ALESS open data portal

Background

Coronaviruses are a family of viruses that cause various illnesses, including the common cold. In January 2020, a new strain of coronavirus (SARS-CoV-2) was identified in China. The disease it causes, named COVID-19 by the World Health Organization, quickly spread around the world. The WHO declared it a pandemic on March 11, 2020. For most people infected with COVID-19, symptoms are mild (dry cough, fever, fatigue). However, some people develop severe symptoms requiring hospitalization. The pandemic has caused millions of deaths worldwide and has had major effects on healthcare systems, economies, and daily life.

The pandemic led to important developments including new vaccine technologies, changes in how people work and study, and new ways of tracking disease spread. While the emergency phase has ended in many countries, COVID-19 continues to circulate globally. Research on COVID-19 involves many fields including medicine, public health, epidemiology, economics, and social science. Open data has been important for understanding the pandemic and guiding responses.

Data Sources

Global COVID-19 Cases and Deaths

1. Our World in Data - COVID-19 Pandemic

https://ourworldindata.org/coronavirus

Most user-friendly source for COVID-19 data
Cases, deaths, testing, and vaccinations by country
All data free to download (CSV format)
Interactive charts help you see patterns
Good for: Almost any COVID-19 research question

2. WHO COVID-19 Dashboard

https://data.who.int/dashboards/covid19/

Official data from the World Health Organization
Cases, deaths, vaccinations by country
Weekly data (many countries stopped daily reporting in 2023-2024)
Downloadable datasets available
Good for: Official international data

3. Johns Hopkins University COVID-19 Data (Historical)

https://coronavirus.jhu.edu/

One of the most widely-used COVID-19 trackers
Note: Stopped updating March 10, 2023, but historical data is available
Good for: Data from 2020-2023 (early pandemic period)

Vaccination Data

4. Our World in Data - COVID-19 Vaccinations

https://ourworldindata.org/covid-vaccinations

Vaccination data by country
Total doses, people vaccinated, fully vaccinated
Daily updates with downloadable data
Easy to compare between countries
Good for: Studying vaccination rollout and coverage

Policy Responses

5. Oxford COVID-19 Government Response Tracker (OxCGRT)

https://www.bsg.ox.ac.uk/research/covid-19-government-response-tracker

Tracks government policies during the pandemic
School closures, workplace closures, travel bans, etc.
"Stringency index" measures how strict policies were
Data available for download
Good for: Comparing how different countries responded

US-Specific Data (if studying the United States)

6. CDC COVID-19 Data

https://www.cdc.gov/covid/php/surveillance/index.html

Detailed US data including hospitalizations
State-level and national data
Testing and vaccination data
Good for: Detailed analysis of COVID-19 in the US

Japan-Specific Data (if studying Japan)

7. Ministry of Health, Labour and Welfare (MHLW) - COVID-19 Data

https://covid19.mhlw.go.jp/en/

Official Japanese government COVID-19 statistics
Cases, deaths, and vaccination data for Japan
Prefecture-level data available
English and Japanese versions available
Good for: Studying COVID-19 in Japan or comparing Japanese prefectures

Important Notes About COVID-19 Data

Data Limitations:

Many countries stopped detailed tracking in 2023-2024 as the emergency ended
Testing varied greatly between countries, affecting case counts
Some countries had better reporting systems than others
Death counts may not capture all COVID-19 deaths

What This Means for Your Research:

Be careful when comparing countries - different testing rates affect case numbers
Death data is generally more reliable than case data
Consider using rates (per 1 million people) instead of total numbers when comparing countries
Focus on trends over time rather than exact numbers
The most complete data is from 2020-2022

Best Practices:

Clearly state which time period you're analyzing
Mention data limitations in your paper
Use per capita data (per 100,000 or per 1 million people) when comparing countries of different sizes
Cross-check important findings with multiple sources

Example research questions

To answer some of these questions, you might need to find other data to combine with the COVID-19 dataset (e.g., population, population density, number of hospitals per 100,000 people, cultural attitudes to face masks, frequency of COVID-19 testing, government response to the pandemic, healthcare spending, age demographics).

What features of a country are related to the spread of COVID-19?

How does the mortality rate vary by country?

How is the spread of COVID-19 related to cultural differences in health practices?

What is the relationship between government policy responses and COVID-19 outcomes?

How does healthcare system capacity relate to COVID-19 death rates?

Is there a relationship between vaccination speed and overall mortality rates across countries?

Tips for Using COVID-19 Data

Getting Started:

Start with Our World in Data - it's the easiest to use
Choose a specific question (don't try to study everything!)
Select a limited number of countries or a specific time period
Download the data and look at it in Excel or Google Sheets first

Understanding the Data:

Cases: Number of confirmed COVID-19 infections (depends on testing)
Deaths: Number of deaths attributed to COVID-19 (more reliable than cases)
Testing rate: Tests per 1,000 people (helps explain case numbers)
Vaccination rate: Percentage of population vaccinated
Per capita: "Per person" - allows fair comparison between countries

Making Good Comparisons:

Compare countries of similar size or development level
Look at rates (per million people), not just total numbers
Consider both the peak and the overall trend
Account for differences in testing and reporting

Combining Datasets: COVID-19 research often requires combining multiple datasets. For example:

COVID-19 deaths + healthcare spending + hospital beds per capita
Case numbers + testing rates + population density
Vaccination rates + government policy stringency + deaths
Mortality rates + age demographics + healthcare capacity

For Your Analysis:

Create clear graphs showing trends over time
Use line graphs for trends, bar graphs for comparisons
Include both your data table and visualizations
Explain any unusual patterns you observe

Citation: Always cite your data source:

Example: "Mathieu, E., Ritchie, H., Rodés-Guirao, L., et al. (2020-2025). Coronavirus Pandemic (COVID-19). Our World in Data. https://ourworldindata.org/coronavirus (accessed October 5, 2025)"

Useful Additional Data Sources

When studying COVID-19, you might want to combine COVID data with:

Healthcare data: Hospital beds per capita, doctors per capita, healthcare spending (World Bank, OECD)
Demographics: Population, age distribution, urban population percentage (World Bank, UN)
Economic data: GDP per capita, income levels (World Bank, OECD)
Policy data: Government response stringency, specific interventions (Oxford COVID-19 Government Response Tracker)
Testing data: Tests per capita, positivity rates (Our World in Data)
Geographic data: Population density, climate data (World Bank, various sources)

Questions? Need Help?

Start with simple questions and simple comparisons
Our World in Data has explanations for all their datasets
If data seems confusing, ask your professor
It's better to do a simple analysis well than a complex one poorly
Remember: Your goal is to ask a clear question and use data to answer it

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