Grand Challenges: Innovative Data and Modeling Approaches to Measure Women's Health

Background

Women's health continues to be under-represented and poorly measured in global health frameworks.

The Challenge

We invite applicants to explore bold, innovative approaches. Specifically, the objectives of the Challenge will be to:

• Reimagine new ways to understand and measure women's health that extend beyond the limitations of existing composite indicators such as DALY.
• Use existing data sets or easily collectible datasets to quantify women's health outcomes across countries. While this Grand Challenge does not fund large-scale data collection, proposals may include small-scale data expansion where it is feasible, policy-relevant, and significantly enhances gendered analysis.
• Design innovative methodologies that incorporate gendered, socio-cultural, economic, and structural determinants of health, ensuring a comprehensive gender-sensitive approach (A gender-sensitive approach takes into consideration how one's gender impacts access to services, risk and protective factors and barriers that are uniquely experienced because of one's gender in a society).
• Create tools or frameworks that enable cross-cultural or subnational comparative analysis, identifying context-specific gaps and progress.
• Reflect the interconnected dimensions of women's health across the life course.
• Incorporate gaps in the measurement of:
  • Skills, knowledge, and networks: addressing how gender disparities in education, training, and professional networks impact health access, decision-making, and service delivery.
  • Supply and access to services: examining how health systems, financing mechanisms, and gender-based barriers affect the availability, affordability, and accessibility of essential services for women.
  • Health and economic impacts: capturing the intersection of health outcomes with economic participation, caregiving burdens, workforce inclusion, and financial independence.
• Produce outputs that are:
  • Methodologically rigorous: applying sound data science, statistical modeling, or analytical techniques that enhance the validity and reliability of women's health measurements.
  • Interpretable and actionable: ensuring results can be understood and applied by policymakers and implementers.
  • Comparative and scalable: enabling cross-cultural or subnational analysis to identify patterns, disparities, and opportunities for intervention.
  • Gender-sensitive and intersectional: incorporating the social, economic, and structural determinants that affect women's health outcomes.
  • Policy-relevant and decision-oriented: providing insights that have the potential to directly inform policies, resource allocation, or program design to improve women's health measurement and action.

Please see FAQs for additional guidelines.

Eligibility

_ You can learn more about this opportunity by visiting the funder's website.