Version 0.0.9000 Available

Climate Science Integrated with SUS

An R package for obtaining data, diagnosis, forecasting, and spatio-temporal analysis of climate, environmental, and health data, focusing on Brazilian public health.

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script.R 
# Install the package
remotes::install_github(
    "ByMaxAnjos/climasus4r")
# Load the package
library(climasus4r)
# Import health data from DATASUS
df_analise <-
 sus_data_import(
  uf = "SP",
  year = 2023,
  system = "SIM-DO")
13
Functionalities
50+
Disease Groups
6
SUS Systems
3
Languages
About the Package

What is climasus4r?

climasus4r is a scientific platform in R for obtaining, integrating, standardizing, and analyzing health, climate, and environmental data in Brazil, with a focus on bioclimatic forecasting. Developed within the scope of INCT Conexão and the Center for Climate and Health of Rondônia (CCSRO–Fiocruz), the package automates the entire epidemiological workflow — from data acquisition from DATASUS to the generation of time series ready for climate modeling and health surveillance.

DATASUS Integration
Climate Data
Spatial Analysis
Predictive Models 
# Reproductible Analitical Pipelines
df_rap <- sus_data_import() %>%
    sus_data_clean_encoding() %>%
    sus_data_standardize() %>%
    sus_data_filter_cid() %>%
    sus_create_variables() %>%
    sus_data_filter_demographics() %>%
    sus_data_aggregate()
100%
Open Source
RAPs
Reproductible Analitical Pipelines
Features

Five Integrated Phases

From raw data to intelligence for public health policies.

01

Phase 1 — Data Infrastructure

Parallel acquisition, cleaning, multilingual standardization, filtering by ICD-10, creation of epidemiological variables, flexible temporal aggregation, quality reports, and export with metadata ready for scientific analysis.

SIM SINAN SIH SIA
02

Phase 2 — Socioeconomic Integration

Spatial linking of geographical boundaries, integration of IBGE data (population, GDP, HDI), matching of census tracts, and population-weighted spatial operations for analyzing health inequalities.

IBGE Census GDP HDI
03

Phase 3 — Climate Integration

Import of meteorological data (INMET, FIORES, INCT-CONEXÃO), air quality (INPE, CETESB), satellite data (MODIS, Sentinel), and climate exposure matching algorithms.

INMET MODIS Sentinel ERA5
04

Phase 4 — Advanced Spatial Analysis

Bayesian spatial models, cluster detection (SaTScan, Kulldorff), local indicators of spatial autocorrelation (LISA), spatial regressions, and relative risk models for hospitalizations and mortality associated with climate.

SaTScan LISA Bayesian
05

Phase 5 — Temporal and Predictive Modeling

Distributed lag non-linear models (DLNM), attributable fraction, time series decomposition, machine learning, and bioclimatic prognosis based on weather forecasts and climate scenarios.

DLNM Machine Learning Bioclimate CMIP6
Multilingual Access

Documentation in 3 Languages + AI

Access the full documentation in your language or use the AI assistant to get instant answers.

🇧🇷

Português

Complete documentation, tutorials, and references in Brazilian Portuguese.
🇺🇸

English

Full documentation, tutorials and function reference in English.
🇪🇸

Español

Complete documentation, tutorials, and function reference in Spanish.
🤖

AI Assistant

Chat with an AI specialist trained on the climasus4r package. Ask questions, get examples, and explore the package.
Who We Are

Our Team

Developed by experts dedicated to the intersection of climate and public health.

Dr. Max Anjos

Dr. Max Anjos

Coordinator & Lead Maintainer

Fiocruz Logo Fundação Oswaldo Cruz Rondônia (FIOCRUZ-RO / CCSRO)

Thauã Menezes

Thauã Menezes

Associate R/Python Developer

Fiocruz Logo UNESP / Universidade Federal de Rondônia (UNIR)

Thauã Menezes
JG

Dr. João Paulo Assis Gobo

Scientific Advisor

Fiocruz Logo UNIR / FIOCRUZ-RO (CCSRO)

Thauã Menezes
AS

Dr. Andreimar Martins Soares

Scientific Advisor

Fiocruz Logo Fundação Oswaldo Cruz Rondônia (FIOCRUZ-RO / CCSRO)

Marlon R. Faria

Marlon Resende Faria

Senior R/Python Developer

USP Logo Universidade de São Paulo (USP)

Adriana

Dra. Adriana Cristina da Silva Nunes

Scientific Advisor

UNIR Logo Universidade Federal de Rondônia -UFRO / Centro Interdepartamental do Biologia Experimental e Biotecnologia - CIBEBI

Carolina

Dra. Carolina L Zilli Vieira

Scientific Advisor

USP Logo Harvard T.H. Chan School of Public Health

Priscilla

Dra Priscilla Venâncio Ikefuti

Research Assistant

USP Logo Universidade de São Paulo (USP)

Natacha

Dra. Natacha Cíntia Regina Aleixo

Scientific Advisor

UFAM Logo Universidade Federal do Amazonas (UFAM)

Mariana

Dra. Mariana Andreotti Dias

Scientific Advisort

UERJ Logo Universidade do Estado do Rio de Janeiro (UERJ)

Euciline

Dra. Euciline Alves Santana

Scientific Advisor

UNB Logo Ministério da Saúde/Departamento de Emergências em Saúde Pública

Institutional Support

Support and Funding

The climasus4r project is funded by the Ministry of Health and the Oswaldo Cruz Foundation Rondônia (Fiocruz-RO), through the Center for Climate and Health of Rondônia (CCSRO), within the scope of INCT-CONEXAO, CNPq process No. 408474/2024-6.

Logo INCT-CONEXAO

Start using climasus4r today

Transform climate and health data into intelligence for public policies.

Get Started View on GitHub