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


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 & 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.

1. Objective

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.

  1. 1 The present RFP has the objective of:
    1. Selecting and contracting proposals in accordance with research topics defined in subitem 1.2.
    2. 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).
  1. 2 Proposals shall comply with the research lines and study types:
  1. Cross sectional
    1. 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);
    2. To analyze primary health care distribution and quality and its relation with health outcomes and infant and maternal nutrition;
    3. 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;
    4. 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.
  2. Children's Health
    1. 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;
    2. 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);
    3. 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;
    4. To assess infectious and non-infectious factors related to the occurrence of changes in growth and development during pregnancy and up until early childhood;
    5. Studies on health care for children with congenital anomalies, such as congenital Zika syndrome;
    6. 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.
  3. Women's Health
    1. 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;
    2. 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;
    3. 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;
    4. To assess the coverage of contraceptive methods in specific populations and in those with difficulties to access them;
    5. To identify factors associated with alcohol and drug abuse among women and their impact on health outcomes;
    6. To develop instruments to assess how the type of delivery impacts the health of woman and child;
    7. To assess the impact of teenage pregnancy on the health of the woman and child;
    8. To develop predictive models of pregnant women who may develop gestational diabetes or eclampsia;
    9. 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.
  4. Food and Nutrition
    1. 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;
    2. To analyze the supply and quality of Primary Health Care and its relationship with outcomes in maternal and child health and nutrition;
    3. To develop predictive and risk stratification models for outcomes related to the double burden of malnutrition, especially on women and children;
    4. 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;
    5. 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
    6. To assess the impact of nutritional status, gestational weight gain and health status on maternal and child outcomes based on data from the SISVAN;
    7. 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.
  1. 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.
  1. 4 We encourage projects to be developed in collaboration with other research centers or individual researchers.
  1. 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.
  1. 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 https://www.synapse.org/#!Synapse:syn22088071/wiki/.
  1. 7 Studies of different designs that allow, according to the proposed methods, to achieve the expect outcomes shall be granted
  1. 7.1 Examples of what we are looking for. Proposals that:
    1. Support innovative collaboration among researchers, health experts and Brazilian data scientists;
    2. Answer scientific questions identified in this GCE RFP, while developing and strengthening the capacity of data sciences in Brazil;
    3. Consider the social, environmental and cultural determinants of health and incorporate in the results a broad understanding of the studied community;
    4. Include the mapping of barriers and restrictions to effective health interventions and contribute to inform the implementation of evidence-based public health programs;
    5. Contribute to a portfolio of funded projects that address regional diversities and the need to provide health equity to diverse and vulnerable populations;
    6. Explain how results are more likely to become relevant in a broad implementation in the public health system;
    7. Show relation with the implementation and evaluation of primary health care, whenever possible;
    8. Describe mechanistic models so as to establish the relationship between interventions and their results;
    9. Perform analysis of indicators, impact analysis, visualizations and predictive models that support the management of public health programs, whenever relevant.
    10. Propose and validate tools for disseminating high-volume data.
  1. 8 Proposals for literature review or systematic review shall not be funded.
  1. 8.1 Examples of what we are NOT looking for:
    1. Proposals submitted by applicants that are not based in Brazil or that aim at studying health conditions outside of the Brazilian territory;
    2. Proposals for studies that depend on the collection of primary data;
    3. Proposals that develop tools for collecting new primary data;
    4. Proposals that do not address women's health, children’s health or maternal and child health;
    5. Projects that propose the development of a scientific data algorithm without clear relevance to the issues described in this call;
    6. Ideas without a hypothesis that is clearly defined and tested by metrics of success;
    7. Proposals that cannot be developed within the scope of GCE Phase 1 funding; (R$ 550,000,00 over 18 months);
    8. Proposals that do not describe the potential impacts of innovation on the formulation of health policies;
    9. 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).

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