Geospatial Analysis
Objective
The main objective of the geospatial analysis component of this project is to apply novel temporospatial modeling techniques to COVID-19 case and vaccination data and associated sociodemographic factors (racialization, migration, and gender) to better understand the course of the pandemic in Peel Region.
Methods
If sociodemographic factors created a disproportionate COVID-19 burden in Ontario, or more specifically, Peel Region, it is imperative to determine which sociodemographic groups faced additional burdens to establish preventative measures for future pandemics. Currently, the team is attempting to establish
1) the relationship between sociodemographic characteristics and COVID-19 over time
2) how soon into a COVID-19 case wave do sociodemographic characteristics begin to have a relationship with COVID-19 case counts.
Using both ArcGIS and R-Studio COVID-19 case distribution has been visualized at a small-scale spatial resolution, Forward Sortation Area (FSA), and has shown that there are FSAs in Peel Region and Ontario with higher COVID-19 case rates. These case rates and case rate characteristics are not geographically independent (spatially autocorrelated). Therefore, spatial models, such as spatial lag models and spatial error models, at varying time points are being used to model the relationships between COVID-19 case rates and selected sociodemographic characteristics.
Current Project Updates
Most recently, the team has been working on defining census-based social vulnerability factors. These factors, we hypothesized, vary by COVID-19 case transmission wave. The team has built spatial error models which illustrate this time-varying relationship between COVID-19 case rates and sociodemographic characteristics. This work will illustrate vulnerabilities to COVID-19 change over time. So, time must be accounted for in pandemic planning and policy.
Next Steps
In the future, the geospatial analysis arm of the project will be developing an ESRI StoryMap – which integrates maps as well as quantitative and qualitative components of the research. This map will be used to disseminate research to stakeholders, community members, and other members of the research community. Future work for determining when in a COVID-19 case wave sociodemographic patterns appear will integrate more temporally granular statistical modeling.