8 datasets found
  1. Opinion on impact of coronavirus (COVID-19) Australia 2020

    • statista.com
    Updated Apr 3, 2024
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    Statista (2024). Opinion on impact of coronavirus (COVID-19) Australia 2020 [Dataset]. https://www.statista.com/statistics/1103950/australia-coronavirus-impact/
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    Dataset updated
    Apr 3, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Feb 28, 2020 - Feb 29, 2020
    Area covered
    Australia
    Description

    In an Ipsos survey carried out in February 2020, over three-quarters of Australian respondents believed a total quarantine would be correct given the risk of the coronavirus (COVID-19) outbreak. Nearly seventy percent of respondents also thought that it was impossible to predict how the virus is spreading. Furthermore, 40 percent of the respondents believed the coronvirus outbreak would have a financial impact on themselves and their family.

  2. COVID-19 death rates in 2020 countries worldwide as of April 26, 2022

    • statista.com
    Updated Mar 20, 2023
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    Statista (2023). COVID-19 death rates in 2020 countries worldwide as of April 26, 2022 [Dataset]. https://www.statista.com/statistics/1105914/coronavirus-death-rates-worldwide/
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    Dataset updated
    Mar 20, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    COVID-19 rate of death, or the known deaths divided by confirmed cases, was over ten percent in Yemen, the only country that has 1,000 or more cases. This according to a calculation that combines coronavirus stats on both deaths and registered cases for 221 different countries. Note that death rates are not the same as the chance of dying from an infection or the number of deaths based on an at-risk population. By April 26, 2022, the virus had infected over 510.2 million people worldwide, and led to a loss of 6.2 million. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

    Where are these numbers coming from?

    The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. Note that Statista aims to also provide domestic source material for a more complete picture, and not to just look at one particular source. Examples are these statistics on the confirmed coronavirus cases in Russia or the COVID-19 cases in Italy, both of which are from domestic sources. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

    A word on the flaws of numbers like this

    People are right to ask whether these numbers are at all representative or not for several reasons. First, countries worldwide decide differently on who gets tested for the virus, meaning that comparing case numbers or death rates could to some extent be misleading. Germany, for example, started testing relatively early once the country’s first case was confirmed in Bavaria in January 2020, whereas Italy tests for the coronavirus postmortem. Second, not all people go to see (or can see, due to testing capacity) a doctor when they have mild symptoms. Countries like Norway and the Netherlands, for example, recommend people with non-severe symptoms to just stay at home. This means not all cases are known all the time, which could significantly alter the death rate as it is presented here. Third and finally, numbers like this change very frequently depending on how the pandemic spreads or the national healthcare capacity. It is therefore recommended to look at other (freely accessible) content that dives more into specifics, such as the coronavirus testing capacity in India or the number of hospital beds in the UK. Only with additional pieces of information can you get the full picture, something that this statistic in its current state simply cannot provide.

  3. Investment considerations during the COVID-19 pandemic Australia 2020

    • statista.com
    Updated Apr 3, 2024
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    Statista (2024). Investment considerations during the COVID-19 pandemic Australia 2020 [Dataset]. https://www.statista.com/statistics/1186559/australia-covid-19-impact-on-investment-considerations/
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    Dataset updated
    Apr 3, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 2020 - May 2020
    Area covered
    Australia
    Description

    In a survey conducted in 2020 about investments during the COVID-19 pandemic in Australia, about 65 percent of respondents who participated said they considered the potential return on investment when making investment decisions. The study also reported that about 48 percent of respondents said they considered the potential risk of investment.

  4. NSW COVID-19 cases by location

    • kaggle.com
    Updated Mar 10, 2025
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    liv heaton (2025). NSW COVID-19 cases by location [Dataset]. https://www.kaggle.com/livheaton/nsw-covid19-cases-by-location/discussion
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 10, 2025
    Dataset provided by
    Kaggle
    Authors
    liv heaton
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    New South Wales
    Description

    Context

    NSW has been hit by the Omicron variant, with skyrocketing cases. This dataset, updated regularly, details the location of positive cases. A prediction of where the most cases could occur can be derived from this dataset and a potential prediction of how many cases there is likely to be.

    Content

    notification_date: Text, dates to when the positive case was notified of a positive test result. postcode: Text, lists the postcode of the positive case. lhd_2010_code: Text, the code of the local health district of the positive case. lhd_2010_name: Text, the name of the local health district of the positive case. lga_code19: Text, the code of the local government area of the positive case. lga_name19: Text, the name of the local government area of the positive case.

    Acknowledgements

    Thanks to NSW Health for providing and updating the dataset.

    Inspiration

    The location of cases is highly important in NSW. In mid-2021, Western Sydney had the highest proportion of COVID-19 cases with many deaths ensuing. Western Sydney is one of Sydney's most diverse areas, with many vulnerable peoples. The virus spread to western NSW, imposing a risk to the Indigenous communities. With location data, a prediction service can be made to forecast the areas at risk of transmission.

  5. f

    Percentage distribution (95% CI) of Australian born and refugee background...

    • plos.figshare.com
    xls
    Updated Jul 3, 2023
    + more versions
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    Susan J. Rees; Mohammed Mohsin; Alvin Kuowei Tay; Batool Moussa; Louis Klein; Nawal Nadar; Fatima Hussain; Yalini Krishna; Batoul Khalil; Mariam Yousif; Derrick Silove; Jane Fisher (2023). Percentage distribution (95% CI) of Australian born and refugee background participants who completed COVID-19 questionnaires by socio-demographic characteristics. [Dataset]. http://doi.org/10.1371/journal.pgph.0002073.t001
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    xlsAvailable download formats
    Dataset updated
    Jul 3, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Susan J. Rees; Mohammed Mohsin; Alvin Kuowei Tay; Batool Moussa; Louis Klein; Nawal Nadar; Fatima Hussain; Yalini Krishna; Batoul Khalil; Mariam Yousif; Derrick Silove; Jane Fisher
    License

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

    Area covered
    Australia
    Description

    Percentage distribution (95% CI) of Australian born and refugee background participants who completed COVID-19 questionnaires by socio-demographic characteristics.

  6. Percentage of out-of-vocabulary words.

    • plos.figshare.com
    xls
    Updated Jun 10, 2023
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    Percentage of out-of-vocabulary words. [Dataset]. https://plos.figshare.com/articles/dataset/Percentage_of_out-of-vocabulary_words_/14868033
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    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ioannis Chalkiadakis; Hongxuan Yan; Gareth W. Peters; Pavel V. Shevchenko
    License

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

    Description

    Percentage of out-of-vocabulary words.

  7. Outcomes.

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
    + more versions
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    Outcomes. [Dataset]. https://plos.figshare.com/articles/dataset/Outcomes_/22271303
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    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Jessica C. O’Keeffe; Meg Constable; Janice Chiang; Margaret Somerville; Arvind Yerramilli; Ross Nolan; Greg Weeks; Daniel P. O’Brien
    License

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

    Description

    Molnupiravir, an oral antiviral shown to reduce COVID-19 severity, is available in Australia via the Pharmaceutical Benefits Scheme (PBS) for treatment of mild-moderate COVID-19. For people less than 70 years of age it is only available with risk factors for severe disease, hence the majority of healthcare workers do not qualify. Currently, Australian health services are under considerable strain due to COVID-related staff shortages. Thirty staff members of a tertiary hospital, not eligible under the PBS, were offered molnupiravir within the first five days of COVID-19 illness. Their median age was 43 years, and 73% were female. All completed treatment with rates of adverse events that were low and comparable with clinical trial data. The reported duration of illness ranged from 1–16 days with a median of four days. A negative rapid antigen test on the final day of treatment was reported in 81% of people, and 73% reported being well enough to return to work at the completion of mandatory isolation. Only 22% of people reported transmission in their household after they commenced treatment. The implementation of a policy allowing access to molnupiravir outside of PBS recommendations for healthcare workers with mild-moderate COVID-19 may have important individual benefits to workers health and wellbeing and help alleviate the acute staff shortages experienced currently by the Australian healthcare workforce.

  8. p

    Household Travel Survey (HTS)

    • data.peclet.com.au
    csv, excel, json
    Updated Jun 30, 2023
    + more versions
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    (2023). Household Travel Survey (HTS) [Dataset]. https://data.peclet.com.au/explore/dataset/transport-survey-data/
    Explore at:
    json, csv, excelAvailable download formats
    Dataset updated
    Jun 30, 2023
    Description

    The Household Travel Survey (HTS) collects information on personal travel behaviour. The study area for the survey is the Sydney Greater Metropolitan Area (GMA) which includes Sydney Greater Capital City Statistical Area (GCCSA), parts of Illawarra and Hunter regions.All residents of occupied private dwellings within the Sydney GMA are considered within scope of the survey and are randomly selected to participate.The HTS has been running continuously since 1997/981 and collects data for all days through the year – including during school and public holidays.Typically, approximately 2,000-3,000 households participate in the survey annually. Data is collected on all trips made over a 24-hour period by all members of the participating households.Annual estimates from the HTS are usually produced on a rolling basis using multiple years of pooled data for each reporting year2. All estimates are weighted to the Australian Bureau of Statistics’ Estimated Resident Population, corresponding to the year of collection3. Unless otherwise stated, all reported estimates are for an average weekday.Due to disruptions in data collection resulting from the lockdowns during the COVID-19 pandemic, post-COVID releases of HTS data are based on a lower sample size than previous HTS releases. To ensure integrity of the results and mitigate risk of sampling errors some post-COVID results have been reported differently to previous years. Please see below for more information on changes to HTS post-COVID (2020/21 onwards).Transport for NSW will work with their partners to boost sample sizes to provide HTS results for smaller geographic and regional areas throughout FY23.Data-source: household-travel-survey

  9. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Statista (2024). Opinion on impact of coronavirus (COVID-19) Australia 2020 [Dataset]. https://www.statista.com/statistics/1103950/australia-coronavirus-impact/
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Opinion on impact of coronavirus (COVID-19) Australia 2020

Explore at:
Dataset updated
Apr 3, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Feb 28, 2020 - Feb 29, 2020
Area covered
Australia
Description

In an Ipsos survey carried out in February 2020, over three-quarters of Australian respondents believed a total quarantine would be correct given the risk of the coronavirus (COVID-19) outbreak. Nearly seventy percent of respondents also thought that it was impossible to predict how the virus is spreading. Furthermore, 40 percent of the respondents believed the coronvirus outbreak would have a financial impact on themselves and their family.

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