Peer learning in immunisation programmes

Peer learning in immunization programmes

and Global health

The path to strengthening immunization systems requires innovative technical assistance approaches to learning and capacity building. A recent correspondence in The Lancet proposes peer learning in immunization programmes as a crucial mechanism for achieving the goals of the Immunization Agenda 2030 (IA2030), arguing for “an intentional, well coordinated, fit-for-purpose, data-driven, and government-led immunisation peer-learning plan of action.” This proposal merits careful examination, particularly as immunization programmes face complex challenges in reaching 2030 goals.

Learn more: 50 years of the Expanded Programme on Immunization (EPI)

Beyond traditional knowledge exchange

The Lancet commentary identifies several key rationales for peer learning in immunization.

  • First, “immunisation policy makers operate in dynamic sociopolitical and economic contexts that often compel quick decision making.” In such environments, peer knowledge becomes crucial “when research evidence is scarce.”
  • Second, the authors recognize that “contextual factors in immunisation systems are constantly interacting to exhibit emergent behaviour and self-organisation,” necessitating constant adaptation of technical approaches.

These insights point toward an important truth: traditional approaches to knowledge sharing – whether through technical guidelines, formal training, or policy exchange – remain necessary but increasingly insufficient for today’s challenges.

The question becomes not just how to share what we know, but how to systematically generate new knowledge about what works in different contexts.

Complementary approaches to peer learning in immunization programmes

While government counterparts learning from each other offers valuable benefits for policy coordination and strategic alignment, implementation challenges are situated – and solved – at the local levels. This call for complementary peer learning approaches. Three stand out as particularly critical:

  • First, the persistent gap between national planning and local implementation suggests the need for systematic learning about how policies and strategies are turned into effective, community-led and -owned action on the ground.
  • Second, as programmes work to sustain coverage gains beyond campaign-based interventions, they need reliable mechanisms for identifying and spreading effective practices for routine immunization.
  • Third, the continuous influx of new staff into EPI teams creates an ongoing need for rapid capacity building that goes beyond technical training to include development of professional networks and practical implementation skills.

From reporting challenges to creating implementation knowledge

A crucial distinction emerges between simply documenting implementation challenges and systematically creating new knowledge about effective implementation. This difference parallels the distinction in epidemiology between case reporting and analytical epidemiology.

When health workers report challenges, they might note that coverage is low in remote areas due to transport limitations, staff shortages, and cold chain issues. This provides valuable surveillance data but does not necessarily generate actionable knowledge. In contrast, systematic analysis of successful remote area coverage can reveal specific transport solutions that work, staff deployment patterns that succeed, and cold chain adaptations that enable reach.

This shift from reporting to knowledge creation requires careful structure and support. Just as analytical epidemiology employs specific methods to move from observation to insight, systematic peer learning needs frameworks and processes that enable pattern recognition, cross-context learning, and theory building about what works.

Enabling systematic learning at scale

Recent experience demonstrates the feasibility of systematic peer learning at scale. For example, Gavi-supported country-led initiatives facilitated by The Geneva Learning Foundation (TGLF) in Côte d’Ivoire and Nigeria, health workers from districts and facilities shared specific strategies through structured processes, they collectively generate new knowledge about effective implementation. Launched in 2022 with support from Wellcome, the Movement for Immunization Agenda 2030 (IA2030) has demonstrated that such ground-level learning, when properly captured and analyzed, provides crucial insights for national planning.

Consider the introduction of new vaccines. When thousands of practitioners share specific experiences about what enables successful introduction, patterns emerge that might be missed in smaller exchanges or formal evaluations. These patterns help reveal not just what works, but how solutions adapt and evolve across contexts.

Learn more: Movement for Immunization Agenda 2030 (IA2030): National EPI leaders from 31 countries share experience of HPV vaccination

Supporting new EPI staff through networked learning

The challenge of rapidly building capacity when new staff join EPI teams highlights the potential value of structured peer learning. Training approaches like Mid-Level Management (MLM) Training provide essential technical foundations, and have been able to reach more professionals by moving online. However, new staff also need to rapidly build professional networks and learn from peers facing similar challenges.

A cohort-based approach combining technical training with structured peer learning can accelerate both capability development and network formation. This helps new staff analyze local challenges, identify priorities, and access peer support for implementation. Cross-country learning opportunities are particularly valuable for young professionals, enabling them to build relationships beyond hierarchical constraints.

From vaccination campaigns to sustainable primary health care systems that integrate routine immunization

For immunization programmes work to sustain coverage gains beyond campaign-based interventions, peer learning networks are needed to support the transition to stronger routine immunization systems. By connecting practitioners across health system levels, these networks help identify and spread effective practices for reaching families through regular services.

This network-based approach complements formal exchange mechanisms by creating multiple pathways for knowledge flow:

  • Ground-level innovations inform national strategy through systematic capture and analysis
  • Peer feedback helps practitioners adapt solutions to local contexts
  • Implementation experiences create evidence about what works and why
  • Cross-level dialogue strengthens connections between policy and practice

Peer learning embedded into government-owned health systems

This peer learning approach does not replace traditional technical assistance, capacity building, or policy exchange. Rather, it transforms them by creating new connections between levels and actors in health systems. While formal exchanges remain crucial for policy coordination, structured peer learning adds vital capabilities:

  1. Granular understanding of implementation challenges while maintaining systematic rigor in knowledge capture;
  2. Documentation of practical innovations while creating frameworks for adaptation across contexts; and
  3. Evidence-based feedback loops between policy and practice.

Success requires careful attention to structure. Through carefully designed processes, practitioners engage in cycles of sharing, feedback, connection, and action. This structure is not bureaucratic control but scaffolding that supports genuine knowledge creation and application.

Looking forward

The World Health Organization’s Executive Board has highlighted widening inequities between and within countries as a critical challenge for immunization programmes. In the African region particularly, where many countries are introducing new vaccines while working to strengthen basic immunization services, innovative approaches are needed.

New evidence from recent large-scale peer learning initiatives suggests that structured approaches can help bridge the gap between strategy and implementation while strengthening both. Success requires investment in learning processes and support structures – but the potential rewards, in terms of accelerated progress and improved outcomes, make this investment worthwhile.

This offers a concrete path toward what WHO calls for: “grounding action in local realities.” By systematically connecting learning across health system levels while maintaining rigorous standards for evidence and implementation support, we can create learning systems that effectively link regional strategy with local innovation and action.

The future of immunization capacity building lies not in choosing between formal exchanges and practitioner networks, but in thoughtfully combining them to create comprehensive learning systems. These systems can drive rapid improvement while strengthening health systems as a whole – an essential goal as we work toward ambitious immunization targets for 2030 and beyond.

Reference

Adamu AA, Ndwandwe D, Jalo RI, Ndoutabe M, Wiysonge CS. Peer learning in immunisation programmes. The Lancet [Internet]. 2024 Jul; 404(10450):334–5. Available from: https://doi.org/10.1016/S0140-6736(24)01340-0

Jones, I., Sadki, R., Brooks, A., Gasse, F., Mbuh, C., Zha, M., Steed, I., Sequeira, J., Churchill, S., & Kovanovic, V. (2022). IA2030 Movement Year 1 report. Consultative engagement through a digitally enabled peer learning platform (1.0). The Geneva Learning Foundation. https://doi.org/10.5281/zenodo.7119648

Image: The Geneva Learning Foundation Collection © 2024

An AI-generated podcast dialogue exploring The Geneva Learning Foundation’s progress in 2024

A generative AI podcast dialogue exploring The Geneva Learning Foundation’s progress in 2024

Global health

This experimental podcast, created in collaboration with generative AI, demonstrates a novel approach to exploring complex learning concepts through a conversational framework that is intended to support dialogic learning. Based on TGLF’s 2024 end-of-year message and supplementary materials, the conversation examines their peer learning model through a combination of concrete examples and theoretical reflection. The dialogue format enables exploration of how knowledge emerges through structured interaction, even in AI-generated content.

Experimental nature and limitations of generative AI for dialogic learning

This content is being shared as an exploration of how generative AI might contribute to learning and knowledge construction. While based on TGLF’s actual 2024 message, the dialogue includes AI-generated elaborations that may contain inaccuracies. However, these limitations themselves provide interesting insights into how knowledge emerges through interaction, even in artificial contexts.

You can read our actual 2024 Year in review message here.

Pedagogical value and theoretical implications of a generative AI conversational framework

Structured knowledge construction: The conversational framework illustrates how knowledge can emerge through structured dialogue, even when artificially generated. This mirrors TGLF’s own insights about how structure enables rather than constrains dialogic learning.

Multi-level learning: The dialogue operates on multiple levels:

  • Direct information sharing about TGLF’s work
  • Modeling of reflective dialogue
  • Meta-level exploration of how knowledge emerges through interaction
  • Integration of concrete examples with theoretical reflection

Network effects in learning: The conversation demonstrates how different types of knowledge (statistical, narrative, theoretical, practical) can be woven together through dialogue to create deeper understanding. This parallels TGLF’s observations about how learning emerges through structured networks of interaction.

    We invite listeners to consider:

    • How a conversational framework enables exploration of complex ideas
    • The role of structure in enabling knowledge emergence
    • The relationship between concrete examples and theoretical understanding
    • The potential and limitations of AI in supporting dialogic learning

    This experiment invites reflection not just on the content itself, but on how knowledge and understanding emerge through structured interaction – whether human or artificial.

    Your insights about how this generative AI format affects your understanding will help inform future explorations of AI’s role in learning.

    What aspects of the conversational framework enhanced or hindered your understanding?

    How did the interplay of concrete examples and reflective discussion affect your learning?

    What difference did it make that you knew before listening that the conversation was created using generative AI?

    We welcome your thoughts on these deeper questions about how learning happens through structured interaction.

    The cost of inaction Quantifying the impact of climate change on health

    The cost of inaction: Quantifying the impact of climate change on health

    Global health

    This World Bank report ‘The Cost of Inaction: Quantifying the Impact of Climate Change on Health in Low- and Middle-Income Countries’ presents new analysis of climate change impacts on health systems and outcomes in the regions that are bearing the brunt of these impacts.

    Key analytical insights to quantify climate change impacts on health

    The report makes three contributions to our understanding of climate-health interactions:

    First, it quantifies the massive scale of climate change impacts on health, projecting 4.1-5.2 billion climate-related disease cases and 14.5-15.6 million deaths in LMICs by 2050. This represents a significant advancement over previous estimates, which the report demonstrates were substantial underestimates.

    Second, it illuminates the profound economic consequences, calculating costs of $8.6-20.8 trillion by 2050 (0.7-1.3% of LMIC GDP). The report employs both Value of Statistical Life and Years of Life Lost approaches to provide a range of economic impact estimates.

    Third, it reveals stark geographic inequities in impact distribution, with Sub-Saharan Africa bearing approximately 71% of cases and nearly half of deaths, while South Asia faces about 18% of cases and a quarter of deaths. This spatial analysis helps identify where interventions are most urgently needed.

    Policy implications and systemic perspectives

    The report’s findings point to several critical policy directions:

    • The need for systemic rather than disease-specific interventions emerges as a central theme. The authors explicitly advocate for strengthening entire health systems rather than pursuing vertical disease programs.
    • The economic analysis makes a compelling case for immediate action, demonstrating that the costs of inaction far exceed potential investment requirements for climate-resilient health systems.
    • The geographic distribution of impacts highlights the need for globally coordinated responses while prioritizing support for the most vulnerable regions.

    The findings suggest that transforming systems to address climate change impacts on health requires not just technical solutions but fundamental rethinking of how health systems are organized and financed in vulnerable regions.

    This aligns with recent scholarship on complex adaptive systems and organizational transformation in global health.

    The report’s emphasis on systemic approaches represents a significant shift in thinking about climate-health interventions. This merits unpacking on several levels:

    1. Inadequacy of vertical disease silos: The report challenges the traditional vertical disease management paradigm that has dominated global health programming for decades. While vertical programs have achieved notable successes in areas like HIV/AIDS or malaria control, the report argues that climate change’s multifaceted health impacts require a fundamentally different approach.
    2. Need for systemic intervention: Climate change simultaneously affects multiple disease pathways, nutrition status, and health infrastructure. These interactions cannot be effectively addressed through isolated disease-specific programs. Building core health system capabilities (surveillance, emergency response, primary care) creates multiplicative benefits across various climate-related health challenges. Strong health systems can better identify and respond to emerging threats, whereas vertical programs often lack this flexibility.
    3. Implementation implications: The report suggests this systemic approach requires: integrated planning across health system components, flexible funding mechanisms that support system-wide capabilities, enhanced coordination between different health programmes and investment in cross-cutting infrastructure and capabilities.

    What about the health workforce facing impacts of climate change on health?

    Between this clear-eyed assessment and effective action lies a critical implementation gap.

    Interestingly, the report gives limited explicit attention to the health workforce dimension of climate-health challenges. Yet that is precisely where we need to focus attention, given that:

    • Health workers based in communities are first responders to climate-related health emergencies
    • Workforce capacity significantly determines a health system’s adaptive capabilities
    • Climate change itself affects health worker distribution and effectiveness

    Given the report’s emphasis on systemic approaches, the lack of detailed discussion about human resources for health represents a missed opportunity to explore what effective action might look like.

    The Geneva Learning Foundation’s network, developed through nearly a decade of research and practice, has led us to identify a path for supporting the health workforce to strengthen preparedness and response in response to climate change impacts on health.

    The network already connects over 60,000 health workers. They represent all job roles, rank, and levels of the health system.

    One distinguishing feature of this network is its deep integration with existing government health systems. Over half of network participants are government employees, from community health workers to district officers to national planners.

    62% of participants work in remote rural areas, 47% serve urban poor populations, and 21% operate in conflict zones.

    These are not just statistics: they represent an unprecedented capability to mobilize knowledge and action where it’s most needed.

    Since 2023, network participants have been sharing observations, experiences, and insights of climate change impacts on health. 

    The model connects different levels of health systems:

    • Community-based health workers share ground-level observations
    • District managers identify emerging patterns
    • National planners gauge system-wide implications
    • Global partners access real-time insights

    When a malaria control officer in Kenya observes changing disease patterns due to altered rainfall, the network enables rapid sharing of this insight with colleagues working on water safety, nutrition, and primary care. These cross-domain connections do not need to be left to chance – they can be enabled through structured peer learning processes that transcend traditional programme, geographic, and hierarchical boundaries

    This creates what organizational theorists call “embedded transformation” – where system change emerges through existing structures rather than requiring new ones.

    Rather than creating new coordination mechanisms, the network enables:

    • Health workers to learn directly from peers in other programs
    • Rapid identification of cross-cutting challenges
    • Spontaneous formation of problem-solving groups
    • Systematic sharing of effective practices

    Rather than replacing existing structures, TGLF’s model demonstrates how digital networks can enable health systems to:

    • Maintain necessary specialization while fostering crucial connections
    • Enable rapid learning and adaptation across programs
    • Optimize resource use through enhanced coordination
    • Build system-wide resilience through structured peer learning

    Such a network enables what complexity theorists call “distributed sensing” that can provide:

    • Early warning of emerging threats
    • Rapid sharing of local solutions
    • System-wide learning from local innovations
    • Continuous adaptation to changing conditions

    This has led us to posit that investment in such emergent digital networks could enable health systems to maintain necessary specialization while fostering crucial connections across domains.

    This is obviously critical to respond to the systems-level complexity of climate change impacts on health.

    World Bank findingTGLF model strategic fit
    Scale of impact (4.1-5.2B cases, 14.5-15.6M deaths by 2050)TGLF’s digital network model demonstrates scalability, already connecting over 60,000 health practitioners across 137 countries. More significantly, the model’s effectiveness increases with scale – as more practitioners join, the network’s ability to identify emerging threats and disseminate effective responses improves. Network analysis shows that larger scale enables more diverse inputs and faster adaptation, suggesting this approach could help health systems respond to the massive scale of projected impacts.
    Economic consequences ($8.6-20.8T by 2050)TGLF’s model offers remarkable cost-effectiveness through its networked learning structure. Rather than requiring massive new investments in parallel systems, it leverages existing health system resources while enabling and accelerating both learning and action. The model demonstrates how digital infrastructure can maximize return on investment – practitioners implement solutions using existing resources, with 82% reporting ability to continue without external support. This suggests potential for significant cost savings while building system resilience.
    Geographic inequities (71% SSA, 18% SA)TGLF’s network already demonstrates strongest presence precisely where the World Bank identifies greatest need – 70% of participants work in Sub-Saharan Africa and South Asia. This concentration is not coincidental; the model’s digital infrastructure and peer learning approach prove particularly effective in resource-constrained settings. The network enables rapid sharing of context-appropriate solutions between regions facing similar challenges, while maintaining sensitivity to local conditions.
    Need for systemic interventionThe network transcends traditional program boundaries through what organizational theorists call “structured emergence” – practitioners naturally form cross-program connections based on shared challenges. When a malaria control officer observes changing disease patterns due to climate shifts, the network enables rapid sharing with colleagues in water safety, nutrition, and primary care. This organic integration emerges through peer learning rather than requiring new coordination mechanisms.
    Urgency of investmentTGLF’s model offers an immediately scalable approach that builds on existing health system capabilities. Rather than waiting years to develop new infrastructure, the network can rapidly expand to connect more practitioners and regions. Evidence shows 7x acceleration in implementation of new approaches compared to conventional means of technical assistance, suggesting potential for rapid, sustainable strengthening of health system resilience.
    Global coordination needWhile enabling global connection, the network maintains strong local grounding through its emphasis on locally-led action and contextual adaptation. Government health workers comprise over 50% of participants, creating what scholars term “embedded transformation” – change emerging through existing structures rather than imposed from outside. This enables coordinated response while respecting local health system authority.
    System transformationThe model demonstrates how digital networks can fundamentally transform how health systems operate without requiring complete restructuring. By enabling rapid knowledge flow across traditional boundaries, supporting emergence of new coordination patterns, and fostering system-wide learning, it shows how transformation can emerge through enhanced connection rather than structural overhaul. Analysis reveals development of new capabilities in surveillance, response, and adaptation through networked learning.

    Reference

    Uribe, J.P., Rabie, T., 2024. The Cost of Inaction: Quantifying the Impact of Climate Change on Health in Low- and Middle-Income Countries. The World Bank, Washington, D.C. https://doi.org/10.1596/42419

    Image: The Geneva Learning Foundation Collection © 2024

    Donald A. Schön The new scholarship requires a new epistemology

    Knowing-in-action: Bridging the theory-practice divide in global health

    Global health

    The gap between theoretical knowledge and practical implementation remains one of the most persistent challenges in global health. This divide manifests in multiple ways: research that fails to address practitioners’ urgent needs, innovations from the field that never inform formal evidence systems, and capacity building approaches that cannot meet the massive scale of learning required. Donald Schön’s seminal 1995 analysis of the “dilemma of rigor or relevance” in professional practice offers crucial insights for “knowing-in-action“. It can help us understand why transforming global health requires new ways of knowing – a new epistemology.

    Listen to this article below. Subscribe to The Geneva Learning Foundation’s podcast for more audio content.

    Schön’s analysis: The dilemma of rigor or relevance

    Schön begins by examining how knowledge becomes institutionalized through education. Using elementary school mathematics as an example, he describes how knowledge is broken into discrete units (“math facts”), organized into progressive modules, assembled into curricula, and measured through standardized tests. This systematization shapes not just content but the entire organization of time, space, and institutional arrangements.

    From this foundation, Schön introduces his central metaphor of two contrasting landscapes in professional practice that prevent “knowing-in-action”. As he describes it:

    “In the varied topography of professional practice, there is a high, hard ground overlooking a swamp. On the high ground, manageable problems lend themselves to solution through the use of research-based theory and technique. In the swampy lowlands, problems are messy and confusing and incapable of technical solution.”

    The cruel irony, Schön observes, lies in the relative importance of these terrains: “The problems of the high ground tend to be relatively unimportant to individuals or to society at large, however great their technical interest may be, while in the swamp lie the problems of greatest human concern.”

    This creates what Schön calls the “dilemma of rigor or relevance” – practitioners must choose between remaining on the high ground where they can maintain technical rigor or descending into the swamp where they must rely on experience, intuition, and what he terms “muddling through.”

    The historical roots of the divide

    Schön traces this dilemma to the epistemology embedded in modern research universities. Drawing on Edward Shils’s historical analysis, he describes how American scholars returning from Germany after the Civil War brought back “the German idea of the university as a place in which to do research that contributes to fundamental knowledge, preferably through science.”

    This was, as Schön notes, “a very strange idea in 1870,” running counter to the prevailing British model of universities as sanctuaries for liberal arts or finishing schools for gentlemen. The new model first took root at Johns Hopkins University, whose president embraced the “bizarre notion that professors should be recruited, promoted, and granted tenure on the basis of their contributions to fundamental knowledge.”

    This shift created what Schön terms the “Veblenian bargain” (named after Thorstein Veblen), establishing a separation between:

    • Research universities focused on “true scholarship” and fundamental knowledge
    • Professional schools dedicated to practical training

    Knowing-in-action in global health: From fragmentation to integration

    The historical division between theory and practice that Schön identified continues to shape global health in profound and often problematic ways. This manifests in three interconnected challenges that demand our urgent attention: the knowledge-practice gap, the scale challenge, and the complexity challenge. Yet emerging approaches suggest potential paths forward, particularly through structured peer learning networks that could help bridge Schön’s “high ground” and “swamp.”

    Three fundamental challenges

    Challenge : The knowing-in-action divide

    The separation between research institutions and field practice creates not just an academic concern but a practical crisis in healthcare delivery. Consider the response to COVID-19: while research institutions rapidly generated new knowledge about the virus, frontline health workers struggled to translate this into practical approaches for their specific contexts. Their hard-won insights about what worked in different settings rarely made it back into formal evidence systems, epitomizing the one-way flow of knowledge that impoverishes both research and practice.

    This pattern repeats across global health. Research agendas, shaped by academic incentives and funding priorities, often fail to address practitioners’ most pressing challenges. A community health worker in rural Bangladesh facing complex challenges around vaccine hesitancy may struggle to find relevant guidance – while global experts are convinced that they already have all the answers. Meanwhile, local solutions to building vaccine confidence remain uncaptured by formal knowledge systems.

    The rise of implementation science attempts to bridge this divide, yet often remains subordinate to “pure” research in academic hierarchies. This reflects Schön’s observation about the privileging of high ground problems over swampy ones, even when the latter hold greater practical significance.

    Challenge : The scale imperative

    Traditional approaches to professional education face fundamental limitations in meeting the massive need for health worker capacity building. The World Health Organization projects a shortfall of 10 million health workers by 2030, mostly in low- and middle-income countries. Conventional training approaches that rely on cascading knowledge through workshops and formal courses can reach only a fraction of those who need support.

    More fundamentally, these knowledge transmission models prove inadequate for addressing complex local realities. A standardized curriculum developed by experts, no matter how well-designed, cannot anticipate the diverse challenges health workers face across different contexts. When a district immunization manager in Nigeria must adapt vaccination strategies for nomadic populations during a drought, they need more than pre-packaged knowledge – they need ways to learn from others who are facing similar challenges.

    Resource constraints further limit the reach of conventional approaches. The cost of traditional training programmes, both in money and time away from service delivery, makes it impossible to scale them to meet the need. Yet the human cost of this capacity gap, measured in preventable illness and death, demands urgent solutions.

    Challenge : The complexity conundrum

    Contemporary global health faces challenges that fundamentally resist standardized technical solutions. Climate change exemplifies this complexity, creating cascading effects on health systems and communities that cannot be addressed through linear interventions. When rising temperatures alter disease patterns while simultaneously disrupting cold chains for vaccine delivery, no single technical fix suffices.

    Similarly, emerging and re-emerging infectious diseases demand responses that cross traditional boundaries between animal and human health, environmental factors, and social determinants. Health workforce development must grapple with complex systemic issues around motivation, retention, and capacity building. The COVID-19 pandemic demonstrated how traditional approaches to health system strengthening often prove inadequate in the face of complex adaptive challenges.

    Emerging solutions: A new paradigm for learning and practice

    Recent innovations suggest promising approaches to bridging these divides through structured peer learning networks. Digital platforms enable health workers to share experiences and solutions across geographical boundaries, creating new possibilities for scaled learning that maintains local relevance.

    Solution : The power of structured peer learning

    Experience from digital learning networks demonstrates how structured peer interaction can enable more efficient and effective knowledge sharing than traditional top-down approaches. When health workers can directly connect with peers facing similar challenges, they not only share solutions but collectively generate new knowledge through their interactions.

    These networks provide mechanisms for validating practical knowledge through peer review processes that complement traditional academic validation. A successful intervention developed by a rural clinic in Thailand can be critically examined by peers, adapted for different contexts, and rapidly disseminated across the network. This creates a more dynamic and responsive knowledge ecosystem than traditional publication cycles allow.

    Solution : Network effects and collective intelligence

    The potential of practitioner networks extends beyond simple knowledge sharing. When properly structured, these networks create possibilities for:

    1. Rapid adaptation to emerging challenges through real-time sharing of experiences
    2. Collective problem-solving that draws on diverse perspectives and contexts
    3. Systematic capture and analysis of field innovations
    4. Development of context-specific solutions that build on shared learning

    Most importantly, these networks can help bridge Schön’s high ground and swamp by creating dialogue between different forms of knowledge and practice. They provide spaces where academic research can inform field practice while simultaneously allowing field insights to shape research agendas.

    Four principles toward knowing-in-action for global health

    Drawing on Schön’s call for a “new epistemology,” we can identify four principles for transforming how we know what we know in global health:

    Principle : Valuing multiple forms of knowledge

    The complexity of contemporary health challenges demands recognition of multiple valid forms of knowledge. The practical wisdom developed by a community health worker through years of service deserves attention alongside randomized controlled trials. This requires challenging existing hierarchies of evidence while maintaining rigorous standards for validating knowledge claims.

    Principle : Enabling knowledge creation from practice

    Health workers must be supported as knowledge producers, not just knowledge consumers. This means creating structures for systematically capturing and validating field insights, building evidence from implementation experience, and enabling continuous learning from practice. Digital platforms can provide scaffolding for this knowledge creation while ensuring quality through peer review processes.

    Principle : Scaling through networked learning

    Traditional scaling approaches that rely on standardization and top-down dissemination must be complemented by networked learning to create and amplify knowing-in-action. This means building systems that can:

    1. Connect practitioners across contexts and boundaries
    2. Enable peer validation of knowledge
    3. Support rapid dissemination of innovations
    4. Build collective intelligence through structured interaction

    Principle : Embracing complexity

    Rather than seeking to reduce complexity through standardization, health systems must build capacity for working effectively within complex adaptive systems. This means supporting adaptive learning, enabling context-specific solutions, and building capacity for systems thinking at all levels.

    The challenges facing global health today demand new ways of creating, validating, and sharing knowledge. By embracing approaches that bridge Schön’s high ground and swamp, we may find paths toward health systems that are both more rigorous and more relevant to the communities they serve.

    Looking forward

    Schön’s analysis helps explain why traditional approaches to global health knowledge and learning often fall short. More importantly, it points toward solutions that could help bridge the theory-practice divide to support knowing-in-action:

    1. New digital platforms that enable peer learning at scale
    2. Networks that connect practitioners across contexts
    3. Approaches that validate practical knowledge
    4. Systems that support rapid learning and adaptation

    Schön’s insights remain remarkably relevant to contemporary global health challenges. His call for a new epistemology that can bridge theory and practice speaks directly to our current needs. By embracing new approaches to learning and knowledge creation that honor both rigor and relevance, we may find ways to address the complex challenges that lie ahead.

    The key lies not in choosing between high ground and swamp, but in building new kinds of bridges between them – bridges that can support the massive scale of learning needed while maintaining the local relevance essential for impact. Recent innovations in peer learning networks and digital platforms suggest this bridging may be increasingly possible, offering hope for more effective global health practice in an increasingly complex world.

    The challenge now is to develop and implement these bridging approaches at the scale needed to support global health workers worldwide. This will require new ways of thinking about knowledge, learning, and practice – ways that honor both the rigor of research and the wisdom of experience. The future of global health may depend on our success in this endeavor.

    Listen to the AI podcast deep dive about this article

    Reference

    Schön, Donald A., 1995. Knowing-in-action: The new scholarship requires a new epistemology. Change: The Magazine of Higher Learning 27, 27–34. https://doi.org/10.1080/00091383.1995.10544673

    Image: The Geneva Learning Foundation Collection © 2024

    What are the consequences of the false dichotomy between global and local knowledge in health systems

    Why guidelines fail: on consequences of the false dichotomy between global and local knowledge in health systems

    Global health

    Global health continues to grapple with a persistent tension between standardized, evidence-based interventions developed by international experts and the contextual, experiential local knowledge held by local health workers. This dichotomy – between global expertise and local knowledge – has become increasingly problematic as health systems face unprecedented complexity in addressing challenges from climate change to emerging diseases.

    The limitations of current approaches

    The dominant approach privileges global technical expertise, viewing local knowledge primarily through the lens of “implementation barriers” to be overcome. This framework assumes that if only local practitioners would correctly apply global guidance, health outcomes would improve.

    This assumption falls short in several critical ways:

    1. It fails to recognize that local health workers often possess sophisticated understanding of how interventions need to be adapted to work in their contexts.
    2. It overlooks the way that local knowledge, built through direct experience with communities, often anticipates problems that global guidance has yet to address.
    3. It perpetuates power dynamics that systematically devalue knowledge generated outside academic and global health institutions.

    The hidden costs of privileging global expertise

    When we examine actual practice, we find that privileging global over local knowledge can actively harm health system performance:

    • It creates a “capability trap” where local health workers become dependent on external expertise rather than developing their own problem-solving capabilities.
    • It leads to the implementation of standardized solutions that may not address the real needs of communities.
    • It demoralizes community-based staff who see their expertise and experience consistently undervalued.
    • It slows the spread of innovative local solutions that could benefit other contexts.

    Evidence from practice

    Recent experiences from the COVID-19 pandemic provide compelling evidence for the importance of local knowledge. While global guidance struggled to keep pace with evolving challenges, local health workers had to figure out how to keep health services going:

    • Community health workers in rural areas adapted strategies.
    • District health teams created new approaches to maintain essential services during lockdowns.
    • Facility staff developed creative solutions to manage PPE shortages.

    These innovations emerged not from global technical assistance, but from local practitioners applying their deep understanding of community needs and system constraints, and by exploring new ways to connect with each other and contribute to global knowledge.

    Towards a new synthesis

    Rather than choosing between global and local knowledge, we need a new synthesis that recognizes their complementary strengths. This requires three fundamental shifts:

    1. Reframing local knowledge

    • Moving from viewing local knowledge as merely contextual to seeing it as a source of innovation.
    • Recognizing frontline health workers as knowledge creators, not just knowledge recipients.
    • Valuing experiential learning alongside formal evidence.

    2. Rethinking technical assistance

    • Shifting from knowledge transfer to knowledge co-creation.
    • Building platforms for peer learning and exchange.
    • Supporting local problem-solving capabilities.

    3. Restructuring power relations

    • Creating mechanisms for local knowledge to inform global guidance.
    • Developing new metrics that value local innovation.
    • Investing in local knowledge documentation and sharing.

    Practical implications

    This new synthesis has important practical implications for how we approach health system strengthening:

    Investment priorities

    • Funding mechanisms need to support local knowledge creation and sharing
    • Technical assistance should focus on building local problem-solving capabilities
    • Technology investments should enable peer learning and knowledge exchange

    Capacity building

    Knowledge management (KM)

    New paths forward

    Moving beyond the false dichotomy between global and local knowledge opens new possibilities for strengthening health systems. By recognizing and valuing both forms of knowledge, we can create more effective, resilient, and equitable health systems.

    The challenges facing health systems are too complex for any single source of knowledge to address alone. Only by bringing together global expertise and local knowledge can we develop the solutions needed to improve health outcomes for all.

    References

    Braithwaite, J., Churruca, K., Long, J.C., Ellis, L.A., Herkes, J., 2018. When complexity science meets implementation science: a theoretical and empirical analysis of systems change. BMC Med 16, 63. https://doi.org/10.1186/s12916-018-1057-z

    Farsalinos, K., Poulas, K., Kouretas, D., Vantarakis, A., Leotsinidis, M., Kouvelas, D., Docea, A.O., Kostoff, R., Gerotziafas, G.T., Antoniou, M.N., Polosa, R., Barbouni, A., Yiakoumaki, V., Giannouchos, T.V., Bagos, P.G., Lazopoulos, G., Izotov, B.N., Tutelyan, V.A., Aschner, M., Hartung, T., Wallace, H.M., Carvalho, F., Domingo, J.L., Tsatsakis, A., 2021. Improved strategies to counter the COVID-19 pandemic: Lockdowns vs. primary and community healthcare. Toxicology Reports 8, 1–9. https://doi.org/10.1016/j.toxrep.2020.12.001

    Jerneck, A., Olsson, L., 2011. Breaking out of sustainability impasses: How to apply frame analysis, reframing and transition theory to global health challenges. Environmental Innovation and Societal Transitions 1, 255–271. https://doi.org/10.1016/j.eist.2011.10.005

    Salve, S., Raven, J., Das, P., Srinivasan, S., Khaled, A., Hayee, M., Olisenekwu, G., Gooding, K., 2023. Community health workers and Covid-19: Cross-country evidence on their roles, experiences, challenges and adaptive strategies. PLOS Glob Public Health 3, e0001447. https://doi.org/10.1371/journal.pgph.0001447

    Yamey, G., 2012. What are the barriers to scaling up health interventions in low and middle income countries? A qualitative study of academic leaders in implementation science. Global Health 8, 11. https://doi.org/10.1186/1744-8603-8-11

    Ahead of Teach to Reach 11, health leaders from 45 countries share malaria solutions in REACH network session

    Ahead of Teach to Reach 11, health leaders from 45 countries share malaria experiences in REACH network session

    Global health

    Nearly 300 malaria prevention health leaders from 45 countries met virtually on November 20, 2024, in parallel English and French sessions of REACH. This new initiative connects organizational leaders tackling malaria prevention and control – and other pressing health challenges – across borders. REACH emerged from Teach to Reach, a peer learning platform with over 23,000 health professionals registered for its eleventh edition on 5-6 December 2024.

    The sessions connected community-based health workers with health leaders from districts to national planners from across Africa, Asia, and South America, bringing together government health staff, civil society organizations, teaching hospitals, and international agencies, in a promising cross-section of local-to-global health expertise.

    Global partnership empowers malaria prevention health leaders

    The sessions featured RBM Partnership to End Malaria as Teach to Reach’s newest global partner, ahead of a special event on malaria planned for December 10. Read about the RBM-TGLF Partnership…

    Request your invitation for the special event on malaria: https://www.learning.foundation/malaria

    “To end malaria, we must empower the people closest to the problem – health workers in affected communities,” said Antonio Pizzuto, Partnership Manager at RBM. “[Teach to Reach] allows us to listen to and learn from those on the frontlines of malaria control, ensuring their voices drive our global strategies.”

    Watch the REACH session focused on health leaders sharing experience to end malaria

    Voir la version française de cet événement

    Community health leaders report prevention challenges

    Health leaders described persistent challenges in malaria prevention, particularly around mosquito net usage.

    “For the mosquito nets, majority of them, mostly those who don’t come to hospital regularly, use it to do their fish ponds. Some use it to do their vegetables,” reported Ajai Patience, who works with WHO in Nigeria. Her team countered this through targeted education: “At antenatal level, we try to make them understand the importance of not having malaria in pregnancy. By the time we give them this health talk, they now calm down to use their mosquito nets. We visit them in the communities to see what they are doing.”

    In Burkina Faso, where pregnancy care is free, similar challenges persist. “Unfortunately, some don’t use their insecticide-treated nets or take their medication during pregnancy,” said Sophie Ramde, Head of Reproductive Health Services. “This remains a challenge in our region, especially with heavy rainfall.”

    What do health leaders do when there are malaria medicine or supply shortages?

    Leaders shared various approaches to medicine and supply shortages.

    “If we don’t have medicines, we request to borrow from other international NGOs,” explained Geoffray Kakesi, Chief of Mission for ALIMA in Mali.

    In DRC, Dr. Mathieu Kalemayi organized a “watch party” for this REACH session, joining with a group of 11 CSO leaders. He explained how the Ministry of Health in his district works together with CSOs on mosquito net distribution: “These organizations play a major role in community sensitization… We’ve taken the initiative to meet each time there’s a session.”

    What are barriers to access?

    Distance to treatment emerged as a critical challenge. Professor Beckie Tagbo from Nigeria’s University Teaching Hospital shared this example, shared by a colleague during the REACH networking session : “He works in a primary health care center unable to treat severe malaria. Patients must travel 60-70 kilometers to higher centers for treatment, and some lack the funds.”

    In Chad, one organization adapted by embedding healthcare workers in communities. “We live with these volunteer nurses in the villages to provide care, with community relays distributing medicines to anyone showing signs of simple malaria,” explained Moguena Koldimadji, Coordinator of the Collective of United Health and Social Workers for Care Improvement and Enhancement.

    How is climate change affecting malaria patterns?

    Participants noted shifting disease patterns due to climate change. “Unlike previous years, malaria now occurs in high altitude areas and in patients who have no travel history,” reported Mersha Gorfu, who works for WHO in Ethiopia.

    What is the value of community engagement?

    Some organizations reported success through structured outreach programs. In Kenya, Taphurother Mutange, a Community Health Worker with Kenya’s Ministry of Health, described their approach: “We have been subdivided into units as health workers. I’ve been given 100 households I visit every week. When they have problems or are sick, I refer them. When there were floods, we were given tablets to give community members to treat water.”

    How do health workers cope personally with malaria?

    Arthur Fidelis Metsampito Bamlatol, Coordinator of AAPSEB (Association for Support to Health, Environment and Good Governance Promotion) in Cameroon’s East Region, shared how personal experience shaped his work: “I had a severe malaria episode. I was shivering, trembling. It hit me hard with waves of heat washing over me… I had to take six doses of IV treatment. Since then, I’ve been advised to sleep under mosquito nets every night, along with my family members. In our association, this is one of the key messages we bring to communities.”

    What is the value of learning across geographic borders?

    Malaria prevention health leaders identified similar challenges across countries. “The challenges in DRC can be the same as in Ivory Coast and what is done in Ivory Coast can also help address challenges in DRC,” noted Patrice Kazadi, Project Director at Save the Children International DRC.

    What’s next for health leaders?

    Health leadership is more needed than ever to drive innovation and collaboration to tackle this global challenge.

    The next REACH session, scheduled for November 27, will focus on climate and health risks and barriers, in partnership with Grand Challenges Canada (GCC). Learn more about the partnership with GCC…

    This is all building up to Teach to Reach’s 11th edition on December 5-6 and the special malaria event on December 10.

    Health professionals can request invitations at www.learning.foundation/teachtoreach

    Learn more about the Teach to Reach Special Event for Malaria: https://www.learning.foundation/malaria

    Teach to Reach Health workers are sharing how they protected their communities when extreme weather hit

    You are not alone: Health workers are sharing how they protected their communities when extreme weather hit

    Global health

    Today, The Geneva Learning Foundation launched a new set of “Teach to Reach Questions” focused on how health workers protect community health during extreme weather events. This initiative comes at a crucial time, as world leaders at COP29 discuss climate change’s mounting impacts on health.

    As climate change intensifies extreme weather events worldwide, health workers are often the first to respond when disasters strike their communities. Their experiences – whether facing floods, droughts, heatwaves, or storms – contain vital lessons that could help others prepare for and respond to similar challenges.

    Read the eyewitness report: From community to planet: Health professionals on the frontlines of climate change, Online. The Geneva Learning Foundation. https://doi.org/10.5281/zenodo.10204660

    Why ask health workers about floods, droughts, and heatwaves?

    “Traditional surveys often ask for general information or statistics,” explains Charlotte Mbuh of The Geneva Learning Foundation. “Teach to Reach Questions are different. We ask health workers to share specific moments – a time when they had to act quickly during a flood, or how they kept services running during a drought. These stories of extreme weather events reveal not just what happened, but how people actually solved problems on the ground.”

    The questions cover six key scenarios:

    1. Disease outbreaks during floods
    2. Health impacts of drought
    3. Care delivery during heatwaves
    4. Mental health support before, during, and after
    5. Maintaining healthcare access
    6. Quick action and local solutions to protect health

    Each scenario includes detailed prompts that help health workers recall and share the specifics of their experience: What exactly did they do? Who helped? What obstacles did they face? How did they know their actions made a difference?

    Strengthening local action: From individual experience to collective learning to protect community health

    What makes Teach to Reach Questions unique is not just how they are asked, but what happens next. Every experience of an extreme weather event shared becomes part of a larger learning process that benefits the entire community.

    “We don’t just collect these experiences – we give them back,” says Reda Sadki, President of The Geneva Learning Foundation. “Whether someone shares their own story or not, they gain access to the complete collection of experiences of extreme weather events. This creates a virtuous cycle of peer learning, where solutions discovered in one community can help another on the other side of the world.”

    The process unfolds in four phases:

    1. Experience Collection: Health workers share their stories through structured questions ahead of the live Teach to Reach event
    2. Live Event: During the Teach to Reach live event, Contributors who shared their experience are invited to do so in plenary sessions. Everyone can listen in – and join one-to-one networking sessions to learn from the experiences of colleagues from all over the world.
    3. Analysis and Synthesis: After the live event, the Foundation’s Insights team works with the Teach to Reach community to identify patterns, innovations, and key lessons
    4. Knowledge Sharing: Insights are returned to the community through comprehensive collections of experiences, thematic insights reports, and Insights Live sessions

    Building momentum for Teach to Reach 11

    These questions are part of the lead-up to Teach to Reach 11, scheduled for December 5-6, 2024. The experiences shared will inform discussions among the 23,000+ registered participants from over 70 countries.

    “But the learning starts now,” emphasizes Mbuh. “Health workers who request their invitation today can immediately begin sharing and learning from peers. The earlier they join, the more they can benefit from this collective knowledge exchange.”

    Why protecting community health against extreme weather events matters

    As extreme weather events become more frequent and severe, the expertise of health workers who have already faced these challenges becomes increasingly valuable.

    “These aren’t just stories – they’re a vital source of knowledge for protecting community health in a changing climate,” says Sadki. “By sharing them widely, we help ensure that health workers everywhere are better prepared when extreme weather strikes their communities.”

    Health professionals interested in participating can request their invitation.

    Listen to the Teach to Reach podcast:

    Is your organisation interested in learning from health workers? Learn more about becoming a Teach to Reach partner.

    Image: The Geneva Learning Foundation Collection © 2024

    Why answer Teach to Reach Questions-small

    Why answer Teach to Reach Questions?

    Global health

    Have you ever wished you could talk to another health worker who has faced the same challenges as you? Someone who found a way to keep helping people, even when things seemed impossible? That’s exactly the kind of active learning that Teach to Reach Questions make possible. They make peer learning easy for everyone who works for health.

    What are Teach to Reach Questions?

    Once you join Teach to Reach (what is it?), you’ll receive questions about real-world challenges that matter to health professionals.

    How does it work?

    1. You choose what to share: Answer only questions where you have actual experience. No need to respond to everything – focus on what matters to you.
    2. Share specific moments: Instead of general information, we ask about real situations you’ve faced. What exactly happened? What did you do? How did you know it worked?
    3. Learn from others: Within weeks, you’ll receive a collection of experiences shared by health workers from over 70 countries. See how others solved problems similar to yours.

    What’s different about these questions?

    Unlike typical surveys that just collect data, Teach to Reach Questions are active learning that:

    • Focus on your real-world experience.
    • Help you reflect on what worked (and what didn’t).
    • Connect you to solutions from other health workers.
    • Give back everything shared to help everyone learn.

    See what we give back to the community. Get the English-language collection of Experiences shared from Teach to Reach 10. The new compendium includes over 600 health worker experiences about immunisation, climate change, malaria, NTDs, and digital health. A second collection of more than 600 experiences shared by French-speaking participants is also available.

    What’s in it for you?

    Peer learning happens when we learn from each other. Your answers can help others – and their answers can help you.

    1. Get recognized: You’ll be honored as a Teach to Reach Contributor and receive certification.
    2. Learn practical solutions: See how other health workers tackle challenges like yours.
    3. Make connections: At Teach to Reach, you’ll meet others who have been sharing and learning about the same issues.
    4. Access support: Global partners will share how they can support solutions you and other health workers develop.

    A health worker’s experience

    Here is what on community health worker from Kenya said:

    “When flooding hit our area, I felt so alone trying to figure out how to keep helping people. Through Teach to Reach, I learned that a colleague in another country had faced the same problem. Their solution helped me prepare better for the next flood. Now I’m sharing my experience to help others.”

    Think about how peer learning could help you when more than 23,000 health professionals are asked to share their experience on a challenge that matters to you.

    Ready to start?

    1. Request your invitation to Teach to Reach now.
    2. Look for questions in your inbox.
    3. Share your experience on topics you know about.
    4. Receive the complete collection of shared experiences.
    5. Join us in December to meet others face-to-face.

    Remember: Your experience, no matter how small it might seem to you, could be exactly what another health worker needs to hear.

    The sooner you join, the more you’ll learn from colleagues worldwide.

    Together, we can turn what each of us knows into knowledge that helps everyone.

    Listen to the Teach to Reach podcast:

    Is your organisation interested in learning from health workers? Learn more about becoming a Teach to Reach partner.

    Image: The Geneva Learning Foundation Collection © 2024

    Health at COP29

    Health at COP29: Workforce crisis meets climate crisis

    Global health

    Health workers are already being transformed by climate change. COP29 stakeholders can either support this transformation to strengthen health systems, or risk watching the health workforce collapse under mounting pressures.

    The World Health Organization’s “COP29 Special Report on Climate Change and Health: Health is the Argument for Climate Action“ highlights the health sector’s role in climate action.

    Health professionals are eyewitnesses and first responders to climate impacts on people and communities firsthand – from escalating respiratory diseases to spreading infections and increasing humanitarian disasters.

    The report positions health workers as “trusted members of society” who are “uniquely positioned” to champion climate action.

    The context is stark: WHO projects a global shortage of 10 million health workers by 2030, with six million in climate-vulnerable sub-Saharan Africa. Meanwhile, our communities and healthcare systems already bear the costs of climate change through increasing disease burdens and system strain.

    Health workers are responding, because they have to. Their daily engagement with climate-affected communities offers insights that can strengthen both health systems and climate response – if we learn to listen.

    A “fit-for-purpose” workforce requires rethinking learning and leadership

    WHO’s report acknowledges that “scale-up and increased investments are necessary to build a well-distributed, fit-for-purpose workforce that can meet accelerating needs, especially in already vulnerable settings.” The report emphasizes that “governments and partners must prioritize access to decent jobs, resources, and support to deliver high-quality, climate-resilient health services.” This includes ensuring “essential protective equipment, supplies, fair compensation, and safe working conditions such as adequate personnel numbers, skills mix, and supervisory capacity.”

    Resources, skills, and supervision are building blocks of every health system.

    They are necessary but likely to be insufficient.

    Such investments could be maximized through cost-effective, scalable peer learning networks that enable rapid knowledge sharing and solution development – as well as their locally-led implementation.

    The WHO report calls for “community-led initiatives that harness local knowledge and practices.”

    Our analyses – formed by listening to and learning from thousands of health professionals participating in the Teach to Reach peer learning platform – suggest that the expertise developed by health professionals through daily engagement with communities facing climate impacts is key to problem-solving, to implementing local solutions, and to ensure that communities are part and parcel of such solutions.

    Why move beyond seeing health workers as implementers of policies or recipients of training?

    We stand to gain much more if their leadership is recognized, nurtured, and supported.

    This is a notion of leadership that diverges from convention: if health workers have leadership potential, it is because they are uniquely positioned to turn what they know – because they are there every day – into action.

    Peer learning has the potential to significantly accelerate progress toward country and global goals for climate change and health.

    By making connections, a health professional expands the horizon of what they are able to know.

    At the Geneva Learning Foundation, we have seen that such leadership emerges when health workers are empowered to:

    • share and validate their experiential knowledge;
    • develop, test, and implement solutions with the communities they serve, using local resources;
    • connect with peers facing similar challenges; and
    • inform policy based on ground-level realities.

    Working with a global community of community-based health workers, we co-developed the Teach to Reach platform, community, and network to listen and learn at scale. Unlike traditional training programs, Teach to Reach creates a peer learning ecosystem where:

    • Health workers from over 70 countries connect directly to share experiences.
    • Solutions are crowdsourced from those closest to the challenges.
    • Knowledge flows horizontally rather than just vertically.
    • Local innovations are rapidly shared and adapted across contexts.

    For example, in June 2024, over 21,000 health professionals participated in Teach to Reach 10, generating hundreds of real-world stories and insights about climate change impacts on health.

    The platform has proven particularly valuable in fragile contexts and resource-limited settings, where traditional capacity building approaches often struggle to reach or engage health workers effectively.

    This approach does not replace formal institutions or traditional scientific methods – instead, it creates new pathways for knowledge to flow rapidly between communities, while building the collective capacity needed to respond to accelerating climate impacts on health.

    Already, this demonstrates the untapped potential for health workers to contribute to our collective understanding and response.

    But we do not stop there.

    As we count down to Teach to Reach 11, participants are now sharing how they have actually used and applied this peer knowledge to make progress against their local challenges.

    They cannot do it alone.

    This is why we ask global partners to join and contribute to this emergent, locally-led leadership for change.

    How different is this ‘ask’ from that of global partners asking health workers to contribute to the climate change and health agenda?

    WHO’s COP29 report makes a powerful case that “community-led initiatives that harness local knowledge and practices in both climate action and health strategies are fundamental for creating interventions that are both culturally appropriate and effective.”

    Furthermore, it recognizes that “these initiatives ensure that climate and health solutions are tailored to the specific needs and realities of those most impacted by climate change but also grounded in their lived realities.”

    What framework for collaboration?

    The path forward requires what the report describes as “cooperation across sectors, stakeholders and rights-holders – governmental institutions, local authorities, local leaders including religious authorities and traditional medicine practitioners, NGOs, businesses, the health community, Indigenous Peoples as well as local communities.”

    Our experience with Teach to Reach demonstrates how such cooperation can be facilitated at scale through digital platforms that enable peer learning and knowledge sharing. Key elements include:

    • a structured yet flexible framework for sharing experiences and insights;
    • direct connections between health workers at all levels of the system;
    • rapid feedback loops between local implementation and broader learning;
    • support for health workers to document and share their innovations; and
    • mechanisms to validate and spread effective local solutions.

    WHO’s recognition that health workers have “a moral, professional and public responsibility to protect and promote health, which includes advocating for climate action, leveraging prevention for climate mitigation and cost savings, and safeguarding healthy environments” sets a clear mandate.

    This WHO report highlights the need for new ways of supporting community-led learning and action to:

    1. support the rapid sharing of local solutions;
    2. build health worker capacity through peer learning;
    3. connect communities facing similar challenges; and
    4. enable health workers to lead change in their communities

    Reference

    Neira, M. et al. (2024) COP 29 Special Report on Climate Change and Health: Health is the Argument for Climate Action. Geneva, Switzerland: World Health Organization.

    Image: The Geneva Learning Foundation Collection © 2024

    ASTMH 2024 How can we reliably spread evidence-based practices at the speed and scale modern health challenges demand

    How can we reliably spread evidence-based practices at the speed and scale modern health challenges demand?

    Global health

    At a symposium of the American Society for Tropical Medicine and Hygiene (ASTMH) Annual Meeting, I explored how peer learning could help us tackle five critical challenges that limit effectiveness in global health.

    1. Performance: How do we move beyond knowledge gains to measurable improvements in health outcomes?
    2. Scale and access: How do we reach and include tens of thousands of health workers, not just dozens?
    3. Applicability: How do we ensure learning translates into changed practice?
    4. Diversity: How do we leverage different perspectives and contexts rather than enforce standardization?
    5. Complexity: How do we support locally-led leadership for change to tackle complex challenges that have no standard solutions?

    For epidemiologists working on implementation science, peer learning provides a new path for solving one of global health’s most persistent challenges: how to reliably spread evidence-based practices at the speed and scale modern health challenges demand.

    The evidence suggests we should view peer learning not just as a training approach, but as a mechanism for viral spread of effective practices through health systems.

    How do we get to attribution?

    Of course, an epidemiologist will want to know if and how improved health outcomes can be attributed to peer learning interventions.

    The Geneva Learning Foundation (TGLF) addresses this fundamental challenge in implementation science – proving attribution – through a three-stage process that combines quantitative indicators with qualitative validation.

    The process begins with baseline health indicators relevant to each context (such as vaccination coverage rates, if it is immunization), which are then tracked through regular “acceleration reports” that capture both metrics and implementation progress.

    Rather than assuming causation from correlation, participants must explicitly rate the extent to which they attribute observed improvements to their intervention.

    The critical innovation comes in the third stage: those claiming attribution must “prove it” to the community of peers, by providing specific evidence of how their actions led to the observed changes – a requirement that both controls for self-reporting limitations and generates rich qualitative data about implementation mechanisms.

    This methodology has proven particularly valuable in complex interventions where randomized controlled trials may be impractical or insufficient.

    What are examples of peer learning in action?

    Here are three examples from The Geneva Learning Foundation’s work that demonstrate scale, reach, and sustainability.

    Within four weeks, a single Teach to Reach cohort of 17,662 health workers across over 80 countries generated 1,800 context-specific experiences describing the “how” of implementation, especially at the district and community levels.

    In Côte d’Ivoire, working with Gavi and The Geneva Learning Foundation, the national immunization team used TGLF’s model to support community engagement. Within two weeks, over 500 health workers representing 85% of the country’s districts had begun implementing locally-led innovations. 82% of participants said they would use TGLF’s model for their own needs, without requiring any further assistance or support.

    In TGLF’s COVID-19 Peer Hub, 30% of participants successfully implemented recovery plans within three months – a rate seven times higher than a control group that did not use TGLF’s model.

    Participants who actively engaged with peers were not only more likely to report successful implementation, but could demonstrate concrete evidence of how peer interactions contributed to their success, creating a robust framework for understanding not just whether interventions work, but how and why they succeed or fail across different contexts.

    Quantifying learning

    Using a simple methodology that measures learning efficacy across five key variables – scalability, information fidelity, cost effectiveness, feedback quality, and uniformity – we calculated that properly structured peer learning networks achieve an efficacy score of 3.2 out of 4, significantly outperforming both traditional cascade training (1.4) and expert coaching (2.2).

    But the real breakthrough came when considering scale. When calculating the Efficacy-Scale Score (ESS) – which multiplies learning efficacy by the number of learners reached – the differences became stark:

    • Peer Learning: 3,200 (reaching 1,000 learners)
    • Cascade Training: 700 (reaching 500 learners)
    • Expert Coaching: 132 (reaching 60 learners)

    Learn more: Calculating the relative effectiveness of expert coaching, peer learning, and cascade training

    The mathematics of scale

    For epidemiologists, the mechanics of this scaling effect may feel familiar.

    In traditional expert-led training, if N is the total number of learners and M is the number of available experts who can each effectively coach K learners, we quickly hit a ceiling where N far exceeds M×K.

    TGLF’s model transforms this equation by structuring interactions so each learner gives and receives feedback from exactly three peers, guided by expert-designed rubrics.

    This creates a linear scaling pattern where total learning interactions = 3N, allowing for theoretically unlimited scale while maintaining quality through structured feedback loops.

    Information loss and network resilience

    One of the most interesting findings concerns information fidelity. In cascade training, knowledge degradation follows a predictable pattern:

    K_n = K \cdot \alpha^n

    where Kn is the knowledge at the nth level of the cascade and α is the loss rate at each step. This explains why cascade training, despite its theoretical appeal, consistently underperforms.

    In contrast, TGLF’s peer learning-to-action networks showed remarkable resilience. By creating multiple pathways for knowledge transmission and building in structured feedback loops, the system maintains high information fidelity even at scale.

    Learn more: Why does cascade training fail?

    References

    Arling, P.A., Doebbeling, B.N., Fox, R.L., 2011. Improving the Implementation of Evidence-Based Practice and Information Systems in Healthcare: A Social Network Approach. International Journal of Healthcare Information Systems and Informatics 6, 37–59. https://doi.org/10.4018/jhisi.2011040104

    Hogan, M.J., Barton, A., Twiner, A., James, C., Ahmed, F., Casebourne, I., Steed, I., Hamilton, P., Shi, S., Zhao, Y., Harney, O.M., Wegerif, R., 2023. Education for collective intelligence. Irish Educational Studies 1–30. https://doi.org/10.1080/03323315.2023.2250309

    Watkins, K.E., Sandmann, L.R., Dailey, C.A., Li, B., Yang, S.-E., Galen, R.S., Sadki, R., 2022. Accelerating problem-solving capacities of sub-national public health professionals: an evaluation of a digital immunization training intervention. BMC Health Serv Res 22, 736. https://doi.org/10.1186/s12913-022-08138-4