Evidence map›Paper›PMID 35457649›Full record

ArticleInternational journal of environmental research and public health2022

PandemonCAT: Monitoring the COVID-19 Pandemic in Catalonia, Spain.

Somnath Chaudhuri, Gerard Giménez-Adsuar, Marc Saez, Maria A Barceló

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Somnath ChaudhuriResearch Group on Statistics, Econometrics and Health (GRECS), University of Girona, 17004 Girona, Spain.ORCID 0000-0003-4899-1870
Gerard Giménez-AdsuarResearch Group on Statistics, Econometrics and Health (GRECS), University of Girona, 17004 Girona, Spain.
Marc SaezResearch Group on Statistics, Econometrics and Health (GRECS), University of Girona, 17004 Girona, Spain.ORCID 0000-0003-1882-0157
Maria A BarcelóResearch Group on Statistics, Econometrics and Health (GRECS), University of Girona, 17004 Girona, Spain.ORCID 0000-0001-9720-690X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe principal objective of this paper is to introduce an online interactive application that helps in real-time monitoring of the COVID-19 pandemic in Catalonia, Spain (PandemonCAT).

methodsThis application is designed as a collection of user-friendly dashboards using open-source R software supported by the Shiny package.

resultsPandemonCAT reports accumulated weekly updates of COVID-19 dynamics in a geospatial interactive platform for individual basic health areas (ABSs) of Catalonia. It also shows on a georeferenced map the evolution of vaccination campaigns representing the share of population with either one or two shots of the vaccine, for populations of different age groups. In addition, the application reports information about environmental and socioeconomic variables and also provides an interactive interface to visualize monthly public mobility before, during, and after the lockdown phases. Finally, we report the smoothed standardized COVID-19 infected cases and mortality rates on maps of basic health areas ABSs and regions of Catalonia. These smoothed rates allow the user to explore geographic patterns in incidence and mortality rates. The visualization of the variables that could have some influence on the spatiotemporal dynamics of the pandemic is demonstrated.

conclusionsWe believe the addition of these new dimensions, which is the key innovation of our project, will improve the current understanding of the spread and the impact of COVID-19 in the community. This application can be used as an open tool for consultation by the public of Catalonia and Spain in general. It could also have implications in facilitating the visualization of public health data, allowing timely interpretation due to the unpredictable nature of the pandemic.

Indexed as

COVID-19Communicable Disease ControlHumansPandemicsSARS-CoV-2SpainCOVID-19mobilityshinyspatiotemporal

Identifiers

PMID35457649
PMCPMC9029369

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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.