80 datasets found
  1. Concern about elderly relatives due to the COVID-19 epidemic in Norway 2020

    • statista.com
    Updated Jul 31, 2024
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    Statista (2024). Concern about elderly relatives due to the COVID-19 epidemic in Norway 2020 [Dataset]. https://www.statista.com/statistics/1104909/health-concerns-elderly-relatives-due-to-the-covid-19-coronavirus-epidemic-in-norway-by-gender/
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    Dataset updated
    Jul 31, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 12, 2020
    Area covered
    Norway
    Description

    In the light of the coronavirus COVID-19 pandemic, more than 64 percent of Norwegians worried about the health of elderly relatives, according to a survey conducted on March 12, 2020. When asked about personal health, however, the Norwegians seem to be much less concerned. Spreading rapidly The coronavirus is currently spreading quickly in Norway. The first case was detected on February 26. Since then the cumulative number of cases has increased drastically on a daily basis. Furthermore, the official numbers of tested and confirmed cases are esteemed to be severely lower than the actual number of coronavirus infected people in Norway. Scandinavia and Europe In comparison to its neighboring countries, Norway has reported the most cases of the virus as of March 18, 2020, followed closely by Sweden and Denmark. On a broader scale, Norway currently ranks 9th among the European countries. In Europe, Italy has suffered the most from coronavirus, and the country accounts for the majority of cases in Europe, with over 30,000 infected individuals.

  2. f

    “Asymptomatic COVID-19 in the elderly: dementia and viral clearance as risk...

    • figshare.com
    txt
    Updated Mar 26, 2022
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    Ignacio Esteban (2022). “Asymptomatic COVID-19 in the elderly: dementia and viral clearance as risk factors for disease progression”. Stata Dofile [Dataset]. http://doi.org/10.6084/m9.figshare.15050220.v2
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    txtAvailable download formats
    Dataset updated
    Mar 26, 2022
    Dataset provided by
    figshare
    Authors
    Ignacio Esteban
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This file contains the STATA dofile of the submitted article: “Asymptomatic COVID-19 in the elderly: dementia and viral clearance as risk factors for disease progression”.

  3. d

    Clinical characteristics, risk factors and complications of COVID-19 among...

    • search.dataone.org
    Updated Nov 30, 2023
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    Arfath Ahmed; Sheetal Raj Moolambally; Archith Boloor; Animesh Jain; Nandish Kumar S; Sharath Babu S. (2023). Clinical characteristics, risk factors and complications of COVID-19 among critically ill older adults – A case control study [Dataset]. http://doi.org/10.5061/dryad.fqz612jxh
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    Dataset updated
    Nov 30, 2023
    Dataset provided by
    Dryad Digital Repository
    Authors
    Arfath Ahmed; Sheetal Raj Moolambally; Archith Boloor; Animesh Jain; Nandish Kumar S; Sharath Babu S.
    Time period covered
    Jan 1, 2023
    Description

    Background: The older population is often disproportionately and adversely affected during humanitarian emergencies, as has also been seen during the COVID-19 pandemic. Data regarding COVID-19 in older adults is usually over-generalised and does not delve into details of the clinical characteristics in them. This study was conducted to analyse clinical and laboratory characteristics, risk factors, and complications of COVID-19 between older adults who survived and those who did not. Methods: We conducted a case-control study among older adults(age > 60 years) admitted to the Intensive Care Unit(ICU) during the COVID-19 pandemic. The non-survivors (cases) were matched with age and sex-matched survivors (control) in a ratio of 1: 3. The data regarding socio-demographics, clinical characteristics, complications, treatment, laboratory data, and outcomes were analysed. Results: The most common signs and symptoms observed were fever (cases vs controls) (68.92 vs. 68.8%), followed by shortn..., A hospital-based case-control study was undertaken. Data was collected from the Intensive Care Unit(ICU) from December 2020 to September 2022. The sample size was calculated with a two-sided confidence level(1-α) of 95, 80% power, and with a ratio of controls to cases at 3:1. A sample size of 260 was calculated consisting of 195 controls and 65 cases. A Case was defined as a COVID-19-positive individual older than 60 years who, after being admitted or transferred to the ICU, did not survive, i.e., non-survivor. A Control was defined as a COVID-19-positive individual with age greater than 60 years who was admitted or transferred to the ICU, following which the patient recovered(survived) and was discharged alive from the hospital, i.e., survivor. Those patients who were admitted for post-COVID-19 complications or for COVID-19 unrelated medical conditions following discharge after initial treatment for COVID-19 pneumonia were excluded. The cases (non-survivors) were recruited according to..., Microsoft Excel, Word

  4. Distribution of coronavirus deaths in Italy as of May 2023, by age group

    • statista.com
    Updated Feb 15, 2022
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    Statista (2022). Distribution of coronavirus deaths in Italy as of May 2023, by age group [Dataset]. https://www.statista.com/statistics/1106367/coronavirus-deaths-distribution-by-age-group-italy/
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    Dataset updated
    Feb 15, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 3, 2023
    Area covered
    Italy
    Description

    The spread of coronavirus (COVID-19) in Italy has not hit uniformly people of every age, as about 60 percent of the individuals infected with the virus were under 50 years old. However, deaths occurred mostly among the elderly. The virus has claimed approximately 190 thousand lives, but, as the chart shows, roughly 85 percent of the victims were older people, aged 70 years or more. People between 80 and 89 years were the most affected, with roughly 76 thousand deaths within this age group.

    Number of total cases Since the first case was detected, coronavirus has spread quickly across Italy. As of April 2023, authorities have reported over 25.8 million cases in the country. This figure includes the deceased, the recovered, and current active cases. COVID recoveries represent the vast majority, reaching approximately 25.5 million.

    Regional differences In terms of COVID cases, Lombardy has been the hardest hit region, followed by the regions of Campania, and Veneto. Likewise, in terms of deaths, Lombardy was the region with the highest number, with roughly 46 thousand losses. On the other hand, this is also the region with the highest number of COVID-19 vaccine administered doses, with a figure of approximately 25.5 million.

    For a global overview visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

  5. m

    5 Waves Covid-19 in Iran

    • data.mendeley.com
    Updated May 28, 2024
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    Abdolrahim Asadollahi, PhD, MSC., GGCP (2024). 5 Waves Covid-19 in Iran [Dataset]. http://doi.org/10.17632/ryx79j8p65.1
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    Dataset updated
    May 28, 2024
    Authors
    Abdolrahim Asadollahi, PhD, MSC., GGCP
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Iran
    Description

    During the five waves of the Covid-19 pandemic from January 2020 to September 2021, Iranians’ concern about the number of elderly cases that were adversely affected by Covid-19 highly increased. The present study aimed to evaluate the mental and the physical health of Iranian older adults across the big waves of the Covid-19 pandemic. In an analytical and longitudinal study, the health of 517 older people with a positive test in Covid 19 disease during 5 waves of coronavirus in south Iran.

  6. COVID-19 deaths reported in the U.S. as of June 14, 2023, by age

    • statista.com
    Updated Jun 21, 2023
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    Statista (2023). COVID-19 deaths reported in the U.S. as of June 14, 2023, by age [Dataset]. https://www.statista.com/statistics/1191568/reported-deaths-from-covid-by-age-us/
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    Dataset updated
    Jun 21, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 1, 2020 - Jun 14, 2023
    Description

    Between the beginning of January 2020 and June 14, 2023, of the 1,134,641 deaths caused by COVID-19 in the United States, around 307,169 had occurred among those aged 85 years and older. This statistic shows the number of coronavirus disease 2019 (COVID-19) deaths in the U.S. from January 2020 to June 2023, by age.

  7. Patient profile of COVID-19 cases Japan 2022, by age group

    • statista.com
    • ai-chatbox.pro
    Updated Jan 9, 2024
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    Statista (2024). Patient profile of COVID-19 cases Japan 2022, by age group [Dataset]. https://www.statista.com/statistics/1105162/japan-patients-detail-novel-coronavirus-covid-19-cases-by-age-and-gender/
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    Dataset updated
    Jan 9, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 8, 2022
    Area covered
    Japan
    Description

    The distribution of coronavirus disease (COVID-19) cases in Japan as of March 16, 2022, showed that the highest number of patients were aged 20 to 29 years old, with a total of over one million cases. The highest number of deaths could be seen among the patients aged 80 years and older at about 15.5 thousand cases.

     Shortage of intensive care beds 

    With over 1,200 hospital beds per 100,000 inhabitants available in the country, Japan is one of the best-equipped OECD nations regarding the medical sector. However, after the COVID-19 outbreak, country has faced a shortage of hospital beds, especially those required for intensive care. ICU beds only constitute a small share of the overall number of hospital beds in the country compared to European countries like Switzerland and Germany. To combat this problem, the Japanese government implemented financial incentives for hospitals upon acquisition of new intensive care beds. Another factor playing a significant part in the shortage of hospital beds is the comparably high average length of hospital stays, since some bedridden seniors are in long-term care in hospitals, as opposed to being cared for in nursing homes or at home.

    Challenges for private hospitals Japan’s over eight thousand hospitals were opened by doctors, leading to the majority of the institutions being privately owned. As many of them are specialized and dependent on outpatient surgeries, COVID-19 patients pose new difficulties, as treating them in a converted ward would hinder day-to-day operations. Acquisition of intensive care beds involves financial and logistical challenges, which smaller private institutions have difficulty meeting, as they are not funded by tax revenues.

    For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated facts and figure page.

  8. Coronavirus (COVID-19) deaths in Italy as of May 2023, by age group

    • statista.com
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    Statista, Coronavirus (COVID-19) deaths in Italy as of May 2023, by age group [Dataset]. https://www.statista.com/statistics/1105061/coronavirus-deaths-by-age-group-in-italy/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    May 3, 2023
    Area covered
    Italy
    Description

    After entering Italy, coronavirus (COVID-19) has been spreading fast. An analysis of the individuals who died after contracting the virus revealed that the vast majority of deaths occurred among the elderly. As of May, 2023, roughly 85 percent were patients aged 70 years and older.

    Italy's death toll was one of the most tragic in the world. In the last months, however, the country saw the end to this terrible situation: as of May 2023, roughly 84.7 percent of the total Italian population was fully vaccinated.

    As of May, 2023, the total number of cases reported in the country were over 25.8 million. The North of the country was the mostly hit area, and the region with the highest number of cases was Lombardy.

    For a global overview visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

  9. New York State Statewide COVID-19 Fatalities by Age Group (Archived)

    • health.data.ny.gov
    • healthdata.gov
    application/rdfxml +5
    Updated Sep 14, 2020
    + more versions
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    New York State Department of Health (2020). New York State Statewide COVID-19 Fatalities by Age Group (Archived) [Dataset]. https://health.data.ny.gov/Health/New-York-State-Statewide-COVID-19-Fatalities-by-Ag/du97-svf7
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    application/rssxml, tsv, csv, json, xml, application/rdfxmlAvailable download formats
    Dataset updated
    Sep 14, 2020
    Dataset authored and provided by
    New York State Department of Health
    Area covered
    New York
    Description

    Note: Data elements were retired from HERDS on 10/6/23 and this dataset was archived.

    This dataset includes the cumulative number and percent of healthcare facility-reported fatalities for patients with lab-confirmed COVID-19 disease by reporting date and age group. This dataset does not include fatalities related to COVID-19 disease that did not occur at a hospital, nursing home, or adult care facility. The primary goal of publishing this dataset is to provide users with information about healthcare facility fatalities among patients with lab-confirmed COVID-19 disease.

    The information in this dataset is also updated daily on the NYS COVID-19 Tracker at https://www.ny.gov/covid-19tracker.

    The data source for this dataset is the daily COVID-19 survey through the New York State Department of Health (NYSDOH) Health Electronic Response Data System (HERDS). Hospitals, nursing homes, and adult care facilities are required to complete this survey daily. The information from the survey is used for statewide surveillance, planning, resource allocation, and emergency response activities. Hospitals began reporting for the HERDS COVID-19 survey in March 2020, while Nursing Homes and Adult Care Facilities began reporting in April 2020. It is important to note that fatalities related to COVID-19 disease that occurred prior to the first publication dates are also included.

    The fatality numbers in this dataset are calculated by assigning age groups to each patient based on the patient age, then summing the patient fatalities within each age group, as of each reporting date. The statewide total fatality numbers are calculated by summing the number of fatalities across all age groups, by reporting date. The fatality percentages are calculated by dividing the number of fatalities in each age group by the statewide total number of fatalities, by reporting date. The fatality numbers represent the cumulative number of fatalities that have been reported as of each reporting date.

  10. f

    Data from: Prevalence and characteristics of Brazilians aged 50 and over...

    • scielo.figshare.com
    xls
    Updated Jun 1, 2023
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    James Macinko; Brayan V. Seixas; Natalia Oliveira Woolley; Fabiola Bof de Andrade; Maria Fernanda Lima-Costa (2023). Prevalence and characteristics of Brazilians aged 50 and over that received a doctor’s diagnosis of COVID-19: the ELSI-COVID-19 initiative [Dataset]. http://doi.org/10.6084/m9.figshare.14280905.v1
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    SciELO journals
    Authors
    James Macinko; Brayan V. Seixas; Natalia Oliveira Woolley; Fabiola Bof de Andrade; Maria Fernanda Lima-Costa
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Abstract: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused over half a million deaths worldwide. Brazil has been particularly impacted, registering more than 1.3 million infections and 57,000 deaths by late June 2020. Aggregate numbers of cases are essential in modeling the epidemic and planning responses; however, more detailed analysis of risk factors associated with SARS-CoV-2 infection are needed. Our study provides an initial examination of characteristics associated with receiving a doctor’s diagnosis of COVID-19 among a nationally representative sample of Brazilians aged 50 and over. Data are derived from the second wave of the Brazilian Longitudinal Study of Aging (ELSI-Brazil) and a telephone follow-up survey to ELSI-Brazil participants, known as the ELSI-COVID-19 initiative. The telephone survey was conducted between 26 May and 8 June 2020. Results show that about 2.4% (n = 70) of the sample reported being told by a doctor they had COVID-19, however, only about half of these individuals (n = 37) reported receiving a diagnostic confirmation from viral testing (RT-PCR). Demographic factors (aged 50-60 years), socioeconomic factors (lower household income), health-related factors (obesity, three or more chronic conditions), and geography (living in the Northern region of the country) were positively associated with reporting a COVID-19 diagnosis. Despite the descriptive and preliminary nature of these findings, results reported here suggest the need for more targeted approaches to enhance personal protection and provide greater viral testing options, especially for older, sicker and more vulnerable adults in Brazil.

  11. Baricitinib in the Treatment of Older Adults with COVID-19 – a Single Center...

    • zenodo.org
    bin
    Updated Sep 6, 2024
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    Vladyslava Kachkovska; Vladyslava Kachkovska; Sebastian Agata; Sebastian Agata; Marcin Madziarski; Ewa Morgiel; Ewa Morgiel; Marta Madej; Marta Madej; Krzysztof Proc; Krzysztof Proc; Janusz Sokołowski; Janusz Sokołowski; Joanna Żórawska; Joanna Żórawska; Michał Gronek; Michał Gronek; Woytala Patryk; Małgorzata Szymala-Pędzik; Małgorzata Szymala-Pędzik; Piotr Wiland; Piotr Wiland; Ewa A Jankowska; Ewa A Jankowska; Katarzyna Madziarska; Marcin Madziarski; Woytala Patryk; Katarzyna Madziarska (2024). Baricitinib in the Treatment of Older Adults with COVID-19 – a Single Center Study [Dataset]. http://doi.org/10.5281/zenodo.13711391
    Explore at:
    binAvailable download formats
    Dataset updated
    Sep 6, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Vladyslava Kachkovska; Vladyslava Kachkovska; Sebastian Agata; Sebastian Agata; Marcin Madziarski; Ewa Morgiel; Ewa Morgiel; Marta Madej; Marta Madej; Krzysztof Proc; Krzysztof Proc; Janusz Sokołowski; Janusz Sokołowski; Joanna Żórawska; Joanna Żórawska; Michał Gronek; Michał Gronek; Woytala Patryk; Małgorzata Szymala-Pędzik; Małgorzata Szymala-Pędzik; Piotr Wiland; Piotr Wiland; Ewa A Jankowska; Ewa A Jankowska; Katarzyna Madziarska; Marcin Madziarski; Woytala Patryk; Katarzyna Madziarska
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    This study investigates the impact of baricitinib, a drug used for treating COVID-19, on both elderly and younger patients. The single-center cohort study analyzed 88 hospitalized COVID-19 patients, 34 of whom were over 65 years old. The results showed that baricitinib was safe and well-tolerated among the elderly population, with no adverse effects observed. Moreover, the length of hospitalization did not differ significantly between age groups. Specific laboratory findings in the elderly group indicated physiological differences, but overall, baricitinib proved to be an effective therapeutic option for moderate to severe COVID-19 cases across all age groups.

  12. Share of U.S. COVID-19 patients who died from Jan. 22-May 30, 2020, by age

    • statista.com
    • ai-chatbox.pro
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    Statista, Share of U.S. COVID-19 patients who died from Jan. 22-May 30, 2020, by age [Dataset]. https://www.statista.com/statistics/1127639/covid-19-mortality-by-age-us/
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    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 22, 2020 - May 30, 2020
    Area covered
    United States
    Description

    It was estimated that around 30 percent of those aged 80 years and older who had COVID-19 in the United States from January 22 to May 30, 2020 died from the disease. Deaths due to COVID-19 are much higher among those with underlying health conditions such as cardiovascular disease, chronic lung disease, or diabetes. This statistic shows the percentage of people in the U.S. who had COVID-19 from January 22 to May 30, 2020 who died, by age.

    For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

  13. f

    Table_1_Risk factors for progression to severe infection and prolonged viral...

    • frontiersin.figshare.com
    bin
    Updated Apr 15, 2024
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    Siqi Tang; Qiuhong Man; Dongliang Zhu; Xueying Yu; Ruilin Chen; Shuo Wang; Yihan Lu; Qiqing Shi; Chen Suo; Lize Xiong (2024). Table_1_Risk factors for progression to severe infection and prolonged viral clearance time in hospitalized elderly patients infected with the Omicron variant of SARS-CoV-2: a retrospective study at Shanghai Fourth People's Hospital, School of Medicine, Tongji University.DOCX [Dataset]. http://doi.org/10.3389/fmicb.2024.1361197.s001
    Explore at:
    binAvailable download formats
    Dataset updated
    Apr 15, 2024
    Dataset provided by
    Frontiers
    Authors
    Siqi Tang; Qiuhong Man; Dongliang Zhu; Xueying Yu; Ruilin Chen; Shuo Wang; Yihan Lu; Qiqing Shi; Chen Suo; Lize Xiong
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Shanghai
    Description

    IntroductionIn elderly patients infected with the Omicron variant, disease progression to severe infection can result in poor outcomes. This study aimed to identify risk and protective factors associated with disease progression to severe infection and viral clearance time in elderly Omicron-infected patients.MethodsShanghai Fourth People's Hospital, School of Medicine, Tongji University, was officially designated to provide treatment to patients with COVID-19. This study was conducted on confirmed Omicron cases admitted to the hospital between 10 April 2022 and 21 June 2022. In total, 1,568 patients aged 65 years or older were included. We conducted a retrospective, observational study using logistic regression to analyze risk and protective factors for the development of severe disease and Cox proportional hazards regression models to analyze factors influencing viral clearance time.ResultsAged over 80 years, having 2 or more comorbidities, combined cerebrovascular disease, chronic neurological disease, and mental disorders were associated with the development of severe disease, and full vaccination was a protective factor. Furthermore, aged over 80 years, combined chronic respiratory disease, chronic renal disease, cerebrovascular disease, mental disorders, and high viral load were associated with prolonged viral clearance time, and full vaccination was a protective factor.DiscussionThis study analyzed risk factors for progression to severe infection and prolonged viral clearance time in hospitalized elderly Omicron-infected patients. Aged patients with comorbidities had a higher risk of developing severe infection and had longer viral clearance, while vaccination protected them against the Omicron infection.

  14. h

    OMOP dataset: Hospital COVID patients: severity, acuity, therapies, outcomes...

    • healthdatagateway.org
    unknown
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    This publication uses data from PIONEER, an ethically approved database and analytical environment (East Midlands Derby Research Ethics 20/EM/0158), OMOP dataset: Hospital COVID patients: severity, acuity, therapies, outcomes [Dataset]. https://healthdatagateway.org/dataset/139
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    unknownAvailable download formats
    Dataset authored and provided by
    This publication uses data from PIONEER, an ethically approved database and analytical environment (East Midlands Derby Research Ethics 20/EM/0158)
    License

    https://www.pioneerdatahub.co.uk/data/data-request-process/https://www.pioneerdatahub.co.uk/data/data-request-process/

    Description

    OMOP dataset: Hospital COVID patients: severity, acuity, therapies, outcomes Dataset number 2.0

    Coronavirus disease 2019 (COVID-19) was identified in January 2020. Currently, there have been more than 6 million cases & more than 1.5 million deaths worldwide. Some individuals experience severe manifestations of infection, including viral pneumonia, adult respiratory distress syndrome (ARDS) & death. There is a pressing need for tools to stratify patients, to identify those at greatest risk. Acuity scores are composite scores which help identify patients who are more unwell to support & prioritise clinical care. There are no validated acuity scores for COVID-19 & it is unclear whether standard tools are accurate enough to provide this support. This secondary care COVID OMOP dataset contains granular demographic, morbidity, serial acuity and outcome data to inform risk prediction tools in COVID-19.

    PIONEER geography The West Midlands (WM) has a population of 5.9 million & includes a diverse ethnic & socio-economic mix. There is a higher than average percentage of minority ethnic groups. WM has a large number of elderly residents but is the youngest population in the UK. Each day >100,000 people are treated in hospital, see their GP or are cared for by the NHS. The West Midlands was one of the hardest hit regions for COVID admissions in both wave 1 & 2.

    EHR. University Hospitals Birmingham NHS Foundation Trust (UHB) is one of the largest NHS Trusts in England, providing direct acute services & specialist care across four hospital sites, with 2.2 million patient episodes per year, 2750 beds & 100 ITU beds. UHB runs a fully electronic healthcare record (EHR) (PICS; Birmingham Systems), a shared primary & secondary care record (Your Care Connected) & a patient portal “My Health”. UHB has cared for >5000 COVID admissions to date. This is a subset of data in OMOP format.

    Scope: All COVID swab confirmed hospitalised patients to UHB from January – August 2020. The dataset includes highly granular patient demographics & co-morbidities taken from ICD-10 & SNOMED-CT codes. Serial, structured data pertaining to care process (timings, staff grades, specialty review, wards), presenting complaint, acuity, all physiology readings (pulse, blood pressure, respiratory rate, oxygen saturations), all blood results, microbiology, all prescribed & administered treatments (fluids, antibiotics, inotropes, vasopressors, organ support), all outcomes.

    Available supplementary data: Health data preceding & following admission event. Matched “non-COVID” controls; ambulance, 111, 999 data, synthetic data. Further OMOP data available as an additional service.

    Available supplementary support: Analytics, Model build, validation & refinement; A.I.; Data partner support for ETL (extract, transform & load) process, Clinical expertise, Patient & end-user access, Purchaser access, Regulatory requirements, Data-driven trials, “fast screen” services.

  15. o

    Deaths Involving COVID-19 by Vaccination Status

    • data.ontario.ca
    • gimi9.com
    • +3more
    csv, docx, xlsx
    Updated Dec 13, 2024
    + more versions
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    Health (2024). Deaths Involving COVID-19 by Vaccination Status [Dataset]. https://data.ontario.ca/dataset/deaths-involving-covid-19-by-vaccination-status
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    docx(26086), docx(29332), xlsx(10972), csv(321473), xlsx(11053)Available download formats
    Dataset updated
    Dec 13, 2024
    Dataset authored and provided by
    Health
    License

    https://www.ontario.ca/page/open-government-licence-ontariohttps://www.ontario.ca/page/open-government-licence-ontario

    Time period covered
    Nov 14, 2024
    Area covered
    Ontario
    Description

    This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group.

    Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak.

    Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool

    Data includes:

    • Date on which the death occurred
    • Age group
    • 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated
    • 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated
    • 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster

    Additional notes

    As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm.

    As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category.

    On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023.

    CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags.

    The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON.

    “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results.

    Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts.

    Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different.

    Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported.

    Rates for the most recent days are subject to reporting lags

    All data reflects totals from 8 p.m. the previous day.

    This dataset is subject to change.

  16. COVID-19: percentage of deaths by age and gender in Spain in May 2020

    • statista.com
    Updated May 24, 2024
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    Statista (2024). COVID-19: percentage of deaths by age and gender in Spain in May 2020 [Dataset]. https://www.statista.com/statistics/1167845/covid-19-percentage-of-deaths-by-age-and-gender-in-spain/
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    Dataset updated
    May 24, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Spain
    Description

    This statistic presents a percentage distribution by gender and age of people who died from COVID-19 in Spain as of May 18, 2020. This disease is most fatal among the elderly population, especially if the individual suffers from some type of respiratory problem. More than 80 percent of the deaths from COVID-19 registered in the country up to that moment corresponded to people over 70 years old, both in the case of men and women.

  17. d

    Weekly United States COVID-19 Long-term Care Data By State, May 28, 2020 to...

    • datadryad.org
    • dataone.org
    zip
    Updated Feb 9, 2022
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    The COVID Tracking Project at The Atlantic (2022). Weekly United States COVID-19 Long-term Care Data By State, May 28, 2020 to March 4, 2021 [Dataset]. http://doi.org/10.7272/Q62F7KPT
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    zipAvailable download formats
    Dataset updated
    Feb 9, 2022
    Dataset provided by
    Dryad
    Authors
    The COVID Tracking Project at The Atlantic
    Time period covered
    2022
    Area covered
    United States
    Description

    Dataset includes README file that describes all datapoints.

  18. f

    Table_1_Internet usage, frequency and intensity in old age during the...

    • frontiersin.figshare.com
    docx
    Updated Oct 26, 2023
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    Ronny König; Alexander Seifert (2023). Table_1_Internet usage, frequency and intensity in old age during the COVID-19 pandemic—a case study for Switzerland.DOCX [Dataset]. http://doi.org/10.3389/fsoc.2023.1268613.s001
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    docxAvailable download formats
    Dataset updated
    Oct 26, 2023
    Dataset provided by
    Frontiers
    Authors
    Ronny König; Alexander Seifert
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Switzerland
    Description

    IntroductionThis study examines the digital divide among older adults in Switzerland within the rapidly evolving digital environment. It investigates changes in internet usage among this population, focusing on the proportion of users, frequency, and the intensity of their internet usage during the COVID-19 pandemic.MethodsDrawing on Swiss data from the Survey of Health, Aging, and Retirement (SHARE), conducted in 2021, the study analyzes a sample of 1,205 older adults.ResultsThe findings indicate a growing proportion of internet users over time. It also highlights that gender differences persist but are decreasing. Notably, around 9% of individuals in this study had never used the internet, while recent users exhibited high activity levels, spending an average of approximately two and a half hours online daily. The study identified age, education, employment, living arrangements, and attitudes toward technology as influential factors shaping internet usage among older adults. Importantly, the COVID-19 pandemic did not have a significant impact on internet adoption among this demographic.DiscussionThese findings shed light on the complex dynamics that shape internet usage among older adults and underscore the need to promote digital inclusion and engagement within this population.

  19. Average number of COVID-19 deaths in last 7 days in select countries, Mar....

    • statista.com
    Updated Aug 24, 2020
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    Statista (2020). Average number of COVID-19 deaths in last 7 days in select countries, Mar. 1-Oct. 27 [Dataset]. https://www.statista.com/statistics/1111867/trailing-seven-day-average-number-of-covid-19-deaths-select-countries-worldwide/
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    Dataset updated
    Aug 24, 2020
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Mar 1, 2020 - Oct 27, 2020
    Area covered
    Worldwide
    Description

    The seven-day average number of COVID-19 deaths in the U.S. decreased significantly from April to July 2020, but it remained higher than in other countries. Seven-day rolling averages are used to adjust for administrative delays in the reporting of deaths by authorities, commonly over weekends.

    The challenges of tracking and reporting the disease The U.S. confirmed its first coronavirus case in mid-January 2020 – the virus was detected in a passenger who arrived in Seattle from China. Since that first case, around 945 people have died every day from COVID-19 in the United States as of August 23, 2020. In total, the U.S. has recorded more coronavirus deaths than any other country worldwide. Accurately tracking the number of COVID-19 deaths has proved complicated, with countries having different rules for what deaths to include in their official figures. Some nations have even changed which deaths they can attribute to the disease during the pandemic.

    Young people urged to act responsibly Between January and May 2020, case fatality rates among COVID-19 patients in the United States increased with age, highlighting the particular risks faced by the elderly. However, COVID-19 is not only a disease that affects older adults. Surges in the number of new cases throughout July 2020 were blamed on young people. The World Health Organization has urged young people not to become complacent, reminding them to maintain social distancing guidelines and take precautions to protect themselves and others.

  20. Distribution of total COVID-19 deaths in the U.S. as of April 26, 2023, by...

    • statista.com
    Updated May 15, 2024
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    Statista (2024). Distribution of total COVID-19 deaths in the U.S. as of April 26, 2023, by age [Dataset]. https://www.statista.com/statistics/1254488/us-share-of-total-covid-deaths-by-age-group/
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    Dataset updated
    May 15, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of April 26, 2023, around 27 percent of total COVID-19 deaths in the United States have been among adults 85 years and older, despite this age group only accounting for two percent of the U.S. population. This statistic depicts the distribution of total COVID-19 deaths in the United States as of April 26, 2023, by age group.

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Statista (2024). Concern about elderly relatives due to the COVID-19 epidemic in Norway 2020 [Dataset]. https://www.statista.com/statistics/1104909/health-concerns-elderly-relatives-due-to-the-covid-19-coronavirus-epidemic-in-norway-by-gender/
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Concern about elderly relatives due to the COVID-19 epidemic in Norway 2020

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Dataset updated
Jul 31, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Mar 12, 2020
Area covered
Norway
Description

In the light of the coronavirus COVID-19 pandemic, more than 64 percent of Norwegians worried about the health of elderly relatives, according to a survey conducted on March 12, 2020. When asked about personal health, however, the Norwegians seem to be much less concerned. Spreading rapidly The coronavirus is currently spreading quickly in Norway. The first case was detected on February 26. Since then the cumulative number of cases has increased drastically on a daily basis. Furthermore, the official numbers of tested and confirmed cases are esteemed to be severely lower than the actual number of coronavirus infected people in Norway. Scandinavia and Europe In comparison to its neighboring countries, Norway has reported the most cases of the virus as of March 18, 2020, followed closely by Sweden and Denmark. On a broader scale, Norway currently ranks 9th among the European countries. In Europe, Italy has suffered the most from coronavirus, and the country accounts for the majority of cases in Europe, with over 30,000 infected individuals.

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