I created this website, with the intent to provide accurate and real-time data, that tracks the novel coronavirus. As the SARS-CoV-2 is rapidly speedily, I hope you can use this site to find up-to-date info for your location, along with current research, and recent news. This site was built using Corvid API and the real-time dashboards were built with ArcGIS, C/C++, Seaborn, Plotly, Python, HTML, and R programming languages. Get in touch if you’d like to learn more about my career and what I’m working on now.
I created this website, with the intent to provide accurate and real-time data, that tracks the novel coronavirus. As the SARS-CoV-2 is rapidly speedily, I hope you can use this site to find up-to-date info for your location, along with current research, and recent news. This site was built using Corvid API and the real-time dashboards were built with ArcGIS, C/C++, Seaborn, Plotly, Python, HTML, and R programming languages. Get in touch if you’d like to learn more about my career and what I’m working on now.
I created this website, with the intent to provide accurate and real-time data, that tracks the novel coronavirus. As the SARS-CoV-2 is rapidly speedily, I hope you can use this site to find up-to-date info for your location, along with current research, and recent news. This site was built using Corvid API and the real-time dashboards were built with ArcGIS, C/C++, Seaborn, Plotly, Python, HTML, and R programming languages. Get in touch if you’d like to learn more about my career and what I’m working on now.
Mortality Risk of COVID-19
What does the data on deaths and cases tell us about the mortality risk of COVID-19? To understand the risks and respond appropriately we would also want to know the mortality risk of COVID-19 – the likelihood that someone who is infected with the disease will die from it.
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One of the most important ways to measure the burden of COVID-19 is mortality. Countries throughout the world have reported very different case fatality ratios – the number of deaths divided by the number of confirmed cases.
The diagonal lines on the chart below correspond to different case fatality ratios (the number of deaths divided by the number of confirmed cases). Countries falling on the uppermost lines have the highest observed case fatality ratios. Points with a black border correspond to the 20 most affected countries by COVID-19 worldwide, based on the number of deaths. Hover over the circles to see the country name and a ratio value.
The chart here shows excess mortality during the pandemic for all ages using the P-score. Shown is how the number of weekly or monthly deaths in 2020–2021 differs as a percentage from the average number of deaths
in the same period over the years 2015–2019. This metric is called the P-score. The reported number of deaths might not count
all deaths that occurred due to incomplete coverage and delays in death reporting.
Besides visualizing excess mortality as a percentage difference, we can also look at the raw death count as shown here in this chart. The raw death count helps give us a sense of scale: for example, the US suffered roughly 500,000 more deaths than the five-year average between 1 March and 27 December 2020, compared to 340,000 confirmed COVID-19 deaths during that period.
However, this measure is less comparable across countries due to large differences in populations.
Shown is how the number of weekly or monthly deaths in 2020–2021 differs from the number of deaths in the same period over
the years 2015–2019. The reported number of deaths might not count all deaths that occurred due to incomplete coverage and
delays in death reporting.