Learn more about the funded projects in each RFP in the menu below.
All Projects
Using geocoded big data to identify causal links between infectious diseases and child developmental outcomes
Infectious diseases may have only transitory impacts on pregnant mothers, but they can have lasting impacts on children. Can public interventions miti…
Data Science I
Data-driven risk stratification for preterm birth in Brazil: development of a machine learning based innovation for health care
Causes and performing early identifying the preventable risk stratification of pregnant women are instrumental to develop strategies to prevent and re…
Data Science I
Use of interactive infographic in the PMCP – Analysis of indicators to improve the quality of maternal and child health
It aims to develop a platform for the analysis and visualization of data that will allow stakeholders involved in the Mãe Coruja Program at Pernambuco…
Data Science I
Using the 100M Cohort to establish critical air pollution thresholds for safe childbirth in Brazil
Does air pollution affect the rates of stillbirths, congenital malformations and neonatal mortality? This study aims to answer this question by mergin…
Data Science I
Data science to inform the design and evaluation of interventions to improve perinatal outcomes: lessons from the Mãe Coruja program
It aims to evaluate the effective ness of Mãe Coruja interventionin reducing low birthweight and preterm birth. The study will use the Cidacs dataset …
Data Science I
Spatial analysis of children vaccination coverage and their relation to socioeconomic and health characteristics in Brazil
By analyzing national children vaccination coverage from spatial perspectives, the study aims to uncover insights into traditional surveillance. This …
Data Science I
