Big Data-Planetary Health approach for evaluating the Brazilian Dengue Control Program

Area of Science:

• Public Health
• Data Science
• Environmental Health

Background:

• The Donabedian model is a framework for evaluating healthcare quality.
• Planetary health considers the health of human civilizations and the state of the natural systems on which they depend.
• Big data offers new opportunities for large-scale health program evaluation.

Purpose of the Study:

• To integrate planetary health and big data concepts into the Donabedian model.
• To evaluate the Brazilian dengue control program in São Paulo state.

Main Methods:

• Utilized data science methods to analyze dengue-related data from 2010-2019.
• Integrated data from DATASUS, IBGE, WorldClim, and MapBiomas into a Data Warehouse.
• Applied K-means clustering, statistical analysis, and spatial visualization.

Main Results:

• Identified four distinct groups of municipalities based on climate variables.
• Worst-performing municipalities in dengue control had better economic conditions but fewer healthcare resources per capita.
• Higher urbanization rates and human activity correlated with poorer dengue control outcomes.

Conclusions:

• The methodology identified significant deficiencies in São Paulo's dengue control program implementation.
• Large-scale evaluation using integrated databases and data science is feasible.
• Findings can inform public administration for targeted actions and investments.