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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.

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Decision-Making Support Platform Based on Visual Analytics and Machine Learning to Subsidize Public Politics Focused on Gestational Health

Tiago CarvalhoInstituto Federal de São PauloCampinas, São Paulo, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

The project will develop a platform to provide services for decision-making support for neonatal death preventive actions by using data from CIDACS cohort. The platform will offer three services: cohort data visualization for decision-making support by comparative human visual analysis, prediction of risk of neonatal death based on machine learning models, and simulator of public policies impact influencing on the risk of neonatal death.

How and When: Disentangling Cash and Care Effects of Conditional Cash Transfers on Birth Outcomes

Cecilia MachadoFundação Getúlio VargasRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

Seeks to understand the impacts of the Bolsa Família conditional cash transfer on birth outcomes (e.g., birth weight, gestational weeks, etc). The proposed design will disentangle the measured effects into two components: one that is associated to the cash transfer; and another related to prenatal care assistance. Moreover, this strategy will allow the researchers to determine the window of opportunity where CCT interventions exhibit highest impacts on birth outcomes, recognizing heterogeneous impacts according to how early in the pregnancy the CCT intervention starts.

Early Childhood Development Friendly Index: Assessing the Enabling Environment for Nurturing Care in Brazilian Municipalities

Muriel GubertUniversidade de BrasíliaBrasília, Distrito Federal, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

The study aims to develop an Early Childhood Development friendly index (ECD-FI) based on a core set of evidence-based nurturing care indicators to assess the factors contributing to enabling environments and promote ECD at the municipal level by monitoring and identifying opportunities to scale up ECD programs. The index will be created through machine learning and will run analytical models considering demographic information and risk factors at the municipal level. This disaggregated data is not available in Brazil.

Using Geocoded Big Data to Identify Causal Links Between Infectious Diseases and Child Developmental Outcomes

Rudi RochaFundação Getúlio VargasRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

Infectious diseases may have only transitory impacts on pregnant mothers, but they can have lasting impacts on children. Can public interventions mitigate these impacts? This project aims to identify how exposure to localized epidemiological risk factors in the fetal period influences developmental outcomes for children through the early years of life. The researchers propose to evaluate in what extent the access to primary health care and social welfare programs mitigate negative impacts in child development.

Spatial Analysis of Child Vaccination Coverage and its Relation to Socioeconomic and Health Characteristics in Brazil

Carolina BarbieriUniversidade Católica de SantosSantos, São Paulo, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

By analyzing national children vaccination coverage from spatial perspectives, the study aims to uncover insights into the traditional surveillance. This will help to identify coverage rates, regions of greater vulnerability by providing a differentiated look at the logic of equity in health. Understanding the low childhood vaccination coverage will help to guide public policies for the purpose of interventions.

New Gestational Weight Gain Recommendations for the Brazilian Unified Health System (SUS)

Gilberto KacUniversidade Federal do Rio de JaneiroRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Data Science Approaches
1 Nov 2018

Aims to validate the International Fetal and Newborn Growth Consortium for the 21st century (Intergrowth-21st) standards for gestational weight gain (GWG) and create new recommendations of GWG based on those standards for first trimester normal and overweight women to be used in the Brazilian Unified Health System (SUS). GWG recommendations currently used in SUS have not been properly tested or validated, thus the project might improve prenatal nutritional care and reduce post gestational weight retention.

Tracking MRSA Evolution to Discover Important Biomarkers to Quickly Characterize Unique MRSA Clones in Hospital Bloodstream Infections

Agnes FigueiredoUniversidade Federal do Rio de JaneiroRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The project will use molecular approaches, including genomics and phylogenomics, to find biomarkers that could indicate the location in the genetic code driving bacterial adaptation. In addition, these biomarkers could be used as a rapid method for screening predominant and high-virulency MRSA clones in hospitals, and thus quickly provide infection control committees with key data on MRSA spread and its antimicrobial resistance profile.

An Artificial Intelligence System to Strengthen Antimicrobial Prescription in a Children's Hospital: SMART-EP

Marcelo PillonettoPontifícia Universidade Católica do ParanáCuritiba, Paraná, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The idea is to develop an artificial intelligence model capable of simultaneously analyzing data from the Laboratory Information System and from the Hospital Information System. This technology aims to enable the delivery to hospital physicians of a ranked list of antimicrobials that are more suitable to treat infection by multi-resistant microorganism with a focus on newborn and young children.

Data Science on Drug-Resistant Tuberculosis in Brazil

Rejane PinheiroUniversidade Federal do Rio de JaneiroRio de Janeiro, Rio de Janeiro, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The researcher will use machine learning techniques and a linked database to analyze mortality from drug-resistant tuberculosis. The goal is to better understand how the flow of patients through the health services network have influenced, or not, the occurrence of resistance.

The Dynamics of Antibiotic-Resistant Microorganism Flow Between Animal Farming and Medical Hospital Assistance

Thaís SinceroUniversidade Federal de Santa CatarinaFlorianópolis, Santa Catarina, Brazil
Grand Challenges Brazil
Drug Resistance Burden
1 Nov 2018

The project proposes to characterize the resistant determinants of microbial communities from key sources in hospitals, environment and farms to model the dynamics of the flow of antibiotic resistant microorganisms. The goal is to understand how the hospital environment and animal farming affect the ecology of antibiotic resistance movement. The project will rely on a methodology that allows the analysis of genes related to antibiotic resistance in a complex microbial community derived from specific samples instead of culture based methods for AMR identification.

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