Abstract
Abstract
Background
The growing need for and interest in geomatics in the medical sector, as well as the pandemic crisis, led us to create a France-wide geomatics project aimed at producing several atlases of all-cause mortality at the municipal and submunicipal district levels via uMap France, a free and open-source collaborative map-sharing platform. In 2020, we decided to circumvent the obstacle of accessing detailed COVID-19 data by adopting a mortality-based approach to map the consequences of the crisis.
Objective
The aim of the uMap study was to provide a webmapping platform with original visualization and knowledge as well as decision-making aids that complement existing information and are relevant to public and health care professionals. Our main hypotheses were as follows: (1) The medical sector could develop a private uMap platform dedicated to health; (2) interest in a municipal mortality atlas for France linked to the pandemic crisis will increase, even if it is produced after the pandemic; and (3) sharing the atlases with the uMap community will enhance their appeal and inspire the creation of similar atlases, owing to the new “experimental choropleth layer” recently developed by the uMap team.
Methods
This approach focused on 3 main parts—data management (data collection, cleansing, and scheduling) and geomatic engineering through a 2-step geomatic action plan to create atlases of the first lockdown period in France displayed on the uMap platform. A logarithmically transformed variable allowed us to obtain an immediate statistical signal of excess mortality or submortality via the Traffic-Light Atlas.
Results
The uMap Traffic-Light Atlas display provides instant statistical signals at a glance, owing to the semantic interplay of colors. The atlas’s double legends make it easy to compare specific regions (northeast, northwest, southeast, and southwest) with all of France. The atlas revealed excess mortality in 41.7% (14,503/34,833) of the municipalities. Of the municipalities, 35% (12,198/34,833) were in the green class (close to average to 2 times the average), 5% (1724/34,833) were in the orange class (2‐4 times the average), and 1.7% (581/34,833) were in the red class (4‐11 times higher than average).
Conclusions
We innovated, enriched, and reinforced the value of uMap for visual rendering by instantiating colored choropleth map atlases and double legends and showed its relevance to the health care sector. We focused on the Traffic-Light Atlas, which is the most relevant aspect because of the instant message it conveys and its interpretability for all audiences. The uMap community can share our all-cause mortality atlases. A second version of the atlas encompassing 4 periods in 2020 and containing a minor error will be updated using either the “experimental choropleth layer” feature recently developed by the uMap team or, if this feature proves insufficient, the geomatic optimization process via the R project.