Evidence map›Paper›PMID 35605752›Full record

ArticleAmerican journal of infection control2022

Viral transmissibility of SARS-CoV-2 accelerates in the winter, similarly to influenza epidemics.

Shinako Inaida, Richard E Paul, Shigeo Matsuno

Abstract read
In one paragraph

Article in American journal of infection control, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Observational
  2. Review
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  5. Observational
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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

3 authors.

Shinako InaidaGraduate School of Medicine, Kyoto University, Kyoto, Japan; Department of Environmental Medicine and Behavioral Science, Faculty of Medicine, Kindai University. Electronic address: inaida.shinako.42x@st.kyoto-u.ac.jp.
Richard E PaulPasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan.
Shigeo MatsunoBiomedical Science Association, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The transmissibility of SARS-CoV-2 is anticipated to increase in the winter because of increased viral survival in cold damp air and thus would exacerbate viral spread in community. Analysis to capture the seasonal trend is needed to be prepared for future epidemics. We compared regression models for the 5-week case prior to each epidemic peak week for both the COVID-19 and influenza epidemics in winter and summer. The weekly case increase ratio was compared, using non-paired t tests between seasons. In order to test the robustness of seasonal transmission patterns, the normalized weekly case numbers of COVID-19 and influenza case rates of all seasons were assessed in a combined quadratic regression analysis. In winter, the weekly case increase ratio accelerated before epidemic peaks, similarly, for both COVID-19 and influenza. The quadratic regression models of weekly cases were observed to be convex curves in the winter and concave curves in the spring/summer for both COVID-19 and influenza. A significant increase of case increase ratio (3.19 [95%CI:0.01-6.37, P = .049]) of the COVID-19 and influenza epidemics was observed in winter as compared to spring/summer before the epidemic peak. The epidemic of COVID-19 was found to mirror that of influenza, suggesting a strong underlying seasonal transmissibility. Influenza epidemics can potentially be a useful reference for the COVID-19 epidemics.

Indexed as

COVID-19EpidemicsInfluenza, HumanHumansSARS-CoV-2SeasonsCase increase ratioEpidemiologyRespiratory virusesSeasonality

Identifiers

PMID35605752
PMCPMC9121648

What OpenQuestion holds

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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.