Evidence map›Paper›PMID 36324043›Full record

ArticleAdvances in experimental medicine and biology2023

Seasonal Variation Analysis for Weekly Cases, Deaths, and Hospitalizations of COVID-19 in the United States.

Tianze Xu, Yingying Cui

Abstract read
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In one paragraph

Article in Advances in experimental medicine and biology, 2023. 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
1.0field-weighted citation impact, top 24% of its field
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, 1 citations in OpenAlex.

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

2 authors at 1 institution in 1 country.

Tianze XuHenan University of Urban Construction, Pingdingshan, China. selecxtz@126.com.
Yingying CuiHenan University of Urban Construction, Pingdingshan, China.
Henan University of Urban Construction · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Knowing the seasonality of COVID-19 helps decision-makers to take suitable interventions against the pandemic. In this study, we performed the Brown-Forsythe variance analysis on seasonal variations on different indicators based on the data on COVID-19 for the United States provided publicly by WHO. Our study finds that the seasonality of weekly cases and deaths of COVID-19 are strongly statistically supported by the data. The weekly total cases(/deaths) in winter are three to seven times(/two to three times) more than the other three single seasons. The ICU patients in winter and autumn are four to five times more than spring. The weekly hospital admissions in winter are four times more than spring. The mean of the positive rate in winter is five times more than spring. The findings of this research can be a reference in decision-making when taking interventions against the pandemic, such as taking stricter interventions in winter while considering less strict interventions in summer, etc.

Indexed as

COVID-19BiometryHospitalizationHumansSeasonsUnited StatesCOVID-19SeasonalityVariance analysis

Identifiers

PMID36324043
OpenAlexW4308056064

What Socratic 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 Socratic graph.