ArticleJournal of medical Internet research2021
SARS-CoV-2: The Second Wave in Europe.
Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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.
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.
Who cites it
7 citing papers in PubMed.
- Comorbidity patterns associated with severe COVID-19 outcomes: A cohort study based on the UK Biobank.PloS one · 2025Article
- An algebraic formula, deep learning and a novel SEIR-type model for the COVID-19 pandemic.Royal Society open science · 2023Article
- Spatiotemporal Patterns of the Omicron Wave of COVID-19 in the United States.Tropical medicine and infectious disease · 2023Article
- Comparison between first and second wave of COVID-19 outbreak in older people: the COPE multicentre European observational cohort study.European journal of public health · 2022Observational
- Influence of Forced Online Distance Education During the COVID-19 Pandemic on the Perceived Stress of Postsecondary Students: Cross-sectional Study.Journal of medical Internet research · 2022Article
- Article
- Analysis of the effects of the first and second/third waves of the COVID-19 pandemic on an Interdisciplinary Endoscopy Unit in a German 'hotspot' area: a single-center experience.Therapeutic advances in gastroenterology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although the SARS-CoV-2 virus has already undergone several mutations, the impact of these mutations on its infectivity and virulence remains controversial. In this viewpoint, we present arguments suggesting that SARS-CoV-2 mutants responsible for the second wave have less virulence but much higher infectivity. This suggestion is based on the results of the forecasting and mechanistic models developed by our study group. In particular, in May 2020, the analysis of our mechanistic model predicted that the easing of lockdown measures will lead to a dramatic second wave of the COVID-19 outbreak. However, after the lockdown was lifted in many European countries, the resulting number of reported infected cases and especially the number of deaths remained low for approximately two months. This raised the false hope that a substantial second wave will be avoided and that the COVID-19 epidemic in these European countries was nearing an end. Unfortunately, since the first week of August 2020, the number of reported infected cases increased dramatically. Furthermore, this was accompanied by an increasingly large number of deaths. The rate of reported infected cases in the second wave was much higher than that in the first wave, whereas the rate of deaths was lower. This trend is consistent with higher infectivity and lower virulence. Even if the mutated form of SARS-CoV-2 is less virulent, the very high number of reported infected cases implies that a large number of people will perish.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.