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

The ESSENCE on Health Research initiative, coordinated by the WHO's TDR, is a forum for funders of health research capacity strengthening in LMICs. Following the World Bank and CEPI's *Money and Microbes* report, which highlighted the importance of clinical research capacity in pandemic preparedness, the ESSENCE Working Group on Review of Investments was established to improve coordination and collaboration among funders. The group, comprising diverse members geographically, by income level, and sector, uses data from WHO's Global Observatory on Health R&D and NIH's World RePORT to guide activities, aiming for increased effectiveness, equity, and reduced duplication. The overall goal is to increase research on national health priorities, improve pandemic preparedness, and reduce the number of countries with limited research capacity. By 2020, the group had developed basic metrics for national health research capacity, assessed coordination models, and conducted in-depth analyses of eight countries to identify coordination opportunities. This article summarizes the findings of their 2021 virtual meeting, which included presentations from Dr. Soumya Swaminathan (WHO Chief Scientist) and Dr. Jean Nachega, focusing on improving collaboration and coordination among funders and stakeholders.

The introduction cites the *Money and Microbes* report (International Vaccines Task Force, 2018) as a catalyst for the Working Group's formation, emphasizing the need for clinical research capacity in pandemic preparedness. It also mentions the WHO Global Observatory on Health R&D and NIH World RePORT as key data sources, along with previous work by the Working Group (Kilmarx et al., 2020) on a mechanism for reviewing investments in health research capacity strengthening. The paper later references various studies and reports related to health research capacity in Africa (Wenham et al., 2021; Mijumbi-Deve et al., 2021; Jones et al., 2021; Nachega et al., 2012), highlighting the complexities of measuring health research systems and the importance of context-specific knowledge. The limitations of using simple metrics are discussed, referencing critiques of using metrics like the number of patents (Katila, 2002; Krieger, 1992).

The methodology involved developing a basic set of metrics for national health research capacity using three indicators: the number of clinical trials registered in the WHO ICTRP, the number of research activities in the NIH World RePORT database, and the number of publications with author affiliations in Scopus. These were averaged from 2018-2020 for all countries with populations greater than 100,000 (N=180). Univariate analyses were conducted to understand the distribution of research capacity across countries, and correlations were analyzed among the three indicators (using Kendall's Tau) and with sociodemographic indicators (GDP, population, disability-adjusted life years, Human Development Index, GDP per capita). The paper also describes the involvement of WHO's Global Observatory on Health R&D and NIH's World RePORT in data provision. Qualitative research is mentioned, drawing from a study by Jones et al. (2021) using qualitative interviews to develop an empirically informed framework for strengthening national health research systems from a systems perspective, incorporating four pillars: governance, financing, creating and sustaining resources, and producing and using knowledge. Finally, the paper presents case studies of capacity strengthening efforts in the West Indies, West and Central Africa, and Bangladesh.

Analysis of the ESSENCE metrics revealed skewed distributions of health research capacity across countries, with variations by geographic region and income group. Strong positive correlations were found among the three indicators, suggesting good internal consistency. Moderate to strong correlations were also observed between the aggregate metric and GDP, total population, and other sociodemographic factors. However, the analysis also identified several smaller, lower-income countries with good research capacity, suggesting potential for learning and replication. The WHO Global Observatory on Health R&D and NIH World RePORT were identified as key data sources for the metrics. The analysis highlighted the complexities of measuring health research systems and the importance of context-specific knowledge. Case studies showed success in capacity building using various strategies in different settings: the University of the West Indies collaboration with SUNY, the MARCAD program in West and Central Africa (under the DELTAS Africa initiative), and efforts in Bangladesh. Best practices identified included establishing research support centers, South-South partnerships, training programs, mentorship networks, annual scientific meetings, and diversifying funding sources. The COVID-19 pandemic highlighted both weaknesses and strengths in global health research systems, emphasizing the need for improved coordination and strengthening of research capacity in LMICs.

The findings demonstrate the feasibility of creating relatively simple metrics for assessing country-level health research capacity using publicly available data. These metrics can guide funders and national health authorities in planning and implementing effective initiatives. The discussion emphasizes the need to balance the use of metrics with an understanding of the complex nature of health research systems and the importance of local context. The case studies highlight successful strategies for capacity building, emphasizing the roles of local leadership, partnerships, and diversified funding sources. The COVID-19 pandemic underscores the critical need for global health research capacity strengthening and improved coordination among funders.

The study concludes that a data- and metric-driven approach to health research capacity strengthening, emphasizing coordination among funders, local leadership, and equitable resource allocation, is essential. This approach will enhance health systems in resource-poor countries and improve global pandemic preparedness. Future research should focus on refining the metrics, exploring additional indicators, and further investigating successful capacity building models.

The study acknowledges the limitations of using simplified metrics to represent complex health research systems. The metrics used are based on readily available data but may not fully capture the nuances of national research capacity. The case studies, while illustrative, may not be fully generalizable to all settings. The paper also notes the potential political nature of metrics and the need to avoid imposing simplistic global indicators that may overshadow local context and knowledge.