Chronic exposure to noise pollution emerges as a modifiable risk factor in public mental health. A recent study correlates the increase in decibels in urban environments with a significant rise in depression diagnoses. To visualize this relationship, we propose an interactive 3D infographic that allows epidemiologists and urban planners to understand the spread of noise and its silent impact on the population.
Visualization Methodology: Heat Maps and Volumetric Acoustic Propagation 🎧
The model is built on a digital twin of the city, where each district is a data voxel. The base layer is an urban noise map generated by traffic and industrial activity simulation, represented with a color palette ranging from blue (50 dB) to red (85 dB). On top of this, semi-transparent volumetric spheres are superimposed, emulating three-dimensional acoustic propagation from pollution sources (avenues, construction sites). These spheres deform upon impacting the geometries of hospitals and schools, indicating critical risk zones. The depression rate per district is visualized using columns of variable height, where elevation directly correlates with the recorded ambient noise level.
Temporal Correlation: The Wave and Diagnosis Graph 📈
A side panel integrates a temporal line graph that synchronizes two axes: the left Y-axis shows the average hourly decibels (with peaks during rush hours), while the right Y-axis reflects the number of clinical depression diagnoses recorded in district health centers. The animation spans a 24-hour period, revealing how cumulative exposure during the night (residual noise) is associated with peaks in morning consultations. This visual resource allows planners to identify districts where noise reduction could have the greatest preventive impact on public health.
How can the three-dimensional visualization of urban noise propagation on epidemiological maps improve the identification of risk zones for depression and optimize public health interventions?
(PS: at Foro3D we know that the only epidemic affecting us is the lack of polygons)