The disease severity of COVID-19 caused by Omicron variants: A brief review

Uemura, Kohei; Kanata, Takumi; Ono, Sachiko; Michihata, Nobuaki; Yasunaga, Hideo

doi:10.37737/ace.23005

Cited by 5 publications

(3 citation statements)

References 32 publications

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“…The Tokyo Olympics took place before the fifth peak, and may have encouraged movement by young people before vaccination. Although the omicron strain was highly infectious, the rate of severe illness is reportedly lower than that of other strains [ 27 , 28 ]. While some vaccines have low efficacy at preventing infection by the omicron strain, vaccination is known to prevent serious illness after infection [ 29 ].…”

Section: Discussionmentioning

confidence: 99%

Medical resource usage for COVID-19 evaluated using the National Database of Health Insurance Claims and Specific Health Checkups of Japan

Fukuyama,

Mori,

Ueshima

et al. 2024

PLoS ONE

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Purpose The coronavirus disease 2019 (COVID-19) pandemic exhibited several different waves threatening global health care. During this pandemic, medical resources were depleted. However, the kind of medical resources provided to each wave was not clarified. This study aimed to examine the characteristics of medical care provision at COVID-19 peaks in preparation for the next pandemic. Methods Using medical insurance claim records in Japan, we examined the presence or absence of COVID-19 infection and the use of medical resources for all patients monthly by age group. Results The wave around August 2021 with the Delta strain had the strongest impact on the working population in terms of hospital admission and respiratory support. For healthcare providers, this peak had the highest frequency of severely ill patients. In the subsequent wave, although the number of patients with COVID-19 remained high, they were predominantly older adults, with relatively fewer patients receiving intensive care. Conclusions In future pandemics, we should refer to the wave around August 2021 as a situation of medical resource shortage resulting from the COVID-19 pandemic.

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Section: Discussionmentioning

confidence: 99%

Medical resource usage for COVID-19 evaluated using the National Database of Health Insurance Claims and Specific Health Checkups of Japan

Fukuyama,

Mori,

Ueshima

et al. 2024

PLoS ONE

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“…Other studies performed in Poland complemented these findings, indicating that the Delta variant is associated with a more severe disease course and a higher risk of death relative to Omicron [ 3 , 35 ]. Furthermore, the mortality of Omicron-infected individuals ranged from 0.01 to 13.1%, but those affected by previous variants ranked between 0.08% and 29.1%, with the proportions of intensive care unit admissions and mechanical ventilation being lower during the Omicron period [ 36 ]. However, it is important to note that some data report a comparable severity of Omicron infections relative to Delta [ 37 ], emphasizing that there is still a substantial risk for severe illness.…”

Section: Discussionmentioning

confidence: 99%

The Course of COVID-19 and Long COVID: Identifying Risk Factors among Patients Suffering from the Disease before and during the Omicron-Dominant Period

Babicki,

Kołat,

Kałuzińska-Kołat

et al. 2024

Pathogens

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SARS-CoV-2 has acquired many mutations that influence the severity of COVID-19’s course or the risk of developing long COVID. In 2022, the dominant SARS-CoV-2 variant was Omicron. This study aimed to compare the course of COVID-19 in the periods before and during the dominance of the Omicron variant. Risk factors for developing long COVID were also assessed. This study was based on stationary visits of patients after COVID-19 and follow-up assessments after 3 months. Clinical symptoms, comorbidities, and vaccination status were evaluated in 1967 patients. Of the analyzed group, 1308 patients (66.5%) were affected by COVID-19 in the period before the Omicron dominance. The prevalence of long COVID was significantly lower among patients of the Omicron group (47.7% vs. 66.9%, p < 0.001). The risk of long COVID was higher for women (OR: 1.61; 95% CI: 1.31, 1.99]) and asthmatics (OR: 1.46; 95% CI: 1.03, 2.07]). Conclusively, infection during the Omicron-dominant period was linked to a lower risk of developing long COVID. Females are at higher risk of developing long COVID independent of the pandemic period. Individuals affected by COVID-19 in the Omicron-dominant period experience a shorter duration of symptoms and reduced frequency of symptoms, except for coughing, which occurs more often.

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“…The evolution of this pandemic and its consequences were reflected in the mortality and morbidity of populations, leading to the development of several scientific studies and research projects all over the world [1][2][3][4][5][6][7][8][9][10][11]. For instance, the study carried out by Florensa et al [1] was carried out in Lleida, Spain, and compared the Alpha variant, first detected in the United Kingdom, and the Delta variant, first detected in India.…”

Section: Introductionmentioning

confidence: 99%

An Interactive Dashboard for Statistical Analysis of Intensive Care Unit COVID-19 Data

Dias,

Ferreira,

Pinto

et al. 2024

BioMedInformatics

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Background: COVID-19 caused a pandemic, due to its ease of transmission and high number of infections. The evolution of the pandemic and its consequences for the mortality and morbidity of populations, especially the elderly, generated several scientific studies and many research projects. Among them, we have the Predictive Models of COVID-19 Outcomes for Higher Risk Patients Towards a Precision Medicine (PREMO) research project. For such a project with many data records, it is necessary to provide a smooth graphical analysis to extract value from it. Methods: In this paper, we present the development of a full-stack Web application for the PREMO project, consisting of a dashboard providing statistical analysis, data visualization, data import, and data export. The main aspects of the application are described, as well as the diverse types of graphical representations and the possibility to use filters to extract relevant information for clinical practice. Results: The application, accessible through a browser, provides an interactive visualization of data from patients admitted to the intensive care unit (ICU), throughout the six waves of COVID-19 in two hospitals in Lisbon, Portugal. The analysis can be isolated per wave or can be seen in an aggregated view, allowing clinicians to create many views of the data and to study the behavior and consequences of different waves. For instance, the experimental results show clearly the effect of vaccination as well as the changes on the most relevant clinical parameters on each wave. Conclusions: The dashboard allows clinicians to analyze many variables of each of the six waves as well as aggregated data for all the waves. The application allows the user to extract information and scientific knowledge about COVID-19’s evolution, yielding insights for this pandemic and for future pandemics.

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The disease severity of COVID-19 caused by Omicron variants: A brief review

Cited by 5 publications

References 32 publications

Medical resource usage for COVID-19 evaluated using the National Database of Health Insurance Claims and Specific Health Checkups of Japan

Medical resource usage for COVID-19 evaluated using the National Database of Health Insurance Claims and Specific Health Checkups of Japan

The Course of COVID-19 and Long COVID: Identifying Risk Factors among Patients Suffering from the Disease before and during the Omicron-Dominant Period

An Interactive Dashboard for Statistical Analysis of Intensive Care Unit COVID-19 Data

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