Rethinking human resources for malaria control and elimination in Africa

The comprehensive policy review by Halima Mwenesi and colleagues “Rethinking human resources and capacity building needs for malaria control and elimination in Africa” argues that the stagnation in global malaria progress is fundamentally a human resources crisis rather than solely a biological or technical failure.

The authors posit that the current workforce is insufficient in number and ill-equipped with the necessary skills to navigate the complex transition from malaria control to elimination.

It is a critical indictment of the status quo in malaria training and offers a roadmap for structural reform.

This article summarizes key points from the policy review and examines how The Geneva Learning Foundation’s peer learning-to-action model could be used by national programmes to transform the health workforce.

The mismatch between training and operational needs

The authors identify a severe imbalance in training priorities where capacity building has historically favored biomedical and basic sciences such as entomology and parasitology.

While essential, this focus has led to a neglect of operational, translational, and implementation sciences.

The report highlights that while the global community produces high-level scientists who understand the parasite, it fails to produce “translational scientists” who can bridge the gap between global guidelines and local realities.

This has resulted, they argue, in a workforce lacking the practical competencies to operationalize complex elimination strategies that require precision and adaptation.

The deficit in leadership and social sciences

A major finding is the specific deficit in so-called “soft skills” and social sciences which are increasingly critical as programs move toward elimination.

The authors argue that modern malaria control requires competencies in leadership, health diplomacy, anthropology, sociology, and political analysis.

Program managers currently lack the training to navigate complex political landscapes, mobilize domestic resources, or engage effectively with communities to sustain interventions.

The review emphasizes that understanding community behavior and social determinants is as critical as understanding vector behavior but this is rarely reflected in curricula.

Data illiteracy and the failure of surveillance

The paper identifies pervasive “data illiteracy” across the workforce.

Health workers collect vast amounts of data to satisfy donor reporting requirements but often lack the skills to interpret or use it for local decision-making.

This results in a “data-rich but information-poor” environment.

As countries move toward elimination, the need for real-time, granular surveillance becomes paramount.

The current workforce is unable to perform the rapid data analysis required to detect and respond to outbreaks at the sub-national level.

Fragmentation and lack of coordination

The review critiques the fragmentation of investments in training, capacity-building, and technical assistance driven by donor agendas.

It notes a lack of coordination among donors and agencies which leads to a proliferation of uncoordinated short courses and workshops that do not necessarily align with national strategic plans.

This fragmentation is exacerbated by a lack of data on the workforce itself.

Many countries lack a central registry of malaria personnel which makes it impossible to forecast needs, plan for attrition, or manage career pathways.

The call for structural transformation

The authors call for a radical shift toward “South-South” collaboration where African institutions take the lead in training.

They advocate for moving away from ad hoc workshops toward institutionalized, long-term capacity building.

Crucially, they recommend the use of digital platforms to democratize access to knowledge for mid-level and community-based cadres who are often excluded from elite fellowships.

How can learning science help transform malaria training investments into tangible health worker performance?

For a global health epidemiologist accustomed to viewing disease control through the lens of biological interventions and coverage rates, the human resource crisis described by Mwenesi and colleagues represents a “delivery failure” of validated tools.

The Geneva Learning Foundation (TGLF) learning science model functions as a structural intervention designed to repair broken delivery mechanisms in global health and humanitarian response.

The following analysis translates the TGLF approach into terms recognizable to an epidemiologist or program manager who operates with the assumption that training is primarily about the transmission of technical knowledge.

Moving from passive transmission to implementation fidelity

Epidemiologists understand that a vaccine with high efficacy in a trial often has low effectiveness in the real world due to poor administration or cold chain failure.

Similarly, Mwenesi et al. identify that technical malaria guidelines fail because the “human infrastructure” cannot implement them.

Traditional training assumes that if you lecture health workers on a protocol, which is a transmission of information, they will execute it.

This is a “single-loop” assumption.

The TGLF model introduces an “implementation loop.”

Instead of merely receiving information, learners in the TGLF network must design a micro-project to apply the new guideline in their specific district, execute it, and report back on the results using their own local data.

This turns the workforce from passive recipients of protocols into active testers of implementation fidelity.

It directly addresses the “translational science” gap identified in the paper by forcing the learner to translate theory into practice immediately.

Sceptics often argue that this approach places an undue burden on an already overworked workforce.

However, the TGLF model embeds learning into the workflow itself.

This is not additional work but rather “learning-based work.”

Participants do not create hypothetical projects.

They identify a bottleneck they are currently facing, such as a specific pocket of malaria transmission, and use the learning cycle to address it.

This transforms the training from an external interruption into an operational support mechanism.

By embedding learning into the workflow, it operationalizes Mwenesi’s call for translational science.

It considers the daily struggle of the health worker as a form of structured scientific inquiry: they hypothesize a solution, test it, and report the results.

This is implementation as science.

Operationalizing data use for local decision-making

Mwenesi notes that health workers collect data but do not use it.

In the TGLF model, data is not something sent “up” to the ministry.

It is the raw material for peer support and feedback.

In a TGLF peer learning exercise, a district medical officer in Ghana shares their case management data to compare performance with a peer in Uganda.

They share because they want to, not because they are required to.

This creates a social incentive to understand and analyze one’s own data.

It builds the “data literacy” the authors call for not through abstract statistics courses but through the practical necessity of explaining one’s own performance to a colleague.

This process transforms data from a compliance burden into a tool for local problem-solving.

Is there a risk that peer learning will pool ignorance?

Is there a valid concern regarding the risk of “pooled ignorance” where peers might reinforce incorrect practices?

The TGLF model mitigates this through “structured emergence.”

The model does not dismiss expert knowledge but uses global guidelines as the “anchor” for local problem-solving.

In this system, a health worker cannot simply state an opinion.

They must submit an action plan that is peer-reviewed against a rubric derived from WHO guidelines.

This process ensures fidelity to technical standards while allowing for necessary local adaptation.

The aggregation of thousands of these peer-reviewed plans creates a new form of rigorous, practice-based evidence that complements expert guidance.

Scaling “soft skills” through structured peer review

The review calls for leadership and diplomacy skills but notes these are hard to teach in workshops.

The TGLF model builds these skills implicitly through its pedagogical structure.

When a participant submits an action plan, they must receive and respond to critical feedback from peers in other countries.

They must negotiate differing viewpoints and defend their technical choices.

This mimics the “health diplomacy” and leadership dynamics required in real-world program management.

Furthermore, because they must engage community stakeholders to implement their projects, they practice the anthropological and social engagement skills Mwenesi identifies as missing.

They learn leadership not by studying a theory of leadership but by leading a change initiative in their facility.

While some experts argue that soft skills require “hard contact” in physical spaces, TGLF results suggest that physical proximity often limits a worker to their known environment and existing biases.

The TGLF model introduces a form of “cosmopolitan localism.”

When a nurse in rural Nigeria must explain her challenge to a peer in urban India, she is forced to articulate her context with a clarity and diplomacy not required when speaking to a neighbor.

This defiance of distance fosters a quantum leap in communication capabilities.

Participants report that the skills learned in negotiating these digital, cross-cultural peer relationships directly translate to better engagement with their physical-world colleagues and community leaders.

Addressing the incentive structure and correcting expertise asymmetry

The paper critiques the “brain drain” and the reliance on experts from the Global North.

TGLF operationalizes the “South-South” collaboration recommended by the authors by creating a flat digital hierarchy.

In this model, the “expert” is not a visiting consultant from Geneva but a peer who has successfully solved the problem in their own context.

A nurse in Nigeria learns how to improve bed net usage from a nurse in Kenya who solved that exact refusal issue last month.

This actually results in greater interest, comprehension, and use of official guidelines.

It also validates local knowledge and creates the “critical mass of thinking professionals” that Mwenesi argues is essential for elimination.

It shifts the source of authority from external experts to the collective intelligence of the network.

Transforming the economy of per diem

A common critique of moving away from face-to-face training is the reliance of health workers on per diems for financial survival.

Mwenesi implies that the current system is unsustainable.

The TGLF model operates on the evidence that per diem-driven training often restricts access to a “training aristocracy” of recurrent participants while excluding the frontline workers who most need the knowledge.

TGLF replaces the financial incentive with a professional survival incentive.

In the Nigeria Immunization Collaborative, over 4,300 health workers participated without per diems.

They did so because the program addressed the specific pain points of their daily work.

This filters the workforce for “positive deviants,” or those with high intrinsic motivation who are most likely to drive elimination efforts, rather than those primarily motivated by daily subsistence allowances.

A “surveillance system” for human resources and performance

Finally, the review notes the lack of registries and data on the workforce itself.

The TGLF digital network acts as a real-time sensor of workforce capacity.

By engaging thousands of health workers simultaneously, the platform generates data on who is active, what problems they are facing, and where their skills are deficient.

For an epidemiologist, this is equivalent to a surveillance system for human resources.

It provides the visibility needed to forecast gaps and target interventions precisely, replacing the “blind” proliferation of uncoordinated workshops with a data-driven approach to capacity building.

Regarding concerns that digital platforms fail in low-resource settings due to poor connectivity, TGLF utilizes a “cognitively quiet” design that functions on low-bandwidth connections and mobile devices.

This design respects the technological reality of the African context.

Data from the Teach to Reach program, which has engaged over 60,000 participants in remote, ongoing peer learning activities , demonstrates that when the technology is adapted to the user rather than the other way around, participation rates exceed those of physical workshops.

This scale allows for the identification of systemic patterns and workforce gaps that would be invisible in a smaller, face-to-face cohort.

Reference

Mwenesi, H., Mbogo, C., Casamitjana, N., Castro, M.C., Itoe, M.A., Okonofua, F., Tanner, M., 2022. Rethinking human resources and capacity building needs for malaria control and elimination in Africa. PLOS Glob Public Health 2, e0000210. https://doi.org/10.1371/journal.pgph.0000210

Reda Sadki (2023). How do we reframe health performance management within complex adaptive systems?. Reda Sadki: Learning to make a difference. https://doi.org/10.59350/mx5qr-qet97

Reda Sadki (2024). Prioritizing the health and care workforce shortage: protect, invest, together. Reda Sadki: Learning to make a difference. https://doi.org/10.59350/zzqr4-9g482

Reda Sadki (2024). Protect, invest, together: strengthening health workforce through new learning models. Reda Sadki: Learning to make a difference. https://doi.org/10.59350/g24b4-7fj64

Reda Sadki (2024). What is double-loop learning in global health?. Reda Sadki: Learning to make a difference. https://doi.org/10.59350/s4xtw-b7274

Reda Sadki (2024). World Malaria Day 2024: We need new ways to support health workers leading change with local communities. Reda Sadki: Learning to make a difference. https://doi.org/10.59350/yrn1r-hpz62

The future of hybrid engagement: accelerated action to tackle global threats

How can we use the new physics of digital connections to save lives? What is the future of hybrid engagement?

Mobilization: validating social presence

Analysis: engineering high-bandwidth interaction

Action: from surveillance to accompaniment

The metrics of connection

A new peer learning programme for those leading change across distance

References

• • Lampel, J. and Meyer, A.D. (2008) ‘Field-Configuring Events as Structuring Mechanisms: How Conferences, Ceremonies, and Trade Shows Constitute New Technologies, Industries, and Markets’, Journal of Management Studies, 45(6), pp. 1025–1035. Available at: https://doi.org/10.1111/j.1467-6486.2008.00797.x

• • Lave, J. and Wenger, E. (1991) Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press. Available at: https://doi.org/10.1017/CBO9780511815355

• • Jarvenpaa, S.L. and Leidner, D.E. (1999) ‘Communication and Trust in Global Virtual Teams’, Organization Science, 10(6), pp. 791–815. Available at: https://doi.org/10.1287/orsc.10.6.791

• • Jones I, Sadki R, Brooks A, Gasse F, Mbuh C, Zha M, et al. IA2030 Movement Year 1 report. Consultative engagement through a digitally enabled peer learning platform. The Geneva Learning Foundation; 2022. Available from: https://doi.org/10.5281/zenodo.7119648.

• • Sadki, R., 2024. How can we reliably spread evidence-based practices at the speed and scale modern health challenges demand? https://doi.org/10.59350/cqxmj-3bd96.

• • Sadki, R., 2025. What is The Geneva Learning Foundation’s Impact Accelerator?https://doi.org/10.59350/redasadki.21161.

• • Sadki, R., 2025. PFA Accelerator: across Europe, practitioners learn from each other to strengthen support to children affected by the humanitarian crisis in Ukraine. https://doi.org/10.59350/redasadki.21155.

• • Watkins, K.E., Bhattarai, A., 2019. Analysis of the Impact Accelerator Launch Pad Individual Acceleration Reports in July 2019. University of Georgia at Athens, Athens, United States.

About the installation

Implementation science for planetary health

Remarks about implementation science for planetary health by Reda Sadki, Executive Director, The Geneva Learning Foundation at the Centre for Planetary Health’s research corner meeting, London School of Hygiene & Tropical Medicine (LSHTM) on December 17, 2025.

Pauline Paterson (LSHTM): We are really delighted to welcome Reda Sadki. Reda is the Executive Director of the Geneva Learning Foundation, a non-profit research organization developing new epistemological and methodological approaches for complex global health challenges. Welcome, Reda.

Reda Sadki (TGLF): Warm greetings from Geneva, Switzerland. I am very pleased to share with you what we have been learning about climate change and health – in particular, how we can move from ground truth to local action on a global scale.

Since 2021, we have been running an initiative called Teach to Reach, led by community-based health professionals from all over the world. It connects people across countries and job roles, supporting the journey from local insight to global health initiative.

The scale of this network has grown significantly. In March 2021, we started with 2,604 participants. By December 2024, at the eleventh meeting of Teach to Reach, we had 24,610 health workers participating.

Who are they? Most work in health facilities and districts. Half work for government and half for civil society organizations.

Where are they? They serve in the most fragile contexts: 62% work in remote rural areas; 47% with the urban poor; 25% with refugees or internally displaced populations. And one in five work in areas of active armed conflict.

Alongside these individuals, we are nurturing the REACH Network, a coalition of more than 4,000 locally-led organizations. This is the backdrop for how we think about leadership as the key to driving change in climate and health.

The “dark matter” of implementation science

As a community working on climate change and health, we are strong – and getting stronger – on diagnosis. But we must be candid: we are weak on delivery. The science keeps getting better, but there is a gap when it comes to translating science into action.

When it comes to formal research, we see what I call the ”dark matter”, a blind spot around hyperlocal adaptation and how implementation actually happens at the local level.

This dark matter includes environmental, behavioral, and systemic signals that formal research might miss: social and economic disruption, hidden mental health burdens in communities with no formal services, community coping mechanisms, and subtle changes in vector behaviors.

Now, I know that for many of you trained in epidemiology, the word “anecdote” sets off alarm bells. We are taught to devalue it for good reason: it is prone to recall bias, selection bias, and lacks denominators. A nurse in Bangladesh noticing “more heatstroke” is a signal, not a prevalence study. We are not claiming it is.

However, we have two ways to answer the questions these signals raise. We can carry out long-term, rigorous academic studies over decades. Or – given that we are past several climate tipping points – we can recognize that aggregate patterns formed by thousands of these signals offer a speed and granularity that traditional studies cannot match. This functions as a massive, distributed sentinel surveillance system. It may be “imperfect” compared to a controlled trial, but is it riskier than the alternative? The alternative is often waiting years for definitive answers while communities suffer damage that may make those findings moot.

This requires a new epistemology. Our hypothesis is that we can build a system where an anecdote becomes an eyewitness report. A health worker, traditionally seen as a “knowledge recipient” presumed ignorant of climate science, becomes a “knowledge creator”. They know things about local impacts that no one else knows, simply because they are there every day.

In July 2023, Charlotte Mbuh, TGLF’s director who started over a decade ago as a sub-national health worker from Cameroon, stood at COP28 and said:

”What we know, we know because we are here every day. We are already managing the impacts of climate change on health. We are doing the best we can, but we need your support.”

Read Charlotte Mbuh’s full statement at COP28: Climate change is a threat to the health of the communities we serve: health workers speak out at COP28

Turning experience into evidence: the global climate change and health survey

To operationalize this, we built a living laboratory powered by a global human sensor network.

In 2025, in partnership with Grand Challenges Canada and a group of 50 global funders (including Gates, Wellcome, and Rockefeller), we conducted what I have been told is the largest-ever climate and health survey, and the one with the highest level of responses from local communities in the most climate-vulnerable regions

We received responses from 6,436 health workers, primarily from the sub-national level. Because of the trust we have built over years, the Teach to Reach network contributed over 60% of these responses, ensuring we heard from the most climate-vulnerable regions.

https://www.youtube.com/watch?v=C67nYqq-hP0

Most importantly for funders, we asked about barriers to action. The top barriers were not just resource shortages, but structural issues.

Pending their formal publications, I am not yet able to share results.

These findings are signals. They generate hypotheses. Here are three examples of hypotheses grounded in health worker experirences:

• Geh Raphaela Agwa, a midwife from Cameroon, told us: “During this unfavourable weather period, people who can paddle canoes come in and help…”. Could community-led transport solutions improve maternal health access during floods?
• Solace Jewel Morgan, a disease control officer in Ghana, told us: “The dry season… results in dust particles known as harmatan. This leads to a high incidence of respiratory illnesses… encourage… free distribution of personal protective masks.” Could prophylactic mask distribution reduces respiratory morbidity during the harmatan season?
• Victoire Odia, a nurse from the Democratic Republic of Congo (DRC), told us that during extreme weather events, maternity “stays were paid for by the women’s group solidarity fund.” Could micro-financing networks increase facility-based deliveries in climate-vulnerable areas?

Of course, we must distinguish between generating a hypothesis and validating an intervention. We do not claim every local idea is safe or effective immediately. But we do claim that listening is the prerequisite to testing them.

From insight to impact: the Accelerator model for implementation science

We do not just extract data. We give it back to the community to prompt action. Since 2016, we have developed an “Accelerator” system that moves from listening to implementation. It works on a simple rhythm: participants set a specific, practical goal on Monday, and on Friday, they report on what happened, receiving feedback from peers.

This brings us to a critical tension: the balance between context and content. Critics might argue that prioritizing “context over content” carries risks. What if health workers implement unproven or suboptimal strategies? That is a valid concern. However, we see this mechanism not as a way to bypass evidence, but as the most effective tool to operationalize it.

In The Geneva Learning Foundation’s Accelerator, every participant commits to work toward their countries’ goals, and to do so by using the best available global knowledge.

Learn more: What is The Geneva Learning Foundation’s Impact Accelerator?

This actually supports effective adoption and use of global guidelines, which otherwise may linger on shelves.

In fact, we have shown in the past that this mechanism increases adherence to proven protocols (e.g., WHO guidelines on heat stress or malaria control). That is one important reason why it is a powerful implementation science tool. It transforms adherence from a wish expressed in the capital city into a reality in local communities.

Furthermore, if national planners and international experts are willing to listen, they may hear back ways to improve and strengthen the global standards, as well as gain new insights into the “how” of local implementation that defies easy generalization.

When we compared this model to conventional technical assistance or “cascade training,” the results were stark :

These results give us confidence. We are not starting from zero. We are building on prior work in immunization and other areas of work where supporting implementation led to exactly these kinds of validated outcomes.

Here are two examples of local solutions in action.

• Côte d’Ivoire: Communities identified stagnant water as a malaria risk and organized youth-led cleanup committees to clear gutters. This resulted in a drastic, locally measured drop in malaria cases.
• Cameroon: In response to frequent floods, communities voluntarily cleaned gutters to ensure water did not stagnate, directly impacting disease vectors.

No one in the capital city – and certainly no one in Geneva or Seattle – knew about these initiatives.

This leads to our most ambitious projection. If we can grow this network from 80,000 to 1 million health workers by 2030, we estimate we could save 7 million lives through simple, locally resourced projects, at a cost of less than $2 per life.

I acknowledge this is an aggressive claim. It is a “back-of-the-envelope” calculation based on our pilot data. It assumes that local projects remain effective at scale and that we can attribute outcomes to the network. But I ask you: if there is even a glimmer of a chance that this is true – that we can save lives at a fraction of the cost of traditional interventions – isn’t it worth investing in the rigorous research to find out?

Discussion

Do you think MOOCs (Massive Open Online Courses) are dead?

Reda Sadki: MOOCs have become primarily marketing tools for higher education. From a pedagogical perspective, they remain transmissive, expert to learner. I do not see how that model can deliver against complex problems. We need a two-way street. We need new ways to organize the production and circulation of knowledge.

Thank you, Reda. I noticed in your results that food security is a major concern. Have you identified local actions focusing on food, given the challenges of working with healthcare workers who might not see this as their primary remit?

Reda Sadki: That is a critical question. Food insecurity is one of the most worrying consequences we are tracking. We often see a mismatch where local actors tasked with, say, immunization, do not see nutrition as their lane. However, at the community level, the approach is naturally integrated – the health worker knows the vet, who knows the farmers. Those connections exist.

We are currently preparing a major insights report that includes a specific chapter on food security. We are also designing an accelerator specifically around this topic to bring together the right set of partners, because the consequences we are documenting are dire.

You mentioned that 78% of participants eventually said “no thank you” to further support. Ideally, shouldn’t these peer networks become self-sustaining, bypassing Geneva or London entirely?

Reda Sadki: That is the goal. We have shown that more than half of each cohort stays in touch to continue leading local action. However, as long as resources and decision-making power remain concentrated in global centers, we cannot just “flip a switch”. We need to build bridges that facilitate that transformation. The goal is autonomy, but the reality requires us to actively dismantle the dependencies that current funding structures create.

Are there new capabilities that we in academia need to develop urgently to support this?

Reda Sadki: It is about moving away from being the “sage on the stage” to a “guide on the side”. For example, in our recent work, global partners and experts joined Teach to Reach sessions not to present the latest guidelines, but to listen to the challenges local practitioners faced. They then had to figure out how their expertise could be useful in response to those specific needs.

For researchers inside academic institutions, this can be difficult. It requires starting not with a research question, but with a willingness to listen to the needs of local actors and let the research questions emerge from that reality. We know this challenges the incentive structures of academia, but we are open to partnering with researchers willing to work in this emergent, demand-driven way.

It is a fascinating dilemma – we want to be guided by needs, but funding requires pre-set hypotheses. Reda, this has been truly impressive. Thank you for sharing these refreshing perspectives.

Reda Sadki: Thank you. We look forward to exploring how we can collaborate. Best wishes for the holidays and the new year.

References

Images: The Geneva Learning Foundation Collection © 2025

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:

• Download the report, as a comprehensive PDF for detailed reference and sharing;
• Listen to the podcast for an audio summary; or
• Chat with the report using artificial intelligence (AI).

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.

https://youtu.be/-48M_tBMhO8

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”.

#dataUse #Gavi #globalHealth #ImmunizationAgenda2030 #learningCulture #Nigeria #NigeriaImmunizationCollaborative #peerLearning #TeachToReach #TheGenevaLearningFoundation

Artificial intelligence, accountability, and authenticity: knowledge production and power in global health crisis

I know and appreciate Joseph, a Kenyan health leader from Murang’a County, for years of diligent leadership and contributions as a Scholar of The Geneva Learning Foundation (TGLF). Recently, he began submitting AI-generated responses to Teach to Reach Questions that were meant to elicit narratives grounded in his personal experience.

Seemingly unrelated to this, OpenAI just announced plans for specialized AI agents—autonomous systems designed to perform complex cognitive tasks—with pricing ranging from $2,000 monthly for a “high-income knowledge worker” equivalent to $20,000 monthly for “PhD-level” research capabilities.

This is happening at a time when traditional funding structures in global health, development, and humanitarian response face unprecedented volatility.

These developments intersect around fundamental questions of knowledge economics, authenticity, and power in global health contexts.

I want to explore three questions:

• What happens when health professionals in resource-constrained settings experiment with AI technologies within accountability systems that often penalize innovation?
• How might systems claiming to replicate human knowledge work transform the economics and ethics of knowledge production?
• And how should we navigate the tensions between technological adoption and authentic knowledge creation?

Artificial intelligence within punitive accountability structures of global health

For years, Joseph had shared thoughtful, context-rich contributions based on his direct experiences. All of a sudden, he was submitting generic mush with all the trappings of bad generative AI content.

Should we interpret this as disengagement from peer learning?

Given his history of diligence and commitment, I could not dismiss his exploration of AI tools as diminished engagement. Instead, I understood it as an attempt to incorporate new capabilities into his professional repertoire. This was confirmed when I got to chat with him on a WhatsApp call.

Our current Teach to Reach Questions system has not yet incorporated the use of AI. Our “old” system did not provide any way for Joseph to communicate what he was exploring.

Hence, the quality limitations in AI-generated narratives highlight not ethical failings but a developmental process requiring support rather than judgment.

But what does this look like when situated within global health accountability structures?

Health workers frequently operate within highly punitive systems where performance evaluation directly impacts funding decisions. International donors maintain extensive surveillance of program implementation, creating environments where experimentation carries significant risk. When knowledge sharing becomes entangled with performance evaluation, the incentives for transparency about AI “co-working” (i.e., collaboration between human and AI in work) diminish dramatically.

Seen through this lens, the question becomes not whether to prohibit AI-generated contributions but how to create environments where practitioners can explore technological capabilities without fear that disclosure will lead to automatic devaluation of their knowledge, regardless of its substantive quality. This heavily depends on the learning culture, which remains largely ignored or dismissed in global health.

The transparency paradox: disclosure and devaluation of artificial intelligence in global health

This case illustrates what might be called the “transparency paradox”—when disclosure or recognition of AI contribution triggers automatic devaluation regardless of substantive quality. Current attitudes create a problematic binary: acknowledge AI assistance and have contributions dismissed regardless of quality, or withhold disclosure and risk accusations of misrepresentation or worse.

This paradox creates perverse incentives against transparency, particularly in contexts where knowledge production undergoes intensive evaluation linked to resource allocation. The global health sector’s evaluation systems often emphasize compliance over innovation, creating additional barriers to technological experimentation. When every submission potentially affects funding decisions, incentives for technological experimentation become entangled with accountability pressures.

This dynamic particularly affects practitioners in Global South contexts, who face more intense scrutiny while having less institutional protection for experimentation. The punitive nature of global health accountability systems deserves particular emphasis. Health workers operate within hierarchical structures where performance is consistently monitored by both national governments and international donors. Surveillance extends from quantitative indicators to qualitative assessments of knowledge and practice.

In environments where funding depends on demonstrating certain types of knowledge or outcomes, the incentive to leverage artificial intelligence in global health may conflict with values of authenticity and transparency. This surveillance culture creates uniquely challenging conditions for technological experimentation. When performance evaluation drives resource allocation decisions, health workers face considerable risk in acknowledging technological assistance—even as they face pressure to incorporate emerging technologies into their practice.

The economics of knowledge in global health contexts

OpenAI’s announced “agents” represent a substantial evolution beyond simple chatbots or language models. If they are able to deliver what they just announced, these specialized systems would autonomously perform complex tasks simulating the cognitive work of highly-skilled professionals. The most expensive tier, priced at $20,000 monthly, purportedly offers “PhD-level” research capabilities, working continuously without the limitations of human scheduling or attention.

These claims, while unproven, suggest a potential future where knowledge work economics fundamentally change. For global health organizations operating in Geneva, where even a basic intern position for a recent master’s degree graduate cost more than 200 times that of a ChatGPT subscription, the economic proposition of systems working 24/7 for potentially comparable costs merits careful examination.

However, the global health sector has historically operated with significant labor stratification, where personnel in Global North institutions command substantially higher compensation than those working in Global South contexts. Local health workers often provide critical knowledge at compensation rates far below those of international consultants or staff at Northern institutions. This creates a different economic equation than suggested by Geneva-based comparisons. Many organizations have long relied on substantially lower local labor costs, often justified through capacity-building narratives that mask underlying power asymmetries.

Given this history, the risk that artificial intelligence in global health would replace local knowledge workers might initially appear questionable. Furthermore, the sector has demonstrated considerable resistance to technological adoption, particularly when it might disrupt established operational patterns. However, this analysis overlooks how economic pressures interact with technological change during periods of significant disruption.

The recent decisions of many government to donors to suddenly and drastically cut funding and shut down programs illustrates how rapidly even established funding structures can collapse. In such environments, organizations face existential questions about maintaining operational capacity, potentially creating conditions where technological substitution becomes more attractive despite institutional resistance.

A new AI divide

ChatGPT and other generative AI tools were initially “geo-locked”, making them more difficult to access from outside Europe and North America.

Now, the stratified pricing structure of OpenAI’s announced agents raises profound equity concerns. With the most sophisticated capabilities reserved for those able to pay high costs for the most capable agents, we face the potential emergence of an “AI divide” that threatens to reinforce existing knowledge power imbalances.

This divide presents particular challenges for global health organizations working across diverse contexts. If advanced AI capabilities remain the exclusive province of Northern institutions while Southern partners operate with limited or no AI augmentation, how might this affect knowledge dynamics already characterized by significant inequities?

The AI divide extends beyond simple access to include quality differentials in available systems. Even as simple AI tools become widely available, sophisticated capabilities that genuinely enhance knowledge work may remain concentrated within well-resourced institutions. This could lead to a scenario where practitioners in resource-constrained settings use rudimentary AI tools that produce low-quality outputs, further reinforcing perceptions of capability gaps between North and South.

Confronting power dynamics in AI integration

Traditional knowledge systems in global health position expertise in academic and institutional centers, with information flowing outward to practitioners who implement standardized solutions. This existing structure reflects and reinforces global power imbalances. 

The integration of AI within these systems could either exacerbate these inequities—by further concentrating knowledge production capabilities within well-resourced institutions—or potentially disrupt them by enabling more distributed knowledge creation processes.

Joseph’s journey demonstrates this tension. His adoption of AI tools might be viewed as an attempt to access capabilities otherwise reserved for those with greater institutional resources. The question becomes not whether to allow such adoption, but how to ensure it serves genuine knowledge democratization rather than simply producing more sophisticated simulations of participation.

These emerging dynamics require us to fundamentally rethink how knowledge is valued, created, and shared within global health networks. The transparency paradox, economic pressures, and emerging AI divide suggest that technological integration will not occur within neutral space but rather within contexts already characterized by significant power asymmetries.

Developing effective responses requires moving beyond simple prescriptions about AI adoption toward deeper analysis of how these technologies interact with existing power structures—and how they might be intentionally directed toward either reinforcing or transforming these structures.

My framework for Artificial Intelligence as co-worker to support networked learning and local action is intended to contribute to such efforts.

Illustration: The Geneva Learning Foundation Collection © 2025

References

Frehywot, S., Vovides, Y., 2024. Contextualizing algorithmic literacy framework for global health workforce education. AIH 0, 4903. https://doi.org/10.36922/aih.4903

Hazarika, I., 2020. Artificial intelligence: opportunities and implications for the health workforce. International Health 12, 241–245. https://doi.org/10.1093/inthealth/ihaa007

John, A., Newton-Lewis, T., Srinivasan, S., 2019. Means, Motives and Opportunity: determinants of community health worker performance. BMJ Glob Health 4, e001790. https://doi.org/10.1136/bmjgh-2019-001790

Newton-Lewis, T., Munar, W., Chanturidze, T., 2021. Performance management in complex adaptive systems: a conceptual framework for health systems. BMJ Glob Health 6, e005582. https://doi.org/10.1136/bmjgh-2021-005582

Newton-Lewis, T., Nanda, P., 2021. Problematic problem diagnostics: why digital health interventions for community health workers do not always achieve their desired impact. BMJ Glob Health 6, e005942. https://doi.org/10.1136/bmjgh-2021-005942

Artificial Intelligence and the health workforce: Perspectives from medical associations on AI in health (OECD Artificial Intelligence Papers No. 28), 2024. , OECD Artificial Intelligence Papers. https://doi.org/10.1787/9a31d8af-en

Sadki, R. (2025). A global health framework for Artificial Intelligence as co-worker to support networked learning and local action. Reda Sadki. https://doi.org/10.59350/gr56c-cdd51

#accountability #accountabilityOverloads #ArtificialIntelligence #compliance #conservatism #globalHealth #healthWorkers #HRH #incentives #innovation #learningCulture #performanceMonitoring #TeachToReach

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.

https://youtu.be/-rRvRyVqy_4

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:

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.

#AIPodcast #ImmunizationAgenda2030 #India #ISAI #learningCulture #peerLearning #TeachToReach #TheGenevaLearningFoundation

HPV vaccination: New learning and leadership to bridge the gap between planning and implementation

This article is based on my presentation about HPV vaccination at the 2nd National Conference on Adult Immunization and Allied Medicine of the Indian Society for Adult Immunization (ISAI), Science City, Kolkata, on 15 February 2025.

https://www.youtube.com/watch?v=R1JO4ySzgzo

The HPV vaccination implementation challenge

The global landscape of HPV vaccination and cervical cancer prevention reveals a mix of progress and persistent challenges. While 144 countries have introduced HPV vaccines nationally and vaccination has shown remarkable efficacy in reducing cervical cancer incidence, significant disparities persist, particularly in low- and middle-income countries.

Evidence suggests that challenges in implementing and sustaining HPV vaccination programs in developing countries are significantly influenced by gaps between planning at national level and execution at local levels. Multiple studies confirm this disconnect as a primary barrier to effective HPV vaccination programmes.

Traditional approaches to knowledge development in global health often rely on expert committee models characterized by hierarchical knowledge flows, formal meeting processes, and bounded timelines. While these approaches offer strengths like high academic rigor and systematic review, they frequently miss frontline insights, develop slowly, and produce static outputs that may be difficult to translate effectively into action.

How the peer learning network alternative can support HPV vaccination

At The Geneva Learning Foundation (TGLF), we have developed a complementary model—one that values the collective intelligence of frontline health workers and creates structured opportunities for their insights to inform policy and practice. This peer learning network model features:

• Large, diverse networks with multi-directional knowledge flow
• Open participation and flexible engagement
• Direct field experience and implementation insights
• Iterative development through experience sharing
• Continuous refinement and living knowledge

This approach captures practical knowledge, enables rapid learning cycles, preserves context, and brings together multiple perspectives in a dynamic process that continuously updates as new information emerges.

HPV vaccination: the peer learning cycle in action

To address HPV vaccination challenges, we implemented a structured five-stage cycle that connected frontline experiences with policy decisions:

This process uniquely values the practical wisdom that emerges from implementation experience. Rather than assuming solutions flow from the top down, we recognize that those doing the work often develop the most effective approaches to complex challenges.

Teach to Reach: Building a learning community for HPV vaccination

Our Teach to Reach programme serves as the hub for this peer learning approach. Since its inception, the community has grown steadily since January 2021 to reach over 24,000 members by December 2024. The participants reflect remarkable diversity.

This diversity of contexts and experiences creates a rich environment for learning. The programme demonstrates significant impact on participants’ professional capabilities—compared to global baselines, Teach to Reach participants show:

• 45% stronger worldview change
• 41% greater impact on professional practice
• 49% higher professional influence

7 insights about HPV vaccination from peer learning at Teach to Reach

Through this process, we uncovered several important implementation insights:

1. Importance of connecting field experience to policy

• Each stage deepened understanding of implementation challenges
• We observed progression from tactical to strategic considerations
• Growing recognition of systemic factors emerged
• Evolution from individual to institutional solutions became apparent
• Value of structured knowledge sharing across levels was demonstrated

2. Implementation learning

• Success requires multi-stakeholder engagement
• Sustained communication proves more effective than one-time campaigns
• School systems provide critical implementation platforms
• Community leadership is essential for acceptance
• Integration with other services increases efficiency
• Local adaptation is key to successful implementation

3. Unexpected implementation findings

• Tribal communities often showed less vaccine hesitancy than urban areas
• Teachers emerged as more influential than health workers in some contexts
• Personal stories proved more persuasive than statistical evidence
• Integration with COVID-19 vaccination improved HPV acceptance
• Social media played both positive and negative roles
• School-based programs sometimes reached out-of-school children

4. Counter-intuitive success factors

• Less formal settings often produced better results
• Simple communication strategies outperformed complex ones
• Male community leaders became strong vaccination advocates
• Religious institutions provided unexpected support
• Health worker vaccination of own children became powerful tool
• Community dialogue proved more effective than expert presentations

5. Unexpected challenges

• Urban areas sometimes showed more resistance than rural areas
• Education level did not correlate with vaccine acceptance
• Health workers themselves sometimes showed hesitancy
• Traditional media was less influential than anticipated
• Formal authority figures were not always the most effective advocates
• Technical knowledge proved less important than communication skills

6. Examples of novel solutions

• Using cancer survivors as advocates
• WhatsApp groups for community health workers
• School children as messengers to families
• Integration with existing women’s groups
• Leveraging religious texts and teachings
• Community theater and storytelling approaches

System-level surprises

• Success was often independent of resource levels
• Informal networks proved more important than formal ones
• Bottom-up strategies were more effective than top-down approaches
• Social factors were more influential than technical ones
• Local adaptation was more important than standardization
• Peer influence was more powerful than expert authority

In some cases, these findings challenge many conventional assumptions about HPV vaccination programmes. In all cases, they highlight the importance of local knowledge, social factors, and adaptation over standardized approaches based solely on technical expertise.

The power of health worker collective intelligence

Our approach demonstrates the value of health worker collective intelligence in improving performance:

• High-quality data and situational intelligence from our network of 60,000+ health workers provides rapid insights
• Field observations on changing disease patterns and resistance can be quickly collected
• Climate change impacts can be tracked through frontline reports
• The TGLF Insights Unit packages this intelligence into knowledge to inform practice and policy

This represents a fundamental shift from assuming expert committees have all the answers to recognizing the distributed expertise that exists throughout health systems.

Continuous learning: The key to improvement

In fact, previous TGLF research has demonstrated that continuous learning is often the “Achilles’ heel” in immunization programs. Common issues include:

In 2020 and 2022, we conducted large-scale measurements of learning culture of more than 10,000 immunization professionals in low- and middle-income countries. The data showed that ‘learning culture’ (a measure of the capacity for change) correlated more strongly with perceived programme performance than individual motivation did. This challenges the common assumption that poor motivation is the root cause of poor performance.

These findings help zero in on six ways to strengthen continuous learning to drive HPV vaccination:

Impact and benefits of peer learning

This approach delivers multiple benefits:

• Frontline workers gain broader perspective
• National planners access grounded insights
• Practical solutions spread more quickly
• Policy decisions are informed by field experience
• Continuous improvement cycle gets established

Key success factors include:

• Scale that enables diverse input collection
• Structure that supports quality knowledge creation
• Regular rhythm that maintains engagement
• Multiple levels of review that ensure relevance
• Clear pathways from insight to action

How can we interpret these findings?

This model generates implementation-focused evidence that complements rather than competes with traditional epidemiological data. 

The findings emerge from a structured methodology that includes initial experience collection at scale, synthesis and analysis, knowledge deepening through case studies, national-level review by EPI planners from 31 countries, and systematic knowledge mobilization. This approach provides rigor and scale that elevate these observations beyond mere anecdotes.

For epidemiologists who become uncomfortable when evidence is not purely quantitative, it is important to understand that structured peer learning fills a critical gap in implementation science by capturing what quantitative studies often miss: the contextual factors and practical adaptations that determine programme success or failure in real-world settings.

When implementers report across different contexts that tribal communities show less vaccine hesitancy than urban areas, or that teachers emerge as more influential than health workers in specific settings, these patterns represent valuable implementation intelligence.

Such insights also help explain why interventions that appear effective in controlled studies often fail to deliver similar results when implemented at scale.

In fact, these findings address precisely what quantitative studies struggle to capture: why education level does not reliably predict vaccine acceptance; why some resource-constrained settings outperform better-resourced ones; how informal networks frequently prove more effective than formal structures; and which communication approaches actually drive behavior change in specific populations.

For programme planners, this knowledge bridges the gap between general guidance (“engage community leaders”) and actionable specifics (“male community leaders became particularly effective advocates when engaged through these specific approaches”). 

Accelerating HPV vaccination progress

To make significant progress on HPV vaccination as part of the Immunization Agenda 2030’s Strategic Priority 4 (life-course and integration), we encourage global health stakeholders to:

By combining expert knowledge with the practical wisdom of thousands of implementers, we can develop more effective strategies for HPV vaccination that bridge the gap between planning and execution.

This peer learning network approach does not replace expertise—it enhances and grounds it in the realities of implementation.

It recognizes that the frontline health worker in a remote village may hold insights just as valuable as those of a technical expert in a capital city.

By creating structures that enable these insights to emerge and connect, we can accelerate progress on HPV vaccination and other public health challenges.

Acknowledgements

I wish to thank ISAI’s Dr Saurabh Kole and his colleagues for their kind invitation. I also wish to recognize and appreciate Charlotte Mbuh and Ian Jones for their invaluable contributions to the Foundation’s work on HPV vaccination, and Dr Satabdi Mitra for her tireless leadership and boundless commitment. Last but not least, I wish to thank the thousands of health workers who contributed their experiences before, during, and after successive Teach to Reach peer learning events. What little I know comes from their collective intelligence, action, and wisdom.

References

Dorji, T. et al. (2021) ‘Human papillomavirus vaccination uptake in low-and middle-income countries: a meta-analysis’, EClinicalMedicine, 34, p. 100836. Available at: https://doi.org/10.1016/j.eclinm.2021.100836.

Faye, W. et al. (2023) IA2030 Case study 18. Wasnam Faye. Vaccine angels – Give us the opportunity and we can perform miracles. The Geneva Learning Foundation. Immunization Agenda 2030 Case study 18. Available at: https://doi.org/10.5281/ZENODO.7785244.

Gonçalves, I.M.B. et al. (2020) ‘HPV Vaccination in Young Girls from Developing Countries: What Are the Barriers for Its Implementation? A Systematic Review’, Health, 12(06), pp. 671–693. Available at: https://doi.org/10.4236/health.2020.126050.

Jones, I. et al. (2024) Making connections at Teach to Reach 8 (IA2030 Listening and Learning Report 6). Available at: https://doi.org/10.5281/ZENODO.8398550.

Jones, I. et al. (2022) IA2030 Case Study 7. Motivation, learning culture and programme performance. The Geneva Learning Foundation. Available at: https://doi.org/10.5281/ZENODO.7004304.

Kutz, J.-M. et al. (2023) ‘Barriers and facilitators of HPV vaccination in sub-saharan Africa: a systematic review’, BMC Public Health, 23(1), p. 974. Available at: https://doi.org/10.1186/s12889-023-15842-1.

Moore, K. et al. (2022) Overcoming barriers to vaccine acceptance in the community: Key learning from the experiences of 734 frontline health workers. The Geneva Learning Foundation. Available at: https://doi.org/10.5281/ZENODO.6965355.

Umbelino-Walker, I. et al. (2024) ‘Towards a sustainable model for a digital learning network in support of the Immunization Agenda 2030 –a mixed methods study with a transdisciplinary component’, PLOS Global Public Health. Edited by M. Pentecost, 4(12), p. e0003855. Available at: https://doi.org/10.1371/journal.pgph.0003855.

Watkins, K.E. et al. (2022) ‘Accelerating problem-solving capacities of sub-national public health professionals: an evaluation of a digital immunization training intervention’, BMC Health Services Research, 22(1), p. 736. Available at: https://doi.org/10.1186/s12913-022-08138-4.

Wigle, J., Coast, E. and Watson-Jones, D. (2013) ‘Human papillomavirus (HPV) vaccine implementation in low and middle-income countries (LMICs): Health system experiences and prospects’, Vaccine, 31(37), pp. 3811–3817. Available at: https://doi.org/10.1016/j.vaccine.2013.06.016.

#2ndNationalConferenceOnAdultImmunizationAndAlliedMedicineOfTheIndianSocietyForAdultImmunization #epistemology #globalHealth #IndianSocietyForAdultImmunization #ISAI #peerLearning #peerLearningCycle #TeachToReach

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

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

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

Global partnership empowers malaria prevention health leaders

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

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

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

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

Voir la version française de cet événement

https://youtu.be/d88wfnPOWnY

Community health leaders report prevention challenges

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

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

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

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

Leaders shared various approaches to medicine and supply shortages.

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

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

What are barriers to access?

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

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

How is climate change affecting malaria patterns?

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

What is the value of community engagement?

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

How do health workers cope personally with malaria?

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

What is the value of learning across geographic borders?

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

What’s next for health leaders?

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

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

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

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

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

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#AntonioPizzuto #globalHealth #leadership #malaria #RBMPartnershipToEndMalaria #REACH #TeachToReach