Introduction to the World Health Summit (WHS)
The World Health Summit (WHS) is a premier international platform that recognizes health and good governance as fundamental human rights—firmly rooted in the understanding that human health is deeply shaped by political choices. It brings together diverse disciplines and voices from civil society around the globe to work collaboratively toward building a healthier future. This is pursued by fostering dialogue and encouraging the exchange of innovative, context-driven solutions to pressing global health challenges, all anchored in the principles of the United Nations Sustainable Development Goals (SDGs).
The overarching theme of the 2025 Regional Meeting in New Delhi focused on health equity, systemic transformation, and cross-sectoral collaboration. I attended this gathering as a researcher working in the field of maternal and child health, motivated by a personal and professional interest in understanding how research can actively contribute to enhancing access to healthcare and improving its utilization on the ground.
I attended this conference as a Banyan Impact Fellow, supported by Professional Development Grant offered through the Fellowship.
Overview of WHS Sessions — And Why This One Caught My Eye
The Summit featured a wide range of sessions exploring various facets of global health. These included discussions on the intersection of climate and health, pandemic preparedness, financing for Universal Health Coverage, food systems and nutrition, and digital innovation in healthcare.
Among this rich array of sessions, one stood out to me: “Bridging the Gap Between Research and Policy in South Asia.” Organized by Campbell South Asia, this session captured my attention because, unlike many others that focused on structural reform or global frameworks, this one zoomed in on the “execution gap”—the space where most research evidence gets lost in translation.
The panel featured Mary Tokhana (WHO New Delhi Office), Dr. Manju Rani (WHO SEARO), Dr. Anju Sinha (Cochrane India Network), and Bianca Pilla (JBI), Bhumika (Campbell South Asia). Together, they explored the often-overlooked “middle space” between knowledge generation and practical application in the form of policy or programs. The session highlighted how the lack of timely, accessible, and synthesized evidence often leaves policymakers and implementers struggling to make informed decisions—ultimately stalling progress on health outcomes and inclusion.
The discussion also addressed the potential of tools like systematic reviews and evidence gap maps to support evidence-informed policymaking. Most importantly, the session aimed to identify practical strategies to close the gap between research, policy, and implementation, ensuring that evidence leads to real-world impact.
Speakers and Key Themes from the Session
Mary Tokhana (WHO New Delhi Office)
Mary emphasized the fragmented state of research capacity and synthesis ecosystems across South-East Asia. She introduced a tiered framework used by WHO to support countries based on their existing capabilities:
- Level 1 – Countries with emerging research capacity: WHO offers online training modules to build foundational skills.
- Level 2 – Countries with growing synthesis capacity: WHO facilitates coalitions and knowledge brokering between researchers and policy actors.
- Level 3 – Countries with implementation capacity: WHO provides evidence-based policy guidance to drive decisions.
- Level 4 – Countries with strong community engagement: WHO focuses on enabling feedback loops between communities, ministries, and researchers to improve future knowledge production.
This model underscored the need to tailor capacity-building to a country’s specific stage in the research-to-policy continuum.
Bhumika (Campbell South Asia)
Bhumika offered a historical perspective on the evolving relationship between research and policy:
- In the 1990s, the focus was on the “Results Agenda”—measuring inputs and tracking outputs.
- By the 2000s, there was a surge in impact evaluations, stressing the importance of testing assumptions using real-world data.
- In 2008, systematic reviews emerged to answer: What works? Where? And for whom?
- Today, we’re entering a phase of knowledge brokering—with growing use of AI and big data to make evidence generation faster and more responsive.
She also pointed to a stark and sobering statistic: less than 0.5% of public funding goes toward evaluating “what works and how.” This underinvestment, she argued, is a key barrier to translating knowledge into impact—especially in social sectors beyond health and defense.
Bianca Pilla (JBI)
Bianca drew a sharp distinction between communication and knowledge translation:
- Communication, she argued, is not just about simplifying jargon. It is about building trust and tailoring messages to resonate with your audience’s context, needs, and lived realities.
- Knowledge translation, on the other hand, involves strategically packaging and sharing findings so they are accessible, actionable, and timely—particularly for policy and program stakeholders.
She emphasized that different audiences require different mediums:
- Policymakers may prefer briefs, slide decks, or decision-support tools.
- Civil society actors might respond better to blogs, editorial articles, or visual storytelling.
- Community health workers may benefit more from training materials, summaries in local languages, or WhatsApp explainers.
Bianca’s message was clear: Effective translation is as much about empathy and adaptability as it is about rigor.
Diagnostic Framework: The Real Game-Changer
Dr. Manju Rani (WHO SEARO, Regional Advisor – R&D) presented the core diagnostic framework on translating research into policy and public goods. She argued that evidence does not automatically lead to action – it requires specific interventions at different bottlenecks.
The Two-Step Model of Translation
Dr. Rani introduced a deceptively simple framework: Research must undergo two transformations before it can improve lives.
- Step 1: Research must be translated into interventions — in the form of products (like drugs or diagnostic tools), policies (like insurance models), or practices (like clinical protocols).
- Step 2: These interventions must then be translated into public goods — accessible, affordable, acceptable, and of sufficient quality for widespread impact.
This framework made immediate sense. It also made me realize how many health innovations stall after Step 1. They’re proven, documented, even policy-endorsed — but never reach the people they were meant for.
Where Things Break Down
To understand why, Dr. Rani offered something extraordinary: a diagnostic flowchart to analyze where translation fails. This was not a theoretical model. It was a practical tool — a triage system for identifying what kind of intervention is needed to get evidence into action.
Let us say we have a new drug that has been proven effective. Why might it still not help people?
- No product available? That is an availability issue. We need IP reform, licensing support, or investment to bring it to market.
- Too expensive? That is an affordability issue. Financing, subsidies, or price regulations might help.
- Affordable but not reaching people? That is an accessibility issue. Logistics, supply chains, or distribution networks are the bottleneck.
- Accessible but not used? That is an acceptability issue. People might distrust it, find it culturally incompatible, or question its quality.
- Even if accepted, still not scaled? That is a delivery issue — requiring systemic strengthening and long-term implementation capacity.
Each of these failures is qualitatively different. And so is the intervention needed to fix it.
What This Reforming Achieves
This model reframed my entire understanding of evidence-to-impact work. It treats translation not as a straight line but as a clinical diagnosis, where different symptoms point to different remedies. It moves us beyond the vague call to “scale things up” and forces us to ask what exactly is broken — and who needs to fix it.
For policymakers, this tool is gold. For researchers, it’s a wake-up call.
Because it also asks a more uncomfortable question: Where does a researcher’s role end?
What This Means for Me — and My Work
I returned to this session thinking about my current research on low birth weight among tribal populations in Jharkhand, under the MANSI initiative supported by the Tata Steel Foundation.
Until now, I’ve been thinking of this project to identify determinants, quantify risks, and maybe produce a policy brief. But now I am asking more pointed questions:
- Which bottleneck is my research exposing?
– Is it accessibility? Are services there but unused?
– Is it affordability? Are women skipping care due to cost?
– Is it acceptability? Is there mistrust toward formal health systems? - What intervention type does my research suggest — and who in the system is best placed to act on it?
- Can I present my findings in a format that matches the decision-making ecosystem — not just in academic language, but through briefs, visuals, presentations, and conversations?
- Most importantly, can I ensure that my research supports and strengthens the existing ecosystem — rather than just evaluating it?
Closing Thoughts
This entire session reminded me that research is not finished when the data is analyzed. It’s finished when it travels — to the ASHA worker, to the program manager, to the policymaker who needs to make a hard decision under resource constraints.
