COVID-19 open source data sets: a comprehensive survey

Abstract

In December 2019, a novel virus named COVID-19 emerged in the city of Wuhan, China. In early 2020, the COVID-19 virus spread in all continents of the world except Antarctica, causing widespread infections and deaths due to its contagious characteristics and no medically proven treatment. The COVID-19 pandemic has been termed as the most consequential global crisis since the World Wars. The first line of defense against the COVID-19 spread are the non-pharmaceutical measures like social distancing and personal hygiene. The great pandemic affecting billions of lives economically and socially has motivated the scientific community to come up with solutions based on computer-aided digital technologies for diagnosis, prevention, and estimation of COVID-19. Some of these efforts focus on statistical and Artificial Intelligencebased analysis of the available data concerning COVID-19. All of these scientific efforts necessitate that the data brought to service for the analysis should be open source to promote the extension, validation, and collaboration of the work in the fight against the global pandemic. Our survey is motivated by the open source efforts that can be mainly categorized as (a) COVID-19 diagnosis from CT scans, X-ray images, and cough sounds, (b) COVID-19 case reporting, transmission estimation, and prognosis from epidemiological, demographic, and mobility data, (c) COVID-19 emotional and sentiment analysis from social media, and (d) knowledge-based discovery and semantic analysis from the collection of scholarly articles covering COVID-19. We survey and compare research works in these directions that are accompanied by open source data and code. Future research directions for data-driven COVID-19 research are also debated. We hope that the article will provide the scientific community with an initiative to start open source extensible and transparent research in the collective fight against the COVID-19 pandemic.

Public Covid-19 X-ray datasets and their impact on model bias - a systematic review of a significant problem

“…Additionally four compilation website were examined 2 3 4 . Finally, review papers on the topic (Shuja et al (2020); Ilyas et al (2020); Islam et al (2020); Shoeibi et al (2020); Wynants et al (2020); Pham et al (2020); Roberts et al (2021); Garcia Santa Cruz et al (2020)) were screened for dataset candidates. For the indirect search, PubMed and preprint services (medRxiv, bioRxiv and arXiv) were queried with the search terms “COVID-19” & “X-ray” & “dataset”.…”

“…The utility is determined by the structure and amount of information, for example, only those datasets including information about patient survival can be used for training prognosis models of risk of death. Thus this paper provides a more in depth description of datasets than previous works (Shuja et al (2020); Sohan (2020); Shoeibi et al (2020); Islam et al (2020); Ilyas et al (2020)), that have focused on surveying papers describing methods, and on identifying the datasets used to train these methods, without assessing the datasets quality or utility.…”

Overview of current state of research on the application of artificial intelligence techniques for COVID-19

“…CHIME is a COVID-19 Hospital Impact Model for Epidemics based SIR modeling that utilizes the number of infected, recovered, and fatality persons to predict the infection caused by coronavirus and the requirement of hospital beds. Table S8 depicts the downloadable links and description of datasets (Shuja et al, 2021).…”

Implementing Public Health Strategies—The Need for Educational Initiatives: A Systematic Review

“…Contact tracing represents one strategy, which slows down the spread of the viral infection and enables the identification of infected cases or those at risk, either by listing all people with whom an infected person has recently been in contact, or by using location-tracking mobile applications (apps) [7][8][9][10][11][13][14][15][16]. There has been an intensive development of contact tracing applications (CTA), using various means of technology, including QR (Quick Response) codes; GPS (Global Positioning System); credit card transmission log; CCTV (Closed Circuit Television); different COVID alert apps; and Bluetooth [1, [10][11][12][13][14][15][16][17][18][19][20]. However, the inadequate level of public compliance with these public health strategies has resulted in mandatory contact tracing strategies as part of a government strategy in some countries [8,17,21].…”