Increasing Effectiveness and Equity in Strengthening Health Research Capacity Using Data and Metrics: Recent Advances of the ESSENCE Mechanism

ESSENCE is a forum of funders coordinated by WHO/TDR to strengthen health research capacity in LMICs. Following the 2018 Money and Microbes report recommending clinical research capacity as essential for pandemic preparedness, the ESSENCE Working Group on Review of Investments was formed to coordinate and align funders using shared data sources (WHO Global Observatory on Health R&D and NIH World RePORT). The group aims to increase research on national priorities, improve pandemic preparedness, and reduce the number of countries with limited research capacity. By 2020, the group developed basic metrics of national research capacity, assessed coordination models, and conducted deeper assessments in eight countries. This article summarizes the November 1–2, 2021 virtual meeting with 100+ global participants, highlighting visions for coordination, data and metrics development, and approaches to improve collaboration and equity in capacity strengthening.

The paper situates its work within existing frameworks and critiques of metrics. It notes that while metrics can guide planning and resource allocation, they may oversimplify complex health research systems and reflect political choices about what is measured. Prior work mapped health R&D indicators in Africa, revealing mixed performance and gaps due to missing data, and highlighted risks that facile global indicators can overshadow local, context-specific knowledge. Drawing on Pang’s conceptualization of national health research systems, an empirically informed framework from LSE and African partners emphasizes four pillars—governance, financing, creating and sustaining resources, and producing and using knowledge—along with processes like research leadership, advocacy, regulatory environment, alignment and prioritization, partnerships, and innovation. Studies report substantial growth in African research outputs, with disparities by language regions and strong relationships to GDP and number of postgraduate training institutions. Evaluations of initiatives such as SACORE and MEPI show achievements and challenges, especially around sustainability and dependence on foreign funding. These bodies of work inform the paper’s emphasis on comprehensive, context-sensitive metrics and equitable, country-led capacity strengthening.

The Working Group developed a basic national health research capacity metric using three publicly available indicators for each country (population >100,000; N=180), averaged over 2018–2020: (1) number of clinical trials in WHO ICTRP; (2) number of project records in NIH World RePORT; and (3) number of publications with at least one author affiliation in the country from Scopus. For each indicator, country rank percentiles were calculated and averaged to yield an aggregate capacity metric. Univariate analyses examined distributions across regions and income groups. Kendall’s Tau tests assessed correlations among indicators and between the aggregate metric and selected country sociodemographic variables (GDP, population, disability-adjusted life years per capita, Human Development Index, GDP per capita). In parallel, the team conducted qualitative and descriptive synthesis of coordination models and performed deeper country-level assessments (eight countries) to characterize capacity and identify coordination opportunities. The article also synthesizes proceedings of a two-day virtual meeting (keynotes, presentations, and discussions) to contextualize metric development and coordination strategies.

- Indicators showed highly skewed distributions across 180 countries and strong positive correlations among the three constituent indicators (Kendall’s tau ≈ 0.60–0.78), indicating internal consistency of the metric set. - The aggregate metric correlated moderately to strongly with national characteristics: GDP (tau = 0.78), total population (tau = 0.56), DALYs per capita (tau = -0.34), Human Development Index (tau = 0.31), and GDP per capita (tau = 0.25). - Larger and higher-income countries generally had greater measured research capacity, yet several smaller and lower-income countries exhibited relatively strong capacity, suggesting transferable lessons from outliers. - WHO Global Observatory on Health R&D is working to establish harmonized core indicators for national health research systems with regular reporting; NIH World RePORT provides open data on >700,000 projects from 14 funders across 26,000+ institutions in 187 countries. - There is no current global framework integrating R&D into core pandemic preparedness assessments (IHR, JEE, GHSA); GHSA launched an R&D Task Force (2021) to link R&D capacity building with health security targets, develop road maps, and identify bottlenecks. - Best practices for sustainable capacity strengthening include: research support centers (including grant/financial management); equitable North–South and South–South partnerships; comprehensive training in research methods, writing, and laboratory skills; triangular mentorship networks; regular scientific meetings; diversified funding with increased domestic investment; country-led agendas; community engagement; and data-/milestone-driven M&E. - Regional/national examples: • West Indies: SUNY–UWI consortium built capacity in emerging infectious diseases with NIH Fogarty-supported GIDRTP, training scholars and establishing Global Virus Network Affiliate Centers; partnerships with Rush University and Abbott Pandemic Defense Coalition; model replicated in oncology and NCDs. • West and Central Africa: MARCAD (under DELTAS Africa) strengthened leadership, training, management, infrastructure, collaboration, and community engagement; documented improvements in malaria control strategies and outcomes (e.g., Senegal, The Gambia); emphasized sustainability and domestic funding. • Bangladesh: Active research publication culture but fragmented, individual-focused training; limited institutional capacity development and lack of a national policy/guideline for systematic research capacity; calls for a ministry-led national strategy with infrastructure upgrades, research administration, training of trainers, budgeting, and M&E integrated into national plans. - Overall conclusion: Data- and metric-driven, coordinated, equitable approaches with strong local leadership can enhance national health systems and global pandemic preparedness.

The findings support the hypothesis that coordinated, data-driven investment strategies can improve the effectiveness and equity of health research capacity strengthening. The strong correlations among simple, publicly available indicators suggest a pragmatic starting point for prioritizing investments where needs are greatest. Identifying outliers with strong capacity despite limited resources highlights opportunities to learn context-specific strategies. Institutional developments (WHO Observatory indicators; GHSA R&D Task Force) provide pathways to embed R&D capacity into broader health security agendas. Best practices distilled from African and other regional experiences underscore the centrality of local leadership, equitable partnerships, sustainable financing, and comprehensive training and support ecosystems. Together, these insights guide funders and national stakeholders toward targeted, collaborative actions that align with national priorities while bolstering global preparedness.

The paper advances a practical framework for using publicly available metrics to inform equitable, coordinated investments in health research capacity, demonstrates internal consistency of these metrics, and integrates lessons from diverse regional initiatives. It calls for embedding R&D capacity within global health security frameworks, expanding harmonized indicator sets, and prioritizing local leadership and ownership. Future work should refine and validate indicators of research preparedness beyond basic metrics, strengthen data completeness and quality, deepen country-led assessments, and secure sustainable domestic funding to maintain gains and reduce dependency on external donors.

- The capacity metric is intentionally basic and may not capture qualitative aspects of national health research systems or context-specific priorities. - Metrics can be political and risk oversimplifying complex systems; choices about what and how to measure may bias interpretations. - Data gaps and mixed indicator performance (notably in parts of Africa) limit completeness and comparability. - Skewed distributions and strong associations with GDP and population may obscure nuanced capacity differences. - Sustainability concerns persist for capacity-building programs reliant on foreign funding. - The article synthesizes a meeting’s presentations and discussions, which may introduce selection or reporting biases and limited generalizability.