Evidence map›Paper›PMID 33774202›Full record

ArticleJournal of biomedical informatics2021

Visual analytics of COVID-19 dissemination in São Paulo state, Brazil.

Wilson E Marcílio-Jr, Danilo M Eler, Rogério E Garcia, Ronaldo C M Correia, Rafael M B Rodrigues

Abstract read
In one paragraph

Article in Journal of biomedical informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

5 authors.

Wilson E Marcílio-JrDepartment of Mathematics and Computer Science, São Paulo State University (UNESP), Presidente Prudente, SP, Brazil. Electronic address: wilson.marcilio@unesp.br.
Danilo M ElerDepartment of Mathematics and Computer Science, São Paulo State University (UNESP), Presidente Prudente, SP, Brazil.
Rogério E GarciaDepartment of Mathematics and Computer Science, São Paulo State University (UNESP), Presidente Prudente, SP, Brazil.
Ronaldo C M CorreiaDepartment of Mathematics and Computer Science, São Paulo State University (UNESP), Presidente Prudente, SP, Brazil.
Rafael M B RodriguesDepartment of Mathematics and Computer Science, São Paulo State University (UNESP), Presidente Prudente, SP, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visual analytics techniques are useful tools to support decision-making and cope with increasing data, particularly to monitor natural or artificial phenomena. When monitoring disease progression, visual analytics approaches help decision-makers to understand or even prevent dissemination paths. In this paper, we propose a new visual analytics tool for monitoring COVID-19 dissemination. We use k-nearest neighbors of cities to mimic neighboring cities and analyze COVID-19 dissemination based on comparing a city under consideration and its neighborhood. Moreover, such analysis is performed within periods, which facilitates the assessment of isolation policies. We validate our tool by analyzing the progression of COVID-19 in neighboring cities of São Paulo state, Brazil.

Indexed as

Data VisualizationBrazilCitiesCOVID-19HumansSARS-CoV-2COVID-19Risk assessmentVisual analytics

Identifiers

PMID33774202
PMCPMC7987578

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.