Currently submitted to: JMIR Medical Informatics
Date Submitted: Aug 22, 2025
Open Peer Review Period: Sep 24, 2025 - Nov 19, 2025
(closed for review but you can still tweet)
NOTE: This is an unreviewed Preprint
Warning: This is a unreviewed preprint (What is a preprint?). Readers are warned that the document has not been peer-reviewed by expert/patient reviewers or an academic editor, may contain misleading claims, and is likely to undergo changes before final publication, if accepted, or may have been rejected/withdrawn (a note "no longer under consideration" will appear above).
Peer review me: Readers with interest and expertise are encouraged to sign up as peer-reviewer, if the paper is within an open peer-review period (in this case, a "Peer Review Me" button to sign up as reviewer is displayed above). All preprints currently open for review are listed here. Outside of the formal open peer-review period we encourage you to tweet about the preprint.
Citation: Please cite this preprint only for review purposes or for grant applications and CVs (if you are the author).
Final version: If our system detects a final peer-reviewed "version of record" (VoR) published in any journal, a link to that VoR will appear below. Readers are then encourage to cite the VoR instead of this preprint.
Settings: If you are the author, you can login and change the preprint display settings, but the preprint URL/DOI is supposed to be stable and citable, so it should not be removed once posted.
Submit: To post your own preprint, simply submit to any JMIR journal, and choose the appropriate settings to expose your submitted version as preprint.
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Relevance of the uMap Collaborative Platform as Support for Choropleth Mapping: A Traffic Light Alert Atlas of All-Cause Mortality—First French Lockdown
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.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.