69 datasets found
  1. Distribution of COVID-19 cases South Korea 2023, by age

    • statista.com
    Updated Jun 4, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2024). Distribution of COVID-19 cases South Korea 2023, by age [Dataset]. https://www.statista.com/statistics/1102730/south-korea-coronavirus-cases-by-age/
    Explore at:
    Dataset updated
    Jun 4, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Aug 28, 2023
    Area covered
    South Korea
    Description

    As of August 28, 2023, confirmed coronavirus (COVID-19) patients in their forties made up the largest share of patients in South Korea, amounting to around 15.2 percent of all positive cases. The first wave lasted until April, with the second wave following in August of 2020. This was further followed by a fourth wave, driven by the delta and omicron variants. Though the country has since achieved high vaccination rates, the omicron variant led to record new daily cases in 2022.

    Patient profile

    In South Korea, the infection rate of coronavirus was the highest among people in the twenties due to their social activities. Indeed, the new infections related to the clubgoers in Seoul are likely to increase the infection rate between young people. 158 out of 261 clubgoer-related confirmed patients were in teenagers or in their twenties, and 36 patients were in their thirties. The mortality rate of coronavirus by age group was somewhat different from the age distribution of total infection cases. It was highest among people in their eighties, with this group making up around 59.6 percent of deaths related to the coronavirus in South Korea. Mortality declined with each younger age group.

    Daily life changes

    In South Korea, a new policy of "With Corona" has been launched in order to ease society back into a new norm of living with the virus, without having too many restrictions in place. This is based on high vaccination rates, and includes strict quarantine measures for those who are infected and their close contacts. There are plans to improve the verification of vaccination and test certificates for use in public spaces. Most South Koreans have responded to rising numbers by once again avoiding crowded places or going out. It is common to wear masks regardless of diseases, so people are continuing to wear masks when they need to go out. Also, people prefer to do online shopping than physical shopping, and online sales of food and health-related products have increased by more than 700 percent compared to last year. Spending on living, cooking, and furniture has increased significantly as people spend more time at home.

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

    • statista.com
    Updated Jun 21, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    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/
    Explore at:
    Dataset updated
    Jun 21, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 1, 2020 - Jun 14, 2023
    Area covered
    United States
    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.

  3. Trends in COVID-19 Cases and Deaths in the United States, by County-level...

    • data.cdc.gov
    • healthdata.gov
    • +1more
    application/rdfxml +5
    Updated Jun 8, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Trends in COVID-19 Cases and Deaths in the United States, by County-level Population Factors - ARCHIVED [Dataset]. https://data.cdc.gov/dataset/Trends-in-COVID-19-Cases-and-Deaths-in-the-United-/njmz-dpbc
    Explore at:
    application/rdfxml, csv, application/rssxml, xml, tsv, jsonAvailable download formats
    Dataset updated
    Jun 8, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response
    Area covered
    United States
    Description

    Reporting of Aggregate Case and Death Count data was discontinued on May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

    The surveillance case definition for COVID-19, a nationally notifiable disease, was first described in a position statement from the Council for State and Territorial Epidemiologists, which was later revised. However, there is some variation in how jurisdictions implemented these case definitions. More information on how CDC collects COVID-19 case surveillance data can be found at FAQ: COVID-19 Data and Surveillance.

    Aggregate Data Collection Process Since the beginning of the COVID-19 pandemic, data were reported from state and local health departments through a robust process with the following steps:

    • Aggregate county-level counts were obtained indirectly, via automated overnight web collection, or directly, via a data submission process.
    • If more than one official county data source existed, CDC used a comprehensive data selection process comparing each official county data source to retrieve the highest case and death counts, unless otherwise specified by the state.
    • A CDC data team reviewed counts for congruency prior to integration and set up alerts to monitor for discrepancies in the data.
    • CDC routinely compiled these data and post the finalized information on COVID Data Tracker.
    • County level data were aggregated to obtain state- and territory- specific totals.
    • Counting of cases and deaths is based on date of report and not on the date of symptom onset. CDC calculates rates in these data by using population estimates provided by the US Census Bureau Population Estimates Program (2019 Vintage).
    • COVID-19 aggregate case and death data are organized in a time series that includes cumulative number of cases and deaths as reported by a jurisdiction on a given date. New case and death counts are calculated as the week-to-week change in cumulative counts of cases and deaths reported (i.e., newly reported cases and deaths = cumulative number of cases/deaths reported this week minus the cumulative total reported the prior week.

    This process was collaborative, with CDC and jurisdictions working together to ensure the accuracy of COVID-19 case and death numbers. County counts provided the most up-to-date numbers on cases and deaths by report date. Throughout data collection, CDC retrospectively updated counts to correct known data quality issues.

    Description This archived public use dataset focuses on the cumulative and weekly case and death rates per 100,000 persons within various sociodemographic factors across all states and their counties. All resulting data are expressed as rates calculated as the number of cases or deaths per 100,000 persons in counties meeting various classification criteria using the US Census Bureau Population Estimates Program (2019 Vintage).

    Each county within jurisdictions is classified into multiple categories for each factor. All rates in this dataset are based on classification of counties by the characteristics of their population, not individual-level factors. This applies to each of the available factors observed in this dataset. Specific factors and their corresponding categories are detailed below.

    Population-level factors Each unique population factor is detailed below. Please note that the “Classification” column describes each of the 12 factors in the dataset, including a data dictionary describing what each numeric digit means within each classification. The “Category” column uses numeric digits (2-6, depending on the factor) defined in the “Classification” column.

    Metro vs. Non-Metro – “Metro_Rural” Metro vs. Non-Metro classification type is an aggregation of the 6 National Center for Health Statistics (NCHS) Urban-Rural classifications, where “Metro” counties include Large Central Metro, Large Fringe Metro, Medium Metro, and Small Metro areas and “Non-Metro” counties include Micropolitan and Non-Core (Rural) areas. 1 – Metro, including “Large Central Metro, Large Fringe Metro, Medium Metro, and Small Metro” areas 2 – Non-Metro, including “Micropolitan, and Non-Core” areas

    Urban/rural - “NCHS_Class” Urban/rural classification type is based on the 2013 National Center for Health Statistics Urban-Rural Classification Scheme for Counties. Levels consist of:

    1 Large Central Metro
    2 Large Fringe Metro 3 Medium Metro 4 Small Metro 5 Micropolitan 6 Non-Core (Rural)

    American Community Survey (ACS) data were used to classify counties based on their age, race/ethnicity, household size, poverty level, and health insurance status distributions. Cut points were generated by using tertiles and categorized as High, Moderate, and Low percentages. The classification “Percent non-Hispanic, Native Hawaiian/Pacific Islander” is only available for “Hawaii” due to low numbers in this category for other available locations. This limitation also applies to other race/ethnicity categories within certain jurisdictions, where 0 counties fall into the certain category. The cut points for each ACS category are further detailed below:

    Age 65 - “Age65”

    1 Low (0-24.4%) 2 Moderate (>24.4%-28.6%) 3 High (>28.6%)

    Non-Hispanic, Asian - “NHAA”

    1 Low (<=5.7%) 2 Moderate (>5.7%-17.4%) 3 High (>17.4%)

    Non-Hispanic, American Indian/Alaskan Native - “NHIA”

    1 Low (<=0.7%) 2 Moderate (>0.7%-30.1%) 3 High (>30.1%)

    Non-Hispanic, Black - “NHBA”

    1 Low (<=2.5%) 2 Moderate (>2.5%-37%) 3 High (>37%)

    Hispanic - “HISP”

    1 Low (<=18.3%) 2 Moderate (>18.3%-45.5%) 3 High (>45.5%)

    Population in Poverty - “Pov”

    1 Low (0-12.3%) 2 Moderate (>12.3%-17.3%) 3 High (>17.3%)

    Population Uninsured- “Unins”

    1 Low (0-7.1%) 2 Moderate (>7.1%-11.4%) 3 High (>11.4%)

    Average Household Size - “HH”

    1 Low (1-2.4) 2 Moderate (>2.4-2.6) 3 High (>2.6)

    Community Vulnerability Index Value - “CCVI” COVID-19 Community Vulnerability Index (CCVI) scores are from Surgo Ventures, which range from 0 to 1, were generated based on tertiles and categorized as:

    1 Low Vulnerability (0.0-0.4) 2 Moderate Vulnerability (0.4-0.6) 3 High Vulnerability (0.6-1.0)

    Social Vulnerability Index Value – “SVI" Social Vulnerability Index (SVI) scores (vintage 2020), which also range from 0 to 1, are from CDC/ASTDR’s Geospatial Research, Analysis & Service Program. Cut points for CCVI and SVI scores were generated based on tertiles and categorized as:

    1 Low Vulnerability (0-0.333) 2 Moderate Vulnerability (0.334-0.666) 3 High Vulnerability (0.667-1)

  4. COVID-19 death rates in the United States as of March 10, 2023, by state

    • statista.com
    Updated Mar 28, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2023). COVID-19 death rates in the United States as of March 10, 2023, by state [Dataset]. https://www.statista.com/statistics/1109011/coronavirus-covid19-death-rates-us-by-state/
    Explore at:
    Dataset updated
    Mar 28, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United States
    Description

    As of March 10, 2023, the death rate from COVID-19 in the state of New York was 397 per 100,000 people. New York is one of the states with the highest number of COVID-19 cases.

  5. COVID-19 infection fatality rates and mortality rates, stratified by age...

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Marta Bertran; Zahin Amin-Chowdhury; Hannah G. Davies; Hester Allen; Tom Clare; Chloe Davison; Mary Sinnathamby; Giulia Seghezzo; Meaghan Kall; Hannah Williams; Nick Gent; Mary E. Ramsay; Shamez N. Ladhani; Godwin Oligbu (2023). COVID-19 infection fatality rates and mortality rates, stratified by age group and variant period. [Dataset]. http://doi.org/10.1371/journal.pmed.1004118.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Marta Bertran; Zahin Amin-Chowdhury; Hannah G. Davies; Hester Allen; Tom Clare; Chloe Davison; Mary Sinnathamby; Giulia Seghezzo; Meaghan Kall; Hannah Williams; Nick Gent; Mary E. Ramsay; Shamez N. Ladhani; Godwin Oligbu
    License

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

    Description

    COVID-19 infection fatality rates and mortality rates, stratified by age group and variant period.

  6. Cumulative cases of COVID-19 in the U.S. from Jan. 20, 2020 - Nov. 11, 2022,...

    • statista.com
    Updated Nov 17, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Cumulative cases of COVID-19 in the U.S. from Jan. 20, 2020 - Nov. 11, 2022, by week [Dataset]. https://www.statista.com/statistics/1103185/cumulative-coronavirus-covid19-cases-number-us-by-day/
    Explore at:
    Dataset updated
    Nov 17, 2022
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 20, 2020 - Nov 11, 2022
    Area covered
    United States
    Description

    As of November 11, 2022, almost 96.8 million confirmed cases of COVID-19 had been reported by the World Health Organization (WHO) for the United States. The pandemic has impacted all 50 states, with vast numbers of cases recorded in California, Texas, and Florida.

    The coronavirus in the U.S. The coronavirus hit the United States in mid-March 2020, and cases started to soar at an alarming rate. The country has performed a high number of COVID-19 tests, which is a necessary step to manage the outbreak, but new coronavirus cases in the U.S. have spiked several times since the pandemic began, most notably at the end of 2022. However, restrictions in many states have been eased as new cases have declined.

    The origin of the coronavirus In December 2019, officials in Wuhan, China, were the first to report cases of pneumonia with an unknown cause. A new human coronavirus – SARS-CoV-2 – has since been discovered, and COVID-19 is the infectious disease it causes. All available evidence to date suggests that COVID-19 is a zoonotic disease, which means it can spread from animals to humans. The WHO says transmission is likely to have happened through an animal that is handled by humans. Researchers do not support the theory that the virus was developed in a laboratory.

  7. Risk of COVID-19 death in CYP with a SARS-CoV-2 positive test within 100...

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Marta Bertran; Zahin Amin-Chowdhury; Hannah G. Davies; Hester Allen; Tom Clare; Chloe Davison; Mary Sinnathamby; Giulia Seghezzo; Meaghan Kall; Hannah Williams; Nick Gent; Mary E. Ramsay; Shamez N. Ladhani; Godwin Oligbu (2023). Risk of COVID-19 death in CYP with a SARS-CoV-2 positive test within 100 days by demographics (adjusted and unadjusted odds ratios). [Dataset]. http://doi.org/10.1371/journal.pmed.1004118.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Marta Bertran; Zahin Amin-Chowdhury; Hannah G. Davies; Hester Allen; Tom Clare; Chloe Davison; Mary Sinnathamby; Giulia Seghezzo; Meaghan Kall; Hannah Williams; Nick Gent; Mary E. Ramsay; Shamez N. Ladhani; Godwin Oligbu
    License

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

    Description

    Risk of COVID-19 death in CYP with a SARS-CoV-2 positive test within 100 days by demographics (adjusted and unadjusted odds ratios).

  8. Incidence of coronavirus (COVID-19) deaths in Europe 2023, by country

    • statista.com
    • flwrdeptvarieties.store
    Updated Jan 23, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Incidence of coronavirus (COVID-19) deaths in Europe 2023, by country [Dataset]. https://www.statista.com/statistics/1111779/coronavirus-death-rate-europe-by-country/
    Explore at:
    Dataset updated
    Jan 23, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 13, 2023
    Area covered
    Europe
    Description

    As of January 13, 2023, Bulgaria had the highest rate of COVID-19 deaths among its population in Europe at 548.6 deaths per 100,000 population. Hungary had recorded 496.4 deaths from COVID-19 per 100,000. Furthermore, Russia had the highest number of confirmed COVID-19 deaths in Europe, at over 394 thousand.

    Number of cases in Europe During the same period, across the whole of Europe, there have been over 270 million confirmed cases of COVID-19. France has been Europe's worst affected country with around 38.3 million cases, this translates to an incidence rate of approximately 58,945 cases per 100,000 population. Germany and Italy had approximately 37.6 million and 25.3 million cases respectively.

    Current situation In March 2023, the rate of cases in Austria over the last seven days was 224 per 100,000 which was the highest in Europe. Luxembourg and Slovenia both followed with seven day rates of infections at 122 and 108 respectively.

  9. Share of people with long COVID symptoms in the UK in 2022, by age

    • statista.com
    Updated Nov 30, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2023). Share of people with long COVID symptoms in the UK in 2022, by age [Dataset]. https://www.statista.com/statistics/1257384/people-with-long-covid-in-the-uk-by-age/
    Explore at:
    Dataset updated
    Nov 30, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    United Kingdom
    Description

    According to a survey conducted in the United Kingdom (UK) in April 2022, 4.13 percent of all people aged between 35 and 49 years reported to be suffering from long COVID symptoms, the highest share across all age groups. Furthermore, around 3.7 percent of the population aged 50 to 69 years were estimated to suffer from long COVID. Overall, around 863 thousand people in the UK reported their ability to undertake daily activities and routines was affected a little by long COVID symptoms.

    Present state of COVID-19 As of May 2022, over 22 million COVID-19 cases had been reported in the UK. The largest surge of cases was noted over the winter period 2021/22. The incidence of cases in the county since the pandemic began stood at around 32,624 per 100,000 population. Cyprus had the highest incidence of COVID-19 cases among its population in Europe at 75,798 per 100,000 people, followed by a rate of 51,573 in Iceland. Over 175 thousand COVID-19 deaths have been reported in the UK. The deadliest day on record was January 20, 2021, when 1,820 deaths were recorded. In the UK, a COVID-19 death is defined as a person who died within 28 days of a positive test.

    Preventing long COVID through vaccination According to the WHO, being fully vaccinated alongside a significant proportion of the population also vaccinated is the best way to avoid the spread of COVID-19 or serious symptoms associated with the virus. It is therefore regarded that receiving a vaccine course as well as subsequent booster vaccines limits the chance of developing long COVID symptoms. As of April 27, 2022, around 53.2 million first doses, 49.7 million second doses, and 39.2 booster doses had been administered in the UK.

  10. i

    Global Financial Inclusion (Global Findex) Database 2021 - Thailand

    • catalog.ihsn.org
    • microdata.worldbank.org
    Updated Dec 16, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Thailand [Dataset]. https://catalog.ihsn.org/catalog/10515
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Thailand
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Thailand is 1017.

    Mode of data collection

    Mobile telephone

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  11. w

    Global Financial Inclusion (Global Findex) Database 2021 - El Salvador

    • microdata.worldbank.org
    • datacatalog.ihsn.org
    • +1more
    Updated Dec 16, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - El Salvador [Dataset]. https://microdata.worldbank.org/index.php/catalog/4639
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    El Salvador
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for El Salvador is 1002.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  12. a

    B.C. COVID-19 - Case Details (Retired)

    • resources-covid19canada.hub.arcgis.com
    • hub.arcgis.com
    • +1more
    Updated Apr 7, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    EM GeoHub (2020). B.C. COVID-19 - Case Details (Retired) [Dataset]. https://resources-covid19canada.hub.arcgis.com/maps/bcgov03::b-c-covid-19-case-details-retired
    Explore at:
    Dataset updated
    Apr 7, 2020
    Dataset authored and provided by
    EM GeoHub
    Area covered
    British Columbia
    Description

    The B.C. COVID-19 Dashboard has been retired and will no longer be updated.Purpose: These data can be used for visual or reference purposes.British Columbia COVID-19 B.C. & Canadian Testing Rates are obtained from the Public Health Agency of Canada’s Daily Epidemiologic Update site: https://www.canada.ca/en/public-health/services/diseases/2019-novel-coronavirus-infection.html.These data were made specifically for the British Columbia COVID-19 Dashboard.

    Terms of use, disclaimer and limitation of liabilityAlthough every effort has been made to provide accurate information, the Province of British Columbia, including the British Columbia Centre for Disease Control, the Provincial Health Services Authority and the British Columbia Ministry of Health makes no representation or warranties regarding the accuracy of the information in the dashboard and the associated data, nor will it accept responsibility for errors or omissions. Data may not reflect the current situation, and therefore should only be used for reference purposes. Access to and/or content of these data and associated data may be suspended, discontinued, or altered, in part or in whole, at any time, for any reason, with or without prior notice, at the discretion of the Province of British Columbia.Anyone using this information does so at his or her own risk, and by using such information agrees to indemnify the Province of British Columbia, including the British Columbia Centre for Disease Control, the Provincial Health Services Authority and the British Columbia Ministry of Health and its content providers from any and all liability, loss, injury, damages, costs and expenses (including legal fees and expenses) arising from such person’s use of the information on this website.Dashboard Updates - GeneralData are updated up to the previous Saturday. Weekly metrics reflect the latest full week, Sunday to Saturday. The “Currently Hospitalized” and “Currently in Critical Care” reflect daily volumes on the Thursday.Data Notes - GeneralThe following data notes define the indicators presented on the public dashboard and describe the data sources involved. Data changes as new cases are identified, characteristics of reported cases change or are updated, and data corrections are made. Specific values may therefore fluctuate in response to underlying system changes. As such, case, hospitalization, deaths, testing and vaccination counts and rates may not be directly comparable to previously published reports. For the latest caveats about the data, please refer to the most recent BCCDC Surveillance Report located at: www.bccdc.ca/health-info/diseases-conditions/covid-19/dataData SourcesLaboratory data are supplied by the B.C. Centre for Disease Control (BCCDC) Public Health Laboratory; tests performed for other provinces have been excluded. See “Data Over Time” for more information on changes to the case definition.Total COVID-19 cases include lab-confirmed, lab-probable and epi-linked cases. Case definitions can be found at: https://www.bccdc.ca/health-professionals/clinical-resources/case-definitions/covid-19-(novel-coronavirus). Currently hospitalized and critical care hospitalizations data are received from Provincial COVID-19 Monitoring Solution, Provincial Health Services Authority. See “Data Over Time” for more information on previous data sources.Vaccine data are received from the B.C. Ministry of Health.Mortality data are received from Vital Statistics, B.C. Ministry of Health. See Data Over Time for more information on precious data sources.Laboratory data is supplied by the B.C. Centre for Disease Control Public Health Laboratory and the Provincial Lab Information Solution (PLIS); tests performed for other provinces have been excluded.Critical care hospitalizations are provided by the health authorities to PHSA on a daily basis. BCCDC/PHSA/B.C. Ministry of Health data sources are available at the links below:Cases Totals (spatial)Case DetailsLaboratory Testing InformationRegional Summary DataData Over TimeThe number of laboratory tests performed and positivity rate over time are reported by the date of test result. See “Laboratory Indicators” section for more details.Laboratory confirmed cases are reported based on the client's first positive lab result.As of April 2, 2022, cases include laboratory-diagnosed cases (confirmed and probable) funded under Medical Services Plan.From January 7, 2021 to April 1, 2022, cases included those reported by the health authorities and those with positive laboratory results reported to the BCCDC. The number of cases over time is reported by the result date of the client's first positive lab result where available; otherwise by the date they are reported to public health. Prior to April 2, 2022, total COVID-19 cases included laboratory-diagnosed cases (confirmed and probable) as well as epi-linked cases. Prior to June 4, 2020, the total number of cases included only laboratory-diagnosed cases.As of January 14, 2022, the data source for "Currently Hospitalized" has changed to better reflect hospital capacity. Comparisons to numbers before this date should not be made.As of April 2, 2022, death is defined as an individual who has died from any cause, within 30 days of a first COVID-19 positive lab result date. Prior to April 22, 2022, death information was collected by Regional Health Authorities and defined as any death related to COVID-19. Comparisons between these time periods are not advised.Epidemiologic Indicators"Currently Hospitalized" is the number of people who test positive for COVID-19 through hospital screening practices, regardless of the reason for admission, as recorded in PCMS on the day the dashboard is refreshed. It is reported by the hospital in which the patient is hospitalized, rather than the patient's health authority of residence.Critical care values (intensive care units, high acuity units, and other critical care surge beds) include individuals who test positive for COVID-19 and are in critical care, as recorded in PCMS.The 7-day moving average is an average daily value over the 7 days up to and including the selected date. The 7-day window moved - or changes - with each new day of data. It is used to smooth new daily case and death counts or rates to mitigate the impact of short-term fluctuations and to more clearly identify the most recent trend over time.The following epidemiological indicators are included in the provincial case data file:Date: date of the client's first positive lab result.HA: health authority assigned to the caseSex: the sex of the clientAge_Group: the age group of the clientClassification_Reported: whether the case has been lab-diagnosed or is epidemiologically linked to another caseThe following epidemiological indicators are included in the regional summary data file:Cases_Reported: the number of cases for the health authority (HA) and health service delivery area (HSDA)Cases_Reported_Smoothed: Seven day moving average for reported casesLaboratory IndicatorsTests represent the number of all COVID-19 tests reported to the BCCDC Public Helath Laboratory since testing began mid-January 2020. Only tests for residents of B.C. are included.COVID-19 positivity rate is calculated for each day as the ratio of 7-day rolling average of number of positive specimens to 7-day rolling average of the total number of specimens tested (positive, negative, indeterminate and invalid). A 7-day rolling average applied to all testing data corrects for uneven data release patterns while accurately representing the provincial positivity trends. It avoids misleading daily peaks and valleys due to varying capacities and reporting cadences.Turn-around time is calculated as the daily average time (in hours) between specimen collection and report of a test result. Turn-around time includes the time to ship specimens to the lab; patients who live farther away are expected to have slightly longer average turn around times.The rate of COVID-19 testing per million population is defined as the cumulative number of people tested for COVID-19/B.C. population x 1,000,000. B.C. Please note: the same person may be tested multiple times, thus it is not possible to derive this rate directly from the number of cumulative tests reported on the B.C. COVID-19 Dashboard.Testing context: COVID-19 diagnostic testing and laboratory test guidelines have changed in British Columbia over time. B.C.'s testing strategy has been characterized by four phases: 1) Exposure-based testing (start of pandemic), 2) Targeted testing (March 16, 2020), 3) Expanded testing (April 9, 2020), 4) Symptom-based testing (April 21, 2020), and 5) Symptom-based testing for targeted populations (a-are at risk of more severe disease and/or b-live or work in high-risk settings such as healthcare workers) and Rapid Antigen Tests deployment (January 18, 2022). Due to changes in testing strategies in BC in 2022, focusing on targeted higher risk populations, current case counts are an underestimate of the true number of COVID-19 cases in BC and may not be representative of the situation in the community.
    The following laboratory indicators are included in the provincial laboratory data file:New_Tests: the number of new COVID-19 testsTotal_Tests: the total number of COVID-19 testsPositivity: the positivity rate for COVID-19 testsTurn_Around: the turnaround time for COVID-19 testsBC Testing Rate: Total PCR + POC tests per day (excluding POC that were confirmed by PCR within 7 days) / Population using BC Stats PEOPLE2021 population projections for the year 2022 * 100,000.Health Authority AssignmentCases are reported by health authority of residence.As of April 2, 2022, cases are reported based on the address provided at the time of testing; when not available, by location of the provider ordering the lab test.As of April 2, 2022, cases who reported having an address outside of B.C. are not included.Prior to April 2, 2022, when

  13. i

    Global Financial Inclusion (Global Findex) Database 2021 - Venezuela, RB

    • datacatalog.ihsn.org
    • microdata.worldbank.org
    Updated Dec 17, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Venezuela, RB [Dataset]. https://datacatalog.ihsn.org/catalog/10526
    Explore at:
    Dataset updated
    Dec 17, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Venezuela, RB
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Venezuela, RB is 1000.

    Mode of data collection

    Landline and mobile telephone

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  14. i

    Global Financial Inclusion (Global Findex) Database 2021 - Chile

    • catalog.ihsn.org
    • datacatalog.ihsn.org
    • +1more
    Updated Dec 16, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Chile [Dataset]. https://catalog.ihsn.org/catalog/study/CHL_2021_FINDEX_v02_M
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Chile
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Chile is 1000.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  15. f

    Table_1_The impact of civil commitment laws for substance use disorder on...

    • frontiersin.figshare.com
    docx
    Updated Feb 2, 2024
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Phillip Cochran; Peter S. Chindavong; Jurian Edelenbos; Amy Chiou; Haylee F. Trulson; Rahul Garg; Robert W. Parker (2024). Table_1_The impact of civil commitment laws for substance use disorder on opioid overdose deaths.docx [Dataset]. http://doi.org/10.3389/fpsyt.2024.1283169.s003
    Explore at:
    docxAvailable download formats
    Dataset updated
    Feb 2, 2024
    Dataset provided by
    Frontiers
    Authors
    Phillip Cochran; Peter S. Chindavong; Jurian Edelenbos; Amy Chiou; Haylee F. Trulson; Rahul Garg; Robert W. Parker
    License

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

    Description

    ObjectiveOur study analyzed the impact of civil commitment (CC) laws for substance use disorder (SUD) on opioid overdose death rates (OODR) in the U.S. from 2010–21.MethodsWe used a retrospective study design using the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) dataset to analyze overdose death rates from any opioid during 2010–21 using ICD-10 codes. We used t-tests and two-way ANOVA to compare the OODR between the U.S. states with the law as compared to those without by using GraphPad Prism 10.0.ResultsWe found no significant difference in the annual mean age-adjusted OODR from 2010–21 between U.S. states with and without CC SUD laws. During the pre-COVID era (2010–19), the presence or absence of CC SUD law had no difference in age-adjusted OODR. However, in the post-COVID era (2020–21), there was a significant increase in OODR in states with a CC SUD law compared to states without the law (p = 0.032). We also found that OODR increased at a faster rate post-COVID among both the states with CC SUD laws (p 

  16. Coronavirus (COVID-19) key figures in the Philippines 2023

    • statista.com
    Updated Jul 13, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Statista (2023). Coronavirus (COVID-19) key figures in the Philippines 2023 [Dataset]. https://www.statista.com/statistics/1100765/philippines-coronavirus-covid19-cases/
    Explore at:
    Dataset updated
    Jul 13, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Philippines
    Description

    As of May 3, 2023, approximately 4.1 million people had been confirmed as infected with the COVID-19 virus in the Philippines. Of those, over four million had recovered and around 66.4 thousand died.

    Vaccination rollout in the Philippines
    The government’s vaccination drives successfully inoculated over 71 million Filipinos, surpassing the initial target of 70 million. This represented about 77 percent of the total eligible population to receive the vaccine. As of June 2022, the National Capital Region accounted for the highest share of the population that have been fully vaccinated from the virus, followed by Region 4-A.

    Hybrid shopping behavior Lockdown restrictions across the country forced consumers to turn to e-commerce channels and digital payment systems to prevent themselves from contracting the virus. A survey revealed that about 46 percent of respondents in the Philippines were first social media shoppers in 2021.

  17. i

    Global Financial Inclusion (Global Findex) Database 2021 - South Sudan

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Dec 16, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - South Sudan [Dataset]. https://datacatalog.ihsn.org/catalog/10507
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    South Sudan
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    Some areas were excluded due to territorial dispute, security reasons, or inaccessibility. The excluded areas represent approximately 10 percent of the total population. In addition, 40 percent of the primary sampling units (PSUs) were replaced during fieldwork, primarily due to flooding.

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for South Sudan is 1001.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  18. i

    Global Financial Inclusion (Global Findex) Database 2021 - Ecuador

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Dec 16, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Ecuador [Dataset]. https://datacatalog.ihsn.org/catalog/10436
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Ecuador
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Ecuador is 1000.

    Mode of data collection

    Landline and mobile telephone

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  19. i

    Global Financial Inclusion (Global Findex) Database 2021 - Peru

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Dec 16, 2022
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - Peru [Dataset]. https://datacatalog.ihsn.org/catalog/10493
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021
    Area covered
    Peru
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    National coverage

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for Peru is 1000.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

  20. i

    Global Financial Inclusion (Global Findex) Database 2021 - China

    • datacatalog.ihsn.org
    • catalog.ihsn.org
    • +1more
    Updated Dec 16, 2022
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Development Research Group, Finance and Private Sector Development Unit (2022). Global Financial Inclusion (Global Findex) Database 2021 - China [Dataset]. https://datacatalog.ihsn.org/catalog/10426
    Explore at:
    Dataset updated
    Dec 16, 2022
    Dataset authored and provided by
    Development Research Group, Finance and Private Sector Development Unit
    Time period covered
    2021 - 2022
    Area covered
    China
    Description

    Abstract

    The fourth edition of the Global Findex offers a lens into how people accessed and used financial services during the COVID-19 pandemic, when mobility restrictions and health policies drove increased demand for digital services of all kinds.

    The Global Findex is the world's most comprehensive database on financial inclusion. It is also the only global demand-side data source allowing for global and regional cross-country analysis to provide a rigorous and multidimensional picture of how adults save, borrow, make payments, and manage financial risks. Global Findex 2021 data were collected from national representative surveys of about 128,000 adults in more than 120 economies. The latest edition follows the 2011, 2014, and 2017 editions, and it includes a number of new series measuring financial health and resilience and contains more granular data on digital payment adoption, including merchant and government payments.

    The Global Findex is an indispensable resource for financial service practitioners, policy makers, researchers, and development professionals.

    Geographic coverage

    Tibet was excluded from the sample. The excluded areas represent less than 1 percent of the total population of China.

    Analysis unit

    Individual

    Kind of data

    Observation data/ratings [obs]

    Sampling procedure

    In most developing economies, Global Findex data have traditionally been collected through face-to-face interviews. Surveys are conducted face-to-face in economies where telephone coverage represents less than 80 percent of the population or where in-person surveying is the customary methodology. However, because of ongoing COVID-19 related mobility restrictions, face-to-face interviewing was not possible in some of these economies in 2021. Phone-based surveys were therefore conducted in 67 economies that had been surveyed face-to-face in 2017. These 67 economies were selected for inclusion based on population size, phone penetration rate, COVID-19 infection rates, and the feasibility of executing phone-based methods where Gallup would otherwise conduct face-to-face data collection, while complying with all government-issued guidance throughout the interviewing process. Gallup takes both mobile phone and landline ownership into consideration. According to Gallup World Poll 2019 data, when face-to-face surveys were last carried out in these economies, at least 80 percent of adults in almost all of them reported mobile phone ownership. All samples are probability-based and nationally representative of the resident adult population. Phone surveys were not a viable option in 17 economies that had been part of previous Global Findex surveys, however, because of low mobile phone ownership and surveying restrictions. Data for these economies will be collected in 2022 and released in 2023.

    In economies where face-to-face surveys are conducted, the first stage of sampling is the identification of primary sampling units. These units are stratified by population size, geography, or both, and clustering is achieved through one or more stages of sampling. Where population information is available, sample selection is based on probabilities proportional to population size; otherwise, simple random sampling is used. Random route procedures are used to select sampled households. Unless an outright refusal occurs, interviewers make up to three attempts to survey the sampled household. To increase the probability of contact and completion, attempts are made at different times of the day and, where possible, on different days. If an interview cannot be obtained at the initial sampled household, a simple substitution method is used. Respondents are randomly selected within the selected households. Each eligible household member is listed, and the hand-held survey device randomly selects the household member to be interviewed. For paper surveys, the Kish grid method is used to select the respondent. In economies where cultural restrictions dictate gender matching, respondents are randomly selected from among all eligible adults of the interviewer's gender.

    In traditionally phone-based economies, respondent selection follows the same procedure as in previous years, using random digit dialing or a nationally representative list of phone numbers. In most economies where mobile phone and landline penetration is high, a dual sampling frame is used.

    The same respondent selection procedure is applied to the new phone-based economies. Dual frame (landline and mobile phone) random digital dialing is used where landline presence and use are 20 percent or higher based on historical Gallup estimates. Mobile phone random digital dialing is used in economies with limited to no landline presence (less than 20 percent).

    For landline respondents in economies where mobile phone or landline penetration is 80 percent or higher, random selection of respondents is achieved by using either the latest birthday or household enumeration method. For mobile phone respondents in these economies or in economies where mobile phone or landline penetration is less than 80 percent, no further selection is performed. At least three attempts are made to reach a person in each household, spread over different days and times of day.

    Sample size for China is 3500.

    Mode of data collection

    Mobile telephone

    Research instrument

    Questionnaires are available on the website.

    Sampling error estimates

    Estimates of standard errors (which account for sampling error) vary by country and indicator. For country-specific margins of error, please refer to the Methodology section and corresponding table in Demirgüç-Kunt, Asli, Leora Klapper, Dorothe Singer, Saniya Ansar. 2022. The Global Findex Database 2021: Financial Inclusion, Digital Payments, and Resilience in the Age of COVID-19. Washington, DC: World Bank.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Statista (2024). Distribution of COVID-19 cases South Korea 2023, by age [Dataset]. https://www.statista.com/statistics/1102730/south-korea-coronavirus-cases-by-age/
Organization logo

Distribution of COVID-19 cases South Korea 2023, by age

Explore at:
23 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 4, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Time period covered
Aug 28, 2023
Area covered
South Korea
Description

As of August 28, 2023, confirmed coronavirus (COVID-19) patients in their forties made up the largest share of patients in South Korea, amounting to around 15.2 percent of all positive cases. The first wave lasted until April, with the second wave following in August of 2020. This was further followed by a fourth wave, driven by the delta and omicron variants. Though the country has since achieved high vaccination rates, the omicron variant led to record new daily cases in 2022.

Patient profile

In South Korea, the infection rate of coronavirus was the highest among people in the twenties due to their social activities. Indeed, the new infections related to the clubgoers in Seoul are likely to increase the infection rate between young people. 158 out of 261 clubgoer-related confirmed patients were in teenagers or in their twenties, and 36 patients were in their thirties. The mortality rate of coronavirus by age group was somewhat different from the age distribution of total infection cases. It was highest among people in their eighties, with this group making up around 59.6 percent of deaths related to the coronavirus in South Korea. Mortality declined with each younger age group.

Daily life changes

In South Korea, a new policy of "With Corona" has been launched in order to ease society back into a new norm of living with the virus, without having too many restrictions in place. This is based on high vaccination rates, and includes strict quarantine measures for those who are infected and their close contacts. There are plans to improve the verification of vaccination and test certificates for use in public spaces. Most South Koreans have responded to rising numbers by once again avoiding crowded places or going out. It is common to wear masks regardless of diseases, so people are continuing to wear masks when they need to go out. Also, people prefer to do online shopping than physical shopping, and online sales of food and health-related products have increased by more than 700 percent compared to last year. Spending on living, cooking, and furniture has increased significantly as people spend more time at home.

Search
Clear search
Close search
Google apps
Main menu