Global view of the pandemic
Check how indicators developed over time for the world. 3 main type of plots are proposed: (1) area plot for confirmed infections, (2) time line of each single variable from "start", "6 months" and "1 month" ago, (3) calendar comparison for the "full year" or for the "last month".
Change "Select View" to "Timeline per calendar year" to see the years' comparison.
Global Covid-19 evolution over time
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Continents Comparison
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COVID-19 main variables
Confirmed infections are those resulting from a positive covid19 test that was communicated to the local authorities.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Timeline per variable
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Vaccination status
Vaccines are a simple count of injected doses, they included also boosters. For this reason the "Vaccination over population size" can have values > 100%.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Europe page
Europian countries are grouped in Macro Areas as defined by United Nations. The Areas are represented by the colors in the heatmap above, used also in the graphs of this page.
Macro Area Comparison
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COVID-19 main variables
Confirmed infections are those resulting from a positive covid19 test that was communicated to the local authorities.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Timeline per variable
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Vaccination status
Vaccines are a simple count of injected doses, they included also boosters. For this reason the "Vaccination over population size" can have values > 100%.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Country Plots within Continent
Country Heat Maps within Continent
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Asia page
Asian countries are grouped in Macro Areas as defined by United Nations. The Areas are represented by the colors in the heatmap above, used also in the graphs of this page.
Macro Area Comparison
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COVID-19 main variables
Confirmed infections are those resulting from a positive covid19 test that was communicated to the local authorities.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Timeline per variable
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Vaccination status
Vaccines are a simple count of injected doses, they included also boosters. For this reason the "Vaccination over population size" can have values > 100%.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Country Plots within Continent
Country Heat Maps within Continent
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Africa page
African countries are grouped in Macro Areas as defined by United Nations. The Areas are represented by the colors in the heatmap above, used also in the graphs of this page.
Macro Area Comparison
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COVID-19 main variables
Confirmed infections are those resulting from a positive covid19 test that was communicated to the local authorities.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Timeline per variable
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Vaccination status
Vaccines are a simple count of injected doses, they included also boosters. For this reason the "Vaccination over population size" can have values > 100%.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Country Plots within Continent
Country Heat Maps within Continent
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Latam & Carib. page
Latin American countries are grouped in Macro Areas as defined by United Nations. The Areas are represented by the colors in the heatmap above, used also in the graphs of this page.
Macro Area Comparison
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COVID-19 main variables
Confirmed infections are those resulting from a positive covid19 test that was communicated to the local authorities.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Loading...
Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Timeline per variable
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Vaccination status
Vaccines are a simple count of injected doses, they included also boosters. For this reason the "Vaccination over population size" can have values > 100%.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Country Plots within Continent
Country Heat Maps within Continent
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Northern America page
Northern America countries are grouped in Macro Areas as defined by United Nations. The Areas are represented by the colors in the heatmap above, used also in the graphs of this page.
Macro Area Comparison
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COVID-19 main variables
Confirmed infections are those resulting from a positive covid19 test that was communicated to the local authorities.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Timeline per variable
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Vaccination status
Vaccines are a simple count of injected doses, they included also boosters. For this reason the "Vaccination over population size" can have values > 100%.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Loading...
Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Country Plots within Continent
Country Heat Maps within Continent
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Oceania page
Oceanian countries are grouped in Macro Areas as defined by United Nations. The Areas are represented by the colors in the heatmap above, used also in the graphs of this page.
Macro Area Comparison
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COVID-19 main variables
Confirmed infections are those resulting from a positive covid19 test that was communicated to the local authorities.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Loading...
Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Timeline per variable
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Vaccination status
Vaccines are a simple count of injected doses, they included also boosters. For this reason the "Vaccination over population size" can have values > 100%.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Loading...
Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
Select the variable to see different views. Use rescaled data
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Country Plots within Continent
Country Heat Maps within Continent
COVID-19 Dashboard Switzerland
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COVID-19 evolution over time
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Evolution over time of Hospitalizations
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Vaccination Pace
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Country Report at Cantonal level
COVID-19 Single Country Dashboard
Only Countries with more than 1000 confirmed cases can be chosen .
Some countries and areas have stopped providing Recovered data.
Recovered, Hospitalized and Tests data can be partially/completely unavailable in our data source for some countries and areas .
Hospitalized, Vaccine doses and Test data are updated with delay for some countries and areas in our data source where available .
Some countries and areas have stopped providing Recovered data.
Recovered, Hospitalized and Tests data can be partially/completely unavailable in our data source for some countries and areas .
Hospitalized, Vaccine doses and Test data are updated with delay for some countries and areas in our data source where available .
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COVID-19 evolution over time
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Evolution over time of Hospitalizations
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Vaccination Pace
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Only Areas with more than 1000 confirmed cases can be chosen .
Some countries and areas have stopped providing Recovered data.
Recovered and Tests data can be partially/completely unavailable in our data source for some countries .
Some countries and areas have stopped providing Recovered data.
Recovered and Tests data can be partially/completely unavailable in our data source for some countries .
Countries Comparison
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COVID-19 main variables
Confirmed infections are those resulting from a positive covid19 test that was communicated to the local authorities.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
From the infections other variables are being derived and used in this page:
Growth Factor: total confirmed cases in the past 2 months as of today / total confirmed cases in the last 2 months 7 days ago.
Prevelence: the impact of the infections on the population size. The prevalence is presented as cases over 1 million (1M) people, this view is utilised for many other additive variables.
Other variables analysed in this section:
Mortality rate: seen as the number of people who died of covid per 1 million (1M) people.
Lethality rate: % of people who died of covid among those infected.
Please consider that active cases may be unreliable for many countries that do not provide record of recovered cases, and that, where testing information is available, no differenciation is done between antigenic and molecolar test to derive the Positive test rate, i.e. % of positive tests. When comparing countries consider the different testing strategies and whether they report a comparable number of tests.
Units in the Scatterplot are missing if the data are not provided or 0.
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Hospitalizations and Intensive Care Units
The number of hospitalized patients on a given date is provided by most of countries and regions within country, however please consider that hospitalized data could be missing also for some important countries.
'Ventilated/Int.Care' variable includes the number of hospitalized patients in intensive therapy and the patients requiring invasive ventilation on a date. The 2 measures have been merged as they are not presented with separated records by all countries
'Ventilated/Int.Care' variable includes the number of hospitalized patients in intensive therapy and the patients requiring invasive ventilation on a date. The 2 measures have been merged as they are not presented with separated records by all countries
Units in the Scatterplot are missing if the data are not provided or 0.
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Units or variables with no data will not appear in the 'barplot'.
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Stringency Lock-Down Index
The 'Stringency Index' represents all the Lock Down measures with single index from 0 (no stringency) to 100 (full stringency).
This would include measures like school / work place closing, events cancellation, gathering restrictions, masks obligations, movements restrictions etc.
More information about the construction of the 'stringency index' is available on the Covid-19 Data Hub documentation.
This would include measures like school / work place closing, events cancellation, gathering restrictions, masks obligations, movements restrictions etc.
More information about the construction of the 'stringency index' is available on the Covid-19 Data Hub documentation.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
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Vaccination status
Vaccines are a simple count of injected doses, they included also boosters. For this reason the "Vaccination over population size" can have values > 100%.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Areas that already started utilizing multiple doses (boosters) would result as more highliy vaccinated than others.
Those who have received 2 doses are labelled as Fully Vaccinated, while the Vaccinated have a partial vaccination.
Not all analyzed areas may have provided data on vaccines, our source is ourworldindata.org.
Units in the Scatterplot are missing if the data are not provided or 0.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
Select Y and X axes to visualize patterns. Zoom to have a closer insight.
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Units or variables with no data will not appear in the 'barplot'.
Select the variable to see different views. Use rescaled data to compare.
If all data are missing for the chosen variable the plot will display a message.
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