JMIR Publications

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 the public and healthcare professionals. Our main hypotheses are 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 focuses on three main parts—data management (data collection, cleansing and scheduling) and geomatic engineering—through a two-step geomatic action plan to create atlases of the first lockdown period in France, displayed on the uMap platform. A logarithmically transformed variable allows us to obtain an immediate warning indicator of excess mortality or submortality via the Traffic Light Atlas.

Results:

The uMap traffic light display provides instant alerts 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, southwest) to the whole of France. The atlas revealed excess mortality in 42% of the municipalities (14,503) out of 34,833. Thirty-five percent are in the green class (close to average to twice the average), 5% are in the orange class (2–4 times the average), and 2% are 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 healthcare sector. We focused on the Traffic Light Atlas, which is the most relevant 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 four 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.