Social challenges brought by COVID-19

Coronavirus has changed the way we live and will bring numerous difficulties. Using data, we hope to shed some light on issues policymakers need to focus on most. We will modify this page with updated data and new analyses on a regular basis.

Social media

Reddit as the leading indicator

Scientific papers

COVID-19 Open Research Dataset and SSRN


News articles


We collected news articles from from the period 01.01.2020 - 05.05.2020.

Sources used: ArsTechnica, Euractiv, Fastcompany, Gizmodo, Guardian, Politico.eu, Reuters, Techcrunch, The Register, Verge, ZDNet

Trending terms in news articles


52 most trending COVID-19 keywords are identified

Based on the weekly changes in term frequencies, the most trending terms were identified. We grouped them into 8 wider areas: first splitting into one related precisely to the coronavirus crisis, second to technological solutions. The size of the bubble is based on the regression coefficient. Bigger bubble: more robust trend.

Social distancing is not only an issue in the COVID-19 crisis, but also a category in technological matters: using new technologies, we may bring our quality of life closer to the pre-quarantine times, and possibly shorten the period of restrictions.

News top words


New crisis, old problems?

Analysing keywords gaining popularity in the tech media articles, we can see that COVID-19 crisis exacerbates many well-known social challenges, e.g. widely spread conspiracy theories and misinformation, growing privacy concerns and anxiety. Economic repercussions of the pandemic are discussed intensively, the focal points are the future of the gig economy, global supply chains and situation of the small businesses. Various apps designed for remote work and video chats have been extensively covered in the tech media. Their perils have been addressed, see e.g.: 'zoomboming', 'troll', 'throttle'.

Sentiment analysis


Contact-tracing
PEPP-PT
Zoom
Misinformation
Ventilator

Contact tracing / PEPP-PT: news articles reported extensively on various tech projects related to tracking the movement of infected individuals. PEPP-PT is a coalition of researchers and tech experts across Europe developing a common standard for contact tracing solutions. The sentiment in paragraphs covering PEPP-PT and other tech solutions have been positive or neutral, with negative sentiments only in case of a few terms (such as "mission creep").

A major angle of discussion is related to privacy and the fear of surveillance. Data protocols can be either "centralised" with data stored in a central location or "decentralised". Both approaches have advantages and disadvantages: in case of centralised systems more advanced data analysis is possible, but with a higher risk of data breach or violation of privacy. Various national governments initially opted for centralised solutions, while the choice led to conflicts within the PEPP-PT project with researchers leaving, including Marcel Salathé. Researchers preferring a decentralised data protocol published an own standard within the DP-3T project, an alternative for PEPP-PT. Additionally, when Google and Apple joined forces to prepare an API for decentralised contact-tracing, national governments needed to reconsider their strategies.

The identified co-occurring terms include various actors of the recent news around PEPP-PT: researchers (Fraunhofer Heinrich Hertz Institute, École polytechnique fédérale de Lausanne, Michael Veale from Digital Rights & Regulation at UCL, Mayank Varia from Boston University), companies (startup Arago with CEO Hans-Christian Boos, PocketCampus) the European Data Protection Supervisor Wojciech Wiewiórowski, government officials (Helge Braun), MEPs (Axel Voss) and worldwide contact-tracing projects (the TraceTogether app in Singapore, Aarogya Setu in India).

Most positive Neutral
close contact mission creep
DP-3T centralised database
TraceTogether app decentralised approach
anonymous public health
central server Marcel Salathé
location data exposure notification
two metres Scott Morrison
opt-in privacy concern

Contact tracing / PEPP-PT: news articles reported extensively on various tech projects related to tracking the movement of infected individuals. PEPP-PT is a coalition of researchers and tech experts across Europe developing a common standard for contact tracing solutions. The sentiment in paragraphs covering PEPP-PT and other tech solutions have been positive or neutral, with negative sentiments only in case of a few terms (such as "mission creep").

A major angle of discussion is related to privacy and the fear of surveillance. Data protocols can be either "centralised" with data stored in a central location or "decentralised". Both approaches have advantages and disadvantages: in case of centralised systems more advanced data analysis is possible, but with a higher risk of data breach or violation of privacy. Various national governments initially opted for centralised solutions, while the choice led to conflicts within the PEPP-PT project with researchers leaving, including Marcel Salathé. Researchers preferring a decentralised data protocol published an own standard within the DP-3T project, an alternative for PEPP-PT. Additionally, when Google and Apple joined forces to prepare an API for decentralised contact-tracing, national governments needed to reconsider their strategies.

The identified co-occurring terms include various actors of the recent news around PEPP-PT: researchers (Fraunhofer Heinrich Hertz Institute, École polytechnique fédérale de Lausanne, Michael Veale from Digital Rights & Regulation at UCL, Mayank Varia from Boston University), companies (startup Arago with CEO Hans-Christian Boos, PocketCampus) the European Data Protection Supervisor Wojciech Wiewiórowski, government officials (Helge Braun), MEPs (Axel Voss) and worldwide contact-tracing projects (the TraceTogether app in Singapore, Aarogya Setu in India).

Most positive Neutral
Aarogya Setu Hans Christian
proximity-tracking Axel Voss
privacy first Pocket Campus
Fraunhofer decentralised model
Michael Veal Schweisshelm
Wiewiórowski said anonymised data
DP-3T phone-tracking
Lausanne Mayank
Helge Braun gps location
central server data-slurp

Zoom: the analysed paragraphs fall into positive or neutral sentiment. The text snippets with higher score include competing solutions and the use-cases during the pandemic. On the other hand, the paragraphs with the lowest scores present the security and privacy issues that were unraveled recently, such as “zoombombing”. With increased use of video chat solutions and higher scrutiny, competing app Houseparty also faced allegations related to security that were dismissed by the company (offering bounty to identify the source of the “commercial smear”).

Most positive Neutral
remote-work zoom bomb
video-conference prankster
slack commercial smear
facetime uninvited
skype eric yuan
video conference waiting room
google hangouts public perception

Misinformation: the positive paragraphs include the efforts of social media platforms to tackle COVID-19 fake news, and research by the activist group Avaaz that highlighted this problem .

The most negative news include Chinese diplomat Lijian Zao’s tweet claiming that the source of the coronavirus was the US and reports on misinformation spread in the EU by Kremlin-backed media. Other major conspiracy theory claims that COVID-19 is caused by 5G masts.

Most positive Most negative
Factcheck.org Lijian
group Avaaz Kremlin-backed
content moderation miracle cure
Pew Research drink bleach
news feed conspiracy theorist

Ventilators: the positive fragments describe ventilator designs (for 3D printers), open-source plans by Medtronic and MIT (E-vent), and the efforts of the automotive industry (Ford with Ventec Life).

The slightly negative and neutral paragraphs report on the struggles in the US to mitigate the ventilator shortage.

Most positive Most negative
bag valve President Trump
face shield Elon Musk
e-vent ventilator shortage
ford stockpiling
medtron war era
face mask overwhelm
ventec intensive care
3d-print Blasio

Changing opinions

The sentiment analysis resulted in a compound score for every paragraph containing a given phrase. The score is calculated from the mean of the valence scores of each word in the paragraph apart from the analysed words themselves, which have been removed from the paragraph's text.

Two methods are combined to:

  • Find the words that appear frequently together (“co-occurrence analysis”) in the same paragraph

  • Examine the sentiment of paragraphs containing the co-occurring word pairs and find the most positive/negative ones

Sentiment analysis measures if a text is using rather positive, neutral or negative expressions. For each paragraph, a compound score was calculated, with range between +1 (extremely positive) and -1 (extremely negative).

Grouping articles based on topic


Next, we mapped articles based on their topic using a process called topic modelling. Topic modelling assumes that each article is a mixture of topics, and each topic is a collection of characteristic terms. Implementing an algorithm called Latent Dirichlet Allocation (LDA), 10 topics were assigned to the articles. However, the vocabulary of news articles is not static, but changes over time. In order to examine trends, we used the dynamic topic modelling (DTM) approach, where the vocabulary of each topic evolves with time. The dataset was divided into samples, containing articles from every two weeks. As an example, you can explore the most characteristic words for the topics based on articles published between 11 and 25 March. The size of the bubbles corresponds to the size of the topic: Topic 1 (the COVID-19 pandemic) is the most frequently appearing topic in the documents, while Topic 10 (telco infrastructure) is the smallest. The location suggests how similar the various topics are to each other: e.g. Topic 3 (science) is overlapping with Topic 4 (IT development), while Topic 8 (business news) is further away on the graph. For each topic, the bars represent the individual terms that are characteristic for the currently selected topic. By adjusting the slider, you can view less frequent words that appear only in the given topic. For more information on LDA, see our blog post.

Evolution of topics


News change rapidly, with terms disappearing and new ones entering public discussion. Performing LDA on each sample, we examined how the probability of various terms changed over time. We focused on two highly relevant topics: Topic 1 (the COVID-19 crisis) and Topic 5 (video conferencing and social media). In Topic 1, it is worth noticing how the frequency of "China" gradually decreased, to finally disappear from the list of the most important terms by 25 March. On the other hand, "New York" entered the topic, most likely due to the massive increase of COVID-19 cases from the end of March. In the case of Topic 5, the rapid increase of Zoom and (Google) Meet can be observed.

Mapping articles


Next, we mapped articles in space based on their topic. In this exercise, we focused on articles that contained any of the terms in root form: "coronavirus", "covid-19" or "contact-tracing". We combined two methods: LDA and t-SNE. With LDA, each article was assigned to a dominant topic which is revealed by the color on the map. To dive deeper, articles using similar vocabulary were assigned to each other using t-SNE. On the map, articles covering the same subject are neighbours: clear clusters are formed around such detailed topics as contact-tracing, remote work or (cancelled) tech conferences. In the interactive version of the map, you can explore the titles of the articles. For more information on t-SNE, visit our blog post.

Click on the image to see an interactive version (4 MB)

Face masks


Masks have been a contentious topic. Early during the pandemic, WHO recommendations suggested that healthy people should not wear masks. Defying WHO's non-binding ordinances, countries like Czech Republic have made it obligatory for citizens to wear masks in public. How did the discussion develop?

Exponential increase in number of submissions

The topic has been sharply increasing in popularity until early April. Peaks can be attributed to Czech response: both the social encouragement and government response. Clearly European countries can be leaders and diversity enables comparison of different approaches, consistent with the principle of subsidiarity.

All days are consistent with UTC time, as they will be throughout whole analysis of Reddit.

A movement for mask-wearing has been started in the Czech Republic by Petr Ludwig. Later, after English subtitles have been added to his YouTube video and other people started spreading the message in various countries of the European Union, more and more European countries decided to introduce appropriate regulations.

A video has been posted about wearing masks, kickstarting a national and then European/international movement. A Czech journalist and author argues for wearing masks even by healthy people

Roušky a kritické myšlení #RouškyVšem

Czech Republic's 🇨🇿 government introduces a regulation making it compulsory to wear masks in public

Polish minister of health argues in media against wearing masks by ordinary citizens

Austria 🇦🇹 makes wearing masks compulsory in supermarkets

Poland 🇵🇱 announces that wearing a mask will be compulsory in public from 16 April

Austria 🇦🇹 starts lifting restrictions and maintains a decreasing number of new cases

Czech Republic 🇨🇿 begins another phase of easing lockdown, including driving schools and gyms

Mental health


Economic uncertainty and health worries put a strain on mental health.

Number of comments in r/anxiety subreddit, 7-day moving average

Number of comments in r/depression subreddit, 7-day moving average

Number of comments in r/SuicideWatch subreddit, 7-day moving average


Rise in anxiety

Users of the r/anxiety subreddit posted almost twice as many comments on the subreddit daily as in the pre-quarantine period. The trend seems to be reversing, but it has rebounded in recent days. Interestingly, subreddits like r/depression experienced a decrease in activity – the opposite of r/anxiety. Worryingly, r/SuicideWatch picked up activity after a fall in March. Theoretical knowledge of psychologists can be combined with real-time data to encourage politicians to make correct decisions and communicate them well: in a more calm or decisive way, depending on social needs.

Job market


Economy is a complex and interconnected system. Hospitality and tourism industries have been hit first, but no sector is fully safe from the effects of coronavirus.
The crisis can be a part of a creative destruction process: we should hope to emerge stronger from it. Particularly, automation can be sped up: machines do not get sick.

7-day moving average of the number of comments. Words: unemployed, unemployment

7-day moving average of the number of comments. Words: automate automation, automated, digitalisation, robot, robots

7-day moving average of the number of submissions. Words: unemployed, unemployment

7-day moving average of the number of submissions. Words: automate automation, automated, digitalisation, robot, robots


Challenges and future developments

Reddit is mostly an American website, but despite different economic and social systems, insights can be drawn also for Europe, especially more developed countries.

Unemployment was at a low level, with the American economy recording record-breaking job creation. Immediately, however, millions of people got laid off, which became visible in social media even earlier than in official unemployment data (in this chart we did not include terms such as "fired" or "laid off"). Apart from the social and economic challenge, it created various technological problems as well: mainframe-based systems (as used in several US states) were not prepared for such a wave of new registrations.

Discussion about automation did not start growing until lately, and the increases – both in the number of posts and comments – are way smaller than with unemployment or masks. Companies may forgo capital investments in times of quarantine. Meanwhile, the role the governments may play is necessary to be discussed: does automation create too much short-run unemployment to be encouraged in the post-COVID economy? How do the long-term gains look like and how to ensure Europe's place as an automation frontrunner?

Comments with words: unemployed, unemployment. Top 16 subreddits

Related problems

As people get fired, they run into other problems. First and foremost, these belong to the legal and financial categories, and laid off workers look for advice in r/legaladvice and r/personalfinance. Other challenges which may appear are connected to relationships (r/relationship_advice) and mental health (r/depression).

Remote work


As the world has moved to remote work, tools making it possible have experience a surge of popularity, but they have not avoided setbacks.

Number of comments with term "zoom", 7-day moving average

Number of comments in with term "discord", 7-day moving average

Number of comments in with term "skype", 7-day moving average

Number of comments in with any of the terms relating to other remote work apps, 7-day moving average

Number of comments in with terms "remote job" or "remote work", 7-day moving average


Main apps

As an easy-to-use video conferencing app, Zoom has enjoyed increased popularity. It did not come without controversy, as Zoom routes some of its traffic by China – a country notable for industrial spying, has been called a "privacy disaster", and has falsely claimed to use end-to-end encryption. Nevertheless, its growth has been fairly stable and stabilized in April at a high level.

Understandably, some users began looking for alternatives. One such app is Discord. It has been commonly used in the gaming community for years. Students in multiple schools suggested this solution to teachers, who supported the idea. Skype (with usage mainly confined to the online sex industry) and other apps seem to be more used as well, although in recent days the discussion calmed down.

Average sentiment of comments with the term "remote job" or "remote work", 7-day moving average from the last 8 weeks

Comments with terms "remote job" or "remote work". Top 16 subreddits


Positive assessment of remote work

Using vaderSentiment, which is a dictionary-based method for analysing sentiments of texts, we computed a sentiment for each comment and averaged sentiments of all comments written in a particular day.

The sentiment of remote work has been significantly positive in the whole analysed period. It dropped in mid-March, when the peak frequency occured, but then grew to values close to 0.4 at a higher and stable frequency. Sudden change to remote work may have surprised people, but they seem to enjoy the new kind of normality. Will they return to offices when the pandemic ends? Offices may be regarded as dangerous: crowded offices are hotbeds for viruses.

Contact tracing


Multiple countries have announced that they are creating apps meant for tracking citizens exposed to coronavirus. South Korea monitors quarantined users, and Singapore has been the frontrunner in using Bluetooth technology. Bluetooth has also been implemented by the Czech Republic, as well as by the Apple-Google cooperation, which is in the development stage.

Number of comments containing the name of the country which has created a tracking app and the term "tracking" or "tracing"
divided by the number of subscribers to the country's largest subreddit, as a percentage

7-days moving average of number of comments containing name of any country with a tracking app and the term "tracking"


Countries with most discussion

Relative to the number of subscribers in the country's largest subreddit (not necessarily the obvious one: r/casualUK has more subscribers than r/UnitedKingdom), South Korea, Iran and Spain have generated most discussion about their tracking efforts. Bahrain's high position is caused by a low number of subscribers to the subreddit. Singapore – the model for many – is sixth, while United Kingdom is just behind the top eight. They both are in the top three with regards to the absolute number of comments, with only South Korea experiencing more tracking-related discussion.

The discussion on contact tracing in particular countries has been slightly increasing in recent days, having started growing in late February and having reached a plateau by mid-March, with a recent spike attributable to the Google-Apple cooperation.

Lockdown


Almost all leading world economies have been put into some kind of lockdown. The city of Wuhan and neighboring cities in the Hubei province have been the first on 23 January. Italy's lockdown started on 9 March. Lockdowns' impact on economy, containment of the virus, and social consequences have been discussed in media and on Reddit, especially in the wake of anti-lockdown protests in the United States.

Number of comments about lockdown protests

Number of comments about easing lockdown, 7-day moving average

Number of all comments with the word "lockdown", 7-day moving average


Comments with word: lockdown. Top 16 subreddits

Lockdown fatigue?

In mid-April, a wave of Republican protests in the United States demanded easing rules on lockdown. Some limited protests happened in Europe as cross-border workers disagreed with Polish quarantine rules.

Lockdown fatigue has been one reason why Sweden did not go into a full lockdown. Anders Tegnell's decisions resulted in a much higher death rate than in other Scandinavian countries to date, but the health care system has not been overcrowded and the virus reproduction rate as estimated by Swedish authorities has fallen below 1. As a high percentage of Stockholm's population may have already been infected, if reports that reinfection is not possible are right, the spread is likely to stay low.

Discussion on easing lockdown has been steadily increasing, although it is not as much of a topic as protests. It is connected to how people see lockdown: as an unpleasurable necessity, an infringement on their rights and an overreaction (like users of r/LockdownSkepticism), or a too-little-too-late measure?

Average sentiment of comments with the word "lockdown", 7-day moving average from the last 8 weeks

Changes in perception

The sentiment started from a level below 0: on average, comments were more negative than positive. As lockdowns were introduced in more and more places in March, the average sentiment value grew and stayed positive for whole April. As in recent days the United States is easing its restrictions, users worry it will result in a higher death toll, which makes the average sentiment negative once again.

Open source


GitHub is the leading website for programmers to share their code. Now more than ever international cooperation has been required to tackle the crisis. Publishing code inspires other programmers and saves them work on solving the same problem once again. How fast have programmers reacted? What is Europe's place in the open source community?

Github repositories in time


The pandemic hit different regions in the world in various points in time. The open source community on GitHub has made attempts to explain the crisis and solve problems in a transparent way. We identified 15 countries with the largest current number of coronavirus-related repositories (plus China, where the virus originated) and checked the development of the number of such repositories.

Run (1 second interval)
Run (400 milliseconds interval)

Virus hotspots

At the beginning of the pandemic, most repositories have been created in China. Italy, as the first-hit country in Europe had slightly more repositories created than other countries in Europe early on, but further developments made Germany and the UK overtake Italy.

Users from the United States and India have created the most repositories. American repositories are more forked and watched by other users than any other, and the most popular repository by far – Johns Hopkins University data – is from the United States. The low number of Chinese repositories does not have to be caused by overwork, lack of interest in open source or similar characteristics, but rather deleting existing repositories, possibly forced by the state: one of the most forked repositories, wuhan2020-timeline, has been deleted recently.

Daily number of COVID-19 related repositories created on GitHub


Open source rush is slowing down. What about activity?

In the wake of global pandemic the open source community rose to the challenge. Hundreds projects aiming mostly at mapping and predicting the spread of the virus have been created each day since the pandemic outbreak. However, after an initial exponential growth we start to observe in the recent weeks a slowdown in the number of created repositories. Probably most ideas have already been proposed and the community has moved to a more stable phase of work on existing projects.

Topics in introduction


What are these repositories about? Common themes must exist. Some users just fork an existing repository and adjust it to local conditions, others are inspired to create a similar – but improved – tool.

Number of occurrences of chosen words in GitHub repositories introduction

Web-based tracking solutions

Most repositories are concerned with visualization: tracking coronavirus, creating dashboards. A large number is analyzing and modeling using statistical tools, particularly for prediction. Is this work actually valuable? Epidemiologists have been created such models for decades, and yet another SIR model is unlikely to help. More data is required to assess the efficacy of crowd knowledge.

The most common topic as found by LDA (see below) was tracking coronavirus, particularly in India (which explains a large number of repositories). The second one was dashboards, often using data from Johns Hopkins. Topic 8 are the repositories which may have the largest positive impact, particularly X-ray scans and virus detection.

Programming


There is a multitude of programming languages, with varying popularity and suitable for different applications. Main language of the repository can tell us what was likely to be the goal of the project. The number of forks or stars can identify projects people find most interesting.

Number of repositories with a given main language

Web development and data analysis

Main languages of repositories: JavaScript, HTML, TypeScript, CSS prove that webpages are a large part of development. Data analysis is done in Python or R, with repositiories using these languages ready for production use – Jupyter Notebook uses one of these languages (usually Python) as well, but its purpose is rather demonstrative in data science.

User / link to repository Forks 👀 Country Description
1 CSSEGISandData 11815 21083 United States Novel Coronavirus (COVID-19) Cases, provided by JHU CSSE
2 tokyo-metropolitan-gov 1795 5384 Japan 東京都 新型コロナウイルス感染症対策サイト / Tokyo COVID-19 Task Force website
3 covid19india 1731 2722 India 📊 Source code of the main website
4 pcm-dpc 1643 3230 Italy COVID-19 Italia - Monitoraggio situazione
5 nytimes 1279 4246 United States An ongoing repository of data on coronavirus cases and deaths in the U.S.
6 phildini 1157 458 United States A list of all the companies WFH or events changed because of covid-19
7 2019ncovmemory 1092 7765 ? 2020新冠肺炎记忆:报道、非虚构与个人叙述(持续更新) Memory of 2020 nCoV: Media Coverage, Non-fiction Writings, and Individual Narratives (Continuously updating)
8 someshkar 674 1012 India :microscope: COVID19 India Cluster Network
9 ieee8023 497 1794 ? We are building an open database of COVID-19 cases with chest X-ray or CT images.
10 NovelCOVID 471 1773 ? API for Current cases and more stuff about COVID-19 or the Novel Coronavirus Strain
11 BlankerL 471 1456 Hong Kong SAR 2019新型冠状病毒疫情时间序列数据仓库 | COVID-19/2019-nCoV Infection Time Series Data Warehouse
12 WorldHealthOrganization 418 1666 Switzerland Official World Health Organization COVID-19 App
13 datasets 356 658 ? Novel Coronavirus 2019 time series data on cases
14 BlankerL 329 1560 Hong Kong SAR 2019新型冠状病毒疫情实时爬虫及API | COVID-19/2019-nCoV Realtime Infection Crawler and API
15 Pratitya 324 1873 Taiwan 以 社会学年鉴模式体例规范地统编自2019年末起新冠肺炎疫情进展的时间线。
16 pomber 321 941 Argentina JSON time-series of coronavirus cases (confirmed, deaths and recovered) per country - updated daily
17 k-sys 305 940 ? A collection of work related to COVID-19
18 soroushchehresa 291 1060 Iran 🦠 Useful projects and resources for COVID-19 (2019 novel Coronavirus)
19 neherlab 259 1027 Switzerland Models of COVID-19 outbreak trajectories and hospital demand
20 github 249 865 United States A site that displays up to date COVID-19 stats, powered by fastpages.
21 ExpDev07 233 1277 Norway 🦠 A simple and fast (< 200ms) API for tracking the global coronavirus (COVID-19, SARS-CoV-2) outbreak. It's written in python using the 🔥 FastAPI framework. Supports multiple sources!
22 mhdhejazi 219 1067 ? Coronavirus tracker app for iOS & macOS with maps & charts
23 lindawangg 213 575 ? COVID-Net Open Source Initiative
24 gcreddy42 207 760 ? Internship status of companies - COVID-19
25 mathdroid 194 934 Indonesia COVID-19 global data (from JHU CSSE for now) as-a-service
26 midas-network 188 577 ? 2019 novel coronavirus repository
27 covidatlas 184 333 ? COVID-19 Coronavirus data scraped from government and curated data sources.
28 ImperialCollegeLondon 169 613 United Kingdom Code for modelling estimated deaths and cases for COVID19.
29 CodeForPhilly 145 178 United States COVID-19 Hospital Impact Model for Epidemics
30 MohGovIL 144 442 Israel Israel's Ministry of Health's COVID-19 Exposure Prevention App
31 soumyadip007 140 37 India This repository contains all codes and materials of the current session. It contains the required code on Android and Covid 19 App
32 UCSD-AI4H 139 420 ? COVID-CT-Dataset: A CT Scan Dataset about COVID-19
33 globalcitizen 139 619 China 2019 Wuhan Coronavirus data (COVID-19 / 2019-nCoV)
34 LAB-MI 138 394 ? Service de génération de l'attestation de déplacement dérogatoire à présenter dans le cadre du confinement lié au virus covid-19
35 kaz-ogiwara 132 928 Japan 新型コロナウイルス感染症(COVID-19)の国内における状況を厚生労働省の報道発表資料からビジュアルにまとめた。
36 geohot 132 1105 United States Reverse engineering SARS-CoV-2
37 ahmadawais 131 1401 Canada 🦠 Track the Coronavirus disease (COVID-19) in the command line. Worldwide for all countries, for one country, and the US States. Fast response time (< 100ms).
38 openZH 130 291 Switzerland COVID19 case numbers Cantons of Switzerland and Principality of Liechtenstein (FL) - case numbers include persons tested in the respective area. The data is updated at best once a day (times of collection and update may vary). Start with the README.
39 covid19india 126 65 India A crowd-sourcing platform for the Covid-19 Pandemic
40 JohnSundell 114 177 Poland A two-week effort to help support indie developers shipping apps on Apple's platforms who have been financially impacted by the COVID-19 pandemic.
41 echen102 108 337 United States The repository contains an ongoing collection of tweets IDs associated with the novel coronavirus COVID-19 (SARS-CoV-2), which commenced on January 28, 2020.
42 owid 105 265 ? Data on COVID-19 confirmed cases, deaths, and tests • All countries • Updated daily by Our World in Data
43 Call-for-Code 105 33 ? Materials for the Call for Code 2020 solution starter kit for crisis communication in the context of COVID-19.
44 AaronWard 101 396 Ireland Covidify - corona virus report and dataset generator for python 📈
45 opencovid19-fr 96 222 France Consolidation des données de sources officielles concernant l'épidémie de COVID19
46 lispczz 95 335 China 中国新型冠状病毒肺炎地级市疫情图
47 dsfsi 91 123 South Africa COVID 19 Data and Dashboard for South Africa
48 COVID-19-electronic-health-system 90 201 ? An easy-to-use PWA to monitor the user's wellness and learn about COVID-19.
49 OssamaRafique 89 221 Pakistan 🦠Corona Virus / Covid 19 Tracker Dashboard With Awesome UI + PWA + NodeJS Scraper
50 heremaps 88 168 Netherlands Using HERE Technologies APIs, fork and build your own COVID-19 Tracker. For a live version, see the website.

Scientific articles


In this part, a diverse set of sources has been used. Social science articles from SSRN have been analysed to find the challenges the society faces, and the dataset from Kaggle has been used to show value of previous scientific research and the potential of European cooperation.

Social science top words


Economic and social challenges

In dataset containing words from SSRN, a diverse set of problems can be identified, ranging from health-related (pneumonia, infectious, epidemiology) to more common for social sciences: recession, policy or GDP. Social sciences deliver a broader picture than news articles, which – even if focusing on social challenges – write rather about particular and immediate problems, such as small business closures or gig workers' plight.

Top countries and potential of cooperation


Research by country

Most papers did not have affiliations with countries available. In those which did, predictably USA and China lead the scientific output. Alone, no European country is even remotely close to either of these two scientific superpowers. However, European Union's scientific output as a whole in the area of coronavirus is slightly greater than output of the United States.


Project

NGI Forward has received funding from the European Union's Horizon 2020 research and innovation programme under the Grant Agreement no 825652. The content of this website does not represent the opinion of the European Union, and the European Union is not responsible for any use that might be made of such content.

Team

DELab UW is a transdisciplinary research institute established in 2014 within the University of Warsaw with the support of Google. Our lab serves as a platform for cooperation and the exchange of ideas between academia, business and public institutions.

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