News about the coronavirus significantly increased in Sweden in March and April 2020, reaching a share of nearly ** percent of the total media reports. Afterwards, the share steadily declined and in September, ********* of news in Swedish media was coronavirus-related.

The first case of the coronavirus in Sweden was registered on February 4, 2020. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

The number of media reports about the coronavirus significantly increased in Sweden in the period from week ten to week ** of 2020, amounting to roughly **** thousand reports. During Easter holidays, the media reported generally less about COVID-19. In week ** of 2020, Swedish printed, online, and broadcasted media released about ** thousand articles related to the virus.

The first case of the coronavirus in Swden was registered on February 4, 2020. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Fact and Figures page.

This dataset contains news articles from Swedish news sites during the covid-19 corona pandemic 2020–2021. The purpose was to develop and test new methods for collection and analyses of large news corpora by computational means. In total, there are 677,151 articles collected from 19 news sites during 2020-01-01 to 2021-04-26. The articles were collected by scraping all links on the homepages and main sections of each site every two hours, day and night.

The dataset also includes about 45 million timestamps at which the articles were present on the front pages (homepages and main sections of each news site, such as domestic news, sports, editorials, etc.). This allows for detailed analysis of what articles any reader likely was exposed to when visiting a news site. The time resolution is (as stated previously) two hours, meaning that you can detect changes in which articles were on the front pages every two hours.

The 19 news sites are aftonbladet.se, arbetet.se, da.se, di.se, dn.se, etc.se, expressen.se, feministisktperspektiv.se, friatider.se, gp.se, nyatider.se, nyheteridag.se, samnytt.se, samtiden.nu, svd.se, sverigesradio.se, svt.se, sydsvenskan.se and vlt.se.

Due to copyright, the full text is not available but instead transformed into a document-term matrix (in long format) which contains the frequency of all words for each article (in total, 80 million words). Each article also includes extensive metadata that was extracted from the articles themselves (URL, document title, article heading, author, publish date, edit date, language, section, tags, category) and metadata that was inferred by simple heuristic algorithms (page type, article genre, paywall).

The dataset consists of the following: article_metadata.csv (53 MB): The file contains information about each news article, one article per row. In total, there are 677,151 observations and 17 variables.

article_text.csv (236 MB): The file contains the id of each news article and how many times (count) a specific word occurs in the news article. The file contains 80,090,784 observations and 3 variables in long format.

frontpage_timestamps.csv (175 MB): The file contains when each news article was found on the front page (homepage and main sections) of the news sites. The file contains 45,337,740 observations and 4 variables in long format.

More information about the content in the files is found in the README-file. In it you will also find the R-script for using the data.

The reach of TV news broadcasts after the coronavirus outbreak increased significantly in Sweden compared to the previous year. Among the 15 to 49 year olds, week ten of 2020 saw a 25 percent increase in the reach of television news broadcasts, while week 11 and 12 saw a growth of even 63 percent and 80 percent respectively.

During the coronavirus outbreak, national news on radio and television were the used news media in Sweden. According to a survey conducted from April to June 2020, ** percent of respondents consumed those broadcast news at least ***** days a week. By comparison, in the fourth quarter of 2019, the share amounted to ** percent. The media with the highest increase within this period were the broadcasters' website svt.se, sr.se, and tv4.se, at ** percent. Contrastingly, social media recorded the largest decline, at *** percent.

sv-covid-19 is a collection of Swedish news texts, scientific and popular science articles and articles from certain blogs and social media wuch as Flashback and Twitter, which started to be published at the beginning of the coronavirus pandemic (early 2020). The latest verision of the corpus consists of approximately eight million words and 9000 articles. The corpus contains various text types and texts with different stylistic levels. The texts have been marked up with word class tags, morphological analysis and lemma, as well as some structural and functional information, such as author names.

When following the coronavirus news in the third quarter of 2020, Swedes of older ages seemed to prefer TV-channels. ** percent of respondents aged 76 years or older stuck to this information channel, whereas ** percent of respondents aged between 16 and 19 years preferred digital newspapers.

This proposal relates to the call of the PSA PSA COVID-19 Rapid Project 001 data collection effort in Sweden. The COVID-19 pandemic presents a critical need to identify best practices for communicating health information to the global public. It also provides an opportunity to test theories about risk communication. As part of a larger Psychological Science Accelerator COVID-19 Rapid Project, a global consortium of researchers will experimentally test competing hypotheses regarding the effects of framing messages in terms of losses versus gains. We will examine effects on three primary outcomes: intentions to adhere to policies designed to prevent the spread of COVID-19, opinions about such policies, and the likelihood that participants seek additional policy information. Whereas research on negativity bias and loss aversion predicts that loss-framing will have greater impact, research on encouraging the adoption of protective health behaviour suggests the opposite (i.e., gain-framing will be more persuasive). We will also assess effects on experienced anxiety. Given the potentially low cost and the scalable nature of framing interventions, results could be valuable to health organizations, policymakers, and news sources globally.

Due to the coronavirus pandemic, four media houses in Sweden stated in a survey to expect a decrease of 41 to 50 percent of their newspaper advertising revenue in April 2020 compared to the same period last year. The same number of media houses expected a similar decrease in advertisement income for the whole year 2020. Two publishers expected a decrease in ad revenue of 21 to 30 percent for April 2020, while just one company expected a decline of 61 to 70 percent for the year 2020.

COVID-19 first phase, Danish-Swedish newspaper data set.

Swedes had the highest confidence in content provided by the public broadcaster Sveriges Television (SVT) during the coronavirus (COVID-19) outbreak. This was the result of a survey conducted from April to June 2020. ** percent of the respondents had high or fairly high trust in SVT, which was growth of ***** percent compared to the fourth quarter of 2019. While the confidence in further broadcasters, such as Sveriges Radio and TV4, increased, trust in newspapers declined from 2019 to 2020.

DISCLAIMER

Dataset consists of historical data of pre-pandemic period and doesn’t represent the current reality which may have changed due to the spikes in demand. This dataset has been generated in collaboration of efforts within CoronaWhy community.

Context

Last updated: April 26th 2020 Updates: April 14th 2020 - Added missing population data April 15th 2020 - Added Brazil statewise ICU hospital beds dataset April 21th 2020 - Added Italy, Spain statewise ICU hospital beds dataset, India statewise TOTAL hospital beds dataset April 26th 2020 - Added Sweden ICU(2019) and TOTAL(2018) beds datasets

Purpose of the dataset

I am trying to produce a dataset that will provide a foundation for policymakers to understand the realistic capacity of healthcare providers being able to deal with the spikes in demand for intensive care. As a way to help, I’ve prepared a dataset of beds across countries and states. Work in progress dataset that should and will be updated as more data becomes available and public on weekly basis.

Importance

This dataset is intended to be used as a baseline for understanding the typical bed capacity and coverage globally. This information is critical for understanding the impact of a high utilization event, like COVID-19.

Current challenges

Datasets are scattered across the web and are very hard to normalize, I did my best but help would be much appreciated.

Data sources / Acknowledgments

arcgis (USA) - https://services1.arcgis.com/Hp6G80Pky0om7QvQ/arcgis/rest/services/Hospitals_1/FeatureServer/0 KHN (USA) - https://khn.org/news/as-coronavirus-spreads-widely-millions-of-older-americans-live-in-counties-with-no-icu-beds/ datahub.io (World) - https://datahub.io/world-bank/sh.med.beds.zs eurostat - https://data.europa.eu/euodp/en/data/dataset/vswUL3c6yKoyahrvIRyew OECD - https://data.oecd.org/healtheqt/hospital-beds.htm WDI (World) - https://data.worldbank.org/indicator/SH.MED.BEDS.ZS NHP(India) - http://www.cbhidghs.nic.in/showfile.php?lid=1147 data.gov.sg (Singapore) - https://data.gov.sg/dataset/health-facilities?view_id=91b4feed-dcb9-4720-8cb0-ac2f04b7efd0&resource_id=dee5ccce-4dfb-467f-bcb4-dc025b56b977 dati.salute.gov.it (Italy)- http://www.dati.salute.gov.it/dati/dettaglioDataset.jsp?menu=dati&idPag=96 portal.icuregswe.org (Sweden) - https://portal.icuregswe.org/seiva/en/Rapport publications: Intensive Care Medicine Journal (Europe) - https://link.springer.com/article/10.1007/s00134-012-2627-8 Critical Care Medicine Journal (Asia) - https://www.researchgate.net/figure/Number-of-critical-care-beds-per-100-000-population_fig1_338520008 Medicina Intensiva (Spain) - https://www.medintensiva.org/en-pdf-S2173572713000878 news: https://lanuovaferrara.gelocal.it/italia-mondo/cronaca/2020/03/19/news/dietro-la-corsa-a-nuovi-posti-in-terapia-intensiva-gli-errori-del-passato-1.38611596 kaggle: germany - https://www.kaggle.com/manuelblechschmidt/icu-beds-in-germany brazil (IBGE) - https://www.kaggle.com/thiagobodruk/brazilianstates Manual population data search from wiki

Data columns

country,state,county,lat,lng,type,measure,beds,population,year,source,source_url - country - country of origin, if present - state - more granular location, if present - lat - latitude - lng - longtitude - type - [TOTAL, ICU, ACUTE(some data could include ICU beds too), PSYCHIATRIC, OTHER(merged ‘SPECIAL’, ‘CHRONIC DISEASE’, ‘CHILDREN’, ‘LONG TERM CARE’, ‘REHABILITATION’, ‘WOMEN’, ‘MILITARY’] - measure - type of measure (per 1000 inhabitants) - beds - number of beds per 1000 - population - population of location based on multiple sources and wikipedia - year - source year for beds and population data - source - source of data - source_url - URL of the original source

Files

for each of datasource: hospital_beds_per_source.csv

US only: US arcgis + khn (state/county granularity): hospital_beds_USA.csv

Global (state(region)/county granularity): hospital_beds_global_regional.csv

Global (country granularity): hospital_beds_global_v1.csv

Contributors

Igor Kiulian - extracting/normalizing/formatting/merging data Artur Kiulian - helped with Kaggle setup Augaly S. Kiedi - helped with country population data Kristoffer Jan Zieba - found Swedish data sources

Possible Improvements

Find and megre more detailed (state/county wise) or newer datasource

After the coronavirus outbreak in Europe, the reach of TV sports channels significantly declined in Sweden due to sports events cancellations and postponements. While ****** people watched broadcasts on the TV station Eurosport at the end of *************, the number of daily viewers of this channel amounted to only ****** two months later. A similar development can be observed for the Swedish TV channel Sportkanalen, which recorded a drop of about ****** daily viewers during the same period. In May, the number of daily viewers of the TV sports stations slightly grew again or remained stable. From ****** on, more and more people were watching sports TV stations in Sweden again and in the second half of the year, the viewership of Eurosport, Eurosport 2 Sweden, and Sportkanalen were even on the same level as before the outbreak.

What did Swedes watch instead? In contrast to the development of the sports channels’ viewership, the reach of television news broadcasts in Sweden considerably increased after the coronavirus outbreak. In total, the first week of ********** saw a ** percent growth in the reach of TV news programs compared to the same period of the previous year. And in mid-March, over half of the population watched TV news more often than a year ago. Among people aged 15 to 49 years, the reach even increased by ** percent.

Cancellation of sporting events worldwide The coronavirus pandemic had a main impact on major sporting events. Amongst others, the Tokyo 2020 Summer Olympic and Paralympic Games were postponed to 2021. The estimated economical loss of the postponement amounted to over *** billion Japanese yen. Additionally, European football leagues suspended their seasons. Broadcasting companies, in particular, have lost a lot of their potential income. To give an example, in **********, they estimated their revenue loss to approximately *** million euros due to postponements or cancellations of the English Premier League’s matches.

TikTok saw an unprecedented increase in popularity during the coronavirus (COVID-19) outbreak in the Nordic region. The largest increase, of up to *** percent was observed among Danish youth. While *** percent of them used TikTik before the COVID-19 outbreak, the corresponding share during the pandemic was ** percent. Overall, TikTok became more popular in Denmark, Sweden, Norway and Finland during the pandemic, regardless of the users’ age.

The rise of TikTok   

TikTok is a Chinese video-sharing social network, initially released in 2018, as Musical.ly. Over the period from 2017 to 2020, the app generated increasingly larger engagement rates, reaching nearly ** million daily active users via iOS as of May 2020 on a global scale. Among the most followed accounts in Norway were the pop duo Marcus & Martinus.

COVID-19 on social media   

As of March 2020, almost all the most popular hashtags on social media in Sweden were related to the coronavirus. In fact, a recent survey showed that especially younger individuals worldwide seemed to rely on social media for updates on the coronavirus that same month . In contrast, the figures were much lower for people aged 55 or older. Nevertheless, social media use generally increased during the pandemic and facilitated the spread of news regarding the coronavirus. In some cases, even false information.