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Strengthening Modeling and Analytics Capacity and Ecosystem for Women's Health

Building Data Modeling Capacity for Gender Equality

Background

Mathematical modeling and analytics are valuable tools to inform policy and programmatic decisions, and there have been many successful examples in global health using disease burden estimation, modeling, and forecasting. It has become increasingly clear that these approaches will need to incorporate a gender lens, either because women and girls comprise a greater fraction of the remaining burden, or because they hold the keys to a more efficient solution.

There are few modelers in low-and-middle-income (LMIC[1]) settings focused on health issues that disproportionally affect women, especially adolescent girls and young women (AGYW), as well as a lack of access to gender-disaggregated data sources. Currently, many units contributing to efforts in these topic areas are based primarily in academic institutions in the Global North. We believe modeling is most impactful when conducted by local partners, with local data where possible, and co-created with relevant decision makers. Deploying "one-size-fits-all" analysis tools and governance processes across different regions from where they were created may produce poor analysis results. Solutions that are not fit-for-purpose could also lead to misleading interpretations and conclusions when scientists analyze data without insight from the context in which it was collected. As such, modeling infrastructure and capacity needs to be proximally focused in the areas where the data emerges to produce solutions that enable strong evidence-based practices to guide interventions.

Therefore, there is significant opportunity to: facilitate collaboration among women's health modelers in low- and middle-income countries, address gender biases in existing methodologies, extend uses of tools and platforms to better account for gendered effects, generate solid evidence to facilitate policy changes, and provide a global public good for Gender Equality that can improve how we allocate internal resources and engage partners to use data to make better decisions.

The Challenge

This RFP seeks innovative approaches to modeling of women's health issues or of broader health topics that incorporate a gender lens. We are looking for projects with a 1-to-3-year timeline that will achieve at least one of the objectives below:

  • Increase the number of trained modelers, especially women with gender expertise based in low-income and middle-income countries
  • Achieve a better understanding of issues that disproportionately affect women through modeling
  • Improve engagement with modeling approaches to support strategic planning and/or evaluation work

Ideally, proposals should also:

  • Bring together discrete modeling units across low-income and middle-income countries to share expertise
  • Enable South-South data-centered collaborations, knowledge transfer, and build on & strengthen existing initiatives and ecosystems
  • Foster innovation with data in the interest of their respective local communities and achieving equality in access to health care
  • Improve data collection, sharing, governance, regulatory compliance, and analysis processes to enable data-centered and gender aware public health research and interventions
  • Explore and improve how to build and strengthen the interface of modeling with policy engagement leading to increased adoption of insights to yield impact

Priority will be given to proposals that 1) advance broad access to data to support gender intentional modelling to improve women's health and 2) enable strong evidence-based practices to guide policy decisions.

The desired outcome of this request for proposals is to build a modeling and analytics ecosystem focusing on applying a gender intentional lens to achieve gender equality in women's health and to facilitate South- South collaborations. Grantees should be able to, over time, answer questions on how their proposal to increase empowerment of modelers, in particular women modelers, at a local level would reduce the impact of issues that disproportionately impact women’s health over the next 10 years in each geography.

Funding level:

The funding level for the Building Data Modeling Capacity for Gender Equality Project is a grant of up to $500,000 USD, provided to the organization, with a term of up to 1-to-3-years. Application budgets should be commensurate with the scope of work proposed. Any indirect costs should be included in the USD $500,000 (subject to the Bill & Melinda Gates Foundation's indirect cost policy).

Selected proposals will become part of a coordinated program aiming at Strengthening Data Science Capacity and the Ecosystem to Enable Data-Centered and Gender Aware Public Health Interventions. We seek to build a network of researchers working together in close collaboration with the existing Data Science Grand Challenges network and its partners to build on lessons learned in different regions and further develop processes, tools and governance that maximize the impact of data-focused research studies, as well as identify and address the global data-related challenges.

What We Are Looking For:

  • Collaborative proposals that are led by investigators in low-income and middle-income countries (LMICs) - we particularly encourage applications from women-led organizations and applications involving projects led by women
  • Proposals that have the potential to have impact on addressing women's health issues within the proposed budget and timeframe of 1-to-3-years
  • Proposals that are gender intentional or transformative:
    • Gender intentional investments will, through novel modeling and analytical approaches, increase understanding of impact that gender gaps/barriers have across relevant global health fields
    • Gender transformative investments will, through novel modeling and analytical approaches, increase the understanding of empowerment on reduction of gender gaps/barriers across relevant global health fields
    • Should demonstrate that their approach will increase knowledge and understanding of gender barriers in modeling OR Should display how their methodologies would show impact alleviating a known gender gap/issue would have across relevant global health fields
    • Proposals should also highlight existing expertise around gender and modeling and how it will contribute to both novel methods and expanding the ecosystem
    • Proposals that demonstrate enhancement of the data value chain for gender intentional modelling
  • Proposals that have timely access to necessary data. Focus on improving gender modeling capacity in women's health in LMICs
  • Proposals that articulate how the project will lead to impact in the near-term and how those benefits will be sustained past the lifetime of the project
  • Proposals that demonstrate engagement with local and/or regional decision makers
  • Proposals that are driven by a shared commitment to open science, data sharing, and building collaboration and analysis infrastructure to enable discoveries that will benefit people everywhere

Note: Global partners may be included. However, priority will be given to proposals that demonstrate at least 80% of the funding is going to LMIC institutions and where the PI is a part of an LMIC institution.

We will not consider funding for proposals that:

  • Aim to collect and generate new data through this funding
  • Are not gender intentional
  • Are not collaborative
  • Do not focus on women's health or incorporate a gender lens into broader health topics
  • Do not engage local and/or regional decision-makers or do not have a plan to do so
  • Do not demonstrate that the work proposed will be led and undertaken by investigators and scientists at institutions based in LMIC
  • Do not have timely access to necessary data
  • Do not demonstrate a pathway to decision making that results in sustainable impact on gender equity and women's health issues
  • Do not demonstrate a clear commitment to open science and making their findings, processes and/or tools developed accessible and reusable

[1] See World Bank - Low Income Countries for definitions). Subject to the eligibility requirements in the Rules & Guidelines, investigators in low- and middle-income countries are invited (in connection with the organization with which they are affiliated) to apply through the Bill & Melinda Gates Foundation’s application portal. We reserve the right to determine eligibility for this call based on these characteristics. Grants will go to investigators in low- and middle-income countries, but we encourage partnerships with investigators in other countries, especially where the opportunity exists to build on existing collaborations.


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