COVID-19 waves: comparative perspectives among high-resource settings

NOTE
Since July 2, 2022, select data from this site have been presented in an interactive app. This site is not maintained regularly anymore.

(Last updated on 2022-10-23 14:16:10. Published on November 13, 2020. An earlier version, “The flattened COVID-19 curve in South Korea - and comparative perspectives among high-resource settings”, was published at Medium)

More than 10 months after the first reported COVID-19 case, the epidemic has hit countries around the globe with different intensity at different time. Some countries like Taiwan has managed to avoid major outbreaks all together, some have controlled outbreaks relatively effectively (e.g., New Zealand and South Korea), but many have had a substantial outbreak, often followed by another.

A clear lesson so far is no country is safe from the pandemic:

We will compare epidemic curves among the Organisation for Economic Co-operation and Development (OECD) member countries. Understanding different epidemic curves to date will help us hopefully address the current crisis and more importantly prevent, delay, and flatten the next waves.

Hover over each figure to see values and more options.

See data sources and methods at the end.

1. Latest snapshot by country

Before we check the epidemic curve to date, let’s briefly compare cumulative incidence (number of reported cases per 100,000 population) and cumulative mortality rates (number of reported COVID-19 deaths per 100,000 population). Considering different testing rates, COVID-19 specific mortality rate per population (right panel) may be more appropriate to compare across countries.

And, cumulative incidence vs. new daily cases (7-day rolling average of daily new reported cases per 100,000 population): New daily cases (right panel) shows the current burden of transmission.

2. Epidemic curve by country

The below shows trends of 7-day rolling averages of daily new cases per 100,000 population since February, 2020.

All countries are presented below in groups, due to varying range of peak height. Top panel has countries with relatively lower peak, and the bottom panel shows countries with higher peak.

Note:
* The x-axis is date since February.
* The y-axis is 7-day rolling average of daily new cases per 100,000 population.
* The light gray box represents the number of daily new cases 20 or lower per 100,000.
* The darker blue section of the line represents the last 30 days.

METHODS

Data
1. All COVID-19 data (i.e., cumulative confirmed cases and deaths by day) come from JHU/CSSE. Accessed on 2022-10-23.
2. All data on country population come from UN World Population Prospects 2019 Revision. Accessed on April 18, 2020.

Note on comparability: JHU/CSSE compiles the best available data, but a definition of confirmed cases (even COVID-19 deaths) may differ across countries and even within a country over time. The abrupt increase in the number of new cases in France, for example, likely reflect changes in the definition of confirmed cases.

Measures The number of new confirmed cases on each date was calculated based on the difference between cumulative numbers over two consecutive days. Then, a seven-day rolling average was calculated, hereinafter referred to as the smoothed number of new confirmed cases. Then, the smoothed number was divided by the total population in the country: the smoothed number of new confirmed cases per 100,000 population.

See GitHub for data, code, and more information. For typos, errors, and questions, contact me at www.isquared.global.

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