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>Artificial Intelligence (AI) has significant potential to transform healthcare around the world. But as AI technology continues to advance, there is an urgent need to position low- and middle-income countries<a href="#_ftn1" title="" id="_ftnref1" name="_ftnref1">[i]</a> (LMICs) to lead on the design and co-creation of AI-enabled technologies – thereby helping to improve the health and well-being of their women, children, and vulnerable communities. Through this call for proposal, we are emphasizing AI solutions that are locally driven and owned hence more relevant to address the needs of people they intend to serve and more likely to be accepted and used by local communities.Responsible global use of AI entails a safe, equitable, transparent, reliable, and beneficial process that is adhered to with a high level of accountability. As the world rapidly moves to seize AI's opportunities, it is imperative to monitor and mitigate the safety, ethical, equity, and reliability dimensions of AI deployment. This will allow the enormous resilience, creativity, and commitment of researchers, scientists, and policymakers to capture the full capability of AI for lasting good.Grand Challenges (GC) partners including GC Brazil, GC Ethiopia, GC India, GC Senegal, GC South Africa, and GC Africa (pan-African), along with the Bill &amp; Melinda Gates Foundation, the Patrick J. McGovern Foundation, and the Pasteur Network, have jointly discussed the need for an equitable and responsible approach to the use of AI and specifically Large Language Models (LLMs) in LMICs. This call by the various GC partners is a follow-up to the initial call by the Bill &amp; Melinda Gates Foundation representing collaborative steps towards identifying, nurturing, and catalyzing the creativity, energy, and skills that researchers, implementers, governments, and technical partners have demonstrated in solving specific challenges in their countries and regions through LLMs. We are optimistic that this family of related AI RFPs will provide a platform for potentially transformative solutions to improve the lives and conditions for numerous vulnerable communities.Note that this request for proposals is being launched by six Grand Challenges partners: African researchers located in Ethiopia, Senegal, and South Africa, should apply through the corresponding country specific Grand Challenges portal; African researchers located in all other African countries should apply through the Grand Challenges Africa portal; Brazilian researchers located in Brazilian organizations should apply through the Grand Challenges Brazil portal; and Indian researchers located in Indian organizations should apply through the Grand Challenges India portal. Eligible Pasteur Network sites located in Africa should apply through Grand Challenges Africa and Pasteur Network sites located in Brazil should apply through Grand Challenges Brazil. All other eligible Pasteur Network sites (not located in Africa or Brazil) should apply through Grand Challenges Senegal. Please consult the information provided in the subsection referencing geography of interest on the linked partner site to ensure that your application fits the requirements of the RFP you are applying to._______________________________________________________<a href="#_ftnref1" title="" id="_ftn1" name="_ftn1">[i]</a> See <a href="https://data.worldbank.org/country/XO" target="_blank">World Bank – Low Income Countries</a> for definitions.

Grand Challenges Brazil

Grand Challenges Brazil: Catalyzing Equitable Artificial Intelligence (AI) Use to Improve Global Health

<h2>Background</h2>
Artificial Intelligence (AI) has significant potential to transform healthcare around the world. But as AI technology continues to advance, there is an urgent need to position low- and middle-income countries<a href="#_ftn1" title name="_ftnref1" id="_ftnref1">[i]</a> (LMICs) to lead on the design and co-creation of AI-enabled technologies – thereby helping to improve the health and well-being of their women, children, and vulnerable communities. Through this call for proposal, we are emphasizing AI solutions that are locally driven and owned hence more relevant to address the needs of people they intend to serve and more likely to be accepted and used by local communities.
Responsible global use of AI entails a safe, equitable, transparent, reliable, and beneficial process that is adhered to with a high level of accountability. As the world rapidly moves to seize AI's opportunities, it is imperative to monitor and mitigate the safety, ethical, equity, and reliability dimensions of AI deployment. This will allow the enormous resilience, creativity, and commitment of researchers, scientists, and policymakers to capture the full capability of AI for lasting good.
Grand Challenges (GC) partners including GC Brazil, GC Ethiopia, GC India, GC Senegal, GC South Africa, and GC Africa (pan-African), along with the Bill &amp; Melinda Gates Foundation, the Patrick J. McGovern Foundation, and the Pasteur Network, have jointly discussed the need for an equitable and responsible approach to the use of AI and specifically Large Language Models (LLMs) in LMICs. This call by the various GC partners is a follow-up to the initial call by the Bill &amp; Melinda Gates Foundation representing collaborative steps towards identifying, nurturing, and catalyzing the creativity, energy, and skills that researchers, implementers, governments, and technical partners have demonstrated in solving specific challenges in their countries and regions through LLMs. We are optimistic that this family of related AI RFPs will provide a platform for potentially transformative solutions to improve the lives and conditions for numerous vulnerable communities.
Note that this request for proposals is being launched by six Grand Challenges partners: African researchers located in Ethiopia, Senegal, and South Africa, should apply through the corresponding country specific Grand Challenges portal; African researchers located in all other African countries should apply through the Grand Challenges Africa portal; Brazilian researchers located in Brazilian organizations should apply through the Grand Challenges Brazil portal; and Indian researchers located in Indian organizations should apply through the Grand Challenges India portal. Eligible Pasteur Network sites located in Africa should apply through Grand Challenges Africa and Pasteur Network sites located in Brazil should apply through Grand Challenges Brazil. All other eligible Pasteur Network sites (not located in Africa or Brazil) should apply through Grand Challenges Senegal. Please consult the information provided in the subsection referencing geography of interest on the linked partner site to ensure that your application fits the requirements of the RFP you are applying to.
_______________________________________________________
<a href="#_ftnref1" title name="_ftn1" id="_ftn1">[i]</a> See <a href="https://data.worldbank.org/country/XO" target="_blank" rel="noopener noreferrer">World Bank – Low Income Countries</a> for definitions.

Artificial Intelligence (AI) has significant potential to transform healthcare around the world. But as AI technology continues to advance, there is an urgent need to position low- and middle-income countries (LMICs) to lead on the design and co-creation of AI-enabled technologies – thereby helping to improve the health and well-being of their women, children, and vulnerable communities. Through this call for proposal, we are emphasizing AI solutions that are locally driven and owned hence more relevant to address the needs of people they intend to serve and more likely to be accepted and used by local communities.

Grand Challenges Brazil Catalyzing Equitable Artificial Intelligence (AI) Use to Improve Global Health

The National Council for Scientific and Technological Development (CNPq), the Department of Science and Technology at the Secretariat of Science, Technology, Innovation and Strategic Inputs for Health (Decit/SCTIE/MS) and the Bill &amp; Melinda Gates Foundation (BMGF), launch this public Request for Proposals (RFP), and invite all interested parties to present their proposals on the basis of what is hereby established.

<h2>1. Objective</h2>

To support research projects that intend to contribute significantly to the scientific and technologic development and to innovation in the country, in the field of data sciences, to improve Maternal and Child Health, Women’s Health and the Health of Children in Brazil.

<ol start="1">
	<li>1 The present RFP has the objective of:
	<ol type="a">
		<li>Selecting and contracting proposals in accordance with research topics defined in subitem 1.2.</li>
		<li>Promoting actions for scientific education and dissemination to different target groups, so as to achieve broad social reach, including experts, groups and institutions that act in the area of formal and informal education, (eg. schools, extension studies, museums, science centers, zoos, botanical gardens, aquariums, conservation units' visitor centers and NGOs).</li>
	</ol>
	</li>
</ol>

<ol start="1">
	<li>2 Proposals shall comply with the research lines and study types:</li>
</ol>

<ol type="i">
	<li>Cross sectional

	<ol type="a">
		<li>To apply innovative and technical analysis that employ machine learning to identify data patterns and natural experiments (e.g. the impact of economic cycles on primary care quality);</li>
		<li>To analyze primary health care distribution and quality and its relation with health outcomes and infant and maternal nutrition;</li>
		<li>To present prospective scenarios in Infant and Maternal Health, evaluating populational and epidemiological trends, to support the planning of programmatic activities and the identification of opportunities for intervention;</li>
		<li>To develop monitoring, visualization, simulation, and health indicator projection tools that support the management of public health programs related to women health, child health, and nutrition programs.</li>
	</ol>
	</li>
	<li>Children's Health
	<ol type="a">
		<li>Development of tools to monitor indicators at the local and federal levels related to growth and development curves and tools that evaluate the impact of social and environmental determinants on child development;</li>
		<li>To develop geo-referenced prediction models with vulnerability risk stratification for infant mortality, including its components: neonatal mortality (total, early and late) and post-neonatal mortality, and / or childhood mortality (under 5 years);</li>
		<li>To assess the impact of vertical or perinatal transmission of diseases such as Zika, Syphilis, HPV and other Sexually Transmitted Infections (STIs) on the health and development of newborns and children;</li>
		<li>To assess infectious and non-infectious factors related to the occurrence of changes in growth and development during pregnancy and up until early childhood;</li>
		<li>Studies on health care for children with congenital anomalies, such as congenital Zika syndrome;</li>
		<li>To develop predictive models for the development of chronic diseases such as hypertension in children whose mothers had eclampsia, pre-eclampsia and hypertension, or even diabetes in children whose mothers were diabetic or had gestational diabetes.</li>
	</ol>
	</li>
	<li>Women's Health
	<ol type="a">
		<li>To develop and/or evaluate strategies for the reduction of maternal mortality, considering the main causes, estimation of preventable deaths and potential recommendations to improve public policies in this field;</li>
		<li>To compare the quality of care provided to women (including adolescents) during prenatal visits, labor and in services related to sexual violence, taking into account the racial variable;</li>
		<li>To evaluate access and quality of the prenatal care (according to MOH protocols) per Federation Unit and per city, taking into account urban, rural and remote areas;</li>
		<li>To assess the coverage of contraceptive methods in specific populations and in those with difficulties to access them;</li>
		<li>To identify factors associated with alcohol and drug abuse among women and their impact on health outcomes;</li>
		<li>To develop instruments to assess how the type of delivery impacts the health of woman and child;</li>
		<li>To assess the impact of teenage pregnancy on the health of the woman and child;</li>
		<li>To develop predictive models of pregnant women who may develop gestational diabetes or eclampsia;</li>
		<li>To present analyses of the causes, levels and trends of premature birth in different regions; evaluations of the effectiveness of interventions to prevent premature birth; and to develop recommendations on how to prevent premature birth.</li>
	</ol>
	</li>
	<li>Food and Nutrition
	<ol type="a">
		<li>To evaluate interventions performed in Primary Health Care to control dietary risk factors for chronic conditions and nutritional problems in women, children and during pregnancy;</li>
		<li>To analyze the supply and quality of Primary Health Care and its relationship with outcomes in maternal and child health and nutrition;</li>
		<li>To develop predictive and risk stratification models for outcomes related to the double burden of malnutrition, especially on women and children;</li>
		<li>To study breastfeeding and / or food intake and nutritional and health outcomes (nutritional status, deaths, hospitalizations) based on data from SISVAN and from other health information systems, preferably those that assess vulnerable populations at different stages of their lives;</li>
		<li>To develop geo-referencing tools that provide visualization of data on breastfeeding and / or food intake and nutritional status of the Brazilian population based on the SISVAN data, as disaggregated as possible</li>
		<li>To assess the impact of nutritional status, gestational weight gain and health status on maternal and child outcomes based on data from the SISVAN;</li>
		<li>To assess the relationship between breastfeeding and child health outcomes (nutritional status, deaths, hospitalizations) using data from the Food and Nutrition Surveillance System (SISVAN) and other information systems, preferably those including assessment in vulnerable populations.</li>
	</ol>
	</li>
</ol>

<ol start="1">
	<li>3 We encourage submitting proposals that consider the impacts of COVID-19 on the topics defined in the item 1.2, such as, for example, the impact of the pandemic on access to healthcare during the prenatal period and after delivery, on gestational health, on birth-related rates, premature birth, nutrition and other factors that can impact pregnancy and child development outcomes.</li>
</ol>

<ol start="1">
	<li>4 We encourage projects to be developed in collaboration with other research centers or individual researchers.</li>
</ol>

<ol start="1">
	<li>5 We seek proposals focused on addressing scientific matters related to the outcomes in development and in maternal and child health, women and children's health. Projects must use innovative approaches to data analysis and modeling that can be applied to databases from DATASUS/MS, in CIDACS (Cohort 100M SINASC-SIM-SISVAN), at ICICT/FIOCRUZ, or to other datasets that the candidate have access to.</li>
</ol>

<ol start="1">
	<li>6 Proposals must be based on linked data sets or on existing secondary data in Brazil, with the potential to produce practical results with the potential to be implemented in health care services and which may significantly impact public health policies. Further detail on this data can be found on <a href="https://www.synapse.org/#!Synapse:syn22088071/wiki/." target="_blank">https://www.synapse.org/#!Synapse:syn22088071/wiki/.</a></li>
</ol>

<ol start="1">
	<li>7 Studies of different designs that allow, according to the proposed methods, to achieve the expect outcomes shall be granted</li>
</ol>

<ol start="1">
	<li>7.1 Examples of what we are looking for. Proposals that:
	<ol type="a">
		<li>Support innovative collaboration among researchers, health experts and Brazilian data scientists;</li>
		<li>Answer scientific questions identified in this GCE RFP, while developing and strengthening the capacity of data sciences in Brazil;</li>
		<li>Consider the social, environmental and cultural determinants of health and incorporate in the results a broad understanding of the studied community;</li>
		<li>Include the mapping of barriers and restrictions to effective health interventions and contribute to inform the implementation of evidence-based public health programs;</li>
		<li>Contribute to a portfolio of funded projects that address regional diversities and the need to provide health equity to diverse and vulnerable populations;</li>
		<li>Explain how results are more likely to become relevant in a broad implementation in the public health system;</li>
		<li>Show relation with the implementation and evaluation of primary health care, whenever possible;</li>
		<li>Describe mechanistic models so as to establish the relationship between interventions and their results;</li>
		<li>Perform analysis of indicators, impact analysis, visualizations and predictive models that support the management of public health programs, whenever relevant.</li>
		<li>Propose and validate tools for disseminating high-volume data.</li>
	</ol>
	</li>
</ol>

<ol start="1">
	<li>8 Proposals for literature review or systematic review shall not be funded.</li>
</ol>

<ol start="1">
	<li>8.1 Examples of what we are NOT looking for:
	<ol>
	</ol>

	<ol type="a">
		<li>Proposals submitted by applicants that are not based in Brazil or that aim at studying health conditions outside of the Brazilian territory;</li>
		<li>Proposals for studies that depend on the collection of primary data;</li>
		<li>Proposals that develop tools for collecting new primary data;</li>
		<li>Proposals that do not address women's health, children’s health or maternal and child health;</li>
		<li>Projects that propose the development of a scientific data algorithm without clear relevance to the issues described in this call;</li>
		<li>Ideas without a hypothesis that is clearly defined and tested by metrics of success;</li>
		<li>Proposals that cannot be developed within the scope of GCE Phase 1 funding; (R$ 550,000,00 over 18 months);</li>
		<li>Proposals that do not describe the potential impacts of innovation on the formulation of health policies;</li>
		<li>Analyzes that would only bring minor improvements to existing approaches (e.g., in the absence of additional innovation, merely replicating an approach in a new geography).</li>
	</ol>
	</li>
</ol>

Grand Challenges Explorations – Brazil: Data Science Approaches to Improve Maternal and Child Health, Women's Health and Children's Health in Brazil

Grand Challenges Explorations – Brazil Data Science Approaches to Improve Maternal and Child Health Womens Health and Childrens Health in Brazil

Note: This document is an unofficial and translated summary of the official notice issued by the Ministry of Health. For complete information, refer to the <a href="http://www.cnpq.br/web/guest/chamadas-publicas?p_p_id=resultadosportlet_WAR_resultadoscnpqportlet_INSTANCE_0ZaM&amp;filtro=abertas&amp;detalha=chamadaDivulgada&amp;idDivulgacao=9202" target="_blank">complete notice in Portuguese</a>

The National Council for Scientific and Technological Development (CNPq), the Ministry of Health (MS), through the Department of Science and Technology of the Secretariat of Science, Technology and Strategic Inputs (Decit/SCTIE) and the Bill &amp; Melinda Gates Foundation make this Call for Proposals public and invite interested parties to submit proposals under the terms set forth herein.

1. Scope

To support research projects that bring significant contribution to the scientific and technological development and innovation of the country, in the areas of prevention, detection and fight against malaria.

1.1 This Call for Proposals has the following goals: To support the development of scientific and technological research (about prevention, detection and fight against malaria in Brazil) that can effectively contribute to the advancement in knowledge, training of human resources, creation of products and improvement of health surveillance programs, control, elimination and prevention of this neglected disease, so as to achieve the Sustainable Development Goals, in line with elimination program established by the World Health Organization, with the purpose of improving the health conditions of Brazilian population.

1.2 Projects should be classified according to the following Themes or Lines of Research:

1.2.1 Treatment:

1.2.1.1 Evaluation of adherence to malaria treatment in Brazil and compliance with the therapeutic regimens recommended by the Ministry of Health.

1.2.1.2 Goal: To support studies that assess strategies to encourage the adherence to treatment in patients with malaria, as well as studies that help assess the effectiveness of therapeutic regimens recommended by the Ministry of Health, so as to promote the improvement of current protocols.

1.2.2. Diagnosis and Epidemiology:

1.2.2.1 Strategies to improve surveillance of malaria cases in the Amazon, in order to better understand the outbreaks of infection and the impact of migration patterns.

1.2.2.1.1 Goal: To support studies that propose new approaches to malaria control and registration in the states that make up the Amazon region; new strategies for the early identification of outbreaks in the region; and studies to assess outcomes related to migration flows in this region.

1.2.2.2 Development of new diagnostic methods and surveillance approaches for P. vivax in patients with low parasitemia, including the detection of latent and sub-clinical infection in humans.

1.2.2.2.1 Goal: To support studies that develop more sensitive methodologies and strategies to detect low parasitemia, aiming to improve surveillance of latent or low parasitemia cases.

1.2.2.3 Development of tests that detect hypnozoites and relapse biomarkers.

1.2.2.3.1 Goal: To support the development of efficient methodological proposals for the detection of hypnozoites and the prediction of malaria relapse.

1.2.2.4 Development and validation of malaria diagnostic technologies in remote areas, in locations which are difficult to access or without electricity.

1.2.2.4.1 Goal: To support the development and improvement of malaria diagnostic strategies in vulnerable populations living in areas without adequate infrastructure or poor health care coverage.

1.2.2.5 Evaluation of sensitivity, specificity and cost-effectiveness of new diagnostic methods compared to microscopy.

1.2.2.5.1 Goal: To support studies that evaluate whether new diagnostic methods for malaria are more sensitive, specific and economically viable than the P. vivax microscopic detection method.

1.2.3 Vector Biology and Control:

1.2.3.1 Studies in vector biology, including vector pathogen interactions, vector ecology and its geographical distribution.

1.2.3.1.1 Goal: To support studies that increase knowledge about the vector, including its biology, interaction with the plasmodium and relationship with the environment, with the purpose of preventing transmission.

1.2.3.2 New tools for vector control and management of insecticide resistance.

1.2.3.2.1 Goal: To support studies that develop more effective tools for vector control and for overcoming of insecticide resistance.

1.2.3.3 Studies on minimal parasitic burden for the infection of anophelines and malaria transmission to humans.

1.2.3.3.1 Goal: To support studies that evaluate and determine the lowest parasite burden required in the vector and in humans, to maintain malaria endemicity.

1.2.3.4 Evaluation of impact and costs associated with strategies and use of insecticides to control malaria vectors.

1.2.3.4.1 Goal: To support studies that measure the economic, environmental and health impact of strategies adopted by health professionals in the control of anopheles mosquitoes.

1.2.4 Economic Impact Assessment of Social Technologies:

1.2.4.1 Economic impact assessment of uncomplicated and severe malaria cases in areas with and without transmission of the disease in Brazil.

1.2.4.1.1 Goal: To support the development of studies that provide an understanding of the economic impact of malaria in endemic (with transmission) and non-endemic (without transmission) areas of Brazil and the development of more accurate tools for this assessment.

1.2.4.2 Assessment of public perception of malaria and their acceptance / satisfaction with the control strategies implemented in Brazil.

1.2.4.2.1 Goal: To support the development of studies on the failures / successes of malaria control measures implemented by the health manager, by assessing popular perception, and proposing more effective alternatives to improve surveillance and health care services.

1.2.5 For all lines of this Call for Proposals, projects are expected to propose solutions that:

<ol type="a">
	<li>Are audacious and clearly different from standard practice;</li>
	<li>Are practical, affordable and scalable;</li>
	<li>Provide ensured access to vulnerable populations;</li>
	<li>Can cause significant and sustainable impact;</li>
	<li>Can be monitored, measured and evaluated.</li>
</ol>

1.2.6 The following shall not be accepted:

<ol start="6" type="a">
	<li>Basic research not directly related to malaria prevention and control;</li>
	<li>Studies proposing solutions that apply only a small number of individuals at risk of being infected with malaria;</li>
	<li>Projects that are not scalable by their very nature or because they apply only to a small subgroup of the population;</li>
	<li>Projects without adequate assessment measures of success or failure that will support decisions on funding continuation;</li>
	<li>Studies proposing solutions that represent only limited advances of existing approaches;</li>
	<li>Studies that propose a repetition of an approach in a new geographical location, without adding innovation.</li>
</ol>

1.2.7 Proposals for literature review or systematic studies shall not be funded.

Research on Malaria Prevention, Detection, and Control

Brazil's National Council for Scientific and Technological Development (CNPq) and Ministry of Health - through the Department of Science and Technology of the Secretariat of Science, Technology and Strategic Inputs (Decit/SCTIE) - with the Bill &amp; Melinda Gates Foundation are inviting proposals for solutions to accelerate impact from malaria research in three areas: treatment, diagnostics and epidemiology, and vector biology and control.

Research on Malaria Prevention Detection and Control

Appropriate antibiotic use has the power to save lives in the most vulnerable communities, and antimicrobial resistance (AMR) impacts multiple global health priority areas: HIV/AIDS, tuberculosis, maternal and neonatal health, pneumonia, and enteric and diarrheal diseases. It is critical to better understand the prevalence of AMR and its impact on mortality in developing countries so that access to appropriate antibiotics is ensured while inappropriate use of antibiotics is limited. In particular, there is a need to better understand resistance in bacterial infections of newborns and young children – and to this end, understanding what is the prevalence of AMR in the community, how it impacts mortality, and how it impacts health targets. Tackling AMR will require a global, coordinated approach and the linking together of different research communities for new perspectives on the problem.

Note that this request for proposals is being launched on sequential dates by four Grand Challenges partnerships: African researchers located in African organizations should apply through the joint Grand Challenges Africa/Grand Challenges South Africa portal; Brazilian researchers located in Brazilian organizations should apply through the Grand Challenges Brazil portal; and Indian researchers located in Indian organizations should apply through the Grand Challenges India portal.

<h3>What we are looking for:</h3>

We seek new approaches that have the potential to transform public health action on a regional or global scale by identifying and filling gaps in knowledge on the burden of resistance to antibacterial agents – we are not seeking incremental improvements in typical disease surveillance solutions. Specifically, we seek projects that propose innovation in the following areas:

<ul>
	<li>Data sources: Pilot tests of new sources of data, particularly those that would bring together different research communities from different disciplines for new perspectives on the problem</li>
	<li>Analytical methods: Pilot tests of bioinformatics approaches, including new ways to analyze, combine or connect existing databases</li>
	<li>Biomarkers: Pilot tests of new biomarkers or combinations of biomarkers that could lead to new understanding of the actionable implications of antimicrobial resistance surveillance data</li>
	<li>Low-cost technologies and products: Exploratory work in developing new technologies and products, including 1) those that specifically target improved infection prevention and control in healthcare settings to reduce reliance on healthcare provider behavior change, and 2) technologies to remove antibiotics from effluents</li>
</ul>

<h3>We will give highest priority to those projects that:</h3>

<ul>
	<li>Pilot test approaches that could be added to existing surveillance platforms, since we are not seeking to create new surveillance platforms</li>
	<li>Incorporate multiple of the areas of innovation listed above</li>
	<li>Could contribute to a portfolio of funded projects that addresses a country’s regional diversity and the diversity of vulnerable populations</li>
	<li>Explain how proposed approaches will be tested so that they have the highest likelihood of being relevant for implementation in the country’s public health system</li>
</ul>

<h3>Examples of what we are looking for:</h3>

<ul>
	<li>Characterizes type examples of the burden of AMR (e.g., exploring the role of AMR in community or hospital sepsis-related mortality, focusing on children)</li>
	<li>Includes data sources that could indirectly reflect AMR burden (e.g., antimicrobial usage patterns or specifically how vaccination against respiratory or diarrheal diseases impacts antimicrobial use)</li>
	<li>Addresses the diversity of vulnerable populations and the different aspects of the AMR burden that might be reflected in urban versus rural settings</li>
	<li>Includes data sources ranging from the level of the individual (e.g., microbiome across body sites) to the community (e.g., public toilets and sanitation systems), while maintaining a focus on gaining new understanding of the actionable consequences of AMR gene flow.</li>
	<li>Includes data sources that could reflect AMR transmission dynamics between communities (e.g., modes of transportation) or within communities over time (e.g., seasonal-related behaviors)</li>
	<li>Provides an ecological perspective, such as a One Health perspective integrating antimicrobial use in livestock or perspectives that can integrate environmental monitoring in the community setting with medical monitoring in the hospital setting – if these perspectives are explicitly linked to human health outcomes and particularly a focus on vulnerable populations</li>
	<li>Leverages opportunities to build in new ways on existing public health interventions or environmental monitoring platforms - and to bring together different research communities</li>
	<li>Contributes to control of infections in healthcare settings: novel techniques and products to control hospital infection rates and break the chain of transmission of bacteria in clinical settings</li>
	<li>Exploratory work into developing low-cost technologies to remove antibiotics and associated chemicals from effluents</li>
</ul>

<h3>We will NOT consider funding for:</h3>

<ul>
	<li>Proposals to develop diagnostic devices and technologies or for drug discovery. Although diagnostic devices and new drugs are potentially critical to AMR solutions, these areas are not unique to AMR challenges and should therefore be advanced more comprehensively against a broader landscape of possible needs and solutions. Thus, while excluded here, they may be part of a future request for proposals.</li>
	<li>Proposals without a clear application to surveillance or facilitating the development of new evidence describing the global burden of AMR</li>
	<li>Proposals seeking to apply existing tools in ways that do not transform our understanding of the global emergence or spread of AMR</li>
	<li>Incremental improvements to conventional solutions or typical disease surveillance. We will not consider local surveillance programs or projects or small improvements in surveillance, e.g., use of mobile data collection, automation of traditional processes, or improving access to existing tools or technologies.</li>
	<li>Proposals that simply expand the availability of primary data without a clear link to informing our understanding of global AMR epidemiology</li>
	<li>Applications proposing basic research</li>
	<li>Ideas not directly relevant to low- and middle-income contexts</li>
	<li>Genomic and other laboratory-based approaches that lack a clear application to AMR surveillance or epidemiology</li>
	<li>Ideas focused on quantifying resistance in animal or livestock populations or in environmental samples without a direct linkage to how data would impact public health practice</li>
	<li>Proposals involving clinical trials in human volunteers or patients (note: use of existing datasets or other outputs from clinical trials may be considered, as long as the proposed approach is feasible within the time and financial envelopes provided).</li>
</ul>

Grand Challenges Explorations - Brazil: New Approaches to Characterize the Global Burden of Antimicrobial Resistance

Appropriate antibiotic use has the power to save lives in the most vulnerable communities, and antimicrobial resistance (AMR) impacts multiple global health priority areas: HIV/AIDS, tuberculosis, maternal and neonatal health, pneumonia, and enteric and diarrheal diseases. It is critical to better understand the prevalence of AMR and its impact on mortality in developing countries so that access to appropriate antibiotics is ensured while inappropriate use of antibiotics is limited. In particular, there is a need to better understand resistance in bacterial infections of newborns and young children – and to this end, understanding what is the prevalence of AMR in the community, how it impacts mortality, and how it impacts health targets. Tackling AMR will require a global, coordinated approach and the linking together of different research communities for new perspectives on the problem.
Note that this request for proposals is being launched on sequential dates by four Grand Challenges partnerships: African researchers located in African organizations should apply through the joint Grand Challenges Africa/Grand Challenges South Africa portal; Brazilian researchers located in Brazilian organizations should apply through the Grand Challenges Brazil portal; and Indian researchers located in Indian organizations should apply through the Grand Challenges India portal.
<h3>What we are looking for:</h3>
We seek new approaches that have the potential to transform public health action on a regional or global scale by identifying and filling gaps in knowledge on the burden of resistance to antibacterial agents – we are not seeking incremental improvements in typical disease surveillance solutions. Specifically, we seek projects that propose innovation in the following areas:
<ul>
<li>Data sources: Pilot tests of new sources of data, particularly those that would bring together different research communities from different disciplines for new perspectives on the problem</li>
<li>Analytical methods: Pilot tests of bioinformatics approaches, including new ways to analyze, combine or connect existing databases</li>
<li>Biomarkers: Pilot tests of new biomarkers or combinations of biomarkers that could lead to new understanding of the actionable implications of antimicrobial resistance surveillance data</li>
<li>Low-cost technologies and products: Exploratory work in developing new technologies and products, including 1) those that specifically target improved infection prevention and control in healthcare settings to reduce reliance on healthcare provider behavior change, and 2) technologies to remove antibiotics from effluents</li>
</ul>
<h3>We will give highest priority to those projects that:</h3>
<ul>
<li>Pilot test approaches that could be added to existing surveillance platforms, since we are not seeking to create new surveillance platforms</li>
<li>Incorporate multiple of the areas of innovation listed above</li>
<li>Could contribute to a portfolio of funded projects that addresses a country’s regional diversity and the diversity of vulnerable populations</li>
<li>Explain how proposed approaches will be tested so that they have the highest likelihood of being relevant for implementation in the country’s public health system</li>
</ul>
<h3>Examples of what we are looking for:</h3>
<ul>
<li>Characterizes type examples of the burden of AMR (e.g., exploring the role of AMR in community or hospital sepsis-related mortality, focusing on children)</li>
<li>Includes data sources that could indirectly reflect AMR burden (e.g., antimicrobial usage patterns or specifically how vaccination against respiratory or diarrheal diseases impacts antimicrobial use)</li>
<li>Addresses the diversity of vulnerable populations and the different aspects of the AMR burden that might be reflected in urban versus rural settings</li>
<li>Includes data sources ranging from the level of the individual (e.g., microbiome across body sites) to the community (e.g., public toilets and sanitation systems), while maintaining a focus on gaining new understanding of the actionable consequences of AMR gene flow.</li>
<li>Includes data sources that could reflect AMR transmission dynamics between communities (e.g., modes of transportation) or within communities over time (e.g., seasonal-related behaviors)</li>
<li>Provides an ecological perspective, such as a One Health perspective integrating antimicrobial use in livestock or perspectives that can integrate environmental monitoring in the community setting with medical monitoring in the hospital setting – if these perspectives are explicitly linked to human health outcomes and particularly a focus on vulnerable populations</li>
<li>Leverages opportunities to build in new ways on existing public health interventions or environmental monitoring platforms - and to bring together different research communities</li>
<li>Contributes to control of infections in healthcare settings: novel techniques and products to control hospital infection rates and break the chain of transmission of bacteria in clinical settings</li>
<li>Exploratory work into developing low-cost technologies to remove antibiotics and associated chemicals from effluents</li>
</ul>
<h3>We will NOT consider funding for:</h3>
<ul>
<li>Proposals to develop diagnostic devices and technologies or for drug discovery. Although diagnostic devices and new drugs are potentially critical to AMR solutions, these areas are not unique to AMR challenges and should therefore be advanced more comprehensively against a broader landscape of possible needs and solutions. Thus, while excluded here, they may be part of a future request for proposals.</li>
<li>Proposals without a clear application to surveillance or facilitating the development of new evidence describing the global burden of AMR</li>
<li>Proposals seeking to apply existing tools in ways that do not transform our understanding of the global emergence or spread of AMR</li>
<li>Incremental improvements to conventional solutions or typical disease surveillance. We will not consider local surveillance programs or projects or small improvements in surveillance, e.g., use of mobile data collection, automation of traditional processes, or improving access to existing tools or technologies.</li>
<li>Proposals that simply expand the availability of primary data without a clear link to informing our understanding of global AMR epidemiology</li>
<li>Applications proposing basic research</li>
<li>Ideas not directly relevant to low- and middle-income contexts</li>
<li>Genomic and other laboratory-based approaches that lack a clear application to AMR surveillance or epidemiology</li>
<li>Ideas focused on quantifying resistance in animal or livestock populations or in environmental samples without a direct linkage to how data would impact public health practice</li>
<li>Proposals involving clinical trials in human volunteers or patients (note: use of existing datasets or other outputs from clinical trials may be considered, as long as the proposed approach is feasible within the time and financial envelopes provided).</li>
</ul>

We seek new approaches that have the potential to transform public health action on a regional or global scale by identifying and filling gaps in knowledge on the burden of resistance to antibacterial agents, including the linking together of different research communities for new perspectives on the problem.

Grand Challenges Explorations - Brazil New Approaches to Characterize the Global Burden of Antimicrobial Resistance

<h2>Preamble</h2>This joint call for proposals targeted specifically to Brazilian researchers is the result of a partnership between the Ministry of Health (MoH), the National Council for Scientific and Technological Development (CNPq), the National Council for State Funding Agencies (CONFAP), engaged State Funding Agency (FAPs) and The Bill &amp; Melinda Gates Foundation (BMGF). This call is part of another initiative funded by the Gates Foundation in 2010 named Healthy Birth, Growth and Development Knowledge integration (HBGDki). The goal of this program is to use data science tools to develop a deep understanding of the risk factors contributing to poor outcomes in preterm birth, physical growth faltering and impaired neurocognitive development. Through Grand Challenges Explorations - Brazil, the above-mentioned partners share this goal and wish to build on the growing expertise in data science, epidemiology and public health in Brazil to address priority issues in maternal and child health.<h2>THE CHALLENGE</h2>There remain key knowledge gaps in understanding how nutrition, prenatal and antenatal care, maternal support, and environmental and social factors contribute to an elevated risk of poor maternal and childhood health outcomes. Such an understanding is required to determine what interventions, including health policies, should be delivered to which group of individuals at what point in their lifecycle to ensure optimal outcomes.<h2>THE OPPORTUNITY</h2>Developing and validating approaches to foster maternal and child health is challenging due to the complex interaction of biological, environmental and social factors. Furthermore, policy recommendations for such approaches frequently lack sufficient supporting scientific evidence, while clinical trials are expensive, time-consuming, and increasingly difficult to implement. There is now a key opportunity to accelerate research in this area by analyzing administrative and clinical outcomes databases in Brazil to formulate public health recommendations that are data-driven and cost effective.The purpose of this call for proposals is to promote new and novel approaches to analyzing data related to social programs and public health in Brazil to produce novel insights which can be used to improve maternal and child health in Brazil and around the world. Applicants may choose to work with large datasets available to them or to collaborate with Center for Data and Knowledge Integration for Health (CIDACS) to explore their linked anonymized dataset (100 million Brazilian Cohort), which integrates information from the Cadastro Unico (CADU) with the live births system (SINASC), the mortality system (SIM) and Bolsa Família program (BFP) - see Appendix A for more information about data access through CIDACS.Successful applicants to this call should assume that with the appropriate agreements and ethical approvals, they will not only receive funding but will be able to access anonymized subsets of these data available from Center for Data and Knowledge Integration for Health (CIDACS) researchers. The utilization of the health and social data, as a key focus of this call, is intended to engage a broad spectrum of collaborators - including research and clinical scientists working with data scientists, bioinformaticians, statisticians, epidemiologists, engineers and computer programmers - to identify how innovative data analytic approaches can be used to develop improved solutions to tackle the burden of maternal and child health problems in Brazil.We also welcome applicants who have access to other relevant data sets, including publicly available data, clinical research, cohort and survey studies and other large datasets that can help address the questions below, to submit their proposals under this call. In this case, researchers who submit applications involving other data sets are responsible for securing appropriate authorization and access to the data. Applicants are encouraged to describe the steps required to access the proposed dataset in their proposals.What we are looking for:We seek proposals designed to answer critical scientific questions related to maternal and child health and development outcomes. Proposals should use innovative data analytics and modeling approaches that can be applied to the CIDACS linked datasets or to other relevant data sets that applicants can access. Proposals should be based on these linked datasets or existing primary data in Brazil and yield actionable results with a potential to significantly impact public health policy.We will give highest priority to proposals that:<ul><li>Support innovative collaborations between Brazilian research scientists, healthcare experts, and data scientists;</li><li>Answer critical scientific questions identified in this GCE, while building and strengthening data science capacity for Brazil;</li><li>Take into account social, environmental and cultural determinants of outcomes and incorporate an understanding of the target community that includes barriers and constraints to delivery of interventions and to implementation of public health programs;</li><li>Contribute to a portfolio of funded projects that addresses regional diversity and the need to provide health equity for diverse and vulnerable populations;</li><li>Explain how answers will have the highest likelihood of being relevant for implementation broadly in the public health system;</li><li>Describe mechanistic models for establishing the relationship between interventions and its related outcomes.</li></ul>Examples of what we are looking for include analytical approaches:<ul><li>That apply innovative analyses or machine learning techniques to identify patterns in data from “natural experiments” (e.g., the impact of economic cycles on the quality of primary care and health outcomes);</li><li>That stratify risk of adverse pregnancy outcomes, including preterm birth and low birth weight;</li><li>That incorporate weight gain during pregnancy as a variable, including helping to determine the relative contributions to neonatal health outcomes of maternal diet quantity versus quality;</li><li>That determine the relative contributions to infant health outcomes of diet quantity versus quality (e.g., protein quantity versus quality);</li><li>That target underexplored subsets of data (e.g., rare but significant HBGD events that can be studied because of the large size and statistical power of the database);</li><li>That help convert correlations to causal hypotheses (e.g., health outcomes correlated to sex differences, maternal education, birth spacing, age of first pregnancy, establishing causal impact of air pollution on fetal growth);</li><li>That identify new ways to aggregate risk factors and identify vulnerable populations for adverse maternal and child health outcomes, including innovative data integration strategies and visualization tools;</li><li>That specifically incorporate the roles of women – as perceived locally – from adolescence to motherhood (including pregnancy during adolescence);</li><li>That evaluate programs for pre-pregnancy intervention for women and the effect of doing so on prenatal, maternal, fetal and neonatal mortality;</li><li>That determine the best care for low-birth-weight babies;</li><li>That help determine the window of opportunity to foster catch-up growth for preterm and low-birth-weight babies, and the most effective interventions for doing so;</li><li>That help identify critical periods for intervention during pregnancy and early childhood;</li><li>That stratify risk of stunting and wasting from birth through two years of age;</li><li>That target root causes of maternal mortality, including caesarean section, and address the most vulnerable population groups considering age and ethnicity;</li><li>That investigate the "double burden" of disease in Brazil leading to pockets of stunting and wasting in parallel with pockets with rising rates of childhood obesity.</li><li>That stratify risks for child development aiming to establish national indicators for healthy development from the neonatal period to the first two years of the children addressing preferably most vulnerable population groups considering age and ethnicity</li><li>That help to understand the relationship between social indicators, nutritional conditions and mortality from the prenatal period to the early childhood. We welcome applications addressing traditional and vulnerable populations.</li></ul>Examples of what we are NOT looking for:<ul><li>Proposals submitted by applicants from outside of Brazil.</li><li>Proposals for new studies to generate new data;</li><li>Proposals that do not focus on health outcomes in Brazil;</li><li>Proposals not related to maternal and child health challenges</li><li>Development of new primary data collection tools;</li><li>Approaches that do not meaningfully involve data from adolescents, mothers, or infants;</li><li>Applications proposing data science algorithm development without clear relevance to answering the types of questions described in this call for proposals;</li><li>Ideas without a clearly articulated and testable hypothesis together with metrics of success;</li><li>Ideas for which the described indicator of success cannot be demonstrated or significantly advanced within the scope of the GCE Phase 1 award (USD $100,000 over 18 months);</li><li>Proposals that do not describe the innovation’s potential effects on health policy making;</li><li>Analyses that are only slight improvements over existing approaches (e.g., replication of an approach in a new geography in the absence of added innovation);</li></ul><h2>APPENDIX</h2>Center for Data and Knowledge Integration for HealthThe Center for Data and Knowledge Integration for Health (CIDACS) was launched in 2016 as part of Fiocruz in Bahia to conduct innovative scientific research that broadens understanding of the effects of social and environmental determinants, including public policy, on population health in Brazil. To achieve this goal, it links information from social programs and other databases of health information systems, such as mortality, birth, communicable and non-communicable infectious diseases, among other outcomes, from different information systems maintained by the Ministry of Health. A central feature of the CIDACS platform is to produce linked datasets, whose main product is the 100 million Brazilians cohort (2006-2015). This cohort is built by linking data from individuals in the Cadastro Único (CADU) to data of the same individuals in the Bolsa Familia Program (BFP), SINASC and SIM. CADU is a national registry of individuals who could be eligible to federal government social programs. BFP is a national conditional cash transfer program which transfers cash to poor households when they comply with conditions related to health and education. (For in-depth analysis of the effects of BFP on childhood mortality, please review Rasella, et al. 2013.)<a href="#_ftn1" title="" id="_ftnref1" name="_ftnref1">[1]</a> Individuals in the BFP database must be registered in CADU. SINASC is the registry of birth certificates. SIM is the registry of death certificates.Previous analyses performed by the CIDACS team have demonstrated that the social protection program contributed to a decrease in childhood mortality overall and in particular for deaths attributable to poverty-related causes such as malnutrition and diarrhea.The CIDACS platform employs the highest levels of security to ensure the privacy, integrity, and ethical use of the data. Considerable research has been required to develop the processes for data receipt, curation, and to provide authorized access for analysis. In this Grand Challenges Explorations – Brazil program, the CIDACS platform will be available for the selected applicants to conduct innovative, interdisciplinary projects in the areas of maternal and child health.<h2>Additional Resources</h2>About <a href="http://hbgdki.org/" target="_blank">HBGDKI.org</a>About <a href="http://www.cidacs.bahia.fiocruz.br/" target="_blank">Center for Data and Knowledge Integration for Health (CIDACS)</a>About <a href="http://www.cidacs.bahia.fiocruz.br/node/93" target="_blank">the 100 million Brazilian cohort managed by CIDACS</a>__________________________________<a href="#_ftnref1" title="" id="_ftn1" name="_ftn1">[1]</a>Rasella, D. et al. (2013) Effect of a conditional cash transfer programme on childhood mortality: a nationwide analysis of Brazilian municipalities. The Lancet. 382:57.

Grand Challenges Explorations - Brazil: Data Science Approaches to Improve Maternal and Child Health in Brazil

<h2>Preamble</h2>
This joint call for proposals targeted specifically to Brazilian researchers is the result of a partnership between the Ministry of Health (MoH), the National Council for Scientific and Technological Development (CNPq), the National Council for State Funding Agencies (CONFAP), engaged State Funding Agency (FAPs) and The Bill &amp; Melinda Gates Foundation (BMGF). This call is part of another initiative funded by the Gates Foundation in 2010 named Healthy Birth, Growth and Development Knowledge integration (HBGDki). The goal of this program is to use data science tools to develop a deep understanding of the risk factors contributing to poor outcomes in preterm birth, physical growth faltering and impaired neurocognitive development. Through Grand Challenges Explorations - Brazil, the above-mentioned partners share this goal and wish to build on the growing expertise in data science, epidemiology and public health in Brazil to address priority issues in maternal and child health.
<h2>THE CHALLENGE</h2>
There remain key knowledge gaps in understanding how nutrition, prenatal and antenatal care, maternal support, and environmental and social factors contribute to an elevated risk of poor maternal and childhood health outcomes. Such an understanding is required to determine what interventions, including health policies, should be delivered to which group of individuals at what point in their lifecycle to ensure optimal outcomes.
<h2>THE OPPORTUNITY</h2>
Developing and validating approaches to foster maternal and child health is challenging due to the complex interaction of biological, environmental and social factors. Furthermore, policy recommendations for such approaches frequently lack sufficient supporting scientific evidence, while clinical trials are expensive, time-consuming, and increasingly difficult to implement. There is now a key opportunity to accelerate research in this area by analyzing administrative and clinical outcomes databases in Brazil to formulate public health recommendations that are data-driven and cost effective.
The purpose of this call for proposals is to promote new and novel approaches to analyzing data related to social programs and public health in Brazil to produce novel insights which can be used to improve maternal and child health in Brazil and around the world. Applicants may choose to work with large datasets available to them or to collaborate with Center for Data and Knowledge Integration for Health (CIDACS) to explore their linked anonymized dataset (100 million Brazilian Cohort), which integrates information from the Cadastro Unico (CADU) with the live births system (SINASC), the mortality system (SIM) and Bolsa Família program (BFP) - see Appendix A for more information about data access through CIDACS.
Successful applicants to this call should assume that with the appropriate agreements and ethical approvals, they will not only receive funding but will be able to access anonymized subsets of these data available from Center for Data and Knowledge Integration for Health (CIDACS) researchers. The utilization of the health and social data, as a key focus of this call, is intended to engage a broad spectrum of collaborators - including research and clinical scientists working with data scientists, bioinformaticians, statisticians, epidemiologists, engineers and computer programmers - to identify how innovative data analytic approaches can be used to develop improved solutions to tackle the burden of maternal and child health problems in Brazil.
We also welcome applicants who have access to other relevant data sets, including publicly available data, clinical research, cohort and survey studies and other large datasets that can help address the questions below, to submit their proposals under this call. In this case, researchers who submit applications involving other data sets are responsible for securing appropriate authorization and access to the data. Applicants are encouraged to describe the steps required to access the proposed dataset in their proposals.
What we are looking for:
We seek proposals designed to answer critical scientific questions related to maternal and child health and development outcomes. Proposals should use innovative data analytics and modeling approaches that can be applied to the CIDACS linked datasets or to other relevant data sets that applicants can access. Proposals should be based on these linked datasets or existing primary data in Brazil and yield actionable results with a potential to significantly impact public health policy.
We will give highest priority to proposals that:
<ul>
<li>Support innovative collaborations between Brazilian research scientists, healthcare experts, and data scientists;</li>
<li>Answer critical scientific questions identified in this GCE, while building and strengthening data science capacity for Brazil;</li>
<li>Take into account social, environmental and cultural determinants of outcomes and incorporate an understanding of the target community that includes barriers and constraints to delivery of interventions and to implementation of public health programs;</li>
<li>Contribute to a portfolio of funded projects that addresses regional diversity and the need to provide health equity for diverse and vulnerable populations;</li>
<li>Explain how answers will have the highest likelihood of being relevant for implementation broadly in the public health system;</li>
<li>Describe mechanistic models for establishing the relationship between interventions and its related outcomes.</li>
</ul>
Examples of what we are looking for include analytical approaches:
<ul>
<li>That apply innovative analyses or machine learning techniques to identify patterns in data from “natural experiments” (e.g., the impact of economic cycles on the quality of primary care and health outcomes);</li>
<li>That stratify risk of adverse pregnancy outcomes, including preterm birth and low birth weight;</li>
<li>That incorporate weight gain during pregnancy as a variable, including helping to determine the relative contributions to neonatal health outcomes of maternal diet quantity versus quality;</li>
<li>That determine the relative contributions to infant health outcomes of diet quantity versus quality (e.g., protein quantity versus quality);</li>
<li>That target underexplored subsets of data (e.g., rare but significant HBGD events that can be studied because of the large size and statistical power of the database);</li>
<li>That help convert correlations to causal hypotheses (e.g., health outcomes correlated to sex differences, maternal education, birth spacing, age of first pregnancy, establishing causal impact of air pollution on fetal growth);</li>
<li>That identify new ways to aggregate risk factors and identify vulnerable populations for adverse maternal and child health outcomes, including innovative data integration strategies and visualization tools;</li>
<li>That specifically incorporate the roles of women – as perceived locally – from adolescence to motherhood (including pregnancy during adolescence);</li>
<li>That evaluate programs for pre-pregnancy intervention for women and the effect of doing so on prenatal, maternal, fetal and neonatal mortality;</li>
<li>That determine the best care for low-birth-weight babies;</li>
<li>That help determine the window of opportunity to foster catch-up growth for preterm and low-birth-weight babies, and the most effective interventions for doing so;</li>
<li>That help identify critical periods for intervention during pregnancy and early childhood;</li>
<li>That stratify risk of stunting and wasting from birth through two years of age;</li>
<li>That target root causes of maternal mortality, including caesarean section, and address the most vulnerable population groups considering age and ethnicity;</li>
<li>That investigate the "double burden" of disease in Brazil leading to pockets of stunting and wasting in parallel with pockets with rising rates of childhood obesity.</li>
<li>That stratify risks for child development aiming to establish national indicators for healthy development from the neonatal period to the first two years of the children addressing preferably most vulnerable population groups considering age and ethnicity</li>
<li>That help to understand the relationship between social indicators, nutritional conditions and mortality from the prenatal period to the early childhood. We welcome applications addressing traditional and vulnerable populations.</li>
</ul>
Examples of what we are NOT looking for:
<ul>
<li>Proposals submitted by applicants from outside of Brazil.</li>
<li>Proposals for new studies to generate new data;</li>
<li>Proposals that do not focus on health outcomes in Brazil;</li>
<li>Proposals not related to maternal and child health challenges</li>
<li>Development of new primary data collection tools;</li>
<li>Approaches that do not meaningfully involve data from adolescents, mothers, or infants;</li>
<li>Applications proposing data science algorithm development without clear relevance to answering the types of questions described in this call for proposals;</li>
<li>Ideas without a clearly articulated and testable hypothesis together with metrics of success;</li>
<li>Ideas for which the described indicator of success cannot be demonstrated or significantly advanced within the scope of the GCE Phase 1 award (USD $100,000 over 18 months);</li>
<li>Proposals that do not describe the innovation’s potential effects on health policy making;</li>
<li>Analyses that are only slight improvements over existing approaches (e.g., replication of an approach in a new geography in the absence of added innovation);</li>
</ul>
<h2>APPENDIX</h2>
Center for Data and Knowledge Integration for Health
The Center for Data and Knowledge Integration for Health (CIDACS) was launched in 2016 as part of Fiocruz in Bahia to conduct innovative scientific research that broadens understanding of the effects of social and environmental determinants, including public policy, on population health in Brazil. To achieve this goal, it links information from social programs and other databases of health information systems, such as mortality, birth, communicable and non-communicable infectious diseases, among other outcomes, from different information systems maintained by the Ministry of Health. A central feature of the CIDACS platform is to produce linked datasets, whose main product is the 100 million Brazilians cohort (2006-2015). This cohort is built by linking data from individuals in the Cadastro Único (CADU) to data of the same individuals in the Bolsa Familia Program (BFP), SINASC and SIM. CADU is a national registry of individuals who could be eligible to federal government social programs. BFP is a national conditional cash transfer program which transfers cash to poor households when they comply with conditions related to health and education. (For in-depth analysis of the effects of BFP on childhood mortality, please review Rasella, et al. 2013.)1 Individuals in the BFP database must be registered in CADU. SINASC is the registry of birth certificates. SIM is the registry of death certificates.
Previous analyses performed by the CIDACS team have demonstrated that the social protection program contributed to a decrease in childhood mortality overall and in particular for deaths attributable to poverty-related causes such as malnutrition and diarrhea.
The CIDACS platform employs the highest levels of security to ensure the privacy, integrity, and ethical use of the data. Considerable research has been required to develop the processes for data receipt, curation, and to provide authorized access for analysis. In this Grand Challenges Explorations – Brazil program, the CIDACS platform will be available for the selected applicants to conduct innovative, interdisciplinary projects in the areas of maternal and child health.
<h2>Additional Resources</h2>
About <a href="http://hbgdki.org/" target="_blank" rel="noopener noreferrer">HBGDKI.org</a>
About <a href="http://www.cidacs.bahia.fiocruz.br/" target="_blank" rel="noopener noreferrer">Center for Data and Knowledge Integration for Health (CIDACS)</a>
About <a href="http://www.cidacs.bahia.fiocruz.br/node/93" target="_blank" rel="noopener noreferrer">the 100 million Brazilian cohort managed by CIDACS</a>
__________________________________
<ol>
<li>Rasella, D. et al. (2013) Effect of a conditional cash transfer programme on childhood mortality: a nationwide analysis of Brazilian municipalities. The Lancet. 382:57.</li>
</ol>

We seek to promote new approaches for analyzing data related to social programs and public health in Brazil, with the goal of insights that can be used to improve maternal and child health in Brazil and around the world. There is now a key opportunity to accelerate research in this area by analyzing administrative and clinical outcomes databases in Brazil to formulate public health recommendations that are data-driven and cost effective. Applicants must be Brazilian researchers located in Brazilian organizations.

Grand Challenges Explorations - Brazil Data Science Approaches to Improve Maternal and Child Health in Brazil

This challenge focuses on new measurement tools and new combinations of approaches to ensure all children thrive – that they not only survive, but also have the chance to live healthy productive lives.&nbsp; The ultimate goal of this challenge is to determine what packages of interventions should be delivered to which group of individuals at what point in their life cycle to reduce the burden of fetal growth impairment and preterm birth, stunted postnatal growth, and impaired cognitive development.This challenge joins the All Children Thriving platform, which links Grand Challenges programs targeting healthy birth, growth, and development, including the global programs <a href="http://www.grandchallenges.ca/saving-brains/" target="_blank">Saving Brains</a> and <a href="http://savinglivesatbirth.net/" target="_blank">Saving Lives at Birth</a> and a set of four new programs launched concurrently. These new programs are Grand Challenges Brazil: All Children Thriving; <a href="http://gcgh.grandchallenges.org/challenge/all-children-thriving-0" target="_blank">Grand Challenges India: All Children Thriving</a>; <a href="http://gcgh.grandchallenges.org/challenge/all-children-thriving-1" target="_blank">Grand Challenges South Africa: All Children Thriving</a>; and <a href="http://gcgh.grandchallenges.org/challenge/creating-and-measuring-integrated-solutions-healthy-birth-growth-and-development" target="_blank">Creating and Measuring Integrated Solutions for Healthy Birth, Growth, and Development</a> (a global program with awards to investigators in low- and middle-income countries).

All Children Thriving - Brazil

The "Reducing the Burden of Preterm Birth" program seeks innovative research in biology, medical technology, delivery mechanisms, and behavior change that leads to high-impact prevention and treatment solutions for reducing the burden of preterm birth. Grants will be to Brazilian researchers, but partnerships with researchers in other countries are encouraged. Solutions developed through the Grand Challenges Brazil preterm birth program could have broad impact, both within Brazil and beyond its borders.