Find research datasets worth reusing

opencc-by-4.0Nov 2020View details →

Linked Data representation of COVID-19 data for Italy

This repository includes a Linked Data representation of the <a href="https://github.com/pcm-dpc/COVID-19">covid19-ita dataset</a> provided by the Department of Civil Protection in Italy, following the <a href="https://www.w3.org/TR/vocab-data-cube/">RDF Data Cube Vocabulary</a> and the <a href="http://w3id.org/kpionto">KPIOnto</a> ontology. The dataset includes measurements of various indicators related to COVID19 spread at the province, regional, and country levels, on a daily basis from February 24th to November 20th, 2020. The RDF format allows describing statistical multidimensional data as Linked Data on the Web. As such, each data point is represented as an observation of the relevant measures along two dimensions, namely time and geographical area. The project is also available on <a href="https://github.com/KDMG/covid19">Github</a>.

opencc-zeroNov 2020View details →

Longitudinal proteomic profiling of high-risk patients with COVID-19 reveals markers of severity and predictors of fatal disease

End-stage kidney disease (ESKD) patients are at high risk of severe COVID-19. We performed dense serial blood sampling in hospitalised and non-hospitalised ESKD patients with COVID-19 (n=256 samples from 55 patients) and used Olink immunoassays to measure 436 circulating proteins. Comparison to 51 non-infected ESKD patients revealed 221 proteins differentially expressed in COVID-19, of which 69.7% replicated in an independent cohort of 46 COVID-19 patients. 203 proteins were associated with clinical severity scores, including IL6, markers of monocyte recruitment (e.g. CCL2, CCL7), neutrophil activation (e.g proteinase-3) and epithelial injury (e.g. KRT19). Random Forests machine learning identified predictors of current or future severity such as KRT19, PARP1, PADI2, CCL7, and IL1RL1 (ST2). Survival analysis with joint models revealed 69 predictors of death including IL22RA1, CCL28, and the neutrophil-derived chemotaxin AZU1 (Azurocidin). Finally, longitudinal modelling with linear mixed models uncovered 32 proteins that display different temporal profiles in severe versus non-severe disease, including integrins and adhesion molecules. Our findings point to aberrant innate immune activation and leucocyte-endothelial interactions as central to the pathology of severe COVID-19. The data from this unique cohort of high-risk individuals provide a valuable resource for identifying drug targets in COVID-19.

opencc-zeroDec 2020View details →

COVID-CDR: An integrative resource for network-based investigation of COVID-19 combinatorial drug repositioning and mechanism of action

Repurposing of the existing medications has become the mainstream focus of anti-COVID-19 drug discovery as it offers rapid and cost-effective solutions for therapeutic development. However, a great effort is still required to enhance the efficacy of repurposing therapeutic options through combination therapy, in which promising drugs with varying mechanisms of action are administered together. Nonetheless, our ability to identify and validate effective combinations is limited due to the vast number of possible drug pairs. Yet, there is no available resource that can systematically guide to identify or choose the effective individual drugs or best possible synergistic drug combinations for the treatment of SARS-CoV-2 infection. To address this resource gap, we developed a web-based platform that displays the network-based mechanism of action of drug combinations, thus simultaneously providing a visual of the cellular interactome involved in modes of action of the chosen drugs. The platform allows the freedom to select two or more drug combinations and provides the options to investigate the network-based efficacy of drug combinations and understand the similarity score, primary indications, and pairwise synergistic scores on different cell-lines. In a nutshell, the platform (accessible via <a href="http://vafaeelab.com/COVID19_repositioning.html">http://vafaeelab.com/COVID19_repositioning.html</a>) is the first of its type, which provides a systematic approach for pre-clinical investigation of combination therapy for treating COVID-19 at the fingertips of the clinicians or researchers.

Measures of Freight Network Resiliency During the Covid-19 Pandemic

Recent headlines depict significant shifts in operations within the freight community in particular, e.g., HOS laws suspended at a national level for the first time in 82 years1; national carriers shifting operations completely to grocery supply chains2; fleet operators laying off employees in response to manufacturing closures3.  As a result of the current COVID-19 pandemic, there is a great need to capture freight movement data (not otherwise collected) to measure the effects of the COVID-19 response and recovery practices on freight network resiliency.  In this project, we consider an expanded definition of the freight network, beyond roads and warehouses, to include truck drivers and driver support systems.   Driver support systems include physical infrastructure like public and private rest stops as well as operational protections like Hours of Service (HOS). COVID-19 responses by public agencies and private citizens have affected drivers and driver support systems by three mechanisms. First, increased demand for medical supplies, food and packaged goods creates a need for more trucks and drivers, and the increased need for quick shipments promotes an environment in which speeding and unsafe driving practices may prevail.  Second, with HOS restrictions lifted by the National Highway Transportation Safety Administration (NHTSA) driver fatigue may occur at greater frequency leading to unsafe driving conditions and higher likelihood of accidents.  Third, the effects of social distancing mandates can lead to closures of critical, but oft forgotten, freight infrastructure like rest areas and truck stops, leaving drivers without necessary rest opportunities. While any single mechanism has detrimental effects on driver health and safety, the economy, and national recovery efforts, when combined, the system can be pushed to failure. Pandemic responses have only exacerbated critical industry issues like driver shortages, lack of available parking, and HOS compliance issues stemming from electronic logbooks.   The purpose of this work was to develop and implement a driver health and safety survey during the pandemic.

opencc-by-4.0Aug 2020View details →

A dataset of media releases (Twitter, News and Comments, Youtube, Facebook) form Poland related to COVID-19 for open research

Social behavior has a fundamental impact on the dynamics of infectious diseases (such as COVID-19), challenging public health mitigation strategies and possibly the political consensus. The widespread use of the traditional and social media on the Internet provides us with an invaluable source of information on societal dynamics during pandemics. With this dataset, we aim to understand mechanisms of COVID-19 epidemic-related social behavior in Poland deploying methods of computational social science and digital epidemiology. We have collected and analyzed COVID-19 perception on the Polish language Internet during 15.01-31.07(06.08) and labeled data quantitatively (Twitter, Youtube, Articles) and qualitatively (Facebook, Articles and Comments of Article) in the Internet by infomediological approach. - manually labelled1,449 articles / Facebook posts from Lower Silesia (facebook_articles_lower_silesia.zip) and 111 texts from outside this region; -manually labelled 1000 most popular tweets (twits_annotated.xlsx) with cathegories is_fake (categorical and numeric) topic and sentiment;  -extracted 57,306 representative articles (articles_till_06_08.zip) in Polish using Eventregitry.org tool in language Polish and topic "Coronavirus" in article body; - extracted 1,015,199 (tweets_till_31_07_users.zip and tweets_till_31_07_text.zip) and Tweets from #Koronawirus in language Polish using Twitter API. - collected 1,574 videos (youtube_comments_till_31_07.zip and youtube_movie.csv) with keyword: Koronawirus on YouTube and 247,575 comments on them using Google API; - We supplemented the media observations with an analysis of 244 social empirical studies till 25.05 on COVID-19 in Poland (empirical_social_studies.csv). Reports and analyzes and coding books can be found in Polish at: <a href="http://www.infodemia-koronawirusa.pl/percepcja-koronowirusa-na-dolnym-slasku/">http://www.infodemia-koronawirusa.pl</a> Main report (in Polish) https://depot.ceon.pl/handle/123456789/19215

opencc-zeroDec 2020View details →

The influence of the global COVID-19 pandemic on manuscript submissions and editor and reviewer performance at six ecology journals

Government policies attempting to slow the spread of COVID-19 have reduced access to research laboratories and shifted many scholars to working from home. These disruptions will likely influence submissions to scholarly journals, and affect the time available for editors and reviewers to participate in peer review. In this editorial we examine how journal submissions, and editorial and peer review processes, have been influenced by the pandemic at six journals published by the British Ecological Society (BES). We find no evidence of a change in the geographic pattern of submissions from across the globe. We also find no evidence that submission of manuscripts by women has been more affected by pandemic disruptions than have submissions by men – the proportion of papers authored by women during the COVID period of 2020 has not changed relative to the same period in 2019. Editors handled papers just as quickly, and reviewers have agreed to review just as often, during the pandemic compared to pre-pandemic. The one notable change in peer review during the pandemic is that reviewers replied more quickly to emails inviting them to review (albeit only 4% sooner), and those that agreed to review returned their reviews more quickly (17% sooner), during the pandemic. We thus find no evidence at these six ecology journals that submissions and peer review processes have been negatively impacted by the pandemic. Also, contrary to analyses in other disciplines, we do not find evidence that there have been disproportionate impacts of the pandemic on female authors and reviewers.

EDTECH AND COVID-19 10 THINGS TO KNOW

Covid-19 has reshaped our world. In education, mass school closures have accelerated the global use of education technologies – EdTech. Yet the benefits do not reach everyone. Since the start of the pandemic, the EdTech Hub and its partners have been researching and applying evidence on what works in technology for education in different contexts. Here are 10 important lessons from that work.

Coping with Fibromyalgia during the COVID-19 pandemic: adjustment and wellbeing

Abstract Objective: Individuals with pre-existing health conditions may be experiencing particular distress under Covid-19 pandemic-related lifestyle restrictions. Fibromyalgia syndrome (FMS) is a chronic condition where symptoms are known to be exacerbated by stress. The present study examined wellbeing, perceived symptom change and coping in individuals with and without FMS during pandemic-related social lockdown in the UK. Design: Participants with a diagnosis of FMS (N = 390) and a general public sample with no FMS (N = 151) completed questionnaires at three time points. Main Outcome Measures: BBC Wellbeing Scale, Cognitive-Emotional Regulation Questionnaire measure of coping, perception of extent to which symptoms have worsened or improved over time. Results: Contrary to expectations, FMS participants reported improved symptoms and wellbeing over the study period. Non-FMS participants experienced worsening health symptoms and no change in wellbeing. Coping strategies involving positive reappraisal, refocussing and planning were positively associated with wellbeing in the FMS group, Conclusion: The unpredictable symptom profile in FMS, and the regular readjustment to coping this necessitates, may support a form of resilience which has been adaptive during the pandemic. The results have implications for supporting people with FMS, and potentially other chronic conditions, especially at times of stress.

Dataset for article: Changes in evidence for studies assessing interventions for COVID-19 reported in preprints: meta-research study. BMC Med 18, 402 (2020).

This dataset was used in the analyses reported in Oikonomidi, T., Boutron, I., Pierre, O. et al. Changes in evidence for studies assessing interventions for COVID-19 reported in preprints: meta-research study. BMC Med 18, 402 (2020). https://doi.org/10.1186/s12916-020-01880-8.  This project is ancillary to the COVID-NMA Living systematic review and network meta-analysis of Covid-19 trials: https://covid-nma.com/ The first spreadsheet entitled "key" includes the full description of the dataset.

opencc-by-4.0Oct 2020View details →

Dataset: COVID-19 implications on maritime trade flows

This dataset can be used to reproduce the results as described in Verschuur et al. (2020), "The implications of large-scale containments policies on global maritime trade during the COVID-19 pandemic", under review.    The dataset includes the port-level estimated maritime trade flows (imports and exports) on a daily time scale from January 2019 till August 2020. The data is disaggregated into a 22 sector classification system, which can be aggregated to a 11 sector classification system given the conversion table included. Moreover, the data can be easily aggregated to a country-level using the iso3 code provided.

opencc-by-4.0Jan 2021View details →

Sensitive mass spectrometric determination of kinin-kallikrein system peptides in light of COVID-19

This dataset provides information on the obtained MS/MS data generated during the conducted validation runs.   Abstract of the corresponding paper: The outbreak of COVID-19 has raised interest in the kinin–kallikrein system, as symptoms were postulated to be in connection. Viral blockade of the angiotensin-converting-enzyme 2 impedes degradation of the active kinin des-Arg(9)-bradykinin, which thus increasingly activates bradykinin receptors known to promote inflammation, cough, and edema – symptoms that are commonly observed in COVID-19. However, lean and reliable investigation of the postulated alterations is currently hindered by non-specific peptide adsorption, lacking sensitivity, and cross-reactivity of applicable assays. Here, an LC-MS/MS method was established to determine the following kinins in respiratory lavage fluids: kallidin, bradykinin, des-Arg(10)-kallidin, des-Arg(9)-bradykinin, bradykinin 1-7, bradykinin 2-9 and bradykinin 1-5. This method was fully validated according to regulatory bioanalytical guidelines of the European Medicine Agency and the US Food and Drug Administration and has a broad calibration curve range (up to a factor of 103), encompassing low quantification limits of 4.4–22.8 pg/mL (depending on the individual kinin). The application of the developed LC-MS/MS method to nasal lavage fluid allowed for the rapid (~2 hours), comprehensive and low-volume (100 µL) determination of kinins for the first time. Hence, this novel assay may support current efforts to investigate the pathophysiology of COVID-19, but can also be extended to other diseases.

Data belonging to Record high solar irradiance in Western Europe during first COVID-19 lockdown largely due to unusual weather,

This data belongs to the paper Record high solar irradiance in Western Europe during first COVID-19 lockdown largely due to unusual weather, (soon to be) published in Communications Earth & Environment.

opencc-by-4.0Jan 2021View details →

Data for publication "COVID-19 lockdowns highlight a risk of increasing ozone pollution in European urban areas"

Data to accompany the "COVID-19 lockdowns highlight a risk of increasing ozone pollution in European urban areas" paper published in Atmospheric Chemistry and Physics. This repository contains metadata for the ambient air quality and surface meteorological sites used for the analysis. The observations have not been included due to licencing issues, but can be shared by reasonable request to the author.  All files are .csv files, with UTF-8 encoding, and are self describing.

opencc-by-4.0Jan 2021View details →

The growth of COVID-19 scientific literature: A forecast analysis of different daily time series in specific settings

Submitted to The ISSI 2021 Conference. The conference is organised by KU Leuven in close collaboration with the university of Antwerp under the auspices of ISSI – the International Society for Informetrics and Scientometrics (<a href="http://www.issi-society.org/">http://www.issi-society.org/</a>).  We present a forecasting analysis on the growth of scientific literature related to COVID-19 expected for 2021. Considering the paramount scientific and financial efforts made by the research community to find solutions to end the COVID-19 pandemic, an unprecedented volume of scientific outputs is being produced. This questions the capacity of scientists, politicians and citizens to maintain infrastructure, digest content and take scientifically informed decisions. A crucial aspect is to make predictions to prepare for such a large corpus of scientific literature. Here we base our predictions on the ARIMA model and use two different data sources: the Dimensions and World Health Organization COVID-19 databases. These two sources have the particularity of including in the metadata information on the date in which papers were indexed.  We present global predictions, plus predictions in three specific settings: by type of access (Open Access), by NLM source (PubMed and PMC), and by domain-specific repository (SSRN and MedRxiv). We conclude by discussing our findings.

opencc-zeroMay 2020View details →

Neurologic manifestations in an infant with COVID-19

Currently, there are over 1.9 million confirmed cases of Coronavirus disease 2019 (COVID-19) globally with over 590,000 cases in the United States.1 The number of COVID-19 positive children in the United States is unknown. A report summarizing 72,314 COVID-19 cases from the Chinese Center for Disease Control and Prevention noted 416 COVID-19 positive children under 10.2 An observational study at Wuhan Children's Hospital noted 31 COVID-19 positive children under 1 year with the youngest confirmed case in a 1 day old.3 Cases were largely characterized by upper respiratory tract infection or pneumonia, fever, cough and pharyngeal erythema.3 Concomitant neurologic problems have been reported amongst COVID-19 positive adult patients.

opencc-by-4.0Nov 2020View details →

Google Trends normalized hits for COVID-19 generated in Switzerland

This dataset contains the normalized hits of the queries on COVID-19 generated in Switzerland between July 2019 and July 2020, the timeline of the normalized hits per Canton, the top associated queries, the frequency analysis of the top associated queries, the categorization of the top associated queries, and the rising queries.  Query: Coronavirus + covid + 2019-nCoV + SARS-CoV2 Query type: keyword Timeframe: 01/01/2020 - 11/06/2021 Date of search: 22/06/2021 Data source: Web searches Location:CH (by canton) Query category:all Rationale for keywords: main semi-synonims for covid-19 This dataset has been generated by and used for the <a href="https://www.ibme.uzh.ch/en/Biomedical-Ethics/Research/Ongoing-Research/Public-Health-Ethics/PubliCo.html">PubliCo research project</a>.

opencc-zeroJun 2021View details →

Scheduling Mechanisms to Control Spread of Covid-19 (Simulation Results)

We study scheduling mechanisms that explore the trade-off between containing the spread of COVID-19 and performing in-person activity in organizations. Our mechanisms, referred to as group scheduling, are based on partitioning the population randomly into groups and scheduling each group on appropriate days with possible gaps (when no one is working and all are quarantined). Each group interacts with no other group and, importantly, any person who is symptomatic in a group is quarantined. We show that our mechanisms effectively trade-off in-person activity for more effective control of the COVID-19 virus spread. In particular, we show that a mechanism which partitions the population into two groups that alternatively work in-person for five days each, flatlines the number of COVID-19 cases quite effectively, while still maintaining in-person activity at 70% of pre-COVID-19 level. Other mechanisms that partitions into two groups with less continuous work days or more spacing or three groups achieve even more aggressive control of the virus at the cost of a somewhat lower in-person activity (about 50%). We demonstrate the efficacy of our mechanisms by theoretical analysis and extensive experimental simulations on various epidemiological models based on real-world data.

opencc-by-4.0Nov 2024View details →

LOCKED: A dataset of sociodemographic, economic, living, and health features to measure the impact of the Spanish lockdown during COVID-19 on mental health conditions

A dataset aimed at enhancing the understanding of the mental health effects of the COVID-19 lockdown in Spain. This dataset serves as a valuable resource by integrating psychological assessments, such as the SA-45 pyschological test, with comprehensive socioeconomic, living, and health-related information. By combining these diverse data points, the dataset enables researchers to analyze how various invidual factors influenced nine mental health conditions during the lockdown, providing a robust foundation for further studies on this critical topic.

opencc-by-4.0Oct 2023View details →

Manifestation of Health Denialism in Attitudes Toward COVID-19 Vaccination: A Qualitative Study

The transcripts of the in-depth interviews used for the qualitative analysis of the manifestations of denializm in attitudes toward COVID-19 preventive measures and other opinions about the pandemic.