Evidence map›Paper›PMID 33551640›Full record

ArticleEvolutionary bioinformatics online2021

Temperature and Latitude Correlate with SARS-CoV-2 Epidemiological Variables but not with Genomic Change Worldwide.

Prakruthi Burra, Katiria Soto-Díaz, Izan Chalen, Rafael Jaime Gonzalez-Ricon, Dave Istanto, Gustavo Caetano-Anollés

Abstract read
In one paragraph

Article in Evolutionary bioinformatics online, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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  18. Comparable seasonal pattern for COVID-19 and flu-like illnesses.One health (Amsterdam, Netherlands) · 2021
    Article
  19. Which influenza viruses will emerge following the SARS-CoV-2 pandemic?Influenza and other respiratory viruses · 2021
    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

6 authors.

Prakruthi BurraDepartment of Computer Science, University of Illinois at Urbana-Champaign, USA.
Katiria Soto-DíazNeuroscience Program, University of Illinois at Urbana-Champaign, USA.ORCID https://orcid.org/0000-0002-7425-6995
Izan ChalenDepartment of Animal Sciences, University of Illinois at Urbana-Champaign, USA.ORCID https://orcid.org/0000-0002-4607-8140
Rafael Jaime Gonzalez-RiconDepartment of Animal Sciences, University of Illinois at Urbana-Champaign, USA.
Dave IstantoDepartment of Crop Sciences, University of Illinois at Urbana-Champaign, USA.
Gustavo Caetano-AnollésDepartment of Crop Sciences, University of Illinois at Urbana-Champaign, USA.ORCID https://orcid.org/0000-0001-5854-4121

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The SARS-CoV-2 virus that causes the COVID-19 disease has spread quickly and massively around the entire globe, causing millions of confirmed cases and deaths worldwide. The disease poses a serious ongoing threat to public health. This study aims to understand the disease potential of the virus in different regions by studying how average spring temperature and its strong predictor, latitude, affect epidemiological variables such as disease incidence, mortality, recovery cases, active cases, testing rate, and hospitalization. We also seek to understand the association of temperature and geographic coordinates with viral genomics. Epidemiological data along with temperature, latitude, longitude, and preparedness index were collected for different countries and US states during the early stages of the pandemic. Our worldwide epidemiological analysis showed a significant correlation between temperature and incidence, mortality, recovery cases and active cases. The same tendency was found with latitude, but not with longitude. In the US, we observed no correlation between temperature or latitude and epidemiological variables. Interestingly, longitude was correlated with incidence, mortality, active cases, and hospitalization. An analysis of mutational change and mutational change per time in 55 453 aligned SARS-CoV-2 genome sequences revealed these parameters were uncorrelated with temperature and geographic coordinates. The epidemiological trends we observed worldwide suggest a seasonal effect for the disease that is not directly controlled by the genomic makeup of the virus. Future studies will need to determine if correlations are more likely the result of effects associated with the environment or the innate immunity of the host.

Indexed as

active casesCOVID-19genome analysishospitalizationincidencemortalitymutationrecovery patientsSARS-CoV-2testing rate

Identifiers

PMID33551640
PMCPMC7841253

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Registered trials

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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.