Grand Challenges is a family of initiatives fostering innovation to solve key global health and development problems. Each initiative is an experiment in the use of challenges to focus innovation on making an impact. Individual challenges address some of the same problems, but from differing perspectives.

Challenges

<h2>Background</h2>Pathogen Genomic Surveillance (PGS) can provide information about pathogen evolution and insight into the genetic basis of changes in virulence or resistance to interventions. During the COVID-19 pandemic, genomic surveillance for SARS-CoV-2 was established by many countries, including countries in Asia. It may be possible to leverage this capacity for genomic surveillance of priority endemic or epidemic pathogens. Research studies in the region have used pathogen genomics to understand transmission of particular pathogens such as dengue, Salmonella Typhi, and V. cholerae. Public labs and institutes may now be able to incorporate routine genomic surveillance of priority pathogens into their surveillance systems. It may also be valuable to build on SARS-CoV-2 genomic surveillance systems to further develop in-country capacity for the rapid immunological evaluation of SARS-CoV-2 variants of concern.<h2>The Challenge</h2>In response to this request for proposals, we seek projects from investigators in South and Southeast Asia that address one or both of the following two goals:<ol><li>Asia Pathogen Genomics Initiative (Asia PGI): Design and pilot a genomic surveillance program for a priority pathogen (other than SARS-CoV-2)&nbsp;</li><li>Global Immunology and Immune Sequencing for Epidemic Response (GIISER) – Asia: Develop capacity for immune characterization of SARS-CoV-2 variants to inform Epidemic Response</li></ol>Across both goals, training of local scientists by collaborators willing and able to share knowledge and tools will create the necessary capabilities. A long-term goal is to establish a sustainable, local infrastructure that can be activated to respond to any new emerging pathogen locally and strengthen connections and collaborations between sites and with international decision-making bodies.Funding Level: Up to 300,000 USD per year for each project, with a grant term of up to 2 years depending on the scope of the project. An additional 300,000 USD may be added to the second year budget if a proposed project includes monoclonal antibody discovery activities.<ol><li>Asia Pathogen Genomics Initiative (Asia PGI)</li></ol>Proposals are invited from country National Public Health Institutions (NPHIs) or public laboratories with links to the public health system.<a class="footnote" href="#_ftn1" title="" id="_ftnref1" name="_ftnref1">[1]</a> NPHI or lab staff may propose to develop a plan for genomic surveillance of priority pathogens or syndromes and to execute a pilot surveillance program. They may identify a priority pathogen or disease/syndrome and undertake surveillance, and may propose staff training in the appropriate epidemiological methods, genomic technologies and bioinformatic tools to develop capability and expertise in viral, bacterial, parasite genomics, or metagenomics. In a two-year period, staff should have developed the ability to plan and conduct genomic surveillance for the chosen priority pathogen and have piloted a genomic surveillance system for the pathogen. Such a pilot system may inform surveillance scale-up or the design of molecular diagnostics for pathogens discovered using metagenomics.Specifically, we seek proposals from NPHIs or public labs to dedicate staff to developing a pathogen genomic surveillance program by spending 2 years working on the identified objectives. This may include collaboration or placement with an expert for 1-3 months to gain training and expertise. It is the proposing organization’s responsibility to identify collaborators or training institutes as needed. Budgets may include NPHI staff salary, reagents and supplies (which may be donated in kind by manufacturers), and training costs at the institution where the staff member may gain expertise.The objectives for Asia PGI are:<ul><li>To establish routine pathogen genomic surveillance to understand the epidemiology and transmission of a priority pathogen (other than SARS-CoV-2)</li><li>To use pathogen genomics in the public health response - including field epidemiology response - to investigate potential evolution of a priority pathogen and its impact on the epidemiology of disease</li><li>To use pathogen genomics to monitor the impact of vaccine introduction on the transmission dynamics or AMR characteristics of pathogen lineages causing disease.</li><li>To use pathogen genomics to inform the development of diagnostics and/or therapeutics.</li></ul>Proposals addressing diseases affecting underserved or socioeconomically disadvantaged populations are encouraged. Surveillance focused on regions suspected to be the source for outbreak pathogens are encouraged.Selected sites will be networked via regular symposia and meetings to ensure that knowledge and learnings are shared in the region.<ol start="2"><li>Global Immunology and Immune Sequencing for Epidemic Response (GIISER) - Asia</li></ol>We invite proposals to increase the in-country capacity for rapid immunological evaluation of SARS-CoV-2 variants in South and Southeast Asia.&nbsp; We would also consider proposals that include other pathogens of global health importance, in addition to SARS-CoV-2. Selected sites would be linked to the existing GIISER program, which was initiated in October of 2021 with 8 sites, located in Uganda, South Africa, Senegal, Nigeria, Kenya, Ghana, India, and Brazil.&nbsp; Points of connection could include standard protocols, bioinformatics pipelines, data sharing meetings, and training opportunities. The goal of the GIISER program is to strengthen local immunological evaluation of pathogens of epidemic importance in order to inform and impact local and global equitable decision making around vaccines, herd immunity, diagnostic assays, and therapeutics.A successful GIISER site will be able to systematically produce data quantifying immune escape and cross protection for variants of local concern/interest. This will require that sites are able to leverage existing pathogen sequencing surveillance infrastructure to rapidly identify emerging SARS-CoV-2 variants, use existing clinical cohorts to obtain sera and blood cells from relevantly infected individuals with appropriate informed consent, and perform detailed immunological characterization of sera/plasma (binding and neutralization assays), as well as single cell analytics for monoclonal antibody discovery.&nbsp; This information will be produced and communicated rapidly enough to inform public health decisions and policy makers within the local and international community. Care should be taken in the proposal to describe how these activities that are often siloed would be brought together.Specifically, we seek proposals from NPHIs or their academic partners to: (1) Identify SARS-CoV-2 pathogen variants and appropriate subjects; (2) Perform sample collection, virus isolation, and B cell sorting; (3) Assess natural-infection-induced and vaccine-induced polyclonal antibody immunity to novel variants; and (4) Discover monoclonal antibodies in appropriate subjects. By the end of the first year of a two-year investment, sites should be performing all necessary binding and neutralization assays in their lab and sharing those results.&nbsp; By the end of the second year, sites should be able to communicate binding and neutralization results within 1-2 months of identifying a variant of local interest or concern. Sites including monoclonal antibody discovery should, by the end of year two, be able to perform single cell sequencing from B cells, repertoire analysis for selection of heavy + light chain pairs for subsequent expression and in vitro screening assays, small scale production of selected high quality mAbs from cDNA sequence, and screening of mAbs for binding to a variety of spike proteins, including epitope mapping.The objectives for GIISER-Asia are:<ul><li>Identify SARS-CoV-2 pathogen variants and appropriate subjects</li><li>Sample Collection and Virus Isolation</li><li>Assessment of natural-infection-induced and vaccine-induced polyclonal antibody immunity to novel variants</li><li>Local monoclonal antibody discovery</li><li>Local monoclonal antibody screening</li><li>Develop capacity for immunological evaluation of SARS-CoV-2 variants of concern (and potentially other additional pathogens of global health importance) through project immersion and targeted training with partners</li><li>Sustain and further develop expertise in virology, immunology, and communication with policy makers</li></ul>What We Are Looking For<ol><li>Asia PGI requirements: A successful Asia PGI site will formalize a framework to identify a priority pathogen or syndrome for genomic surveillance, build on the experience of sourcing samples for SARS-CoV-2 genomic surveillance and on the genomic sequencing skills gained during the pandemic, and access the expertise of epidemiologists and clinicians with insight into the epidemiology of the chosen pathogen or syndrome. We will prioritize funding for public labs or institutes that provide surveillance data to the government to inform public health interventions. Proposals should mention other available funding for the proposed work. Pathogens that are not covered by other funding mechanisms including large international programs will be prioritized. We also encourage applicants to describe the impact of ongoing, related work at the organization/site.</li></ol>All Asia PGI proposals must:<ul><li>Describe the framework used to prioritize the chosen pathogen or syndrome</li><li>Describe in brief the SARS-CoV-2 genomic surveillance system in place</li><li>Describe how staff can immediately put to use pathogen genomic sequencing technology at your site to respond to at least one of the Asia PGI objectives listed above.</li><li>Describe how skills will be developed in sequencing of the priority pathogen chosen</li><li>Describe the sampling approach for obtaining specimens for genomic sequencing and how the sampling approach will be optimized to answer at least one of the objectives outlined above. In addition, describe how metadata and clinical, epidemiological, or other data will be collected and combined with the sequencing data.</li><li>Describe how the data generated from your project will be used to inform public health decision making in your area, country and/or region in a timely manner. How will you communicate your findings and engage with stakeholders to ensure uptake and use of your findings for these public health purposes? We expect that PGS data will be shared immediately with local government health officials as well as uploaded to a standard repository for genetic data such as GISAID, NCBI, or ENA.</li><li>Articulate how the capacity built through the proposed project will strengthen your institute’s approach to using pathogen genomics for surveillance.</li></ul><ol start="2"><li>GIISER-Asia requirements: A successful GIISER site will have access to existing pathogen sequencing capacity and bioinformatics, access to existing cohorts or clinical infrastructure, access to existing BLS3 labs and trained virologists and immunologists with some expertise in protein reagent generation.&nbsp; Not every site will have everything in place, but enthusiastic, creative and collaborative groups who want to get things done are encouraged to include specific requests for the support they need to get there (training, connections, technology, etc.)</li></ol>All GIISER-Asia proposals must:<ul><li>Describe the site's ability to link together pathogen sequencing, clinical epidemiology, and immunology to rapidly produce high-quality, interpretable and informative data on neutralization breadth and cross protection for locally identified SARS-CoV-2 variants of concern.<ul><li>This includes, but is not limited to, outgrowth of variant SARS-CoV-2 virus in appropriate BLS3 containment labs for live virus neutralization assays. Examples of anticipated results: <a href="https://www.nature.com/articles/s41586-021-03471-w" target="_blank">Cele et al Nature 2021, </a><a href="https://www.nejm.org/doi/full/10.1056/NEJMc2104192?query=main_nav_lg" target="_blank">Moyo-Gwete et al NEJM 2021, </a><a href="https://www.nejm.org/doi/full/10.1056/NEJMc2103740?query=main_nav_lg" target="_blank">Shen et al NEJM 2021 </a>and <a href="https://www.nature.com/articles/s41591-021-01285-x" target="_blank">Wibmer et al</a> <a href="https://www.nature.com/articles/s41591-021-01285-x" target="_blank">Nature Medicine 2021.</a></li></ul></li><li>Describe how, within the first year of the grant, the GIISER site will bring all required binding and neutralization assays into their lab and communicate their results.</li><li>Describe how, within the second year of the grant, the GIISER site will be communicating results within 1-2 months of identifying a variant of local concern.</li><li>Describe how, within the second year of the grant, the GIISER site will bring in all required capabilities for monoclonal antibody discovery and screening. (Proposals without an antibody scope will still be eligible for funding under this call.)</li><li>Describe how the site will leverage existing local expertise, collaborate, and share data effectively with other GIISER sites and international networks</li></ul>Across both goals, we will not consider funding for:<ul><li>Sequencing of extant samples or isolates will not be considered as responsive to this RFP. The proposal must include a plan for prospective genomic surveillance rather than simply genomic sequencing of existing samples.</li><li>Funding of genomic surveillance in a setting with no experience with SARS-CoV-2 surveillance. The proposed studies must leverage equipment and/or human resource capacity that was instituted during the COVID-19 pandemic.</li><li>GIISER-Asia sites that do not have funded pathogen genomics surveillance and existing clinical cohorts to build on for the immune characterization studies.</li><li>Studies focused on T cell immunity and characterizing the overall immune response to SARS-CoV-2 are out of scope.</li></ul><a href="#_ftnref1" title="" id="_ftn1" name="_ftn1">[1]</a> Government-funded institutes and labs that are mandated to provide surveillance data to health ministries for public health action are eligible to apply. This may include public health labs at the state or provincial level.

Grand Challenges Global Call-to-Action

Pathogen Genomic Surveillance and Immunology in Asia

<h2>Background</h2>
Pathogen Genomic Surveillance (PGS) can provide information about pathogen evolution and insight into the genetic basis of changes in virulence or resistance to interventions. During the COVID-19 pandemic, genomic surveillance for SARS-CoV-2 was established by many countries, including countries in Asia. It may be possible to leverage this capacity for genomic surveillance of priority endemic or epidemic pathogens. Research studies in the region have used pathogen genomics to understand transmission of particular pathogens such as dengue, Salmonella Typhi, and V. cholerae. Public labs and institutes may now be able to incorporate routine genomic surveillance of priority pathogens into their surveillance systems. It may also be valuable to build on SARS-CoV-2 genomic surveillance systems to further develop in-country capacity for the rapid immunological evaluation of SARS-CoV-2 variants of concern.
<h2>The Challenge</h2>
In response to this request for proposals, we seek projects from investigators in South and Southeast Asia that address one or both of the following two goals:
<ol>
<li>Asia Pathogen Genomics Initiative (Asia PGI): Design and pilot a genomic surveillance program for a priority pathogen (other than SARS-CoV-2)&nbsp;</li>
<li>Global Immunology and Immune Sequencing for Epidemic Response (GIISER) – Asia: Develop capacity for immune characterization of SARS-CoV-2 variants to inform Epidemic Response</li>
</ol>
Across both goals, training of local scientists by collaborators willing and able to share knowledge and tools will create the necessary capabilities. A long-term goal is to establish a sustainable, local infrastructure that can be activated to respond to any new emerging pathogen locally and strengthen connections and collaborations between sites and with international decision-making bodies.
Funding Level: Up to 300,000 USD per year for each project, with a grant term of up to 2 years depending on the scope of the project. An additional 300,000 USD may be added to the second year budget if a proposed project includes monoclonal antibody discovery activities.
<ol>
<li>Asia Pathogen Genomics Initiative (Asia PGI)</li>
</ol>
Proposals are invited from country National Public Health Institutions (NPHIs) or public laboratories with links to the public health system.<a class="footnote" href="#_ftn1" title name="_ftnref1" id="_ftnref1">1</a> NPHI or lab staff may propose to develop a plan for genomic surveillance of priority pathogens or syndromes and to execute a pilot surveillance program. They may identify a priority pathogen or disease/syndrome and undertake surveillance, and may propose staff training in the appropriate epidemiological methods, genomic technologies and bioinformatic tools to develop capability and expertise in viral, bacterial, parasite genomics, or metagenomics. In a two-year period, staff should have developed the ability to plan and conduct genomic surveillance for the chosen priority pathogen and have piloted a genomic surveillance system for the pathogen. Such a pilot system may inform surveillance scale-up or the design of molecular diagnostics for pathogens discovered using metagenomics.
Specifically, we seek proposals from NPHIs or public labs to dedicate staff to developing a pathogen genomic surveillance program by spending 2 years working on the identified objectives. This may include collaboration or placement with an expert for 1-3 months to gain training and expertise. It is the proposing organization’s responsibility to identify collaborators or training institutes as needed. Budgets may include NPHI staff salary, reagents and supplies (which may be donated in kind by manufacturers), and training costs at the institution where the staff member may gain expertise.
The objectives for Asia PGI are:
<ul>
<li>To establish routine pathogen genomic surveillance to understand the epidemiology and transmission of a priority pathogen (other than SARS-CoV-2)</li>
<li>To use pathogen genomics in the public health response - including field epidemiology response - to investigate potential evolution of a priority pathogen and its impact on the epidemiology of disease</li>
<li>To use pathogen genomics to monitor the impact of vaccine introduction on the transmission dynamics or AMR characteristics of pathogen lineages causing disease.</li>
<li>To use pathogen genomics to inform the development of diagnostics and/or therapeutics.</li>
</ul>
Proposals addressing diseases affecting underserved or socioeconomically disadvantaged populations are encouraged. Surveillance focused on regions suspected to be the source for outbreak pathogens are encouraged.
Selected sites will be networked via regular symposia and meetings to ensure that knowledge and learnings are shared in the region.
<ol start="2">
<li>Global Immunology and Immune Sequencing for Epidemic Response (GIISER) - Asia</li>
</ol>
We invite proposals to increase the in-country capacity for rapid immunological evaluation of SARS-CoV-2 variants in South and Southeast Asia.&nbsp; We would also consider proposals that include other pathogens of global health importance, in addition to SARS-CoV-2. Selected sites would be linked to the existing GIISER program, which was initiated in October of 2021 with 8 sites, located in Uganda, South Africa, Senegal, Nigeria, Kenya, Ghana, India, and Brazil.&nbsp; Points of connection could include standard protocols, bioinformatics pipelines, data sharing meetings, and training opportunities. The goal of the GIISER program is to strengthen local immunological evaluation of pathogens of epidemic importance in order to inform and impact local and global equitable decision making around vaccines, herd immunity, diagnostic assays, and therapeutics.
A successful GIISER site will be able to systematically produce data quantifying immune escape and cross protection for variants of local concern/interest. This will require that sites are able to leverage existing pathogen sequencing surveillance infrastructure to rapidly identify emerging SARS-CoV-2 variants, use existing clinical cohorts to obtain sera and blood cells from relevantly infected individuals with appropriate informed consent, and perform detailed immunological characterization of sera/plasma (binding and neutralization assays), as well as single cell analytics for monoclonal antibody discovery.&nbsp; This information will be produced and communicated rapidly enough to inform public health decisions and policy makers within the local and international community. Care should be taken in the proposal to describe how these activities that are often siloed would be brought together.
Specifically, we seek proposals from NPHIs or their academic partners to: (1) Identify SARS-CoV-2 pathogen variants and appropriate subjects; (2) Perform sample collection, virus isolation, and B cell sorting; (3) Assess natural-infection-induced and vaccine-induced polyclonal antibody immunity to novel variants; and (4) Discover monoclonal antibodies in appropriate subjects. By the end of the first year of a two-year investment, sites should be performing all necessary binding and neutralization assays in their lab and sharing those results.&nbsp; By the end of the second year, sites should be able to communicate binding and neutralization results within 1-2 months of identifying a variant of local interest or concern. Sites including monoclonal antibody discovery should, by the end of year two, be able to perform single cell sequencing from B cells, repertoire analysis for selection of heavy + light chain pairs for subsequent expression and in vitro screening assays, small scale production of selected high quality mAbs from cDNA sequence, and screening of mAbs for binding to a variety of spike proteins, including epitope mapping.
The objectives for GIISER-Asia are:
<ul>
<li>Identify SARS-CoV-2 pathogen variants and appropriate subjects</li>
<li>Sample Collection and Virus Isolation</li>
<li>Assessment of natural-infection-induced and vaccine-induced polyclonal antibody immunity to novel variants</li>
<li>Local monoclonal antibody discovery</li>
<li>Local monoclonal antibody screening</li>
<li>Develop capacity for immunological evaluation of SARS-CoV-2 variants of concern (and potentially other additional pathogens of global health importance) through project immersion and targeted training with partners</li>
<li>Sustain and further develop expertise in virology, immunology, and communication with policy makers</li>
</ul>
What We Are Looking For
<ol>
<li>Asia PGI requirements: A successful Asia PGI site will formalize a framework to identify a priority pathogen or syndrome for genomic surveillance, build on the experience of sourcing samples for SARS-CoV-2 genomic surveillance and on the genomic sequencing skills gained during the pandemic, and access the expertise of epidemiologists and clinicians with insight into the epidemiology of the chosen pathogen or syndrome. We will prioritize funding for public labs or institutes that provide surveillance data to the government to inform public health interventions. Proposals should mention other available funding for the proposed work. Pathogens that are not covered by other funding mechanisms including large international programs will be prioritized. We also encourage applicants to describe the impact of ongoing, related work at the organization/site.</li>
</ol>
All Asia PGI proposals must:
<ul>
<li>Describe the framework used to prioritize the chosen pathogen or syndrome</li>
<li>Describe in brief the SARS-CoV-2 genomic surveillance system in place</li>
<li>Describe how staff can immediately put to use pathogen genomic sequencing technology at your site to respond to at least one of the Asia PGI objectives listed above.</li>
<li>Describe how skills will be developed in sequencing of the priority pathogen chosen</li>
<li>Describe the sampling approach for obtaining specimens for genomic sequencing and how the sampling approach will be optimized to answer at least one of the objectives outlined above. In addition, describe how metadata and clinical, epidemiological, or other data will be collected and combined with the sequencing data.</li>
<li>Describe how the data generated from your project will be used to inform public health decision making in your area, country and/or region in a timely manner. How will you communicate your findings and engage with stakeholders to ensure uptake and use of your findings for these public health purposes? We expect that PGS data will be shared immediately with local government health officials as well as uploaded to a standard repository for genetic data such as GISAID, NCBI, or ENA.</li>
<li>Articulate how the capacity built through the proposed project will strengthen your institute’s approach to using pathogen genomics for surveillance.</li>
</ul>
<ol start="2">
<li>GIISER-Asia requirements: A successful GIISER site will have access to existing pathogen sequencing capacity and bioinformatics, access to existing cohorts or clinical infrastructure, access to existing BLS3 labs and trained virologists and immunologists with some expertise in protein reagent generation.&nbsp; Not every site will have everything in place, but enthusiastic, creative and collaborative groups who want to get things done are encouraged to include specific requests for the support they need to get there (training, connections, technology, etc.)</li>
</ol>
All GIISER-Asia proposals must:
<ul>
<li>Describe the site's ability to link together pathogen sequencing, clinical epidemiology, and immunology to rapidly produce high-quality, interpretable and informative data on neutralization breadth and cross protection for locally identified SARS-CoV-2 variants of concern.
<ul>
<li>This includes, but is not limited to, outgrowth of variant SARS-CoV-2 virus in appropriate BLS3 containment labs for live virus neutralization assays. Examples of anticipated results: <a href="https://www.nature.com/articles/s41586-021-03471-w" target="_blank" rel="noopener noreferrer">Cele et al Nature 2021, </a><a href="https://www.nejm.org/doi/full/10.1056/NEJMc2104192?query=main_nav_lg" target="_blank" rel="noopener noreferrer">Moyo-Gwete et al NEJM 2021, </a><a href="https://www.nejm.org/doi/full/10.1056/NEJMc2103740?query=main_nav_lg">Shen et al NEJM 2021 </a>and <a href="https://www.nature.com/articles/s41591-021-01285-x" target="_blank" rel="noopener noreferrer">Wibmer et al</a> <a href="https://www.nature.com/articles/s41591-021-01285-x" target="_blank" rel="noopener noreferrer">Nature Medicine 2021.</a></li>
</ul>
</li>
<li>Describe how, within the first year of the grant, the GIISER site will bring all required binding and neutralization assays into their lab and communicate their results.</li>
<li>Describe how, within the second year of the grant, the GIISER site will be communicating results within 1-2 months of identifying a variant of local concern.</li>
<li>Describe how, within the second year of the grant, the GIISER site will bring in all required capabilities for monoclonal antibody discovery and screening. (Proposals without an antibody scope will still be eligible for funding under this call.)</li>
<li>Describe how the site will leverage existing local expertise, collaborate, and share data effectively with other GIISER sites and international networks</li>
</ul>
Across both goals, we will not consider funding for:
<ul>
<li>Sequencing of extant samples or isolates will not be considered as responsive to this RFP. The proposal must include a plan for prospective genomic surveillance rather than simply genomic sequencing of existing samples.</li>
<li>Funding of genomic surveillance in a setting with no experience with SARS-CoV-2 surveillance. The proposed studies must leverage equipment and/or human resource capacity that was instituted during the COVID-19 pandemic.</li>
<li>GIISER-Asia sites that do not have funded pathogen genomics surveillance and existing clinical cohorts to build on for the immune characterization studies.</li>
<li>Studies focused on T cell immunity and characterizing the overall immune response to SARS-CoV-2 are out of scope.</li>
</ul>
<a href="#_ftnref1" title name="_ftn1" id="_ftn1">1</a> Government-funded institutes and labs that are mandated to provide surveillance data to health ministries for public health action are eligible to apply. This may include public health labs at the state or provincial level.

Genomic surveillance of pathogens can provide information about pathogen evolution and insight into the genetic basis of changes in virulence or resistance to interventions. During the COVID-19 pandemic, genomic surveillance for SARS-CoV-2 was established by many countries, including countries in Asia. In response to this request for proposals, we seek projects from investigators in South and Southeast Asia that address one - or both - of the following goals: 1) Design and pilot a genomic surveillance program for a priority pathogen (other than SARS-CoV-2) and 2) Develop capacity for Immunology and Immune Sequencing of SARS-CoV-2 to inform Epidemic Response.

<h2>Background</h2>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<a class="footnote" href="#_ftn1" title="" id="_ftnref1" name="_ftnref1">[1]</a>) 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.<h2>The Challenge</h2>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:<ul><li>Increase the number of trained modelers, especially women with gender expertise based in low-income and middle-income countries</li><li>Achieve a better understanding of issues that disproportionately affect women through modeling</li><li>Improve engagement with modeling approaches to support strategic planning and/or evaluation work</li></ul>Ideally, proposals should also:<ul><li>Bring together discrete modeling units across low-income and middle-income countries to share expertise</li><li>Enable South-South data-centered collaborations, knowledge transfer, and build on &amp; strengthen existing initiatives and ecosystems</li><li>Foster innovation with data in the interest of their respective local communities and achieving equality in access to health care</li><li>Improve data collection, sharing, governance, regulatory compliance, and analysis processes to enable data-centered and gender aware public health research and interventions</li><li>Explore and improve how to build and strengthen the interface of modeling with policy engagement leading to increased adoption of insights to yield impact</li></ul>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 <a href="https://docs.gatesfoundation.org/Documents/Indirect_Cost_Policy.pdf" target="_blank">Bill &amp; Melinda Gates Foundation's indirect cost policy</a>).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 <a href="https://gcgh.grandchallenges.org/grants/JTdCJTIyc29ydCUyMiUzQSUyMmRlc2NlbmRpbmclMjIlMkMlMjJzb3J0RmllbGQlMjIlM0ElMjJkYXRlJTIyJTJDJTIybnVtYmVyUGVyUGFnZSUyMiUzQTEwMCUyQyUyMnBhZ2VOdW1iZXIlMjIlM0EwJTdE/JTdCJTIyeWVhcnMlMjIlM0ElNUIlNUQlMkMlMjJjaGFsbGVuZ2VzJTIyJTNBJTVCJTIyMTE3JTIyJTVEJTJDJTIydGVybXMlMjIlM0ElNUIlNUQlMkMlMjJpbml0aWF0aXZlcyUyMiUzQSU1QiU1RCUyQyUyMmxvY2F0aW9ucyUyMiUzQSU1QiU1RCU3RA==" target="_blank">Data Science Grand Challenges network</a> 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:<ul><li>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</li><li>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</li><li>Proposals that are gender intentional or transformative:<ul><li>Gender intentional investments will, through novel modeling and analytical approaches, increase understanding of impact that gender gaps/barriers have across relevant global health fields</li><li>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</li><li>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</li><li>Proposals should also highlight existing expertise around gender and modeling and how it will contribute to both novel methods and expanding the ecosystem</li><li>Proposals that demonstrate enhancement of the data value chain for gender intentional modelling</li></ul></li><li>Proposals that have timely access to necessary data. Focus on improving gender modeling capacity in women's health in LMICs</li><li>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</li><li>Proposals that demonstrate engagement with local and/or regional decision makers</li><li>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</li></ul>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:<ul><li>Aim to collect and generate new data through this funding</li><li>Are not gender intentional</li><li>Are not collaborative</li><li>Do not focus on women's health or incorporate a gender lens into broader health topics</li><li>Do not engage local and/or regional decision-makers or do not have a plan to do so</li><li>Do not demonstrate that the work proposed will be led and undertaken by investigators and scientists at institutions based in LMIC</li><li>Do not have timely access to necessary data</li><li>Do not demonstrate a pathway to decision making that results in sustainable impact on gender equity and women's health issues</li><li>Do not demonstrate a clear commitment to open science and making their findings, processes and/or tools developed accessible and reusable</li></ul><a class="footnote" href="#_ftnref1" title="" id="_ftn1" name="_ftn1">[1]</a> See <a href="https://data.worldbank.org/country/XO" target="_blank" rel="noopener">World Bank - Low Income Countries for definitions</a>). Subject to the eligibility requirements in the <a href="https://gcgh.grandchallenges.org/sites/default/files/files/strengthening-modeling-and-analytics-capacity-rules-and-guidelines.pdf" target="_blank" rel="noopener">Rules &amp; Guidelines</a>, investigators in low- and middle-income countries are invited (in connection with the organization with which they are affiliated) to apply through the Bill &amp; 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.

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

<h2>Background</h2>
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<a class="footnote" href="#_ftn1" title id="_ftnref1" name="_ftnref1">1</a>) 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.
<h2>The Challenge</h2>
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:
<ul>
<li>Increase the number of trained modelers, especially women with gender expertise based in low-income and middle-income countries</li>
<li>Achieve a better understanding of issues that disproportionately affect women through modeling</li>
<li>Improve engagement with modeling approaches to support strategic planning and/or evaluation work</li>
</ul>
Ideally, proposals should also:
<ul>
<li>Bring together discrete modeling units across low-income and middle-income countries to share expertise</li>
<li>Enable South-South data-centered collaborations, knowledge transfer, and build on &amp; strengthen existing initiatives and ecosystems</li>
<li>Foster innovation with data in the interest of their respective local communities and achieving equality in access to health care</li>
<li>Improve data collection, sharing, governance, regulatory compliance, and analysis processes to enable data-centered and gender aware public health research and interventions</li>
<li>Explore and improve how to build and strengthen the interface of modeling with policy engagement leading to increased adoption of insights to yield impact</li>
</ul>
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 <a href="https://docs.gatesfoundation.org/Documents/Indirect_Cost_Policy.pdf" target="_blank" rel="noopener noreferrer">Bill &amp; Melinda Gates Foundation's indirect cost policy</a>).
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 <a href="https://gcgh.grandchallenges.org/grants/JTdCJTIyc29ydCUyMiUzQSUyMmRlc2NlbmRpbmclMjIlMkMlMjJzb3J0RmllbGQlMjIlM0ElMjJkYXRlJTIyJTJDJTIybnVtYmVyUGVyUGFnZSUyMiUzQTEwMCUyQyUyMnBhZ2VOdW1iZXIlMjIlM0EwJTdE/JTdCJTIyeWVhcnMlMjIlM0ElNUIlNUQlMkMlMjJjaGFsbGVuZ2VzJTIyJTNBJTVCJTIyMTE3JTIyJTVEJTJDJTIydGVybXMlMjIlM0ElNUIlNUQlMkMlMjJpbml0aWF0aXZlcyUyMiUzQSU1QiU1RCUyQyUyMmxvY2F0aW9ucyUyMiUzQSU1QiU1RCU3RA==" target="_blank" rel="noopener noreferrer">Data Science Grand Challenges network</a> 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:
<ul>
<li>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</li>
<li>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</li>
<li>Proposals that are gender intentional or transformative:
<ul>
<li>Gender intentional investments will, through novel modeling and analytical approaches, increase understanding of impact that gender gaps/barriers have across relevant global health fields</li>
<li>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</li>
<li>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</li>
<li>Proposals should also highlight existing expertise around gender and modeling and how it will contribute to both novel methods and expanding the ecosystem</li>
<li>Proposals that demonstrate enhancement of the data value chain for gender intentional modelling</li>
</ul>
</li>
<li>Proposals that have timely access to necessary data. Focus on improving gender modeling capacity in women's health in LMICs</li>
<li>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</li>
<li>Proposals that demonstrate engagement with local and/or regional decision makers</li>
<li>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</li>
</ul>
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:
<ul>
<li>Aim to collect and generate new data through this funding</li>
<li>Are not gender intentional</li>
<li>Are not collaborative</li>
<li>Do not focus on women's health or incorporate a gender lens into broader health topics</li>
<li>Do not engage local and/or regional decision-makers or do not have a plan to do so</li>
<li>Do not demonstrate that the work proposed will be led and undertaken by investigators and scientists at institutions based in LMIC</li>
<li>Do not have timely access to necessary data</li>
<li>Do not demonstrate a pathway to decision making that results in sustainable impact on gender equity and women's health issues</li>
<li>Do not demonstrate a clear commitment to open science and making their findings, processes and/or tools developed accessible and reusable</li>
</ul>
<a class="footnote" href="#_ftnref1" title id="_ftn1" name="_ftn1">1</a> See <a href="https://data.worldbank.org/country/XO" target="_blank" rel="noopener noreferrer">World Bank - Low Income Countries for definitions</a>). Subject to the eligibility requirements in the <a href="https://gcgh.grandchallenges.org/sites/default/files/files/strengthening-modeling-and-analytics-capacity-rules-and-guidelines.pdf" target="_blank" rel="noopener noreferrer">Rules &amp; Guidelines</a>, investigators in low- and middle-income countries are invited (in connection with the organization with which they are affiliated) to apply through the Bill &amp; 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.

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. This RFP seeks innovative approaches to modeling of women's health issues or of broader health topics that incorporate a gender lens.

Strengthening Modeling and Analytics Capacity and Ecosystem for Womens Health

<h2>Background</h2>

The scale and scope of the COVID-19 pandemic have reiterated the need for access to and analysis of timely accurate health data to support the implementation of control measures and to guide health interventions and evidence-based practices. The supporting infrastructures and capacities through which researchers access and analyze these data, however, vary greatly. For several reasons, researchers in the Global South often are skeptical of broad calls for data sharing when they are left out of the analysis and results interpretation. Additionally, deploying “one-size-fits-all” analysis tools and governance processes across different regions from where they were created may produce poor analysis results and could even lead to misleading interpretations and conclusions when scientists analyze data without insight from the context in which it was collected.

As such, data science infrastructure and capacity needs to be proximally focused in the areas where the data emerge, to produce solutions that enable strong evidence-based practices to guide health interventions.

<h2>The Challenge</h2>

Collecting, sharing, analyzing and interpreting health-related data are essential to the planning, implementation, and evaluation of public health practice as well as enabling advanced knowledge for heath emergency preparedness. Many data resources are not reusable if they have not been sufficiently documented and contextualized, or appropriately collected and licensed for use, particularly in cases where secondary analyses are planned that were not originally anticipated when the data were originally generated.

The desired outcome of this request for proposals is development of tools and processes that are "fit-for-purpose" to facilitate collaboration among researchers in low- and middle-income countries. This effort is focused on filling data science gaps and challenges whose solutions will address global health problems while fostering multi-disciplinary collaborations among researchers. We are specifically interested in funding proposals led by early and mid-career researchers. We expect each primary applicant to have a senior scientific advisor who would commit to provide scientific and technical guidance and mentorship to the team and facilitate connections with international networks as needed.

Specifically, the objectives of the challenge will be to:

<ul>
	<li>Develop and improve foundational tools, standards and protocols that enable data-centered health research, interventions, and health surveillance</li>
	<li>Improve access to curated and linked datasets for research and training purposes</li>
	<li>Enable South-South data-centered collaborations and build on and strengthen existing initiatives and ecosystems</li>
	<li>Enhance Data Science infrastructure, analysis capabilities and local leadership to address public health problems</li>
	<li>Foster innovation with health data in the interest of their respective local communities</li>
	<li>Bridge the gap between data-centered research and policy through collaborations and design of appropriate data science communication tools and channels</li>
	<li>Increase health data reliability and enable reuse by developing tools and processes to curate, standardize and aggregate data</li>
	<li>Improve data collection, sharing, governance, regulatory compliance, and analysis processes to enable data-centered public health research</li>
</ul>

What We Are Looking For

We will be developing a coordinated program in order to support these objectives. This will include cross-cutting cores which will provide specific functions to the program as well as individual research projects focusing on one of more specific disease areas.

Applications are invited from researchers working in healthcare, academia, industry, or research foundations, and will be welcomed from researchers based in any of the following regions: Africa, India, Bangladesh, Pakistan, Nepal, and Brazil. Each proposal should be submitted by one primary applicant, but the awards require the participation of at least two research institutions from the regions listed above and not both in the same country.

Program structure

<img alt="Strengthening Data Science Capacity and the Ecosystem Diagram" height="329" src="https://gcgh.grandchallenges.org/sites/default/files/images/picture1.png" width="540" />

Data governance and standards core

We seek to fund one data governance and standards core. This core would:

<ul>
	<li>Support the research projects funded through this initiative including the capacity strengthening core</li>
	<li>Leverage the funded research projects as use cases for development and refinement of data sharing processes and governance</li>
	<li>Seek to strengthen global communities and multi-disciplinary collaboration from researchers in low- to middle-income countries (LMICs) by developing processes to enable South-South collaborative analysis</li>
	<li>Develop adapted standards or Standard Operating Procedures that address data sharing issues including anonymization and perturbation protocols</li>
	<li>Develop re-usable tools, protocols, and standards to collect, clean, harmonize, and commonly structure individual data and meta-data related to one or many disease areas to increase health data reliability and enable reuse. New tools and process development should leverage and build on existing work</li>
	<li>Develop data informed processes to overcome barriers to the collection of complete and accurate information; and challenges related to data and information governance and data reuse</li>
</ul>

Capacity strengthening core

We seek to fund one capacity strengthening core to:

<ul>
	<li>Support the research projects and the data infrastructure and governing core funded through this initiative</li>
	<li>Bridge the gap between data scientists, modelers, regulators and policy makers, through trainings and best practices development</li>
	<li>Develop re-usable training materials and handbooks</li>
	<li>Lead and coordinate collaborative analysis efforts through different formats (workshops, hackathons, jamborees, etc.)</li>
	<li>Lead capacity-building efforts targeting existing gaps in data science trainings in LMICs and building on existing initiatives (reusing available resources when available to avoid duplication of efforts)</li>
	<li>Develop data-informed processes to overcome barriers to the collection of complete and accurate information, and challenges related to data and information governance and data reuse</li>
</ul>

Data re-use research projects

We seek to fund two data re-use projects where research will focus on one of more specific disease areas:

<ul>
	<li>Build data-driven public health platforms, tools and dashboards that guide policy making and public health interventions</li>
	<li>Identify, use, curate and link clearly defined datasets (administrative, clinical, environmental, etc.) to address policy gaps or deliver insights and conceptual and/or technological leaps on Global Health research priorities including:
	<ul>
		<li>Maternal, Newborn and Child Health</li>
		<li>Infectious diseases</li>
		<li>COVID-19 and pandemic preparedness</li>
	</ul>
	</li>
</ul>

<ul>
	<li>Proposals could focus on a specific disease area but need to demonstrate commitment to providing access to all research products including tools and processes developed</li>
</ul>

Funding level 

Successful proposals will receive an award of up to USD $250,000 with an 18- to 24-month grant duration. While proposals require the collaborative participation of at least two investigators at institutions in different countries based in any of the regions listed above, proposals should be submitted by one primary applicant/institution. While restricted to one application per institution as the primary applicant, researchers may participate as collaborators in multiple collaborative applications.

Selected proposals will become part of a coordinated program aiming at Strengthening Data Science Capacity and the Ecosystem to Enable Data-Centered Public Health Interventions. We seek to build a network of researchers working together in close collaboration with the existing <a href="https://gcgh.grandchallenges.org/grants/JTdCJTIyc29ydCUyMiUzQSUyMmRlc2NlbmRpbmclMjIlMkMlMjJzb3J0RmllbGQlMjIlM0ElMjJkYXRlJTIyJTJDJTIybnVtYmVyUGVyUGFnZSUyMiUzQTEwMCUyQyUyMnBhZ2VOdW1iZXIlMjIlM0EwJTdE/JTdCJTIyeWVhcnMlMjIlM0ElNUIlNUQlMkMlMjJjaGFsbGVuZ2VzJTIyJTNBJTVCJTIyMTE3JTIyJTVEJTJDJTIydGVybXMlMjIlM0ElNUIlNUQlMkMlMjJpbml0aWF0aXZlcyUyMiUzQSU1QiU1RCUyQyUyMmxvY2F0aW9ucyUyMiUzQSU1QiU1RCU3RA==">Data Science Grand Challenges network</a> 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 to identify and address the global data-related challenges.

Successful proposals to be considered should: 

<ul>
	<li>Be driven by a shared commitment to open science, data sharing, and building collaboration and analysis infrastructure to enable discoveries that will benefit people everywhere</li>
	<li>Seek to strengthen global communities and multi-disciplinary collaboration from researchers in LMICs, and involve patients and the wider public</li>
	<li>Involve substantial collaboration between at least two research institutions in different countries encompassing Africa, India, Bangladesh, Pakistan, Nepal, and Brazil. The suggested collaboration should be key to advancing the project goals and yield insights that are unlikely in the absence of the co-produced approaches. In addition, however, applications could include collaborations with institutions in other geographical areas</li>
	<li>Have the potential to have impact on addressing public health issues within the proposed budget and timeframe of 18 -24 months</li>
	<li>Data re-use proposals should use well-defined datasets that directly address the core research questions and have a clear governance plan and demonstrate how the data could benefit the broader community at a later stage.</li>
	<li>Demonstrate a commitment to impact policies and the general public</li>
</ul>

We will not consider funding for: 

<ul>
	<li>Studies that aim to collect and generate new data through this funding</li>
	<li>Proposals led by institutions not based in any of these regions: Africa, India, Bangladesh, Pakistan, Nepal, and Brazil</li>
	<li>Proposals that will involve a single research institution or solely involve collaborators from multiple institutions from the same country</li>
	<li>Proposals that do not demonstrate a clear commitment to open science and making their findings, processes and/or tools developed accessible and reusable</li>
	<li>Proposals that do not demonstrate how they would leverage existing work and networks</li>
	<li>Proposals that do not demonstrate how they can benefit from and support other projects funded through this coordinated program</li>
	<li>Proposals that are not accomplishable within the grant term</li>
</ul>

Strengthening Data Science Capacity and the Ecosystem: Enabling Data-Centered Public Health Interventions

<h2>Background</h2>
The scale and scope of the COVID-19 pandemic have reiterated the need for access to and analysis of timely accurate health data to support the implementation of control measures and to guide health interventions and evidence-based practices. The supporting infrastructures and capacities through which researchers access and analyze these data, however, vary greatly. For several reasons, researchers in the Global South often are skeptical of broad calls for data sharing when they are left out of the analysis and results interpretation. Additionally, deploying “one-size-fits-all” analysis tools and governance processes across different regions from where they were created may produce poor analysis results and could even lead to misleading interpretations and conclusions when scientists analyze data without insight from the context in which it was collected.
As such, data science infrastructure and capacity needs to be proximally focused in the areas where the data emerge, to produce solutions that enable strong evidence-based practices to guide health interventions.
<h2>The Challenge</h2>
Collecting, sharing, analyzing and interpreting health-related data are essential to the planning, implementation, and evaluation of public health practice as well as enabling advanced knowledge for heath emergency preparedness. Many data resources are not reusable if they have not been sufficiently documented and contextualized, or appropriately collected and licensed for use, particularly in cases where secondary analyses are planned that were not originally anticipated when the data were originally generated.
The desired outcome of this request for proposals is development of tools and processes that are "fit-for-purpose" to facilitate collaboration among researchers in low- and middle-income countries. This effort is focused on filling data science gaps and challenges whose solutions will address global health problems while fostering multi-disciplinary collaborations among researchers. We are specifically interested in funding proposals led by early and mid-career researchers. We expect each primary applicant to have a senior scientific advisor who would commit to provide scientific and technical guidance and mentorship to the team and facilitate connections with international networks as needed.
Specifically, the objectives of the challenge will be to:
<ul>
<li>Develop and improve foundational tools, standards and protocols that enable data-centered health research, interventions, and health surveillance</li>
<li>Improve access to curated and linked datasets for research and training purposes</li>
<li>Enable South-South data-centered collaborations and build on and strengthen existing initiatives and ecosystems</li>
<li>Enhance Data Science infrastructure, analysis capabilities and local leadership to address public health problems</li>
<li>Foster innovation with health data in the interest of their respective local communities</li>
<li>Bridge the gap between data-centered research and policy through collaborations and design of appropriate data science communication tools and channels</li>
<li>Increase health data reliability and enable reuse by developing tools and processes to curate, standardize and aggregate data</li>
<li>Improve data collection, sharing, governance, regulatory compliance, and analysis processes to enable data-centered public health research</li>
</ul>
What We Are Looking For
We will be developing a coordinated program in order to support these objectives. This will include cross-cutting cores which will provide specific functions to the program as well as individual research projects focusing on one of more specific disease areas.
Applications are invited from researchers working in healthcare, academia, industry, or research foundations, and will be welcomed from researchers based in any of the following regions: Africa, India, Bangladesh, Pakistan, Nepal, and Brazil. Each proposal should be submitted by one primary applicant, but the awards require the participation of at least two research institutions from the regions listed above and not both in the same country.
Program structure
<img alt="Strengthening Data Science Capacity and the Ecosystem Diagram" height="329" src="https://gcgh.grandchallenges.org/sites/default/files/images/picture1.png" width="540">
Data governance and standards core
We seek to fund one data governance and standards core. This core would:
<ul>
<li>Support the research projects funded through this initiative including the capacity strengthening core</li>
<li>Leverage the funded research projects as use cases for development and refinement of data sharing processes and governance</li>
<li>Seek to strengthen global communities and multi-disciplinary collaboration from researchers in low- to middle-income countries (LMICs) by developing processes to enable South-South collaborative analysis</li>
<li>Develop adapted standards or Standard Operating Procedures that address data sharing issues including anonymization and perturbation protocols</li>
<li>Develop re-usable tools, protocols, and standards to collect, clean, harmonize, and commonly structure individual data and meta-data related to one or many disease areas to increase health data reliability and enable reuse. New tools and process development should leverage and build on existing work</li>
<li>Develop data informed processes to overcome barriers to the collection of complete and accurate information; and challenges related to data and information governance and data reuse</li>
</ul>
Capacity strengthening core
We seek to fund one capacity strengthening core to:
<ul>
<li>Support the research projects and the data infrastructure and governing core funded through this initiative</li>
<li>Bridge the gap between data scientists, modelers, regulators and policy makers, through trainings and best practices development</li>
<li>Develop re-usable training materials and handbooks</li>
<li>Lead and coordinate collaborative analysis efforts through different formats (workshops, hackathons, jamborees, etc.)</li>
<li>Lead capacity-building efforts targeting existing gaps in data science trainings in LMICs and building on existing initiatives (reusing available resources when available to avoid duplication of efforts)</li>
<li>Develop data-informed processes to overcome barriers to the collection of complete and accurate information, and challenges related to data and information governance and data reuse</li>
</ul>
Data re-use research projects
We seek to fund two data re-use projects where research will focus on one of more specific disease areas:
<ul>
<li>Build data-driven public health platforms, tools and dashboards that guide policy making and public health interventions</li>
<li>Identify, use, curate and link clearly defined datasets (administrative, clinical, environmental, etc.) to address policy gaps or deliver insights and conceptual and/or technological leaps on Global Health research priorities including:
<ul>
<li>Maternal, Newborn and Child Health</li>
<li>Infectious diseases</li>
<li>COVID-19 and pandemic preparedness</li>
</ul>
</li>
</ul>
<ul>
<li>Proposals could focus on a specific disease area but need to demonstrate commitment to providing access to all research products including tools and processes developed</li>
</ul>
Funding level 
Successful proposals will receive an award of up to USD $250,000 with an 18- to 24-month grant duration. While proposals require the collaborative participation of at least two investigators at institutions in different countries based in any of the regions listed above, proposals should be submitted by one primary applicant/institution. While restricted to one application per institution as the primary applicant, researchers may participate as collaborators in multiple collaborative applications.
Selected proposals will become part of a coordinated program aiming at Strengthening Data Science Capacity and the Ecosystem to Enable Data-Centered Public Health Interventions. We seek to build a network of researchers working together in close collaboration with the existing <a href="https://gcgh.grandchallenges.org/grants/JTdCJTIyc29ydCUyMiUzQSUyMmRlc2NlbmRpbmclMjIlMkMlMjJzb3J0RmllbGQlMjIlM0ElMjJkYXRlJTIyJTJDJTIybnVtYmVyUGVyUGFnZSUyMiUzQTEwMCUyQyUyMnBhZ2VOdW1iZXIlMjIlM0EwJTdE/JTdCJTIyeWVhcnMlMjIlM0ElNUIlNUQlMkMlMjJjaGFsbGVuZ2VzJTIyJTNBJTVCJTIyMTE3JTIyJTVEJTJDJTIydGVybXMlMjIlM0ElNUIlNUQlMkMlMjJpbml0aWF0aXZlcyUyMiUzQSU1QiU1RCUyQyUyMmxvY2F0aW9ucyUyMiUzQSU1QiU1RCU3RA==">Data Science Grand Challenges network</a> 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 to identify and address the global data-related challenges.
Successful proposals to be considered should: 
<ul>
<li>Be driven by a shared commitment to open science, data sharing, and building collaboration and analysis infrastructure to enable discoveries that will benefit people everywhere</li>
<li>Seek to strengthen global communities and multi-disciplinary collaboration from researchers in LMICs, and involve patients and the wider public</li>
<li>Involve substantial collaboration between at least two research institutions in different countries encompassing Africa, India, Bangladesh, Pakistan, Nepal, and Brazil. The suggested collaboration should be key to advancing the project goals and yield insights that are unlikely in the absence of the co-produced approaches. In addition, however, applications could include collaborations with institutions in other geographical areas</li>
<li>Have the potential to have impact on addressing public health issues within the proposed budget and timeframe of 18 -24 months</li>
<li>Data re-use proposals should use well-defined datasets that directly address the core research questions and have a clear governance plan and demonstrate how the data could benefit the broader community at a later stage.</li>
<li>Demonstrate a commitment to impact policies and the general public</li>
</ul>
We will not consider funding for: 
<ul>
<li>Studies that aim to collect and generate new data through this funding</li>
<li>Proposals led by institutions not based in any of these regions: Africa, India, Bangladesh, Pakistan, Nepal, and Brazil</li>
<li>Proposals that will involve a single research institution or solely involve collaborators from multiple institutions from the same country</li>
<li>Proposals that do not demonstrate a clear commitment to open science and making their findings, processes and/or tools developed accessible and reusable</li>
<li>Proposals that do not demonstrate how they would leverage existing work and networks</li>
<li>Proposals that do not demonstrate how they can benefit from and support other projects funded through this coordinated program</li>
<li>Proposals that are not accomplishable within the grant term</li>
</ul>

The scale and scope of the COVID-19 pandemic have reiterated the need for access to and analysis of timely accurate health data to support the implementation of control measures and to guide health interventions and evidence-based practices. The supporting infrastructures and capacities through which researchers access and analyze these data, however, vary greatly. For several reasons, researchers in the Global South often are skeptical of broad calls for data sharing when they are left out of the analysis and results interpretation.

Strengthening Data Science Capacity and the Ecosystem Enabling Data-Centered Public Health Interventions

<h2>Background</h2>

While mathematical modeling approaches have been used to understand malaria epidemiology and the potential impact of antimalarial interventions for some time, National Malaria Control Programs (NMCPs) across sub-Saharan Africa are showing a growing interest in working with modeling units to shape their National Strategic Plans and Global Fund applications, as well to evaluate the ongoing impact of control programs. Furthermore, R&amp;D partners in the malaria space are also increasingly working with modelers as part of the product development process, using quantitative insights to shape target product profiles, plan trials, and understand the market for a given product.

At present, many of the malaria modeling units contributing to these efforts are based in academic institutions in the Global North. At the Bill &amp; Melinda Gates Foundation, we believe that having local modeling expertise embedded within or easily accessible to NMCPs will improve programs' uptake of modeling as a strategic planning and evaluation tool, ultimately leading to improved data-driven decision-making by NMCPs. However, for this vision to be realized, the malaria modeling ecosystem across sub-Saharan Africa needs to be strengthened.

<h2>The Challenge</h2>

This RFP seeks innovative approaches to building a stronger malaria mathematical modeling ecosystem in sub-Saharan Africa. We are looking for 1 to 3 years projects that will achieve one or more of the objectives below:

<ul>
	<li>Increasing the number of Ph.D.-trained mathematical modelers with malaria expertise based at sub-Saharan African institutions</li>
	<li>Improving NMCP's understanding of and engagement with modeling approaches as a tool that can support strategic planning and/or evaluation work</li>
	<li>Connecting malaria Product Development Partners (PDPs) with sub-Saharan African modelers</li>
	<li>Bringing together discrete modeling units across sub-Saharan Africa to share expertise</li>
	<li>Improving modelers' access to timely, high-quality data</li>
</ul>

Funding level: up to USD $1,000,000 per year for each project, with a grant term of 1 to 3 years depending on the scope of the project.

We are looking for proposals that:

<ul>
	<li>Are led by a PI based in sub-Saharan Africa (other global partners may be included). Teams comprising multiple African institutions will be given preference over applicants from single institutions</li>
	<li>Demonstrate at least 80% of the funding is going to sub-Saharan African institutions</li>
	<li>Focus on improving geospatial and/or mathematical modeling capacity for malaria (other related diseases may be included; for example, modelers may also work on vector-borne neglected tropical diseases)</li>
	<li>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</li>
	<li>Demonstrate engagement with local and/or regional malaria decision-makers</li>
</ul>

We will not fund proposals that:

<ul>
	<li>Do not demonstrate that the majority of the work proposed will be undertaken by African scientists at African institutions</li>
	<li>Do not demonstrate a pathway to sustainable impact</li>
	<li>Do not engage local and/or regional malaria decision-makers</li>
	<li>Do not focus on expanding geospatial or mathematical modeling capacity</li>
</ul>

Building Malaria Modeling Capacity in Sub-Saharan Africa

<h2>Background</h2>
While mathematical modeling approaches have been used to understand malaria epidemiology and the potential impact of antimalarial interventions for some time, National Malaria Control Programs (NMCPs) across sub-Saharan Africa are showing a growing interest in working with modeling units to shape their National Strategic Plans and Global Fund applications, as well to evaluate the ongoing impact of control programs. Furthermore, R&amp;D partners in the malaria space are also increasingly working with modelers as part of the product development process, using quantitative insights to shape target product profiles, plan trials, and understand the market for a given product.
At present, many of the malaria modeling units contributing to these efforts are based in academic institutions in the Global North. At the Bill &amp; Melinda Gates Foundation, we believe that having local modeling expertise embedded within or easily accessible to NMCPs will improve programs' uptake of modeling as a strategic planning and evaluation tool, ultimately leading to improved data-driven decision-making by NMCPs. However, for this vision to be realized, the malaria modeling ecosystem across sub-Saharan Africa needs to be strengthened.
<h2>The Challenge</h2>
This RFP seeks innovative approaches to building a stronger malaria mathematical modeling ecosystem in sub-Saharan Africa. We are looking for 1 to 3 years projects that will achieve one or more of the objectives below:
<ul>
<li>Increasing the number of Ph.D.-trained mathematical modelers with malaria expertise based at sub-Saharan African institutions</li>
<li>Improving NMCP's understanding of and engagement with modeling approaches as a tool that can support strategic planning and/or evaluation work</li>
<li>Connecting malaria Product Development Partners (PDPs) with sub-Saharan African modelers</li>
<li>Bringing together discrete modeling units across sub-Saharan Africa to share expertise</li>
<li>Improving modelers' access to timely, high-quality data</li>
</ul>
Funding level: up to USD $1,000,000 per year for each project, with a grant term of 1 to 3 years depending on the scope of the project.
We are looking for proposals that:
<ul>
<li>Are led by a PI based in sub-Saharan Africa (other global partners may be included). Teams comprising multiple African institutions will be given preference over applicants from single institutions</li>
<li>Demonstrate at least 80% of the funding is going to sub-Saharan African institutions</li>
<li>Focus on improving geospatial and/or mathematical modeling capacity for malaria (other related diseases may be included; for example, modelers may also work on vector-borne neglected tropical diseases)</li>
<li>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</li>
<li>Demonstrate engagement with local and/or regional malaria decision-makers</li>
</ul>
We will not fund proposals that:
<ul>
<li>Do not demonstrate that the majority of the work proposed will be undertaken by African scientists at African institutions</li>
<li>Do not demonstrate a pathway to sustainable impact</li>
<li>Do not engage local and/or regional malaria decision-makers</li>
<li>Do not focus on expanding geospatial or mathematical modeling capacity</li>
</ul>

While mathematical modeling approaches have been used to understand malaria epidemiology and the potential impact of antimalarial interventions for some time, National Malaria Control Programs (NMCPs) across sub-Saharan Africa are showing a growing interest in working with modeling units to shape their National Strategic Plans and Global Fund applications, as well to evaluate the ongoing impact of control programs. This RFP seeks innovative approaches to building a stronger malaria mathematical modeling ecosystem in sub-Saharan Africa.

<h2>Background</h2>

Digital health is revolutionizing the landscape of global healthcare. Solutions such as telemedicine, electronic medical records, and digitally enabled devices help to provide accessible, high-quality care around the world. These services have the potential to be especially impactful in low-income areas where care provided by highly trained individuals is not as common. Digital health can empower individual patients by enabling them to manage their own healthcare journeys. It can also drive systemic change through affordable, wide-reaching services that reduce the strain on healthcare professionals and facilities in low-resource settings.

The Maternal, Newborn &amp; Child Health Discovery &amp; Tools team believes that the ability to leverage digital health systems can enhance care and reduce adverse birth outcomes in low-and-middle income countries. One area of focus is the stratification of pregnancy risk to ensure that patients are put on the appropriate care pathway. This can enable tertiary facilities to focus their constrained resources on high-risk pregnancies, while low-risk pregnancies are managed at lower levels of care. Antenatal Risk Stratification (ARS) is a portfolio of devices and data that predicts a pregnant woman’s risk of experiencing adverse birth outcomes in early pregnancy. Building and implementing an ARS solution requires three key steps. 1) Collect data on pregnant women (e.g., patient history, clinical data, and diagnostic results with an emphasis on ultrasound and hemoglobin assessment). 2) Use data as inputs in a robust, AI decision model that accurately predicts a pregnant woman’s risk of adverse birth outcomes. 3) Support clinical decision making by using the predicted risk to pre-emptively triage patients across different levels of the healthcare system. Through this process, ARS would enable more efficient resource allocation by sending the riskiest patients to high-level facilities, while referring low-risk patients to community or public health centers. ARS would aim to improve the quality of care for pregnant women by ensuring that they can receive the right level of care.

Developing and delivering an ARS solution will require a robust digital backbone including tools for data collection, automated analytics, and platforms that connect to patients and healthcare providers. Before ARS can be successfully implemented, a landscape of digital health devices, partners, and services must be put into place.

<h2>The Challenge</h2>

We seek patient-facing digital health services for pregnant women that have been developed and are actively being provided in sub-Saharan Africa (SSA). We will consider proposals for services that can support or contribute to our ARS vision via digital applications. Types of services that we would consider include:

<ul>
	<li>Engagement: Services that increase the participation of pregnant women in digital healthcare. (E.g., a platform to provide group antenatal care or a telemedicine platform that allows pregnant women to send medical questions to doctors by text)</li>
	<li>Adoption of existing platforms: Services that leverage existing digital systems/platforms to support pregnant women (e.g., contacting patients about care or scheduling using an existing messaging app like WhatsApp)</li>
	<li>Data collection: Services that collect data from pregnant women that could support clinical care. (E.g., a mobile app that allows pregnant women to track their pregnancy through metrics such as weight and fetal movement)</li>
	<li>Algorithm development: Services that use data from pregnant women to assess or make predictions about their health (e.g., a web-based tool where pregnant women can input information to receive an automatic assessment on whether or not they should see a doctor)</li>
</ul>

We seek projects that will help us develop and deliver an ARS solution in sub-Saharan Africa. Proposals should endeavor to build upon existing solutions to help support ARS. Potential options include (but are not limited to):

<ul>
	<li>Researching implementation methods for a solution (e.g., conducting market research for an existing app that supports one or more of the objectives outlined above)</li>
	<li>Expanding the scope of a solution (e.g., translating a web-based app to mobile platforms to increase engagement)</li>
	<li>Adding features/functionality to a solution (e.g., adding cloud-based data collection to a mobile app)</li>
	<li>Improving the delivery of a solution (e.g., integrating a mobile app into an existing clinical health system)</li>
</ul>

Funding level: up to USD $500,000 for each project, with a grant term of 6 to 24 months depending on the scope of the project.

We will consider solutions that are:

<ul>
	<li>Developed and/or actively supported in sub-Saharan Africa (note: development/active support does not include cases when groups outside of SSA are testing their solutions on users in SSA)</li>
	<li>Delivered in sub-Saharan Africa</li>
	<li>Providing pregnancy-related services</li>
	<li>Offered directly to pregnant women (i.e., patient-facing)</li>
	<li>Currently available for use and interested in expansion</li>
	<li>Serving a substantial and active user base in sub-Saharan Africa (e.g., more than ~100 users)</li>
	<li>Digitally integrated (i.e., have a strong, technical component) &nbsp;</li>
	<li>Clearly linked to the development and implementation of ARS</li>
	<li>Reaching women in both rural and urban areas in sub-Saharan Africa (note: this is a preference, not a requirement)</li>
</ul>

We will not consider solutions that are:

<ul>
	<li>Exclusively developed and maintained outside of sub-Saharan Africa</li>
	<li>Currently unavailable to pregnant women in sub-Saharan Africa</li>
	<li>Unrelated to pregnancy</li>
	<li>Targeted primarily towards health-care providers (e.g., doctors or health centers)</li>
	<li>Still in a proof-of-concept state (e.g., an idea for an app that has not yet been developed)</li>
	<li>Still being beta tested (e.g., an app that is not being offered to the general public)</li>
	<li>Primarily analog (i.e., are not digital services)</li>
	<li>Unrelated to the development and implementation of ARS</li>
</ul>

Digital Health Services for Pregnant Women to Support Antenatal Risk Stratification in Sub-Saharan Africa

<h2>Background</h2>
Digital health is revolutionizing the landscape of global healthcare. Solutions such as telemedicine, electronic medical records, and digitally enabled devices help to provide accessible, high-quality care around the world. These services have the potential to be especially impactful in low-income areas where care provided by highly trained individuals is not as common. Digital health can empower individual patients by enabling them to manage their own healthcare journeys. It can also drive systemic change through affordable, wide-reaching services that reduce the strain on healthcare professionals and facilities in low-resource settings.
The Maternal, Newborn &amp; Child Health Discovery &amp; Tools team believes that the ability to leverage digital health systems can enhance care and reduce adverse birth outcomes in low-and-middle income countries. One area of focus is the stratification of pregnancy risk to ensure that patients are put on the appropriate care pathway. This can enable tertiary facilities to focus their constrained resources on high-risk pregnancies, while low-risk pregnancies are managed at lower levels of care. Antenatal Risk Stratification (ARS) is a portfolio of devices and data that predicts a pregnant woman’s risk of experiencing adverse birth outcomes in early pregnancy. Building and implementing an ARS solution requires three key steps. 1) Collect data on pregnant women (e.g., patient history, clinical data, and diagnostic results with an emphasis on ultrasound and hemoglobin assessment). 2) Use data as inputs in a robust, AI decision model that accurately predicts a pregnant woman’s risk of adverse birth outcomes. 3) Support clinical decision making by using the predicted risk to pre-emptively triage patients across different levels of the healthcare system. Through this process, ARS would enable more efficient resource allocation by sending the riskiest patients to high-level facilities, while referring low-risk patients to community or public health centers. ARS would aim to improve the quality of care for pregnant women by ensuring that they can receive the right level of care.
Developing and delivering an ARS solution will require a robust digital backbone including tools for data collection, automated analytics, and platforms that connect to patients and healthcare providers. Before ARS can be successfully implemented, a landscape of digital health devices, partners, and services must be put into place.
<h2>The Challenge</h2>
We seek patient-facing digital health services for pregnant women that have been developed and are actively being provided in sub-Saharan Africa (SSA). We will consider proposals for services that can support or contribute to our ARS vision via digital applications. Types of services that we would consider include:
<ul>
<li>Engagement: Services that increase the participation of pregnant women in digital healthcare. (E.g., a platform to provide group antenatal care or a telemedicine platform that allows pregnant women to send medical questions to doctors by text)</li>
<li>Adoption of existing platforms: Services that leverage existing digital systems/platforms to support pregnant women (e.g., contacting patients about care or scheduling using an existing messaging app like WhatsApp)</li>
<li>Data collection: Services that collect data from pregnant women that could support clinical care. (E.g., a mobile app that allows pregnant women to track their pregnancy through metrics such as weight and fetal movement)</li>
<li>Algorithm development: Services that use data from pregnant women to assess or make predictions about their health (e.g., a web-based tool where pregnant women can input information to receive an automatic assessment on whether or not they should see a doctor)</li>
</ul>
We seek projects that will help us develop and deliver an ARS solution in sub-Saharan Africa. Proposals should endeavor to build upon existing solutions to help support ARS. Potential options include (but are not limited to):
<ul>
<li>Researching implementation methods for a solution (e.g., conducting market research for an existing app that supports one or more of the objectives outlined above)</li>
<li>Expanding the scope of a solution (e.g., translating a web-based app to mobile platforms to increase engagement)</li>
<li>Adding features/functionality to a solution (e.g., adding cloud-based data collection to a mobile app)</li>
<li>Improving the delivery of a solution (e.g., integrating a mobile app into an existing clinical health system)</li>
</ul>
Funding level: up to USD $500,000 for each project, with a grant term of 6 to 24 months depending on the scope of the project.
We will consider solutions that are:
<ul>
<li>Developed and/or actively supported in sub-Saharan Africa (note: development/active support does not include cases when groups outside of SSA are testing their solutions on users in SSA)</li>
<li>Delivered in sub-Saharan Africa</li>
<li>Providing pregnancy-related services</li>
<li>Offered directly to pregnant women (i.e., patient-facing)</li>
<li>Currently available for use and interested in expansion</li>
<li>Serving a substantial and active user base in sub-Saharan Africa (e.g., more than ~100 users)</li>
<li>Digitally integrated (i.e., have a strong, technical component) &nbsp;</li>
<li>Clearly linked to the development and implementation of ARS</li>
<li>Reaching women in both rural and urban areas in sub-Saharan Africa (note: this is a preference, not a requirement)</li>
</ul>
We will not consider solutions that are:
<ul>
<li>Exclusively developed and maintained outside of sub-Saharan Africa</li>
<li>Currently unavailable to pregnant women in sub-Saharan Africa</li>
<li>Unrelated to pregnancy</li>
<li>Targeted primarily towards health-care providers (e.g., doctors or health centers)</li>
<li>Still in a proof-of-concept state (e.g., an idea for an app that has not yet been developed)</li>
<li>Still being beta tested (e.g., an app that is not being offered to the general public)</li>
<li>Primarily analog (i.e., are not digital services)</li>
<li>Unrelated to the development and implementation of ARS</li>
</ul>

Digital health is revolutionizing the landscape of global healthcare. Solutions such as telemedicine, electronic medical records, and digitally enabled devices help to provide accessible, high-quality care around the world. We seek patient-facing digital health services for pregnant women that have been developed and are actively being provided in sub-Saharan Africa (SSA). We will consider proposals for services that can support or contribute to our ARS vision via digital applications.

<h2>Background</h2>

The elimination of neglected tropical diseases (NTDs) is feasible but its progress is hindered by the suboptimal implementation of available interventions. Challenges faced by NTD programs can range from poor targeting of interventions, low treatment coverage among specific sub-groups, and lack of surveillance systems that can meet the sensitivity and specificity requirements for the endgame of disease elimination. These challenges could be addressed by the development of innovative solutions but also by the application of existing tools and technologies which are effectively used by other health programs, including polio, malaria and immunization. We see an opportunity to identify and demonstrate feasibility of innovative solutions and new applications of existing technologies to address the challenges faced by national NTD programs in mapping, targeting, disease and vector surveillance, and other endgame strategies.

<h2>The Challenge</h2>

We have partnered with <a href="https://twitter.com/kikundi_cop" target="_blank">Kikundi</a>, a community of practice for NTD program managers in Africa, to identify areas for transformational innovation in service of national NTD programs. We invite proposals that will address one or more of the following areas:

<ul>
	<li>Methods to rapidly map NTDs, including integrated mapping</li>
	<li>Methods to better target existing interventions</li>
	<li>Strategies to target subgroups routinely missed by programs</li>
	<li>Approaches to vector surveillance</li>
	<li>Integrated surveillance that leverages other health surveillance platforms</li>
	<li>Strategies for post-elimination surveillance, including cross-border surveillance.</li>
</ul>

Funding level: up to USD $200,000 for each project, with a grant term of up to 18 months depending on the scope of the project.

We are looking for proposals that:

<ul>
	<li>Are led by institutions, which could be ministries of health, based in sub-Saharan Africa or South Asia (other global partners may be included but at least 80% of funding should go to sub-Saharan Africa or South Asia)</li>
	<li>Demonstrate partnership with national NTD programs</li>
	<li>Propose innovations and applications that are scalable</li>
	<li>Have a plan for how the proposed solution would be tested or validated, and report its impact on NTD elimination goals and program efficiency</li>
</ul>

We will not consider proposals that:

<ul>
	<li>Do not include a lead investigator from an NTD-endemic country</li>
	<li>Do not consider explicit collaboration with endemic country governments, government NTD programs and/or partners</li>
	<li>Focus on current NTD intervention delivery or piloting of tools already used by NTD programs</li>
	<li>Do not outline a clear path forward to scale and sustainable impact</li>
</ul>

Innovations in Eliminating Neglected Tropical Diseases

<h2>Background</h2>
The elimination of neglected tropical diseases (NTDs) is feasible but its progress is hindered by the suboptimal implementation of available interventions. Challenges faced by NTD programs can range from poor targeting of interventions, low treatment coverage among specific sub-groups, and lack of surveillance systems that can meet the sensitivity and specificity requirements for the endgame of disease elimination. These challenges could be addressed by the development of innovative solutions but also by the application of existing tools and technologies which are effectively used by other health programs, including polio, malaria and immunization. We see an opportunity to identify and demonstrate feasibility of innovative solutions and new applications of existing technologies to address the challenges faced by national NTD programs in mapping, targeting, disease and vector surveillance, and other endgame strategies.
<h2>The Challenge</h2>
We have partnered with <a href="https://twitter.com/kikundi_cop" target="_blank" rel="noopener noreferrer">Kikundi</a>, a community of practice for NTD program managers in Africa, to identify areas for transformational innovation in service of national NTD programs. We invite proposals that will address one or more of the following areas:
<ul>
<li>Methods to rapidly map NTDs, including integrated mapping</li>
<li>Methods to better target existing interventions</li>
<li>Strategies to target subgroups routinely missed by programs</li>
<li>Approaches to vector surveillance</li>
<li>Integrated surveillance that leverages other health surveillance platforms</li>
<li>Strategies for post-elimination surveillance, including cross-border surveillance.</li>
</ul>
Funding level: up to USD $200,000 for each project, with a grant term of up to 18 months depending on the scope of the project.
We are looking for proposals that:
<ul>
<li>Are led by institutions, which could be ministries of health, based in sub-Saharan Africa or South Asia (other global partners may be included but at least 80% of funding should go to sub-Saharan Africa or South Asia)</li>
<li>Demonstrate partnership with national NTD programs</li>
<li>Propose innovations and applications that are scalable</li>
<li>Have a plan for how the proposed solution would be tested or validated, and report its impact on NTD elimination goals and program efficiency</li>
</ul>
We will not consider proposals that:
<ul>
<li>Do not include a lead investigator from an NTD-endemic country</li>
<li>Do not consider explicit collaboration with endemic country governments, government NTD programs and/or partners</li>
<li>Focus on current NTD intervention delivery or piloting of tools already used by NTD programs</li>
<li>Do not outline a clear path forward to scale and sustainable impact</li>
</ul>

The elimination of neglected tropical diseases (NTDs) is feasible but its progress is hindered by a paucity of effective intervention tools, the suboptimal implementation of existing tools, or both. We see an opportunity to identify and demonstrate feasibility of new applications of cutting-edge technologies used by other disease areas to address the challenges faced by national NTD programs and accelerate the elimination of NTDs.

The COVID-19 pandemic is a turning point for global health. It has emphasized how fragile progress can be, exposed major gaps in the global health system, and highlighted opportunities to change how we work to get better results, faster.In order to restore progress, fill those gaps, and seize those opportunities, the world needs even more strong science leadership in communities around the world. For this program, we believe "leadership" is demonstrated by scientists who have not only the expertise to do transformative science on the ground but also the experience, networks, and skills to anchor health and development R&amp;D in their communities, design or co-design projects with local and global partners, and mobilize key institutions in their countries. To help meet this need, the Bill &amp; Melinda Gates Foundation (BMGF) is launching the Calestous Juma Fellowship program for scientists permanently located at an African research organization.The fellowship is designed around a holistic view of leadership, so, in addition to five years of funding, the program will provide networking opportunities and access to trainings in critical non-scientific skills. Rather than focusing on a specific discipline or problem set, our hope is to establish a cohort of fellows with a wide range of expertise and interests so they can complement and support each other as a collaborative community of practice.NOTE: This opportunity was open to an invited set of African investigators. Please see the <a href="https://gcgh.grandchallenges.org/champions" target="_blank">Calestous Juma Science Leadership Fellowship</a> page for more information.

Calestous Juma Science Leadership Fellowship

The COVID-19 pandemic is a turning point for global health. It has emphasized how fragile progress can be, exposed major gaps in the global health system, and highlighted opportunities to change how we work to get better results, faster.
In order to restore progress, fill those gaps, and seize those opportunities, the world needs even more strong science leadership in communities around the world. For this program, we believe "leadership" is demonstrated by scientists who have not only the expertise to do transformative science on the ground but also the experience, networks, and skills to anchor health and development R&amp;D in their communities, design or co-design projects with local and global partners, and mobilize key institutions in their countries. To help meet this need, the Bill &amp; Melinda Gates Foundation (BMGF) is launching the Calestous Juma Fellowship program for scientists permanently located at an African research organization.
The fellowship is designed around a holistic view of leadership, so, in addition to five years of funding, the program will provide networking opportunities and access to trainings in critical non-scientific skills. Rather than focusing on a specific discipline or problem set, our hope is to establish a cohort of fellows with a wide range of expertise and interests so they can complement and support each other as a collaborative community of practice.
NOTE: This opportunity was open to an invited set of African investigators.

The COVID-19 pandemic is a turning point for global health. It has emphasized how fragile progress can be, exposed major gaps in the global health system, and highlighted opportunities to change how we work to get better results, faster.