Evidence map›Paper›PMID 42695700›Full record

ArticleJMIR medical informatics2026

Relevance of the uMap Collaborative Platform as Support for Choropleth Mapping of a Traffic-Light Statistical Signal Atlas of All-Cause Mortality During the First French Lockdown: Geospatial Analysis.

Anne Quesnel-Barbet, Thierry Pages, Julien Soula, Gilles Maignant, Arnaud Hansske

Abstract read
In one paragraph

Article in JMIR medical informatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Anne Quesnel-Barbet *Public Health - Regional House of Clinical Research (MRRC), Lille University Hospital (CHU de Lille), 6 rue du Pr Laguesse, CS 70001, Lille cedex, 59037, France, 33 0658066808.ORCID 0000-0003-1038-7344
Thierry Pages *TITSOFT Inc, Montpellier, France.ORCID 0000-0002-6075-7633
Julien Soula *ULR 2694 - METRICS: Évaluation des technologies de santé et des pratiques médicales, University of Lille, CHU Lille, F-59000 Lille, France.ORCID 0000-0003-0875-7713
Gilles Maignant *Faculty of Medicine, Laboratory of RETINES, University of Côte d'Azur (UCA), Nice Cedex 2, France.ORCID 0000-0003-2017-3972
Arnaud Hansske *DSI/CIO/CMIO, Catholic Hospitals of Lille (GHICL), Lille, France.ORCID 0000-0001-7029-2318

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

COVID-19Geographic MappingMortalityQuarantineCause of DeathDashboard SystemsFranceHumansSARS-CoV-2choropleth mappingcollaborative platformgeographic information systemsgeomatics atlasGIShealth information systemsinformation scienceinformation servicesmortalitytraffic light semanticuMap online map creator

Identifiers

PMID42695700
PMCPMC13543287

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.