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Complete Table (12.10.2020)

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Growth Rate Coloring
  • 0 % to 10 %
  • 10 % to 20 %
  • 20 % to 33 %
  • 33 % to 50 %
  • 50 % to 75 %
  • > 75 % (worsening)

  • 0 % to 10 %
  • 10 % to 20 %
  • 20 % to 33 %
  • > 33 % (improving)

Evolution of Cases since Outbreak

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Cases per Country

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Evolution of Cases since 10th/100th case

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Case Fatality

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Evolution of Doubling Times per Country

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Note: The doubling time is calculated based on the growth rate over the last seven days.

Case Trajectory

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Health Expenditure

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Human Freedom

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Immunization to Influenza

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Life Expectancy

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Government actions with respect to confirmed cases

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Government actions with respect to deaths

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Policy Measures Indexes

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About this project

CovidDExp (COVID-19 Data Exploration) is an exploratory data analysis tool with a visually rich presentation of the COVID-19 pandemic. It includes processing of reliable real-time evolving data with qualitative data examined against a series of selected indicators to monitor and detail the worldwide virus outbreak situation under a holistic approach.

Motivation

CovidDExp was born by scientific curiosity and eagerness to understand and examine the global pandemic crisis and its parameters from the data scientist perspective. Beyond the evolution of the pandemic and epidemic statistics, our intention is to discover and explore correlations and connections with socio-economic and governmental indicators that can highlight alternate angles and provide further insights to the interested viewer. This initiative is launched and supported by members of the Data and Web Science Lab (DATALAB) an active research group engaged in ICT research and innovation on data science and multi scope analytics under the Department of Informatics, Aristotle University of Thessaloniki, Greece. Since, apparently, the case of Greece is important to us, there is a specialized section that examines the evolution of the disease in the country. You may find a page dedicated to Greece here . It explores available regional data for Greece, as well as an analysis of social media (Twitter) traffic.

Data Sources

This project aggregates and combines publicly available data from several different sources. These include:

Links to this page

You may link to this page using its main URL: https://covid19.csd.auth.gr/

You may also link directly to any one of the different tabs:

Issues and Suggestions

If you encounter any issue or have a suggestion to improve or add new content, please create an issue with our issue tracker at Github.

The Team

  • Prof. Athena Vakali - Data and Web Science Lab director
  • Vasileios Psomiadis - Post doc researcher
  • George Arvanitakis - Post doc researcher
  • Pavlos Sermpezis - Post doc researcher
  • Ilias Dimitriadis - PhD researcher
  • Stefanos Efstathiou - PhD researcher
  • Dimitra Karanatsiou - PhD researcher
  • Marinos Poiitis - PhD researcher
  • George Vlahavas - PhD researcher
  • Sofia Yfantidou - PhD researcher
  • Konstantinos Georgiou - MSc student

Licencing

The creators of this initiative are strong advocates of open-source culture and its fundamental benefits for open scientific research. This effort utilizes open datasets and is based on open-source technologies. This project is released to the public under an MIT license. You may find all relevant source code in our project page at Github.