Abstract:
Environmental justice (EJ) advocates equal protection against environmental and public health risks. Despite its relevance, objective metrics to quantify EJ are limited. We propose a statistical framework to define and estimate EJ indicators, grounded in count time series models. Specifically, the daily number of hospital admissions is modeled using INGARCH models with environmental covariates. EJ measures are constructed as weighted sums of environmental effects, with weights derived from the spatial distribution of socioeconomic groups. Future developments include extensions of INGARCH models to handle zero-inflation, seasonality, and spatio-temporal dynamics. Applications to Portuguese data will help identify vulnerable populations, with all methods to be implemented in an R package.
Short bio: Adriano Gomes is a PhD student in Applied Mathematics (MAP-PDMA) and a student researcher at IEETA. He holds a BSc in Applied Mathematics from the University of Évora and two MSc degrees from the University of Aveiro: one in Data Science for Social Sciences and another in Data Science. His research focuses on statistical models for time series of counts, with applications in public health and environmental justice, integrating spatio-temporal dynamics and environmental covariates to assess population vulnerability.
This seminar will take place at the IEETA auditorium, on 15/05/2025, 11h.
