Persistent noise pollution is not just an environmental nuisance, but a chronic stressor that the WHO classifies as a risk factor for cardiovascular and mental diseases. To visualize this silent impact, we propose an interactive 3D infographic that overlays urban noise maps with stress incidence rates by district, using data from the Public Health Surveillance Network.
Acoustic propagation modeling and epidemiological data 🎧
The infographic will integrate acoustic propagation models based on ISO 9613 standards to calculate the equivalent continuous sound pressure level (Leq) on building facades. Over this acoustic heat layer, district polygons with chronic stress prevalence rates adjusted for age and sex will be overlaid. Correlation charts will show the relationship between the 90th percentile of night noise (Lnight) and mean morning salivary cortisol levels, extracted from local cohort studies. We will include a slider to filter by time of day (day/night) and a biomarker selector (cortisol, alpha-amylase, blood pressure).
The invisible weight of decibels on mental health ðŸ§
Noise does not leave bruises, but it leaves a chemical footprint on the HPA axis. Visualizing how a 10 dB increase in road traffic translates into a 12% increase in the prevalence of anxiety disorders in the most exposed districts turns an abstract data point into an urban planning urgency. This tool serves not only for diagnosis but also to push for acoustic zoning policies and the installation of green barriers in critical points of the city.
How can the integration of 3D models of urban noise pollution with visual biomarker data (such as pupil dilation or blink rate) improve the early detection of chronic stress in populations exposed to persistent noise?
(PS: modeling health data is like going on a diet: you start with energy and end up quitting)