Evidence map›Paper›PMID 33815029›Full record

ArticleEcological informatics2021

Numerical analysis of factors, pace and intensity of the corona virus (COVID-19) epidemic in Poland.

Piotr Andrzej Kowalski, Marcin Szwagrzyk, Jolanta Kielpinska, Aleksander Konior, Maciej Kusy

Abstract read
In one paragraph

Article in Ecological informatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Changes in Air-Pollution-Related Information-Seeking Behaviour during the COVID-19 Pandemic in Poland.International journal of environmental research and public health · 2022
    Article
  8. Air Pollution in Poland: A 2022 Narrative Review with Focus on Respiratory Diseases.International journal of environmental research and public health · 2022
    Review
  9. Article
  10. 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.

Piotr Andrzej KowalskiFaculty of Physics and Applied Computer Science, AGH University of Science and Technology, al. Mickiewicza 30, 30-059 Cracow, Poland.
Marcin SzwagrzykFaculty of Geography and Geology, Institute of Geography and Spatial Management, Jagiellonian University, Gronostajowa 7, 30-387 Cracow, Poland.
Jolanta KielpinskaDepartment of Aquatic Bioengineering and Aquaculture, Faculty of Food Science and Fisheries, West Pomeranian University of Technology in Szczecin, Poland.
Aleksander KoniorAirly Inc., ul. Mogilska 43, 31-545 Cracow, Poland.
Maciej KusyFaculty of Electrical and Computer Engineering, Rzeszow University of Technology, al. Powstancow Warszawy 12, 35-959 Rzeszow, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article focuses on a statistical analysis of the corona virus disease 2019 (COVID-19) data that appeared until November 31, 2020 in Poland. The studied database, expressed in terms of both population and air pollution (particulate) indicators, is provided mainly by the Airly company, the Central Statistical Office (GUS) and the Rogalski project. The particular measured factors, which underwent standardization, were assessed for mutual dependency by means of a Pearson correlation coefficient and analysed by a linear regression. Based on the presented models, our results indicate that air quality (air pollution level) is the most important factor in the context of enabling COVID-19 case load increase in Poland.

Indexed as

Corona virusCOVID-19Disease curveEpidemiological modelExcess mortalityFactor analysisLeast-squares estimationMultivariate linear regressionPearson's correlation

Identifiers

PMID33815029
PMCPMC8006517

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.