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Tag: peer learning

  • Nigeria Immunization Agenda 2030 Collaborative: Piloting a national peer learning programme

    Nigeria Immunization Agenda 2030 Collaborative: Piloting a national peer learning programme

    Insights report about Nigeria’s Immunization Agenda 2030 Collaborative surfaces surprising solutions for both demand- and supply-side immunization challenges

    When 4,434 practitioners from all 36 states asked why children in their communities remained unvaccinated, the problems they thought they understood often had entirely different root causes.

    “I ended up being surprised at the answer I got,” said one health worker.

    Half of the health workers who participated in Nigeria’s largest-ever peer learning exercise in July 2024 discovered that their initial assumptions about local immunization challenges were wrong. The six-week programme generated 409 detailed analyses of local immunization challenges, with each reviewed by peers across the country.

    One year after The Geneva Learning Foundation launched the first Immunization Agenda 2030 Collaborative, in partnership with UNICEF and Gavi, under the auspices of the Nigeria Primary Health Care Development Agency (NPHCDA), a comprehensive insights report documents findings that illuminate persistent gaps between health system planning and community realities.

    How to access the Nigeria Immunization Collaborative’s first insights report:

    Chat with the report

    Health workers report being asked for insights for first time

    A recurring theme emerged from participant feedback that surprised programme organizers. “Many said no one has ever asked us what we think should happen or why do you think that is,” said TGLF’s Charlotte Mbuh, during the February 2025 presentation of the findings to NPHCDA and the country’s immunization partners.

    This potential for linking community experience with formal planning processes became evident when systematic analysis revealed that participants consistently identified practical solutions—many of which they could implement with existing resources.

    “Through my participation in the immunization Collaborative, I learned the critical value of root cause analysis,” reported one participant from Apo Resettlement Primary Health Centre in Abuja. “I applied this approach to uncover that insufficient manpower was the primary issue limiting vaccine coverage”—not the community resistance initially assumed.

    Dr. Akinpelu Adetola, a government public health specialist in Lagos State, exemplified this pattern. Her investigation of declining vaccination rates revealed poor scheduling that created both overcrowded and quiet clinic days. “A register and scheduling system were introduced to address this issue,” she shared with colleagues from across the country.

    Implementation gaps – not knowledge gaps – in the Nigeria Immunization Collaborative

    The Collaborative’s most significant finding challenges a common assumption in global health programming. Participants consistently proposed solutions that were “already well-known, suggesting that progress is limited by implementation issues rather than a lack of solutions,” according to the evaluation report.

    This pattern appeared across diverse contexts and challenge types. When health workers applied root cause analysis to local problems, they frequently identified straightforward interventions that had been overlooked by previous efforts focused on changing community attitudes or providing additional training.

    The evaluation found that 42% of participating health workers identified zero-dose challenges as their top local priority—aligning with national strategy priorities while providing granular intelligence about how these challenges manifest in specific communities.

    Nigeria Immunization Agenda 2030 Collaborative: Reconnecting data collection with local problem-solving

    A striking finding illuminated a fundamental disconnect in Nigeria’s health information systems: only 25% of participants knew their local coverage rates for key vaccines, despite many being responsible for collecting and reporting these figures at the local levels.

    “Many said, well, I collect these numbers, pass them on, but I didn’t know I could actually use them. They could actually help me in my work,” Mbuh explained, describing how participants began analyzing data they were already gathering within the first four weeks of the programme.

    While participants initially focused on demand-side issues—why communities do not seek vaccination services—systematic investigation often revealed supply-side problems underlying apparent “hesitancy.”

    Six primary supply-side challenges consistently undermine immunization delivery: poor data quality hampering service planning; vaccine stockouts due to inadequate inventory management; non-functional cold chain equipment; missed opportunities for catch-up vaccination; service quality issues that deter families; and systematic exclusion of hard-to-reach populations.

    Scale, speed, and sustainability across a complex federal system

    Launched by The Geneva Learning Foundation on 22 July 2024 in partnership with NPHCDA with support from UNICEF and Gavi, the Nigeria Immunization Agenda 2030 Collaborative connected health workers and other immunization stakeholders from more than 300 local government areas – with most based in northern States – within two weeks. Over 600 government facilities, private sector providers, and civil society organizations then signed on as organizational partners. Participants included 65% from local government and facility levels—both the community health workers who directly deliver immunization services and the LGA managers who support them.

    The initiative achieved this scale while operating at faster speed and significantly lower cost than conventional technical assistance and capacity-building approaches.

    The programme supported participants in using a simple, practical “five-whys” root cause analysis methodology, with each analysis reviewed by three peers across Nigeria’s diverse contexts. This peer review process provided depth to complement scale: it improved analytical quality regardless of participants’ initial skill levels.

    “The peer review was another mind-blowing innovation where intellect from other parts of Nigeria viewed your work and made constructive input,” noted one reviewer. “It made me realize I can be a team player.”

    Rapid implementation documented within weeks

    Within six weeks, health workers began reporting connections between new activities based on their root cause analyses and improved health outcomes.

    “During the Collaborative, we discussed successful case studies from other regions. Inspired by these stories, I have strengthened partnerships with local health authorities and other stakeholders to deepen immunization coverage, especially among under-fives. This collaboration has resulted in a significant increase in childhood vaccination rates in my community,” reported one participant from Ebonyi State.

    Unlike conventional training programs that end with certificates, evidence emerged that participants were applying insights within their ongoing work responsibilities and sustaining collaboration independently.

    Evidence of sustained networks and application one year later

    In fact, evidence one year on points to surprising sustainability, as the network continues to function without any external support.

    Four months after the programme concluded, TGLF organized a Teach to Reach session with 24,610 health workers participating, featuring Collaborative participants sharing early outcomes from the Nigeria initiative. This session revealed participants maintaining connections and applying methodologies in new contexts.

    “When we applied the root cause analysis, the five ‘whys’, this opened our eyes to see that it was not all about community members alone,” reported Uyebi Enosandra, a disability specialist working in Delta State. “We have challenges with the primary health workers, not knowing how to incorporate children with disability in the immunization programme.”

    Her account exemplified the pattern documented across participant testimonials: systematic analysis revealed different root causes than initially assumed, leading to more targeted solutions.

    Gregory, a retired professional who participated in outbreak response work in Borno State, described encountering Collaborative participants in the field: “I was pleased to hear that they participated in the Collaborative. And whatever step I wanted to take, they were almost ahead of me to say, sir, we have learned this and we are going to apply it.”

    “In my everyday activities at work I use this ‘5 whys’ to get to the root cause of any complaint and in my own little space make an impact on the patient,” one participant reported in follow-up feedback.

    The methodology’s application extended beyond immunization contexts. Participants reported using the analytical framework for disability inclusion, malaria programming, and broader health system challenges, suggesting the transferable value of structured problem-solving approaches.

    The December 2024 Teach to Reach session revealed ongoing demand for the methodology. Despite significant connectivity challenges affecting West Africa during the session, participants expressed eagerness to share the approach with colleagues. “Presently I’m even encouraging my colleagues to join,” one participant noted. “They’ve been asking me, how do I join, when will this come and all that.”

    The most significant sustainability indicator, according to Mbuh, appeared in widespread participant feedback: “I did not realize how much I could do with what we already have.” This response gained particular relevance as Nigeria and other countries navigate current funding constraints affecting global health programming.

    Potential to strengthen existing systems

    For NPHCDA and international partners, the Collaborative provided intelligence typically unavailable through conventional assessments. The analysis of root cause analyses offers detailed insights into how challenges manifest across Nigeria’s diverse geographic and cultural contexts.

    The approach demonstrated potential to complement existing training, supervision, and technical assistance systems by harnessing health workers’ practical experience and problem-solving capacity. The model addresses real-world challenges participants can immediately influence while building professional networks alongside technical competencies.

    “This pilot programme has demonstrated demand for peer learning, and the feasibility of running a national peer learning programme that brings together the strengths of a national immunization programme, a global partner and an educational organization,” the evaluation concludes.

    For Nigeria’s work toward Zero-Dose Immunization Recovery Plan goals through 2028, the Collaborative provides an innovative approach for translating national strategies into local action while building health worker capacity for continuous adaptation and problem-solving.

    The programme has evolved into what participants describe as a self-sustaining platform that continues operating independent of formal support, suggesting potential for integration with existing health system structures and processes in a true “sector-wide” approach.

    Reference

    Jones, I., Sadki, R., Sequeira, J., & Mbuh, C. (2025). Nigeria Immunization Agenda 2030 Collaborative: Piloting a national peer learning programme (1.0). The Geneva Learning Foundation (TGLF). https://doi.org/10.5281/zenodo.14167168

    Image: Cover the report “Nigeria Immunization Agenda 2030 Collaborative: Piloting a national peer learning programme”.

  • What is The Geneva Learning Foundation’s Impact Accelerator?

    What is The Geneva Learning Foundation’s Impact Accelerator?

    Imagine a social worker in Ukraine supporting children affected by the humanitarian crisis. Thousands of kilometers away, a radiation specialist in Japan is trying to find effective ways to communicate with local communities. In Nigeria, a health worker is tackling how to increase immunization coverage in their remote village. These professionals face very different challenges in very different places. Yet when they joined their first “Impact Accelerator”, something remarkable happened. They all found a way forward. They all made real progress. They all discovered they are not alone.

    The Impact Accelerator is a simple, practical method developed by The Geneva Learning Foundation that helps professionals turn intent into action, results, and outcomes. It has worked equally well in every country where it has been tried. It has helped people – whatever their knowledge domain or context – strengthen action and accelerate progress to improve health outcomes. Each time, in each place, whatever the challenge, it has produced the same powerful results.

    The social worker joins other professionals facing similar challenges. The radiation specialist connects with safety experts dealing with comparable concerns. The health worker collaborates with others working to improve immunization. Each group shares a common purpose.

    What makes the Impact Accelerator different?

    Most training programs teach you something and then send you away. You return to your workplace full of ideas but face the same obstacles. You have new knowledge but struggle to apply it. (Some people call this “knowledge transfer” but it is not only about knowledge. Others call this the “applicability problem”.) You feel alone with your challenges.

    The Impact Accelerator works differently. It stays with you as you implement change. It connects you with others facing similar challenges. It helps you take small, concrete steps each week toward your bigger goal.

    Each Impact Accelerator brings together professionals working on the same type of challenge. Social workers who support children join with others who do the same – but the group may also include teachers and psychologists they do not usually work with. Safety specialists connect with safety specialists, but also people in other job roles. It is their shared purpose that makes this diversity productive:  every discussion, every shared experience, every piece of advice directly applies to their work.

    Think of it like learning to ride a bicycle. Traditional training is like someone explaining how bicycles work. The Impact Accelerator is like having someone run alongside you, keeping you steady as you pedal, cheering when you succeed, and helping you get back on when you fall. Everyone learns to ride, together. And everyone is going somewhere.

    How does the Impact Accelerator work?

    The Impact Accelerator follows a simple weekly rhythm that fits into daily work. It is learning-based work and work-based learning.

    Monday: Set your goal

    Every Monday, you decide on one specific action you will complete by Friday. Not a vague hope or a grand plan. One concrete thing you can actually do.

    For example:

    • “I will create a safe space activity for five children showing signs of trauma.”
    • “I will develop a visual guide for the new radiation monitoring procedures.”
    • “I will meet with three community leaders to discuss vaccine concerns.”

    You share this goal with others in the Accelerator. This creates accountability. You know that on Friday, your peers will ask how it turned out.

    Wednesday: Check in with peers

    Midweek, you connect with others in your group who face the same type of challenges. You share what is working, what is difficult, and what you are learning.

    This is where magic happens. Someone else tried something that failed. Now you know to try differently. Another person found a creative solution. Now you can adapt it for your situation. You realize you are part of something bigger than yourself.

    Friday: Report and reflect

    On Friday, you report on your progress. Did you achieve your goal? What happened when you tried? What did you learn?

    This is not about judging success or failure. Sometimes the most valuable learning comes from things that did not work as expected. The important thing is that you took action, you reflected on what happened, and you are ready to try again next week.

    Monday again: Build on what you learned

    The next Monday, you set a new goal. But now you are not starting from zero. You have the experience from last week. You have ideas from your peers. You have momentum.

    Week by week, action by action, you make progress toward your larger goal.

    The power of structured support in the Impact Accelerator

    The Impact Accelerator provides several types of support to help you succeed.

    Peer learning networks

    You join a community of professionals who understand your challenges because they face similar ones. 

    Each Impact Accelerator brings together people working on the same type of challenge. This shared purpose means that every suggestion, every idea, every lesson learned is likely to be relevant to your work. The learning comes not from distant experts but from people doing the same work you do. Their solutions are practical and tested in real conditions like yours.

    Guided structure

    While you choose your own goals and actions, the Accelerator provides a framework that keeps you moving forward. The weekly rhythm creates momentum. The reporting requirements ensure reflection. The peer connections prevent isolation.

    This structure is like the banks of a river. The water (your energy and creativity) flows freely, but the banks keep it moving in a productive direction.

    Expert guidance when needed

    Sometimes you need specific technical input or help with a particular challenge. The Accelerator provides “guides on the side” – experts who offer targeted support without taking over your process. They help you think through problems and connect you with resources, but you remain in charge of your own change effort.

    What participants achieve

    Across different countries and different challenges, Impact Accelerator participants report similar outcomes.

    Increased confidence

    “Before, I knew what should be done but felt overwhelmed about how to start. Now I take one step at a time and see real progress.” This confidence comes from successfully completing weekly actions and seeing their impact.

    Tangible progress

    Participants do not just learn about change; they create it. A vaccination program reaches new communities. Safety procedures actually get implemented. Children receive support when they need it. The changes may start small, but they are real and they grow.

    Expanded networks

    “I used to feel like I was the only one facing these problems. Now I have colleagues across my country who understand and support me.” These networks last beyond the Accelerator, providing ongoing support and collaboration.

    Enhanced problem-solving

    Through weekly practice and peer exchange, participants develop stronger skills for analyzing challenges and developing solutions. They learn to break big problems into manageable actions and to adapt based on results.

    Resilience in facing obstacles

    Every change effort faces barriers. The Accelerator helps participants expect these obstacles and work through them with peer support rather than giving up when things get difficult.

    How can the same methodology work everywhere?

    The Impact Accelerator has succeeded across vastly different contexts – from supporting children in Ukrainian cities to enhancing radiation safety in Japanese facilities to improving immunization in Nigerian villages. Each Accelerator focuses on one specific challenge area, bringing together professionals who share that common purpose. Why does the same approach work for such different challenges?

    The answer lies in focusing on universal elements of successful change:

    • Breaking big goals into weekly actions;
    • Learning from peers who understand your specific context and challenges;
    • Reflecting on what works and what does not;
    • Building momentum through consistent progress; and
    • Creating accountability through a community united by shared purpose.

    Each group focuses on their specific challenge and context, but the process of creating change remains remarkably similar.

    A typical participant journey in the Impact Accelerator

    Let us follow Yuliia, a social worker in Ukraine helping children affected by the humanitarian crisis.

    Week 1: Getting started

    Yuliia joins the Impact Accelerator after developing her action plan. Her big goal: establish effective psychological support for 50 displaced children in her community center within three months.

    On Monday, she sets her first weekly goal: “During daily activities, I will observe and document how 10 children are affected.”

    By Friday, she has detailed observations. She notices that loud noises sometimes cause reactions in most children, and several withdraw completely during group activities. This gives her concrete starting points.

    Week 2: Building on learning

    Based on her observations, Yuliia sets a new goal: “I will create a quiet corner with calming materials and test it with three children who are withdrawn.”

    During the Wednesday check-in, another social worker shares how she uses art therapy for non-verbal expression with traumatized children. A colleague working in a different city describes success with sensory materials. Yuliia incorporates both ideas into her quiet corner.

    The quiet corner proves successful – two of the three children spend time there and begin to engage with the materials. One child draws for the first time since arriving at the center.

    Week 3: Creative solutions

    Yuliia’s new goal: “I will develop a simple ‘feelings chart’ with visual cues and introduce it during morning circle time.”

    Her peers from Ukraine and all over Europe – all working with children – help refine the idea. A psychologist from another region shares that abstract emotions are hard for traumatized children to identify. She suggests using colors and weather symbols instead of facial expressions. Another colleague recommends making the chart interactive rather than static.

    The feelings chart becomes a breakthrough tool. Children who never spoke about their emotions begin pointing to images. Yuliia’s colleagues can better understand and respond to children’s needs.

    Week 4: Scaling what works

    Energized by success, Yuliia aims higher: “I will train two other staff members to use the quiet corner and feelings chart, and create a simple guide for these tools.”

    By now, Yuliia has concrete evidence that these approaches work. She documents specific examples of children’s progress. Her guide is so practical that the center director wants to share it with other locations.

    The ripple effect

    Yuliia’s tools spread throughout the network of centers supporting displaced children. Through the Accelerator network, colleagues adapt her approaches for different age groups and settings. Soon, hundreds of children across Ukraine benefit from these simple but effective interventions.

    The evidence of impact

    The true test of any approach is whether it creates lasting change. Impact Accelerator participants consistently report:

    • Specific improvements in their work that they can measure and document;
    • Sustained changes that continue after the Accelerator ends;
    • Solutions that others adopt and spread;
    • Professional growth that enhances all their future work; and
    • Networks that provide ongoing support and learning.

    These outcomes appear whether participants work on mental health support in Ukraine, radiation safety in Japan, or immunization in Nigeria. The challenges differ, but the pattern of success remains consistent.

    How we prove the Accelerator makes a difference

    In global health, the biggest challenge is proving that your intervention actually caused the improvements you see. This is called “attribution.” How do we know that better health outcomes happened because of the Impact Accelerator and not for other reasons?

    The Geneva Learning Foundation solves this challenge through a three-step process that connects the dots between learning, action, and results.

    Step 1: Measuring where we start

    Before participants begin taking action, they document their baseline – the current situation they want to improve. For example:

    • A social worker records how many children show severe trauma symptoms.
    • A radiation specialist documents current safety incident rates.
    • A health worker notes the vaccination coverage in their area.

    These starting numbers give us a clear picture of where improvement begins.

    Step 2: Tracking progress and actions

    Every week, participants complete “acceleration reports” that capture two things:

    • The specific actions they took; and
    • Any changes they observe in their measurements.

    This creates a detailed record connecting what participants do to what happens as a result. Week by week, the picture becomes clearer.

    Step 3: Proving the connection

    Here is where the Impact Accelerator becomes special. When participants see improvements, they must answer a crucial question: “How much of this change happened because of what you learned and did through the Accelerator?”

    But they cannot just claim credit. They must prove it to their peers by showing:

    • Exactly which actions led to which results;
    • Why the changes would not have happened without their intervention; and
    • Evidence that their specific approach made the difference.

    This peer review process is powerful. Your colleagues understand your context. They know what is realistic. They can spot when claims are too bold or when someone is being too modest. They ask tough questions that help clarify what really caused the improvements.

    After the first-ever Accelerator in 2019, we compared the implementation progress after six months between those who joined this final stage and a control group that also developed action plans, but did not join.

    Why this method works

    This approach solves several problems that make attribution difficult:

    1. Traditional studies often cannot capture the complexity of real-world change. The Impact Accelerator’s method shows not just that change happened, but how and why it happened.
    2. Self-reporting can be unreliable when people work alone. But when you must convince peers who understand your work, the reports become more accurate and honest.
    3. Numbers alone do not tell the whole story. By combining measurements with detailed descriptions of actions and peer validation, we get a complete picture of how change happens.

    The invitation to act

    Around the world, professionals like you are transforming their work through the Impact Accelerator. They start with the same doubts you might have: “Can I really create change? Will this work in my context? Do I have time for this?”

    Week by week, action by action, they discover the answer is yes. Yes, they can create change. Yes, it works in their context. Yes, they can find time because the Accelerator fits into their real work rather than adding to it.

    The Impact Accelerator does not promise overnight transformation. It offers something better: a proven process for creating real, sustainable change through your own efforts, supported by peers who understand your journey.

    If you work in a field where you seek to make a difference, the Impact Accelerator can help you move from good intentions to meaningful impact. The same process can work for you.

    The question is not whether the Impact Accelerator can help you create change. The question is: What change do you want to create?

    Your journey can begin Monday.

    Image: The Geneva Learning Foundation Collection © 2025

  • PFA Accelerator: across Europe, practitioners learn from each other to strengthen support to children affected by the humanitarian crisis in Ukraine

    PFA Accelerator: across Europe, practitioners learn from each other to strengthen support to children affected by the humanitarian crisis in Ukraine

    In the PFA Accelerator, practitioners supporting children are teaching each other what works.

    Every Friday, more than 240 education, social work, and health professionals across Ukraine and Europe file reports on the same question: What happened when you tried to help a child this week?

    Their answers – grounded in their daily work – are creating new insights into how Psychological First Aid (“PFA”) works in active conflict zones, displacement centers, and communities hosting Ukrainian families. These practitioners implement practical actions with children each week, then share what they learn with colleagues from all over Europe who face similar challenges.

    The tracking reveals stark patterns. More than half work with children showing anxiety, fear, and stress responses triggered by air raids, family separation, or displacement. Another 42% focus on children struggling to connect with others in unfamiliar places—Ukrainian teenagers isolated in Polish schools, families in Croatian refugee centers, children moved from eastern Ukraine to western regions.

    “We have a very unique experience that you cannot get through lectures,” said PFA practitioner and Ukrainian-language facilitator Hanna Nyzkodobova during Monday’s session, speaking to over 200 of her peers. “The Ukrainian context is not comparable to any other country.”

    Locally-led organizations leading implementation

    The programme’s most striking feature is its reach into organizations operating closest to active hostilities—precisely where support needs are most acute and convention training programs may not operate. For example, the charitable foundation “Everything will be fine Ukraine” implements approaches within 20 kilometers of active fighting, supporting 6,000 children across Donetsk, Dnipropetrovsk, and Kharkiv regions. Weekly reports from their participants document how psychological first aid help when air raid sirens interrupt sessions or when families face repeated displacement.

    Posmishka UA, Ukraine’s largest participating organization with over 400 staff members, demonstrates how peer learning can support local actors directly at scale. During Monday’s learning session, Posmishka participants shared experiences from work in local communities that would be difficult to capture through conventional research or training approaches.

    South Ukrainian National Pedagogical University has integrated the program across 339 faculty and 3,783 students, bringing PFA into the work of its Mental Health Center. Youth Platform is now offering PFA to 600 young people aged 14-35 across five Ukrainian regions, while the All-Ukrainian Public Center “Volunteer” scales implementations to over 10,000 children nationwide.

    These partnerships reveal something crucial: when crisis response is most urgent, peer learning between local actors may prove more effective and sustainable than waiting for external expertise and costly training to develop solutions.

    Learning what works through implementation

    The Geneva Learning Foundation (TGLF) and the International Federation of Red Cross and Red Crescent Societies (IFRC), within the project Provision of quality and timely psychological first aid to people affected by Ukraine crisis in impacted countries, supported by the European Union, created what they call the PFA Accelerator—a component of a broader certificate program reaching over 330 organizations supporting more than 1 million children affected by the humanitarian crisis in Ukraine. This “Accelerator” methodology emerged from recognizing that new approaches are necessary in unprecedented crises. When children face trauma from active conflict, family separation, and repeated displacement simultaneously, guidelines can help but cannot tell you how to adapt to your specific situation.

    The breakthrough lies in turning scale from an obstacle into an advantage. Rather than trying to train individuals who then work in isolation, the programme creates learning networks where practitioners immediately share what works, what doesn’t, and why.

    Analysis of the first 60 action plans shows PFA Accelerator participants setting specific, measurable goals: 88% of those working with anxious children plan concrete emotional regulation activities rather than vague “support” approaches.

    Iryna from Kryvyi Rih reported that schools actively sought partnerships after her initial outreach succeeded: “They wanted us to come to them,” she said, describing how her mobile facilitation team exceeded the goal she set for herself in the Accelerator – because she managed to help school administrators recognize the value of Psychological First Aid (PFA) for children.

    Practical innovations emerge from necessity

    The weekly implementation requirement forces creative problem-solving with limited resources. Mariya from Zaporizhzhia described combining parent and child sessions: “We conducted joint sessions with psychosocial support, where together we learned calming techniques and did exercises oriented toward team building.” This approach addressed both parent stress and child needs while optimizing scarce time and space resources.

    In the PFA Accelerator, other participants can then share their feedback – or realize that Mariya’s local solution can help them, too. “The exchange of experience that happens on this platform is very important because someone is more experienced, someone less experienced,” noted participant Liubov during the Ukrainian session.

    Such practical adaptations become documented knowledge shared across the network. However, in the first week, although 82% identify colleague support as their primary resource, only 49% initially planned collaborative approaches involving other adults. The peer feedback process helps participants recognize such patterns and adjust their methods accordingly.

    Defying distance to solve problems together

    What emerges is not only better implementation of existing approaches—it’s new knowledge about how psychological support works under difficult conditions. The weekly reports create rapid feedback loops showing which approaches help children cope with ongoing uncertainty, how to maintain therapeutic relationships during displacement, and which interventions remain effective when basic safety cannot be guaranteed.

    The programme operates across Ukraine and 27 European countries, supported by over 80 European focal points and more than 20 organizational partners. This enables pattern recognition impossible without scale. Practitioners can better discern which approaches work across different contexts, how cultural differences affect intervention effectiveness, and which methods prove most adaptable to rapidly changing circumstances.

    The larger significance extends beyond Ukraine. By demonstrating how local actors can rapidly develop and refine effective practices when given proper structure for peer learning, the programme offers a model for responding to other crises where traditional expert-led approaches prove too slow or disconnected from local realities. Sometimes the most valuable expertise exists not in training manuals but in the accumulated experience of practitioners working directly with affected populations.

    Learn more and enroll in the PFA Accelerator: https://www.learning.foundation/ukraine-accelerator

    This project is funded by the European Union. Its contents are the sole responsibility of TGLF and IFRC, and do not necessarily reflect the views of the European Union.

  • Why peer learning is critical to survive the Age of Artificial Intelligence

    Why peer learning is critical to survive the Age of Artificial Intelligence

    María, a pediatrician in Argentina, works with an AI diagnostic system that can identify rare diseases, suggest treatment protocols, and draft reports in perfect medical Spanish. But something crucial is missing. The AI provides brilliant medical insights, yet María struggles to translate them into action in her community. What is needed to realize the promise of the Age of Artificial Intelligence?

    Then she discovers the missing piece. Through a peer learning network—where health workers develop projects addressing real challenges, review each other’s work, and engage in facilitated dialogue—she connects with other health professionals across Latin America who are learning to work with AI as a collaborative partner. Together, they discover that AI becomes far more useful when combined with their understanding of local contexts, cultural practices, and community dynamics.

    This speculative scenario, based on current AI developments and existing peer learning successes, illuminates a crucial insight as we ascend into the age of artificial intelligence. Eric Schmidt’s San Francisco Consensus predicts that within three to six years, AI will reason at expert levels, coordinate complex tasks through digital agents, and understand any request in natural language.

    Understanding how peer learning can bridge AI capabilities and human thinking and action is critical to prepare for this future.

    Collaboration in the Age of Artificial Intelligence

    The three AI revolutions—language interfaces, reasoning systems, and agentic coordination—will offer unprecedented capabilities. If access is equitable, this will be available to any health worker, anywhere. Yet having access to these tools is just the beginning. The transformation will require humans to learn together how to collaborate effectively with AI.

    Consider what becomes possible when health workers combine AI capabilities with collective human insight:

    • AI analyzes disease patterns; peer networks share which interventions work in specific cultural contexts.
    • AI suggests optimal treatment protocols; practitioners adapt them based on local resource availability.
    • AI identifies at-risk populations; community workers know how to reach them effectively.

    The magic happens in integration of AI and human capabiltiies through peer learning. Think of it this way: AI can analyze millions of health records to identify disease patterns, but it may not know that in your district, people avoid the Tuesday clinic because that is market day, or that certain communities trust traditional healers more than government health workers.

    When epidemiologists share these contextual insights with peers facing similar challenges—through structured discussions and collaborative problem-solving—they learn together how to adapt AI’s analytical power to local realities.

    For example, when an AI system identifies a disease cluster, epidemiologists in a peer network can share strategies for investigating it: one colleague might explain how they gained community trust for contact tracing, another might share how they adapted AI-generated survey questions to be culturally appropriate, and a third might demonstrate how they used AI predictions alongside traditional knowledge to improve outbreak response.

    This collective learning—where professionals teach each other how to blend AI’s computational abilities with human understanding of communities—creates solutions more effective than either AI or individual expertise could achieve alone.

    Understanding peer learning in the Age of Artificial Intelligence

    Peer learning is not about professionals sharing anecdotes. It is a structured learning process where:

    • Participants develop concrete projects addressing real challenges in their contexts, such as improving vaccination coverage or adapting AI tools for local use.
    • Peers review each other’s work using expert-designed rubrics that ensure quality while encouraging innovation.
    • Facilitated dialogue sessions help surface patterns across different contexts and generate collective insights.
    • Continuous cycles of action, reflection, and revision transform individual experiences into shared wisdom.
    • Every participant becomes both teacher and learner, contributing their unique insights while learning from others.

    This approach differs fundamentally from traditional training because knowledge flows horizontally between peers rather than vertically from experts. When applied to human-AI collaboration, it enables rapid collective learning about what works, what fails, and why.

    Why peer networks unlock the potential of the Age of Artificial Intelligence

    Contextual intelligence through collective wisdom

    AI systems train on global data and identify universal patterns. This is their strength. Human practitioners understand local contexts intimately. This is theirs. Peer learning networks create bridges between these complementary intelligences.

    When a health worker discovers how to adapt AI-generated nutrition plans for local food availability, that insight becomes valuable to peers in similar contexts worldwide. Through structured sharing and review processes, the network creates a living library of contextual adaptations that make AI recommendations actionable.

    Trust-building in the age of AI

    Communities often view new technologies with suspicion. The most sophisticated AI cannot overcome this alone. But when local health workers learn from peers how to introduce AI as a helpful tool rather than a threatening replacement, acceptance grows.

    In peer networks, practitioners share not just technical knowledge but communication strategies through structured dialogue: how to explain AI recommendations to skeptical patients, how to involve community leaders in AI-assisted health programs, how to maintain the human touch while using digital tools. This collective learning makes AI acceptable and valuable to communities that might otherwise reject it.

    Distributed problem-solving

    When AI provides a diagnosis or recommendation that seems inappropriate for local conditions, isolated practitioners might simply ignore it. But in peer networks with structured review processes, they can explore why the discrepancy exists and how to bridge it.

    A teacher receives AI-generated lesson plans that assume resources her school lacks. Through her network’s collaborative problem-solving process, she finds teachers in similar situations who have created innovative adaptations. Together, they develop approaches that preserve AI’s pedagogical insights while working within real constraints.

    The new architecture of collaborative learning

    Working effectively with AI requires new forms of human collaboration built on three essential elements:

    Reciprocal knowledge flows

    When everyone has access to AI expertise, the most valuable learning happens between peers who share similar contexts and challenges. They teach each other not what AI knows, but how to make AI knowledge useful in their specific situations through:

    • Structured project development and peer review;
    • Regular assemblies where practitioners share experiences;
    • Documentation of successful adaptations and failures;
    • Continuous refinement based on collective feedback.

    Structured experimentation

    Peer networks provide safe spaces to experiment with AI collaboration. Through structured cycles of action and reflection, practitioners:

    • Try AI recommendations in controlled ways;
    • Document what works and what needs adaptation using shared frameworks;
    • Share failures as valuable learning opportunities through facilitated sessions;
    • Build collective knowledge about human-AI collaboration.

    Continuous capability building

    As AI capabilities evolve rapidly, no individual can keep pace alone. Peer networks create continuous learning environments where:

    • Early adopters share new AI features through structured presentations;
    • Groups explore emerging capabilities together in hands-on sessions;
    • Collective intelligence about AI use grows through documented experiences;
    • Everyone stays current through shared discovery and regular dialogue.

    Evidence-based speculation: imagining peer networks that include both machines and humans

    While the following examples are speculative, they build on current evidence from existing peer learning networks and emerging AI capabilities to imagine near-future possibilities.

    The Nigerian immunization scenario

    Based on Nigeria’s successful peer learning initiatives and current AI development trajectories, we can envision how AI-assisted immunization programs might work. AI could help identify optimal vaccine distribution patterns and predict which communities are at risk. Success would come when health workers form peer networks to share:

    • Techniques for presenting AI predictions to community leaders effectively;
    • Methods for adapting AI-suggested schedules to local market days and religious observances;
    • Strategies for using AI insights while maintaining personal relationships that drive vaccine acceptance.

    This scenario extrapolates from current successes in peer learning for immunization in Nigeria to imagine enhanced outcomes with AI partnership.

    Climate health innovation networks

    Drawing from existing climate health responses and AI’s growing environmental analysis capabilities, we can project how peer networks might function. As climate change creates unprecedented health challenges, AI models will predict impacts and suggest interventions. Community-based health workers could connect these ‘big data’ insights with their own local observations and experience to take action, sharing innovations like:

    • Using AI climate predictions to prepare communities for heat waves;
    • Adapting AI-suggested cooling strategies to local housing conditions;
    • Combining traditional knowledge with AI insights for water management.

    These possibilities build on documented peer learning successes in sharing health workers observations and insights about the impacts of climate change on the health of local communities.

    Addressing AI’s limitations through collective wisdom

    While AI offers powerful capabilities, we must acknowledge that technology is not neutral—AI systems carry biases from their training data, reflect the perspectives of their creators, and can perpetuate or amplify existing inequalities. Peer learning networks provide a crucial mechanism for identifying and addressing these limitations collectively.

    Through structured dialogue and shared experiences, practitioners can:

    • Document when AI recommendations reflect biases inappropriate for their contexts;
    • Develop collective strategies for identifying and correcting AI biases;
    • Share techniques for adapting AI outputs to ensure equity;
    • Build shared understanding of AI’s limitations and appropriate use cases.

    This collective vigilance and adaptation becomes essential for ensuring AI serves all communities fairly.

    What this means for different stakeholders

    For funders: Investing in collaborative capacity

    The highest return on AI investment comes not from technology alone but from building human capacity to use it effectively. Peer learning networks:

    • Multiply the impact of AI tools through shared adaptation strategies;
    • Create sustainable capacity that grows with technological advancement;
    • Generate innovations that improve AI applications for specific contexts;
    • Build resilience through distributed expertise.

    For practitioners: New collaborative competencies

    Working effectively with AI requires skills best developed through structured peer learning:

    • Partnership mindset: Seeing AI as a collaborative tool requiring human judgment.
    • Adaptive expertise: Learning to blend AI capabilities with contextual knowledge.
    • Reflective practice: Regularly examining what works in human-AI collaboration through structured reflection.
    • Knowledge sharing: Contributing insights through peer review and dialogue that help others work better with AI.

    For policymakers: Enabling collaborative ecosystems

    Policies should support human-AI collaboration by:

    • Funding peer learning infrastructure alongside AI deployment;
    • Creating time and space for structured peer learning activities;
    • Recognizing peer learning as essential professional development;
    • Supporting documentation and spread of effective practices.

    AI-human transformation through collaboration: A comparative view

    Working with AI individuallyWorking with AI through structured peer networks
    Powerful tools but limited adaptation
    Insights remain isolated
    Success depends on individual skill    		Continuous adaptation through structured sharing
    Insights multiply across network through peer review
    Collective wisdom enhances individual capability
    AI recommendations may miss local context
    Trial and error in isolation
    Slow spread of effective practices    		Context-aware applications emerge through dialogue
    Structured experimentation with collective learning
    Rapid diffusion through documented innovations
    Overwhelmed by rapid AI changes
    Struggling to keep pace alone
    Uncertainty about appropriate use    		Collective sense-making through facilitated sessions
    Shared discovery in peer projects
    Growing confidence through structured support

    The collaborative future

    As AI capabilities expand, two paths emerge:

    Path 1: Individuals struggle alone to make sense of AI tools, leading to uneven adoption, missed opportunities, and growing inequality between those who figure it out and those who do not.

    Path 2: Structured peer networks enable collective learning about human-AI collaboration, leading to widespread effective use, continuous innovation, and shared benefit from AI advances.

    What determines outcomes is how humans organize to learn and work together with AI through structured peer learning processes.

    María’s projected transformation

    Six months after her initial struggles, we can envision how María’s experience might transform. Through structured peer learning—project development, peer review, and facilitated dialogue—she could learn to see AI not as a foreign expert imposing solutions, but as a knowledgeable colleague whose insights she can adapt and apply.

    Based on current peer learning practices, she might discover techniques from colleagues across Latin America and the rest of the world:

    • Methods for using AI diagnosis as a conversation starter with traditional healers;
    • Strategies for validating AI recommendations through community health committees;
    • Approaches for using AI analytics to support (not replace) community knowledge.

    Following the pattern of peer learning networks, Maríawould begin contributing her own innovations through structured sharing, particularly around integrating AI insights with indigenous healing practices. Her documented approaches would spread through peer review and dialogue, helping thousands of health workers make AI truly useful in their communities.

    Conclusion: The multiplication effect

    AI transformation promises to augment human capabilities dramatically. Language interfaces will democratize access to advanced tools. Reasoning systems will provide expert-level analysis. Agentic AI will coordinate complex operations. These capabilities are beginning to transform what individuals can accomplish.

    But the true multiplication effect will come through structured peer learning networks. When thousands of practitioners share how to work effectively with AI through systematic project work, peer review, and facilitated dialogue, they create collective intelligence about human-AI collaboration that no individual could develop alone. They transform AI from an impressive but alien technology into a natural extension of human capability.

    For funders, this means the highest-impact investments combine AI tools with structured peer learning infrastructure. For policymakers, it means creating conditions where collaborative learning flourishes alongside technological deployment. For practitioners, it means embracing both AI partnership and peer collaboration through structured processes as essential to professional practice.

    The future of human progress may rest on our ability to find effective ways to build powerful collaboration in networks that combine human and artificial intelligence. When we learn together through structured peer learning how to work with AI, we multiply not just individual capability but collective capacity to address the complex challenges facing our world.

    AI is still emergent, changing constantly and rapidly. The peer learning methods are proven: we know a lot about how humans learn and collaborate. The question is how quickly we can scale this collaborative approach to match the pace of AI advancement. In that race, structured peer learning is not optional—it is essential.

    Image: The Geneva Learning Foundation Collection © 2025

    Fediverse Reactions
  • The funding crisis solution hiding in plain sight

    The funding crisis solution hiding in plain sight

    “I did not realize how much I could do with what we already have.”

    A Nigerian health worker’s revelation captures what may be the most significant breakthrough in global health implementation during the current funding crisis. While organizations worldwide slash programs and lay off staff, a small Swiss non-profit, The Geneva Learning Foundation (TGLF), is demonstrating how to achieve seven times greater likelihood of improved health outcomes while cutting costs by 90 percent.

    The secret lies not in new technology or additional resources, but in something deceptively simple: health workers learning from and supporting each other.

    Nigeria: Two weeks to connect thousands, four weeks to change, and six weeks to outcomes

    On June 26, 2025, representatives from 153 global health and humanitarian organizations gathered for a closed-door briefing seeking proven solutions to implementation challenges they knew all too well. TGLF presented evidence from the Nigeria Immunization Agenda 2030 Collaborative that sounds almost too good be true to senior leaders who have to make difficult decisions given the funding cuts: documented results at unprecedented speed and scale – and at lower cost.

    Working with Gavi, Nigeria’s Primary Health Care Development Agency, and UNICEF, they facilitated connections among 4,300 health workers and more than 600 local organizations across all Nigerian states, in just two weeks. Not fleeting digital clicks, but what Executive Director Reda Sadki calls “deep, meaningful engagement, sharing of experience, problem solving together.”

    The challenge was reaching zero-dose children in fragile areas affected by armed conflict. The timeline was impossible by traditional standards. The results transformed many skeptics into advocates – including those who initially said it sounded too good to be true.

    A civil society organization (CSO) volunteer reported that government staff initially dismissed the initiative: “They heard about this, thought it was just another CSO initiative. Two weeks in, they came back asking how to join.”

    Funding crisis: How does sharing experience lead to better outcomes?

    What happened next addresses the most critical question about peer learning approaches: do health workers learning from each other actually improve health outcomes?

    TGLF’s comparative research demonstrated that groups using structured peer learning are seven times more likely to achieve measurable health improvements versus conventional approaches.

    In Nigeria, health workers learned the “five whys” root cause analysis from each other. Many said no one had ever asked them: “What do you think we should do?” or “Why do you think that is?” The transformation was both rapid and measurable.

    For example, at the program start, only 25 percent knew their basic health indicators for local areas. “I collect these numbers and pass them on, but I never realized I could use them in my work,” participants reported.

    Four weeks in, they had produced 409 root cause analyses. Many realized that their existing activities were missing these root causes. After six weeks, health workers began credibly reporting attribution of new activities that led to finding and vaccinating zero-dose children.

    Given limited budget, TGLF had to halt development. But here is the key point: more than half of participating have maintained and continued the peer support network independently, addressing sustainability concerns that plague traditional capacity-building efforts.

    The snowball effect at scale

    The breakthrough emerged from what Sadki describes as reaching “critical mass” where motivated participants pull others along. “This requires clearing the rubble of all the legacy of top-down command and control systems, figure out how to negotiate hierarchies, especially because government integration is systematically our goal.”

    Nigeria represents one of four large-scale implementations demonstrating consistent results. In Côte d’Ivoire, 501 health workers from 96 districts mapped out 3.5 million additional vaccinations in four weeks. Global initiatives are likely to cost no more than a single country-specific program: the global Teach to Reach network has engaged 24,610 participants across more than 60 countries. The global Movement for Immunization Agenda 2030, launched in March 2022, grew from 6,186 to more than 15,000 members in less than four months.

    The foundation tracks what they call a “complete measurement chain” from individual motivation through implementation actions to health outcomes. Cost efficiency stems from scale and sustainability, with back-of-envelope calculations suggesting 90 percent cost reduction compared to traditional methods.

    Solving the abundance paradox

    “You touched upon an important issue that I am struggling with—the abundance of guidance that my own organization produces and also guidance that comes from elsewhere,” noted a senior manager from an international humanitarian network during the briefing. “It really feels intriguing to put all that material into a course and look at what I am going to do with this. It is a precious process and really memorable and makes the policies and materials relevant.”

    This captures a central challenge facing global health organizations: not lack of knowledge, but failure to translate knowledge into action. The peer learning model transforms existing policies and guidelines into peer learning experiences where practitioners study materials to determine specific actions they will take.

    “Learning happens not simply by acquiring knowledge, but by actually doing something with it,” Sadki explained.

    For example, a collaboration with Save the Children converted a climate change policy brief into a peer learning course accessed by more than 70,000 health workers, developed and deployed in three days with initial results expected within six weeks.

    Networks that outlast the funding crisis

    The foundation’s global network now includes more than 70,000 practitioners across 137 countries, with geographic focus on nations with highest climate vulnerability and disease burden. More than 50 percent are government staff. More than 80 percent work at district and community levels.

    Tom Newton-Lewis, a leading health systems researcher and consultant who attended the briefing, captured what makes this approach distinctive: “I am always inspired by the work of TGLF. There are very few initiatives that work at scale that walk the talk on supporting local problem solving, and mobilize systems to strengthen themselves.”

    This composition ensures that peer learning initiatives operate within rather than parallel to official health systems. More than 1,000 national policy planners connect directly with field practitioners, creating feedback loops between strategy development and implementation reality.

    Networks continue functioning when external support changes. The foundation has documented continued peer connections through network analysis, confirming that established relationships maintain over time.

    Three pathways forward

    The foundation outlined entry points for organizations seeking proven implementation approaches. First, organizations can become program partners, providing their staff access to existing global programs while co-developing new initiatives. Available programs include measles, climate change and health, mental health, non-communicable diseases, neglected tropical diseases, immunization, and women’s leadership.

    Second, using the model to connect policy and implementation at scale and lower cost. Timeline: three days to build, four to six weeks for initial results. Organizations gain direct access to field innovations while receiving evidence-based feedback on what actually works in practice.

    Third, testing the model on current problems where policy exists but implementation remains inconsistent. Organizations can connect their staff to practitioners who have solved similar problems without additional funding. Timeline: six to eight weeks from start to documented results.

    The foundation operates through co-funding partnerships rather than grant-making, with flexible arrangements tailored to partner capacity and project scope. What they call “economy of effort” often delivers initiatives spanning more than 50 countries for the cost of single-country projects.

    Adaptability across contexts

    The model has demonstrated remarkable versatility across different contexts and challenges. The foundation has successfully adapted the approach to new geographic areas like Ukraine and thematic areas like mental health and psychosocial support. Each adaptation requires understanding specific contexts, needs, and goals, but the fundamental peer learning principles remain consistent.

    An Indian NGO raised a fundamental challenge: “Where we struggle with program implementation post-funding is without remuneration frontline workers. Although they want to bring change in the community, are motivated, and have enough data, cannot continue.”

    Sadki’s response: “By recognizing the capabilities for analysis, for adaptation, for carrying out more effective implementation because of what they know, because they are there every day, that should contribute to a growing movement for recognition that CHWs in particular should be paid for the work that they do.”

    The path forward

    The Nigerian health worker’s realization—discovering untapped potential in existing resources—represents more than individual transformation. It demonstrates how peer learning unlocks collective intelligence already present within communities and health systems.

    In two weeks, health workers connected with each other across Nigeria’s most challenging regions, facilitated by the foundation’s proven methodology. By the sixth week, they had begun reporting credible, measurable health improvements. The model works because it values local knowledge, creates peer support systems, and integrates with government structures rather than bypassing them.

    With funding cuts forcing difficult choices across global health, this model offers documented evidence that better health outcomes can cost less, sustainable networks continue without external support, and local solutions scale globally. For organizations seeking proven implementation approaches during resource constraints, the question is not whether they can afford to try peer learning, but whether they can afford not to.

    Image: The Geneva Learning Foundation Collection © 2025

  • When funding shrinks, impact must grow: the economic case for peer learning networks

    When funding shrinks, impact must grow: the economic case for peer learning networks

    Humanitarian, global health, and development organizations confront an unprecedented crisis. Donor funding is in a downward spiral, while needs intensify across every sector. Organizations face stark choices: reduce programs, cut staff, or fundamentally transform how they deliver results.

    Traditional capacity building models have become economically unsustainable. Technical assistance, expert-led workshops, international travel, and venue-based training are examples of high-cost, low-volume activities that organizations may no longer be able to afford.

    Yet the need for learning, coordination, and adaptive capacity has never been greater.

    The opportunity cost of inaction

    Organizations that fail to adapt face systematic disadvantage. Traditional approaches cannot survive current funding constraints while maintaining effectiveness. Meanwhile, global challenges intensify: climate change drives new disease patterns; conflict disrupts health systems; demographic transitions strain capacity.

    These complex, interconnected challenges require adaptive systems that respond at the speed and scale of emerging threats. Organizations continuing expensive, ineffective approaches will face programmatic obsolescence.

    Working with governments and trusted partners that include UNICEF, WHO, Gates Foundation, Wellcome Trust, and Gavi (as part of the Zero-Dose Learning Hub), the Geneva Learning Foundation’s peer learning networks have consistently demonstrated they can deliver measurably superior outcomes while reducing costs by up to 86% compared to conventional approaches.

    Peer learning networks offer both immediate financial relief and strategic positioning for long-term sustainability. The evidence spans nine years, 137 countries, and collaborations with the most credible institutions in global health, humanitarian response, and research.

    The unsustainable economics of traditional capacity building

    A comprehensive analysis reveals the structural inefficiencies of conventional approaches. Expert consultants command daily rates of $800 or more, plus travel expenses. International workshops may require $15,000-30,000 for venues alone. Participant travel and accommodation averages $2,000 per person. A standard 50-participant workshop costs upward of $200,000.

    When factoring limited sustainability, the economics become even more problematic. Traditional approaches achieve measurable implementation by only 15-20% of participants within six months. This translates to effective costs of $10,000-20,000 per participant who actually implements new practices.

    A rudimentary cost-benefit analysis demonstrates how peer learning networks restructure these economics fundamentally.

    ComponentTraditional approachPeer learning networksEfficiency gain
    Cost per participant$1,850$26786% reduction
    Implementation rate15-20%70-80%4x higher success
    Duration of engagement2-3 days90+ days30x longer
    Post-training supportNoneContinuous networkSustained capacity

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

    Evidence of measurable impact at scale

    Value for money requires clear attribution between investments and outcomes.

    In January 2020, we compared outcomes between two groups. Both had intent to take action to achieve results. Health workers using structured peer learning were seven times more likely to implement effective strategies resulting in improved outcomes, compared to the other group that relied on conventional approaches.

    What about speed and scale?

    In July 2024, working with Nigeria’s National Primary Health Care Development Agency (NPHCDA) and UNICEF, we connected 4,300 health workers across all states and 300+ local government areas within two weeks. Over 600 local organizations including government facilities, civil society, faith-based groups, and private sector actors joined this Immunization Collaborative.

    With two more weeks, participants produced 409 peer-reviewed root cause analyses. By Week 6, we began to receive credible vaccination coverage improvements after six weeks, especially in conflict-affected northern regions where conventional approaches had consistently failed. The total programme cost was equivalent to 1.5 traditional workshops for 75 participants. Follow-up has shown that more than half of the participants are staying connected long after TGLF’s “jumpstarting” activities, driven by intrinsic motivation.

    Côte d’Ivoire demonstrates crisis response capability. Working with Gavi and the Ministry of Health, we recruited 501 health workers from 96 districts (85% of the country) in nine days ahead of the country’s COVID-19 vaccination campaign in November 2021. Connected to each other, they shared local solutions and supported each other, contributing to vaccination of an additional 3.5 million additional people at $0.26 per vaccination delivered.

    TGLF’s model empowers health workers to share knowledge, solve local challenges, and implement solutions via a digital platform. Unlike top-down training and technical assistance, it fosters collective intelligence, enabling rapid adaptation to crises. Since 2016, TGLF has mobilized networks for immunization, COVID-19 response, neglected tropical diseases (NTDs), mental health and psychosocial support, noncommunicable diseases, and climate-health resilience.

    These cases illustrate the ability of TGLF’s model to address strategic global priorities—equity, resilience, and crisis response—while maximizing efficiency. This model offers a scalable, low-cost alternative that delivers measurable impact across diverse priorities.

    Our mission is to share such breakthroughs with other organizations and networks that are willing to try new approaches.

    Resource allocation for maximum efficiency

    Our partnership analysis reveals optimal resource allocation patterns that maximize impact while minimizing cost:

    • Human resources (85%): Action-focused approach leveraging human facilitation to foster trust, grow leadership capabilties, and nurture networks with a single-minded goal of supporting implementation to rapidly and sustainably achieve tangible outcomes.
    • Digital infrastructure (10%): Scalable platform development enabling unlimited concurrent participants across multiple countries.
    • Travel (5%): Minimal compared to 45% in traditional approaches, limited to essential coordination where social norms require face-to-face meetings, for example in partnership engagement with governments.

    This structure enables remarkable economies of scale. While traditional approaches face increasing per-participant costs, peer learning networks demonstrate decreasing unit costs with growth. Global initiatives reaching 20,000+ participants across 60+ countries operate with per-participant costs under $10.

    Sustainability through combined government and civil society ownership

    Sustainability is critical amidst funding cuts. TGLF’s networks embed organically within government systems, involving both central planners in the capital as well as implementers across the country, at all levels of the health system.

    Country ownership: Programs work within existing health system structures and national plans. Networks include 50% government staff and 80% district/community-level practitioners—the people who actually deliver services. In Nigeria, 600+ local organizations – both private and public – collaborated, embedding learning in both civil society and government structures.

    Sustainability: In Côte d’Ivoire, 82% sustained engagement without incentives, fostering self-reliant networks. 78% said they no longer needed any assistance from TGLF to continue.

    This approach enhances aid effectiveness, reducing dependency on external funding.

    Aid effectiveness: Rather than bypassing systems, peer learning strengthens existing infrastructure. Networks continue functioning when external funding decreases because they operate through established government channels linked to civil society networks.

    Transparency: Digital platforms create comprehensive audit trails providing unprecedented visibility into program implementation and results for donor oversight.

    Implementation pathways for resource-constrained organizations

    Organizations can adopt peer learning approaches through flexible pathways designed for immediate deployment.

    1. Rapid response initiatives (2-6 weeks to results): Address critical challenges requiring immediate mobilization. Suitable for disease outbreaks, humanitarian emergencies, or longer-term policy implementation.
    2. Program transformation (3-6 months): Convert existing technical assistance programs to peer learning models, typically reducing costs by 80-90% while expanding reach, inclusion, and outcomes.
    3. Cross-portfolio integration: Single platform investments serve multiple technical areas and geographic regions simultaneously, maximizing efficiency across donor portfolios with marginal costs approaching zero for additional countries or topics.

    The strategic choice

    The funding environment will not improve. Economic uncertainty in traditional donor countries, competing domestic priorities, and growing skepticism about aid effectiveness create permanent pressure for better value for money.

    Organizations face a fundamental choice: continue expensive approaches with limited impact, or transition to emergent models that have already shown they can achieve superior results at dramatically lower cost while building lasting capability.

    The question is not whether to change—budget constraints mandate adaptation. The question is whether organizations will choose approaches that thrive under resource constraints or continue hoping that some donors will fill the gaping holes left by funding cuts.

    The evidence demonstrates that peer learning networks achieve 86% cost reduction while delivering 4x implementation rates and 30x longer engagement. These gains are not theoretical—they represent verified outcomes from active partnerships with leading global institutions.

    In an era of permanent resource constraints and intensifying challenges, organizations that embrace this transformation will maximize their mission impact. Those that do not will find themselves increasingly unable to serve the communities that depend on their work.

    Image: The Geneva Learning Foundation Collection © 2025

  • Patterns of prejudice: Connecting the dots helps health workers combat bias worldwide

    Patterns of prejudice: Connecting the dots helps health workers combat bias worldwide

    English | Français

    “I noticed that every time he went to appointments or emergency services, he was often met with suspicion or treated as if he was exaggerating his symptoms,” shared a community support worker from Canada, describing how an Indigenous teenager waited three months for mental health services while non-Indigenous youth were seen within weeks.

    This testimony was just one of hundreds shared during an unusual global gathering where frontline health workers confronted an uncomfortable truth: healthcare systems worldwide are riddled with biases that determine who lives and who dies.

    “Equity Matters: A Practical Approach to Identify and Eliminate Biases,” a special event hosted by the Geneva Learning Foundation (TGLF) on 10-11 April 2025, drew nearly 5,000 health professionals from 72 countries. What made the event distinctive wasn’t just its scope, but its approach: creating a forum where community health workers from rural Nigeria could share insights alongside WHO officials from Switzerland, where district nurses from South Sudan could analyze cases with medical college professors from India.

    When healthcare isn’t equal: Global patterns emerge

    Despite working in vastly different contexts, participants described remarkably similar patterns of bias.

    “A pregnant woman was about to deliver in the hospital, but the doctor said they need to deposit 500,000 naira before she can touch the woman,” recounted Onosi Chikaodiri Peter, a community health worker with Light Bringer’s Outreach in Nigeria. “The husband was begging, pleading, with 100,000 naira, telling the doctor that he could sell all his livestock to make sure that the wife was okay. But the doctor wouldn’t attend to the woman. Along the line, the woman gave up. The child died.”

    Dr. Tusiime Ramadhan, who works with Humanitarian Volunteers International in Uganda, observed the same pattern: “People with money are referred to private clinics and hospitals for better health services often owned by the same government workers who sent them there.”

    Some biases manifest in subtler ways. Hussainah Abba Ali, who works with Impact Santé Afrique in Cameroon, described seeking treatment for malaria during her university years: “Because I was a young woman, the nurse assumed I was just exaggerating. She barely examined me, gave me paracetamol and told me to rest. I later found out that several men who came in after me with similar symptoms were tested immediately for malaria.”

    The stories came from everywhere—a physiotherapist in Nigeria whose expertise was ignored in favor of a male colleague; a nutritionist in DR Congo whose albino neighbor avoided vaccination clinics because of stigma; a public health specialist in Ethiopia’s Somali Region who explained how healthcare systems are designed for settled communities, leaving pastoralist populations behind.

    Alina Onica, a psychologist with Romania’s Icar Foundation working with domestic violence survivors, noted: “Victims are often judged for ‘not leaving’ the abuser, as if staying means it’s not serious. This bias ignores the complex trauma and fear they live with every day.”

    A framework for sense-making beyond single-issue analysis

    What united these diverse testimonies was the application of the BIAS FREE Framework, a practical tool that helps identify and eliminate discriminatory patterns in health systems.

    “Margaret Eichler and I started this work back in 1995 after developing some gender-based analysis tools,” explained Mary Anne Burke, the framework’s co-author. “We realized we had created something that could be applied to all social hierarchies. We’ve workshopped it on every continent but Antarctica and found it applicable everywhere.”

    Unlike approaches that focus exclusively on gender, ethnicity, or disability, the BIAS FREE Framework examines how these factors intersect. Brigid Burke, a researcher who’s used and taught the framework for 15 years, explained how to identify three distinct problem types:

    • H problems: Where existing hierarchies are maintained
    • F problems: Where relevant differences between groups are ignored
    • D problems: Where different standards are applied to different groups

    “It is easier to understand a hierarchy when you’re experiencing the oppression,” Burke told participants. “You can feel that you’re being treated in a way that takes away your dignity. It’s harder when you might be the one who is either consciously or unconsciously oppressing other people.”

    During the event, participants first shared their own experiences, then began to analyze them using the framework. Abdoulie Bah, a regional Red Cross officer from The Gambia, offered his analysis: “Oppressive hierarchies suggest that certain groups experience more oppression than others, often leading to a competitive dynamic among marginalized groups.”

    Solutions from the ground up

    What distinguished this event from typical global health conferences was its emphasis on solutions developed by frontline workers themselves.

    Dr. Orimbato Raharijaona, a medical doctor from Madagascar, described his team’s efforts to reach children in remote areas: “We prioritized areas with low vaccination coverage and strengthened birth follow-up to target zero-doses. Community dialogue helped raise awareness of the need for vaccination.”

    In Mali, Bouréma Mounkoro, a public health medical assistant, discovered that simply rescheduling vaccination days to align with community availability dramatically improved coverage rates and reduced dropouts.

    Dayambo Yendoukoua from Niger’s Red Cross developed an integrated approach addressing rural women’s exclusion from maternal care: “Women from villages and farming hamlets have three times less access to obstetric care than urban women. We grouped women into Mothers’ Clubs, provided literacy training, set up income-generating activities, and established traditional ambulances managed by women.”

    This emphasis on community-based solutions resonated with Esther Y. Yakubu, a health worker with the Health and Development Support Programme in Nigeria: “This program will surely be of great value in the health sector. If put in place, it will make a huge difference and patients will receive quality treatment without any segregations.”

    Practical action – not academic debates – to decolonize global health

    The event itself embodied the principles it aimed to teach. Rather than positioning Western experts as authorities, TGLF structured the event to value diverse forms of expertise.

    “Community health workers can see barriers that researchers miss. Global researchers spot patterns invisible at the local level. Policy makers understand system constraints that affect implementation,” explained Reda Sadki, TGLF’s Executive Director. “It’s when these perspectives connect that we find better solutions.”

    On 24-25 April 2025, this community will reconvene to determine if there is enough interest and momentum to launch the Foundation’s Certificate peer learning programme for equity in research and practice. An inaugural course could be launched as early as June 2025.

    “Your participation helps determine if we develop a full program on identifying and removing bias in health systems,” TGLF explained in its materials. “When more than 1,000 people participate, it shows enough interest to create a more comprehensive learning opportunity.”

    The certificate program will bring together participants from across professional hierarchies—community health workers, district managers, national planners, and global researchers—creating a rare space where knowledge flows in all directions.

    Across time zones and contexts, the conversation highlighted a shared understanding: addressing bias in healthcare isn’t just about fairness—it’s about survival. As Haske Akiti Joseph, a radiographer from Nigeria’s National Orthopaedic Hospital, reflected: “These issues are happening everywhere because governments will not provide free medical services to the people, and medical considerations come due to who you are, not based on priority.”

    In a world where your chances of receiving timely, appropriate healthcare often depend on your gender, ethnicity, wealth, or location, the BIAS FREE Framework offers a practical way forward—one that begins with recognizing patterns of oppression that transcend borders and cultures.

    Image: The Geneva Learning Foundation Collection © 2025

  • L’équité compte: quand les soignants du monde entier témoignent des inégalités en santé

    L’équité compte: quand les soignants du monde entier témoignent des inégalités en santé

    English | Français

    GENÈVE, le 11 avril 2025 – Une initiative internationale inédite a rassemblé près de 5000 professionnels de santé pour partager leurs expériences face aux discriminations dans l’accès aux soins

    « Un enfant est mort parce que sa famille ne pouvait pas déposer 500 000 nairas [environ 300 francs suisses] avant le début des soins. Le père avait pourtant supplié qu’on s’occupe de l’enfant, proposant 100 000 nairas et promettant de vendre son bétail pour payer le reste. » Ce récit glaçant d’un professionnel de santé nigérian illustre la dure réalité des inégalités d’accès aux soins dont de nombreux témoignages ont été partagés lors d’un événement international consacré à l’équité en santé.

    Le 11 avril dernier, la Fondation Apprendre Genève a créé un espace de dialogue sans précédent, rassemblant près de 5 000 professionnels de la santé de 72 pays, dont 1 830 francophones. Intitulé « L’équité compte: une approche pratique pour identifier et éliminer les biais », cet événement a permis à des médecins, infirmiers, agents de santé communautaires et autres acteurs du terrain de raconter, dans leurs propres mots, les discriminations qu’ils observent quotidiennement.

    Des récits convergents malgré la diversité des contextes

    « L’originalité de cette rencontre réside dans sa capacité à faire émerger des expériences habituellement invisibilisées », explique Reda Sadki, directeur exécutif de la Fondation. « Des praticiens qui n’ont jamais accès aux tribunes internationales ont pu témoigner des réalités qu’ils affrontent chaque jour. »

    Ces témoignages, remarquablement similaires malgré la diversité des contextes, révèlent que le statut social détermine encore largement la qualité et la rapidité des soins. « Nous avions amené un enfant gravement malade à l’hôpital », raconte Neville Kasongo, du Corps des jeunes contre le paludisme en République démocratique du Congo. « Pendant que nous attendions plus de six heures, j’ai vu notre voisin arriver avec son enfant malade. Comme il avait des relations particulières dans cette institution, les cadres soignants se sont précipités pour s’occuper de son fils. Pour nous qui n’avions aucune connexion, quand ils sont finalement venus, l’enfant était déjà très affaibli. Une heure après, il est décédé. »

    Brigitte Meugang, point focal du Programme élargi de vaccination au Cameroun, a observé un phénomène similaire lors d’une visite à l’hôpital: « J’avais un malade hospitalisé et je suis arrivée un peu en retard pendant les heures de visite. Le vigile m’a dit: “Tu n’entres pas parce que l’heure de visite est déjà passée.” Quelques minutes plus tard, un cousin militaire est arrivé en tenue. Le vigile a ouvert le portail et lui a dit d’entrer. » Quand elle a demandé pourquoi, on lui a répondu qu’il était en uniforme. C’est seulement après avoir présenté sa carte professionnelle qu’elle a été autorisée à entrer.

    Les intervenants ont également souligné comment des groupes entiers sont systématiquement laissés pour compte. « Dans les zones de conflit au Burkina Faso, les femmes, les enfants et les personnes âgées déplacés subissent des violences basées sur le genre car leurs besoins spécifiques ne sont pas pris en compte », témoigne une spécialiste genre et inclusion sociale. « Les enfants souffrent de malnutrition, les femmes enceintes n’ont pas accès aux consultations prénatales, et les personnes âgées ne bénéficient pas de soins adaptés. »

    Quand l’injustice touche même les soignants

    Particulièrement frappants sont les témoignages de professionnels de santé ayant eux-mêmes subi des discriminations. Le Dr Balkissa Modibo Hama, coordonnatrice du programme mondial d’éradication de la poliomyélite pour l’OMS en Guinée, raconte: « Lors de l’accouchement de ma seconde fille, le personnel ne s’est pas occupé de moi jusqu’à ce que la sage-femme responsable arrive et leur dise qui j’étais. Soudain, tous se sont mobilisés autour de moi en me reprochant de ne pas m’être présentée. Après mon accouchement, j’ai convoqué tout le personnel pour les sensibiliser sur le fait qu’on ne devrait pas avoir besoin de dire qui on est pour recevoir des soins de qualité. »

    Dans certains cas, c’est l’expérience personnelle de l’injustice qui a motivé l’engagement professionnel. « À 13 ans, j’ai accompagné ma mère à l’hôpital », poursuit le Dr Hama. « L’infirmière, qui connaissait ma mère, a voulu me faire passer avant une femme Bororo dont l’enfant était plus mal en point. J’ai refusé, mais j’ai ensuite constaté que cette femme et son enfant avaient été négligés. Cette expérience m’a profondément marquée et a motivé ma décision de devenir médecin. »

    Christian Kpoyablé Clahin, infirmier en Côte d’Ivoire, a partagé un cas tragique: « Une femme est venue avec son enfant gravement malade. Elle n’avait pas d’argent pour payer les analyses. L’enfant a été mis à l’écart au laboratoire et cela a traîné jusqu’à ce qu’il soit trop tard. L’enfant est mort. J’ai interpellé le directeur de l’hôpital, mais les sanctions n’ont été que verbales. »

    Des initiatives locales qui font la différence

    Au-delà du constat, les participants ont partagé des solutions concrètes qu’ils ont développées face à ces inégalités. Arthur Fidelis Metsampito Bamlatol, coordinateur d’une association de santé au Cameroun, explique: « J’avais observé que les enfants Baka [pygmées] étaient insuffisamment vaccinés. Après avoir signalé ce problème au médecin-chef de district, nous avons cartographié les campements dans la forêt et institué des stratégies spéciales. Lors des campagnes suivantes, nous marchions parfois plusieurs heures à pied pour atteindre ces communautés isolées. »

    D’autres adaptations créatives ont été mentionnées, comme celle rapportée par Bouréma Mounkoro, assistant médical au Mali: « Le planning des activités de vaccination n’était pas synchronisé avec la disponibilité de la communauté. Nous avons reprogrammé les jours de vaccination en tenant compte des réalités locales, ce qui a amélioré la couverture vaccinale et réduit considérablement les cas d’abandon. »

    Pour Brice Alain Dakam Ncheuta, responsable de l’engagement communautaire à Médecins Sans Frontières au Niger, comprendre les dynamiques culturelles est essentiel: « Dans le Grand Sahel, pour réduire les biais dans la prise en charge des violences basées sur le genre, nous travaillons étroitement avec les leaders communautaires. Nous proposons des soins médicaux sans heurter la sensibilité culturelle, car cela fait partie de l’identité des personnes que nous accompagnons. »

    Les solutions peuvent parfois être simples mais révolutionnaires, comme l’illustre l’initiative de Dayambo Yendoukoua, délégué de programme santé à la Croix-Rouge au Niger: « Dans les villages et hameaux agricoles, nous avons constaté que les femmes ont trois fois moins accès aux soins obstétricaux que les femmes urbaines. Nous avons créé des Clubs de Mères, offert des formations d’alphabétisation, mis en place des activités génératrices de revenus, et établi des ambulances traditionnelles gérées par les femmes elles-mêmes. »

    Vers un partage de savoirs plus équitable

    L’originalité de cet événement réside également dans sa méthodologie même. Plutôt que de suivre le schéma classique des conférences internationales où les experts occidentaux partagent leur savoir avec les praticiens du Sud, la Fondation Apprendre Genève a délibérément inversé cette logique. « Ce sont les professionnels de terrain qui ont pris la parole en premier », souligne Reda Sadki, directeur exécutif de la Fondation.

    « Les agents de santé communautaire peuvent voir des obstacles que les chercheurs manquent. Les décideurs comprennent les contraintes systémiques qui affectent la mise en œuvre des politiques. C’est lorsque ces perspectives se connectent que nous trouvons de meilleures solutions », poursuit-il.

    Pour faciliter l’analyse de ces expériences, Brigid Burke a accompagné la rencontre en tant que Guide. Burke est une chercheuse spécialisée dans le cadre BIAS FREE, un outil développé par Mary-Anne Burke et Margaret Eichler, permettant d’identifier différents types de biais. Cela a permis d’aller au-delà des constats en proposant une grille d’analyse des échanges entre participants qui ont constitué le cœur de la rencontre.

    Le succès de cette approche pourrait conduire à la création d’un programme de formation international, dont le lancement sera discuté lors d’une nouvelle rencontre fin avril. « Nous souhaitons développer un espace où les connaissances circulent véritablement dans toutes les directions, plutôt que du Nord vers le Sud », précise M. Sadki.

    La participation massive à cet événement – bien au-delà des attentes des organisateurs – témoigne d’un besoin urgent d’aborder ces questions. « Votre participation aide à déterminer si nous développons un programme plus complet sur ces questions », a expliqué la Fondation. « Quand près de 5000 personnes participent, cela montre qu’il y a suffisamment d’intérêt. »

    « La meilleure stratégie pour corriger tous les biais reste l’installation partout dans nos pays d’une couverture maladie universelle », suggère le Dr Oumar Traoré, médecin de santé publique en Guinée. Une vision à laquelle fait écho Amadou Gueye, président du Malaria Youth Corps en Guinée: « Ces témoignages nous rappellent que l’équité en santé n’est pas qu’une question technique, mais aussi une question de justice fondamentale. »

    Image: Collection de la Fondation Apprendre Genève © 2025

  • Peer learning for Psychological First Aid: New ways to strengthen support for Ukrainian children

    Peer learning for Psychological First Aid: New ways to strengthen support for Ukrainian children

    This article is based on Reda Sadki’s presentation at the ChildHub “Webinar on Psychological First Aid for Children; Supporting the Most Vulnerable” on 6 March 2025. Learn more about the Certificate peer learning programme on Psychological First Aid (PFA) in support of children affected by the humanitarian crisis in Ukraine. Get insights from professionals who support Ukrainian children.

    “I understood that if we want to cry, we can cry,” reflected a practitioner in the Certificate peer learning programme on Psychological First Aid (PFA) in support of children affected by the humanitarian crisis in Ukraine – illustrating the kind of personal transformation that complements technical training.

    During the ChildHub “Webinar on Psychological First Aid for Children; Supporting the Most Vulnerable”, the Geneva Learning Foundation’s Reda Sadki explained how peer learning provides value that traditional training alone cannot deliver. The EU-funded program on Psychological First Aid (PFA) for children demonstrates that practitioners gain five specific benefits:

    First, peer learning reveals contextual wisdom missing from standardized guidance. While technical training provides general principles, practitioners encounter varied situations requiring adaptation. When Serhii Federov helped a frightened girl during rocket strikes by focusing on her teddy bear, he discovered an approach not found in manuals: “This exercise helped the girl switch her focus from the situation around her to caring for the bear.”

    Second, practitioners document pattern recognition across diverse cases. Sadki shared how analysis of practitioner experiences revealed that “PFA extends beyond emergency situations into everyday environments” and “children often invent their own therapeutic activities when given space.” These insights help practitioners recognize which approaches work in specific contexts.

    Third, peer learning validates experiential knowledge. One practitioner described how simple acknowledgment of feelings often produced visible relief in children, while another found that basic physical comforts had significant psychological impact. These observations, when shared and confirmed across multiple practitioners, build confidence in approaches that might otherwise seem too simple.

    Fourth, the network provides real-time problem-solving for urgent challenges. During fortnightly PFA Connect sessions, practitioners discuss immediate issues like “supporting children under three years” or “recognizing severe reactions requiring referrals.” As Sadki explained, these sessions produce concise “key learning points” summarizing practical solutions practitioners can immediately apply.

    Finally, peer learning builds professional identity and resilience. “There’s a lot of trust in our network,” Sadki quoted from a participant, demonstrating how sharing experiences reduces isolation and builds a supportive community where practitioners can acknowledge their own emotions and challenges.

    The webinar highlighted how this approach creates measurable impact, with practitioners developing case studies that transform tacit knowledge into documented evidence and structured feedback that helps discover blind spots in their practice.

    For practitioners interested in joining, Sadki outlined multiple entry points from microlearning modules completed in under an hour to more intensive peer learning exercises, all designed to strengthen support to children while building practitioners’ own professional capabilities.

    This project is funded by the European Union. Its contents are the sole responsibility of TGLF, and do not necessarily reflect the views of the European Union.

    Illustration: The Geneva Learning Foundation Collection © 2025

  • AI podcast explores surprising insights from health workers about HPV vaccination

    AI podcast explores surprising insights from health workers about HPV vaccination

    This is an AI podcast featuring two hosts discussing an article by Reda Sadki titled “New Ways to Learn and Lead HPV Vaccination: Bridging Planning and Implementation Gaps.” The conversational format involves the AI hosts taking turns explaining key points and sharing insights about Sadki’s work on HPV vaccination strategies. While the conversation is AI-generated, everything is based on the published article and insights from the experiences of thousands of health workers participating in Teach to Reach.

    The Geneva Learning Foundation’s approach

    Throughout the podcast, the hosts explore how the Geneva Learning Foundation (TGLF) has developed a five-step process to improve HPV vaccination implementation through their “Teach to Reach” program. This process involves:

    1. Gathering experiences from health workers worldwide
    2. Analyzing these experiences for patterns and innovative solutions
    3. Conducting deep dives into specific case studies
    4. Bringing national EPI planners into the conversation
    5. Synthesizing and sharing knowledge back with frontline workers

    The hosts emphasize that this approach represents a shift from traditional top-down strategies to one that values the collective intelligence of over 16,000 global health workers who implement these programs.

    Surprising findings

    The AI hosts discuss several findings from peer learning that may seem counterintuitive, including:

    • Tribal communities often show less vaccine hesitancy than urban populations, potentially due to stronger community ties and trust in traditional leaders
    • Teachers sometimes have more influence than health workers when it comes to vaccination recommendations
    • Simple, clear communication is often more effective than complex strategies
    • Religious institutions can become powerful allies when approached respectfully
    • Male community leaders can be crucial advocates for what’s typically framed as a women’s health issue

    Effective implementation strategies

    The hosts highlight various successful implementation approaches mentioned in Sadki’s article:

    • Cancer survivors serving as powerful advocates
    • WhatsApp groups connecting community health workers for information sharing
    • Engaging schoolchildren as messengers to initiate family conversations
    • Integrating vaccination efforts with existing women’s groups
    • Community theater and traditional storytelling methods
    • Less formal settings often producing better results than clinical environments

    System-level insights

    The podcast discussion reveals that successful vaccination programs don’t necessarily require abundant resources. Instead, key factors include:

    • Strong leadership and clear vision
    • Commitment to continuous learning
    • Community mobilization and trust-building
    • Leveraging informal networks
    • Prioritizing social factors over technical ones
    • Local adaptation rather than standardization

    The AI hosts conclude by reflecting on how these principles challenge global health epidemiologists to reconsider their roles—moving beyond data analysis to becoming facilitators who empower communities to develop their own solutions.