Country-Level COVID-19 Cases with Population Data for Epidemic Modeling

A combined dataset from Johns Hopkins University and population sources tracks cumulative and daily COVID-19 cases, fatalities, and recoveries by country from January 22, 2020 onward. It includes population figures for calculating incidence and prevalence rates, and was used to build a public visualization and analysis tool. The data is structured to support the development of epidemic models like SIR.

Use Cases

• Developing SIR or SIR-with-mortality epidemic models based on daily new case and fatality data.
• Calculating and comparing incidence and prevalence rates across countries using the provided population figures.
• Building interactive dashboards for visualizing the progression of confirmed, recovered, and fatal cases over time.
• Analyzing mortality and recovery rate trends from the cumulative and daily case time series.

Strengths

• Integrates data from a primary, authoritative source (JHU CSSE) for COVID-19 case tracking.
• Includes derived fields like daily new cases and remaining confirmed cases, which are directly useful for modeling.
• Merges case data with country population, enabling per-capita rate calculations.

Limitations

• Description metadata is limited; actual data quality, column definitions, and row count require manual inspection after download.
• The author notes a lack of credible data sources for probable cases, which are not included.
• Last update date is unknown; freshness unverified.

Provenance

Source

Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) COVID-19 dataset, supplemented by population data from Worldometer and other sources.

Collection Method

Data retrieved and merged from multiple open sources, with derived calculations performed by the dataset creator.

Time Range

From 2020-01-22 onward.

Geography

Country/region level worldwide.