social sustainability reflects the complex intergenerational dynamics shaping agricultural transformation. Younger farmers often demonstrate greater openness to technological innovations and modern management practices, while older farmers possess invaluable traditional knowledge and established social networks [31]. Successful sustainability strategies must bridge this generational divide, creating knowledge exchange platforms that combine traditional wisdom with modern techniques. The aging farmer population in many dairy communities also raises succession concerns, emphasizing the need for youth engagement strategies that make dairy farming attractive to the next generation.

3.7 Technological dimension challenges

The technological dimension reveals the most significant sustainability challenges, with scores ranging from 45.09 to 58.31, placing most areas in “poor” to “moderate” categories. This technological gap represents both a critical constraint and a major opportunity for sustainability enhancement through targeted innovation adoption. Figure 7 illustrates the RAPFISH ordination plot for the technological dimension, with leverage analysis revealing exceptional opportunities for improvement.

The leverage analysis presented in Figure 8 demonstrates that “Feed Technology Application” has an extraordinary leverage value (14.72), substantially exceeding all other factors across dimensions. This is followed by “Technology Training Intensity” (10.58) and “Feed Production Equipment Ownership” (8.63). The magnitude of these leverage values, particularly for feed technology, indicates that technological interventions offer the highest potential for transformative impacts on system sustainability.

Figure 8:

Institutional sustainability analysis results and leverage analysis.

Technology training intensity (10.58) emerges as a critical enabler of sustainable technology adoption. Effective capacity building must extend beyond simple technology transfer to encompass principles understanding, local adaptation skills, and troubleshooting capabilities that enable farmers to modify and optimize technologies for their specific contexts [32]. The finding that training intensity significantly influences sustainability outcomes challenges conventional approaches that prioritize technology provision over capacity development. Successful technology adoption requires sustained engagement, practical demonstration, and peer learning mechanisms that build farmer confidence and competence.

Feed production equipment ownership (8.63) represents a tangible constraint to technology adoption, as capital-intensive equipment remains inaccessible to individual smallholder farmers. Simple technologies like chaff cutters can significantly reduce labor requirements while improving feed utilization efficiency, yet their cost exceeds many farmers’ investment capacity [33]. This finding suggests the potential for collective ownership models, equipment rental services, or graduated technology packages that make essential equipment accessible while building farmer capacity for more advanced technologies.

3.8 Institutional sustainability framework

The institutional sustainability assessment reveals moderate to strong performance, with significant variation among locations (Kalipare: 82.93, Gondanglegi: 79.81, Bantur: 67.58). This variation reflects differences in local governance effectiveness, organizational density, and institutional support quality that fundamentally shape dairy development outcomes. Figure 8 depicts the RAPFISH ordination plot for the institutional dimension, with leverage analysis highlighting key intervention points.

As illustrated in Figure 9, “Government Official or Local Leader Roles” emerges as the most influential institutional factor (5.07), followed by “Stakeholder Involvement” (3.51) and “Extension or Training Programs” (3.27). The prominence of leadership roles in the leverage analysis highlights the critical importance of effective governance in facilitating sustainable dairy development. Effective leaders serve multiple functions: bridging farmers with external support systems, mediating conflicts, enforcing collective agreements, and championing innovation adoption [34]. In the context of disease management, local leadership becomes particularly crucial for ensuring compliance with biosecurity measures, coordinating outbreak responses, and maintaining community cohesion during crisis periods.

Figure 9:

Information systems sustainability analysis results and leverage analysis.

Stakeholder involvement (3.51) reflects the importance of participatory governance approaches that engage diverse actors in planning and implementation processes. Multi-stakeholder platforms that bring together farmers, government agencies, private sector actors, and civil society organizations can enhance program relevance, improve resource allocation, and ensure sustained support for dairy development initiatives. The moderate leverage value suggests that while stakeholder engagement is important, its effectiveness depends on the quality of engagement processes and the genuine empowerment of farmer voices in decision-making.

Extension and training programs (3.27) show surprisingly modest influence on institutional sustainability, suggesting that traditional extension approaches may have limited impact without complementary institutional reforms. These finding challenges conventional agricultural development models that prioritize technical extension while neglecting broader institutional environments [35]. Effective extension systems must be embedded within supportive institutional frameworks that ensure consistent funding, appropriate incentive structures, and meaningful farmer participation in program design and evaluation.

3.9 Information systems sustainability

Information systems sustainability shows moderate performance across locations (Kalipare: 78.03, Gondanglegi: 76.85, Bantur: 72.20), indicating significant potential for enhancement through improved information access and management. Figure 9 illustrates the RAPFISH ordination plot for information systems dimension, revealing remarkably similar leverage values for marketing (5.54), production (5.34), and animal health (5.28) information systems. This convergence suggests that comprehensive information strategies addressing multiple domains simultaneously are necessary for sustainable dairy development.

The balanced leverage values across information system types shown in Figure 9 indicate that no single information domain can be prioritized in isolation. Marketing information systems enable farmers to make informed decisions about production timing, quality standards, and market selection, particularly crucial during post-outbreak market recovery when consumer confidence requires rebuilding [36]. Production information systems support evidence-based farm management through systematic record keeping and performance monitoring, while animal health information systems assume critical importance for disease prevention and early outbreak detection [37].

Production information systems support evidence-based farm management through systematic record keeping and performance monitoring. In post-FMD contexts, production records become essential for tracking recovery progress, identifying persistent impacts, and demonstrating biosecurity compliance to market actors [38]. Digital tools and mobile applications offer potential for simplifying record keeping, though successful adoption requires user-friendly interfaces and clear value propositions that demonstrate tangible benefits to farmers [39], [40], [41].

Animal health information systems assume critical importance for disease prevention and early outbreak detection. Effective health information networks can facilitate rapid disease reporting, coordinate veterinary responses, and disseminate prevention guidelines [37]. The integration of traditional community-based surveillance with modern digital reporting systems offers promising approaches for enhancing disease detection sensitivity while maintaining local engagement and ownership.

3.10 Mitigation strategies and interventions

Based on the sustainability assessment and leverage analysis results, several mitigation strategies emerge as priorities for enhancing dairy farming sustainability in post-FMD contexts. Table 6 presents a comprehensive framework of five key mitigation strategies, each addressing specific vulnerabilities identified through the Rapdairy assessment and designed to enhance system resilience against future disease outbreaks and sustainability challenges.

As outlined in the mitigation strategies framework, enhanced biosecurity emerges as the foundational strategy, addressing the immediate disease risks while building long-term system resilience. Comprehensive biosecurity programs must extend beyond individual farm practices to encompass community-level coordination, as disease transmission dynamics in smallholder systems transcend individual farm boundaries [42]. Effective biosecurity implementation requires balancing technical effectiveness with practical feasibility and economic viability for resource-constrained farmers. This includes developing low-cost biosecurity options, community-based surveillance systems, and collective action mechanisms that distribute costs and benefits equitably.

Business diversification strategies acknowledge the inherent vulnerability of specialized dairy systems to disease shocks and market volatility. Diversification options must consider local resource endowments, market opportunities, and farmer capabilities while maintaining dairy as the primary enterprise [43]. Integrated farming systems that combine dairy with complementary enterprises – such as biogas production, fodder cultivation, or small-scale processing – can create synergies that enhance overall farm resilience while improving resource use efficiency.

Production cost efficiency improvements target the economic sustainability constraints identified in the assessment. Beyond simple cost reduction, efficiency strategies should focus on optimizing input use, reducing waste, and enhancing value capture throughout the production process [44]. This includes developing local feed resources, improving reproductive efficiency, and adopting appropriate technologies that reduce labor requirements while maintaining production quality.

Institutional strengthening addresses the governance and coordination challenges that limit effective disease management and sustainable development. Strengthening farmer organizations, improving inter-agency coordination, and developing clear institutional frameworks for disease management can significantly enhance system resilience [45]. Particular attention should focus on developing institutional mechanisms for rapid disease response, equitable resource allocation, and sustained support for vulnerable farmers during recovery periods.

Partnership and collaboration strategies recognize that sustainable dairy development requires coordinated action among diverse stakeholders with complementary resources and capabilities. Public-private partnerships can leverage private sector efficiency with public sector mandates for inclusive development, while farmer-industry linkages can ensure stable markets and technology access [46]. Successful partnerships require clear benefit-sharing agreements, transparent governance structures, and mechanisms for ensuring smallholder farmers’ meaningful participation in decision-making processes.