Integration

We integrate data from official birth registration systems, multicenter studies, climate monitoring centers, and national socioeconomic databases.

Protection

We use anonymization techniques to protect individual privacy.

Intelligence

We create classification models using artificial intelligence, such as convolutional neural networks, among other techniques, to identify clusters and high-risk areas for preterm births.

What data is being compiled and integrated into the dataset?

Climaterna’s data curation looks for comprehensive and varied information, essential for analyzing the effects of climate change on maternal and perinatal health in Brazil.

01

Demographic Data

collected by national institutions like the Brazilian Institute of Geography and Statistics (IBGE), including information on population, birth and death rates, age, sex distribution, and socioeconomic characteristics. These data help understand the characteristics of the population affected by climate change and identify vulnerable groups, such as pregnant women and newborns, who may be more susceptible to adverse impacts.

02

Maternal and Perinatal Health Data

includes information obtained from health registration systems collected by the Brazilian Ministry of Health, such as hospital information systems (SIH), birth and death records (SINASC and SIM), as well as data collected by public health research institutions (epidemiological studies). These data enable the analysis of maternal health indicators such as maternal mortality, morbidity, preterm births, birth weight, and neonatal complications, essential for identifying trends and health disparities that may be exacerbated by climatic factors.

03

Environmental Data (Climate and Pollution)

provided by meteorological and climate research institutions, such as the Brazilian National Institute of Meteorology (INMET), the National Institute for Space Research (INPE), compiled from modeling in the Brazilian Daily Weather Gridded Data (BR-DWGD) database and institutions such as CETESB (Environmental Company of the State of São Paulo). Includes information on temperature, precipitation, extreme events (such as droughts and floods), pollution, and air quality. These data help understand climatic and environmental patterns and extreme events, correlating climatic conditions with maternal and perinatal health, enabling the analysis of how specific climate variables affect the health and well-being of pregnant women and newborns.
Our Research

How do these datasets connect?

The integration of demographic, maternal and perinatal health, and climatic data is essential for understanding and mitigating the impacts of climate change on public health in Brazil. This project not only provides valuable insights into how climatic factors affect maternal and perinatal health, but it can also guide the formulation of effective policies to protect the most vulnerable populations. The combination of these datasets is unprecedented in Brazil and innovates by connecting this information through five main axes:

Integrated Analysis of Demographic and Health Data

cross-referencing maternal and perinatal health information to identify vulnerability and risk patterns in different population groups across the country, outlining the most affected population profiles by climate impacts.

Predictive Modeling

models that help anticipate challenges and plan more effective public health interventions in response to climate risks.

Scientific Evidence for Public Policies

this project seeks to support the formulation of public policies aimed at mitigating the impacts of climate change on health, with a special focus on vulnerable populations. These policies may include climate adaptation measures and strengthening healthcare infrastructure.

Correlation between Climatic Events and Health Indicators

the relationship between extreme climatic events (such as heatwaves and floods) and maternal and perinatal health is analyzed to identify correlations, such as the association between exposure to extreme temperatures and an increase in preterm births.

Identification of Risk Areas

by combining climate data with geographic and health information, it is possible to identify geographic areas at higher risk of the negative impacts of climate change on maternal and perinatal health, enabling resources and efforts to be directed to the most vulnerable zones.