Abstract
Abstract. The paper presents an ongoing project devoted to the study, the analysis and the representation of epidemiological data related to CoViD-19 spread in the territory of the Province of Trento (Italy), both for scientific and communication purposes. In this broader context, the construction of a digital cartography tool as a WebGIS to allow local communities understanding of epidemiological spread is presented. Data have been supplied by the local Provincial Health Authority; statistic have been processed in order to develop municipality scale vector polygonal coropleth and point maps in order to show affected, health and death rate distribution. A timeline allows the representation of changes and dynamics from Spring 2020 to the current date. The database provides “on-the-fly” data to the production scripts of maps and time charts. These scripts querying the database produce a geographic file in the geojson standard interchange format. This file is read by the javascript scripts based on the leaflet libraries for the production of the final maps. In a similar process, scripts based on the chart.js library produce the graph of the data temporal variation, automatically reading dates and interval time of analysis. A custom procedure was developed to allow the periodic update of the dataset. New information is added to the database by uploading an external spreadsheet. The study presents the methodology to develop and assess the WebGIS for managing, visualize and analyse Coronavirus diffusion. Future implementation of the WebGIS will expand the used data and allow the comparison with social and environmental factors.
Highlights
In December 2019 a severe human respiratory disease, afterwards named CoViD-19, emerged in China (Lu et al, 2020), and rapidly became the worst planetary health emergency probably since the 1918 “Spanish Flu”, affecting any country in the world just in few months
Within the framework of epidemiological geography, thematic cartography has always been the main instrument for the collection and dissemination of health datasets, as well as for their deeper spatial analysis (Carroll et al, 2014)
Proximity to Lombardy, touristic flows, infra and inter regional commuting have been identified as the most influential factors to explain the dynamics of internal diffusion (Brunialti et al, 2020), In order (1) to develop a new approach of digital cartographic representation of data at the largest possible scale for a better identification of epidemiological dynamics, and (2) to develop a tool for monitoring the health situation in Trentino, an Agreement between the Trento Autonomous Province Local Health Authority (APSS) and the Geo-cartographic Center of the University of Trento (GeCo) was signed
Summary
In December 2019 a severe human respiratory disease, afterwards named CoViD-19, emerged in China (Lu et al, 2020), and rapidly became the worst planetary health emergency probably since the 1918 “Spanish Flu”, affecting any country in the world just in few months. According to the World Health Organization guidelines, transparent communication is one of the main strategic axes in epidemic fighting and controlling, together with data analysis and health service management (WHO, 2005). Within the framework of epidemiological geography, thematic cartography has always been the main instrument for the collection and dissemination of health datasets, as well as for their deeper spatial analysis (Carroll et al, 2014). The steady shift towards a data-rich environment that research in applied geography recently experienced (Miller, Goodchild, 2015) strongly enhanced the need to outline effective and functional tools able to collect, manage, analyse and display the growingly available georeferenced data in any field of spatially-based studies. Dashboards became one of the most popular and effective tools for connecting large public to scientific results and official data communication
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