Find research datasets worth reusing

opencc-by-4.0Sep 2024View details →

Effects of continuous management on anxiety and depression after pacemaker implantation in the COVID-19 era:a randomised trial

Open the record for dataset details and reuse information.

opencc-by-4.0Dec 2023View details →

Five Years of COVID-19 Discourse on Instagram: A Labeled Instagram Dataset of Over Half a Million Posts for Multilingual Sentiment Analysis

Please cite the following paper when using this dataset: N. Thakur, “Five Years of COVID-19 Discourse on Instagram: A Labeled Instagram Dataset of Over Half a Million Posts for Multilingual Sentiment Analysis”, Proceedings of the 7th International Conference on Machine Learning and Natural Language Processing (MLNLP 2024), Chengdu, China, October 18-20, 2024 (Paper accepted for publication, Preprint available at: https://arxiv.org/abs/2410.03293)   Abstract The outbreak of COVID-19 served as a catalyst for content creation and dissemination on social media platforms, as such platforms serve as virtual communities where people can connect and communicate with one another seamlessly. While there have been several works related to the mining and analysis of COVID-19-related posts on social media platforms such as Twitter (or X), YouTube, Facebook, and TikTok, there is still limited research that focuses on the public discourse on Instagram in this context. Furthermore, the prior works in this field have only focused on the development and analysis of datasets of Instagram posts published during the first few months of the outbreak. The work presented in this paper aims to address this research gap and presents a novel multilingual dataset of 500,153 Instagram posts about COVID-19 published between January 2020 and September 2024. This dataset contains Instagram posts in 161 different languages. After the development of this dataset, multilingual sentiment analysis was performed using VADER and twitter-xlm-roberta-base-sentiment. This process involved classifying each post as positive, negative, or neutral. The results of sentiment analysis are presented as a separate attribute in this dataset. For each of these posts, the Post ID, Post Description, Date of publication, language code, full version of the language, and sentiment label are presented as separate attributes in the dataset. The Instagram posts in this dataset are present in 161 different languages out of which the top 10 languages in terms of frequency are English (343041 posts), Spanish (30220 posts), Hindi (15832 posts), Portuguese (15779 posts), Indonesian (11491 posts), Tamil (9592 posts), Arabic (9416 posts), German (7822 posts), Italian (5162 posts), Turkish (4632 posts) There are 535,021 distinct hashtags in this dataset with the top 10 hashtags in terms of frequency being #covid19 (169865 posts), #covid (132485 posts), #coronavirus (117518 posts), #covid_19 (104069 posts), #covidtesting (95095 posts), #coronavirusupdates (75439 posts), #corona (39416 posts), #healthcare (38975 posts), #staysafe (36740 posts), #coronavirusoutbreak (34567 posts) The following is a description of the attributes present in this dataset <ul> <li>Post ID: Unique ID of each Instagram post</li> <li>Post Description: Complete description of each post in the language in which it was originally published</li> <li>Date: Date of publication in MM/DD/YYYY format</li> <li>Language code: Language code (for example: “en”) that represents the language of the post as detected using the Google Translate API </li> <li>Full Language: Full form of the language (for example: “English”) that represents the language of the post as detected using the Google Translate API </li> <li>Sentiment: Results of sentiment analysis (using the preprocessed version of each post) where each post was classified as positive, negative, or neutral</li> </ul> Open Research Questions This dataset is expected to be helpful for the investigation of the following research questions and even beyond: <ol> <li>How does sentiment toward COVID-19 vary across different languages?</li> <li>How has public sentiment toward COVID-19 evolved from 2020 to the present?</li> <li>How do cultural differences affect social media discourse about COVID-19 across various languages?</li> <li>How has COVID-19 impacted mental health, as reflected in social media posts across different languages?</li> <li>How effective were public health campaigns in shifting public sentiment in different languages?</li> <li>What patterns of vaccine hesitancy or support are present in different languages?</li> <li>How did geopolitical events influence public sentiment about COVID-19 in multilingual social media discourse?</li> <li>What role does social media discourse play in shaping public behavior toward COVID-19 in different linguistic communities?</li> <li>How does the sentiment of minority or underrepresented languages compare to that of major world languages regarding COVID-19?</li> <li>What insights can be gained by comparing the sentiment of COVID-19 posts in widely spoken languages (e.g., English, Spanish) to those in less common languages?</li> </ol> All the Instagram posts that were collected during this data mining process to develop this dataset were publicly available on Instagram and did not require a user to log in to Instagram to view the same (at the time of writing this paper).

opencc-by-4.0Oct 2024View details →

Brazilian COVID-19

Open the record for dataset details and reuse information.

opencc-by-4.0Oct 2024View details →

Supplemental Online Material for "Comparing the Effects of Euclidean Distance Matching and Dynamic Time Warping in the Clustering of COVID-19 Evolution": Interactive Figures

This repository contains the interactive figures accompanying the manuscript "Comparing the Effects of Euclidean Distance Matching and Dynamic Time Warping in the Clustering of COVID-19 Evolution". These interactive visualizations provide a dynamic exploration of some of the data and results discussed in the paper. The following interactive figures are included: <ul> <li><code>Figure-1.html</code>: Interactive version of Figure 1 from the paper, showing a time series heatmap of the 14-day simple moving average of reported COVID-19 cases for each of Europe's 298 NUTS 2 regions, from 02/10/2020 - 07/12/2020.</li> <li><code>Figure-2.html</code>: Interactive version of Figure 2, which visualizes two heatmap dendrograms showcasing the pairwise distance matrices and hierarchical clustering results for (a) the Euclidean distance and (b) the Dynamic Time Warping distance.</li> <li><code>cluster_maps.html</code>: Interactive cluster maps, allowing for detailed exploration of the clusters discussed in the paper. Users can select between different distance metrics (Euclidean or Dynamic Time Warping) and adjust the number of clusters to visualize, providing greater flexibility in exploring the clustering patterns. This figure is not included as a static figure in the paper but is provided merely as supplemental online material.</li> </ul> These interactive figures are best viewed using a modern web browser (e.g., Chrome, Firefox ...). For all visualizations, upon hovering over the figure, a label appears displaying the NUTS 2 region and the country it is in, providing additional geographic context.

opencc-by-4.0Nov 2024View details →

Spatially resolved single-cell atlas unveils A distinct cellular signature of fatal lung COVID-19 in a Malawian population

Postmortem single-cell studies have transformed understanding of lower respiratory tract diseases (LRTD) including Covid19, but there is minimal data from African settings where HIV, malaria and other environmental exposures may affect disease pathobiology and treatment targets. We used histology and high-dimensional imaging to characterise fatal lung disease in Malawian adults with (n=9) and without (n=7) Covid19, and generated single-cell transcriptomics data from lung, blood and nasal cells. Data integration with other  cohorts showed a conserved Covid19 histopathological signature, driven by contrasting immune and inflammatory mechanisms:  in USA, European and Asian cohorts by type I/III interferon responses, particularly in blood-derived monocytes, in the Malawi cohort, by response to interferon-gamma (IFN-γ) in lung-resident macrophages. HIV status had minimal impact on histology or immunopathology. Our study provides a data resource and highlights the importance of studying the cellular mechanisms of disease in underrepresented populations, indicating shared and distinct targets for treatment.  Here, there are scripts containing pre-processing, image denoise, cell segmentation, single-cell and spatial statistics analysis as well as visualisation plots for the Imaging Mass Cytometry of the post-mortem lung sections.  Check out the interactive single cell atlas hosted on the cellxgeneVIP platform hosted by the University of Glasgow, by clicking on <a href="https://cellatlas-cxg.mvls.gla.ac.uk/COSMIC/view/COSMIC_IMC_Lung.h5ad/" rel="nofollow">https://cellatlas-cxg.mvls.gla.ac.uk/COSMIC/view/COSMIC_IMC_Lung.h5ad/</a>

opencc-by-4.0Oct 2024View details →

The number of sources limiting equality before the law during COVID-19

Rak Joanna, Bäcker Roman, The number of sources limiting equality before the law during COVID-19.   This dataset was elaborated for the research project Civil Disorder in Pandemic-ridden European Union. The latter was financially supported by the National Science Centre, Poland [grant number 2021/43/B/HS5/00290].

opencc-by-4.0Nov 2024View details →

Análisis estadísticos y encuesta validada aplicada en Medicina tradicional y COVID-19 influencia en la recuperación y satisfacción de la nacionalidad Tsáchila

Análisis estadísticos y encuesta validada aplicada, de una investigación correlacional, con diseño transversal realizada en Ecuador, en un total de 1 003 miembros de la nacionalidad Tsáchila, con el objetivo de establecer si la medicina ancestral influyó en los niveles de satisfacción y tiempo de recuperación de dichos miembros que presentaron síntomas de contagio de COVID-19.

opencc-zeroJun 2021View details →

Global & Community Health: Implementation of and patient satisfaction with the first neurologic telemedicine program in Mexico during COVID-19

Since the coronavirus disease 2019 (COVID-19) pandemic outbreak, due to the large number of patients requiring in-hospital care, hospitals worldwide were converted into COVID-19 referral centers. In addition, as part of the mitigation strategies besides social distancing and mandatory use of facemasks, other measures to reduce the risk of infection among healthcare workers such as increasing the time between work shifts and sending high-risk personnel to in-home isolation were taken, leading to a significantly reduced workforce, requiring relocation of medical personnel from multiple specialties to the frontline. By April 2020, due to the reduction of medical and administrative staff in addition to the steadily increasing number of patients, our center decided to stop all face-to-face non-COVID-19 consultations. Therefore, we decided to adapt to the challenges and started researching how to implement a teleneurology program to re-open our neurology continuity clinic. Here, we describe our experience developing and implementing a teleneurology program in Mexico and patient satisfaction with our program. To assess patient satisfaction and quality of the healthcare received, at the end of the consultations, to those who had internet access, we sent via e-mail or text message an anonymous 24-question online-based questionnaire (modified for the COVID-19 pandemic) developed and validated for the Spanish-speaking population. We included 304 patients. The most common neurologic disorders we attended were neuromuscular disorders in 33.6% of patients, headache disorders in 32.9%, epilepsy in 11.5%, cerebrovascular diseases in 5.9%, and movement disorders in 5.6%. None of the patients required an in-person visit. Of the 304 patients, only 125 (41%) answered the survey, 86.4% preferred teleneurology instead of an in-person consultation, 83.3% (90/108) of them because of concerns about getting COVID-19; 92% completely agree that they felt comfortable when talking to the neurologist through a camera and a microphone; 96% reported being satisfied with their consultation; 87.2% completely agree in trusting that their privacy would be protected. However, 4% were not satisfied, but their reasons were not specified. Our findings suggest that telemedicine is a feasible and acceptable option to continue with neurological patient care during the COVID-19 pandemic.

Mountain lions reduce movement, increase efficiency during the COVID-19 shutdown

Wildlife strongly alter behavior in response to human disturbance; however, fundamental questions remain regarding the influence of human infrastructure and activity on animal movement. The Covid-19 pandemic created a natural experiment providing an opportunity to evaluate wildlife movement during a period of greatly reduced human activity. Speculation in scientific reviews and the media suggested that wildlife might be increasing movement and colonizing urban landscapes during pandemic slowdowns. However, theory predicts that animals should move and use space as efficiently as possible, suggesting that movement might actually be reduced relative to decreased human activity. We quantified space use, movement, and resource-selection of 12 GPS-collared mountain lions (8 females, 4 males) occupying parklands in greater Los Angeles during the Spring 2020 California stay-at-home order when human activity was far below normal. We also tested the hypothesis that reduced traffic on Los Angeles area roadways increased permeability of these barriers to animal movement. Contrary to expectations that wildlife roamed more widely during pandemic shutdowns, resident mountain lions used smaller areas and moved shorter distances relative to their historical behavior in greater Los Angeles. They also relaxed avoidance of anthropogenic landscape features such as trails and development, which likely facilitated increased traveling efficiency. However, there was no detectable change in road-crossing, despite reduced traffic volume. Our results support the theoretical prediction that animals maximize movement efficiency and suggest that carnivores incur energetic costs while avoiding humans. While mountain lions may restrict movement at the landscape-level relative to barriers, they appear to increase distances moved at finer scales when avoiding human activity - highlighting the scale-dependent nature of animal responses to human disturbance. Avoiding humans can reduce direct mortality of large carnivores and is often suggested to be an important mechanism promoting coexistence in shared landscapes. However, energetic costs incurred by increased movement and space-use while avoiding human activity may have important consequences for population viability, predator-prey interactions, community structure, and human-wildlife conflict. Management providing sufficient wild prey and education regarding best practices for protection of domestic animals are important for conserving large carnivores in human-dominated landscapes.

Telerehabilitation program for COVID-19 survivors (TERECO) - Randomized controlled trial

Objectives To investigate superiority of a telerehabilitation program for Covid-19 (TERECO) over no rehabilitation with regard to exercise capacity, lower-limb muscle strength (LMS), pulmonary function, health-related quality of life (HRQOL), and dyspnoea. Design Parallel-group randomised controlled-trial with 1:1 block-randomisation. Setting Three major hospitals from Jiangsu and Hubei provinces, China. Participants 120 formerly hospitalised Covid-19 survivors with remaining dyspnoea complaints were randomised with 61 allocated to control and 59 to TERECO. Intervention Unsupervised home-based 6-week exercise program comprising breathing control and thoracic expansion, aerobic exercise, and LMS exercise, delivered via smartphone, and remotely monitored with heart rate telemetry. Outcomes Primary outcome was 6-minute walking distance (6MWD) in metres. Secondary outcomes were squat time in seconds; pulmonary function assessed by spirometry; HRQOL measured with SF-12; and mMRC-dyspnoea. Outcomes were assessed at 6 weeks (post-treatment) and 28 weeks (follow-up). Results Adjusted between-group difference in change in 6MWD was 65.45 metres (95% CI 43.8, 87.1; p<0.001) at post-treatment and 68.62 metres (95% CI 46.39, 90.85; p<0.001) at follow-up. Treatment effects for LMS were 20.12 seconds (95% CI 12.34, 27.9; p<0.001) post-treatment and 22.23 seconds (95% CI 14.24, 30.21; p<0.001) at follow-up. No group differences were found for lung function except post-treatment MVV. Increase in SF-12 physical component was greater in the TERECO group with treatment effects estimated as 3.79 (95% CI 1.24, 6.35; p=0.004) at post-treatment and 2.69 (95% CI 0.06, 5.32; p=0.045) at follow-up. Conclusions This trial demonstrated superiority of TERECO over no rehabilitation for 6MWD, LMS, and physical HRQOL. Trial registration: ChiCTR2000031834, URL: <a href="http://www.chictr.org.cn/showproj.aspx?proj=52216">http://www.chictr.org.cn/showproj.aspx?proj=52216</a>

Epidemic Dreams: Dreaming about health during the COVID-19 pandemic

The continuity hypothesis of dreams - a widely studied model of dreaming - suggests that the content of dreams is largely continuous with the waking experiences of the dreamer. Given the unprecedented nature of the experiences during the pandemic of COVID-19, we studied the continuity hypothesis in the context of such a pandemic. To that end, we implemented a state-of-the-art deep-learning algorithm that can accurately extract mentions of virtually any medical condition from text and applied it to two sets of data collected during the COVID-19 pandemic: 2,888 dream reports (dreaming life experiences), and 57M tweets mentioning the pandemic (waking life experiences). We found that the health expressions that were shared by both sets were common COVID-19 symptoms (e.g., coronavirus, anxiety, coughing, and stress), suggesting that dreams reflected people's real-world experiences. On the other hand, we found that the health expressions that distinguished the two sets reflected differences in thought processes: health expressions in waking life reflected a linear and logical thought process and, as such, described realistic symptoms or related disorders (e.g., body aches, nasal pain, SARS, H1N1); by contrast, those in dreaming life reflected a thought process likely based on the activation of the visual and emotional areas of the brain and, as such, described either conditions not necessarily associated with the pandemic's virus (e.g., maggots, deformities, snakebites), or conditions of surreal nature (e.g., teeth suddenly falling out, body crumbling into sand). Our results confirm that, in addition to the sources of health data being researched lately (e.g., psychological conditions inferred from social media posts, physiological readings from commercial wearables), dream reports, if interpreted correctly, represent an understudied yet valuable source of people's health experiences in the real world.

opencc-by-4.0Jul 2021View details →

Base de datos- Ansiedad de estudiantes de Estomatología cubanos e intención de abandonar estudios durante la pandemia COVID-19

Base de datos para SPSS de la investigación citada en el título.

Daily United States COVID-19 Testing and Outcomes Data By State, March 7, 2020 to March 7, 2021

The COVID Tracking Project was a volunteer organization launched from The Atlantic and dedicated to collecting and publishing the data required to understand the COVID-19 outbreak in the United States. Our dataset was in use by national and local news organizations across the United States and by research projects and agencies worldwide. Every day, we collected data on COVID-19 testing and patient outcomes from all 50 states, 5 territories, and the District of Columbia by visiting official public health websites for those jurisdictions and entering reported values in a spreadsheet. The files in this dataset represent the entirety of our COVID-19 testing and outcomes data collection from March 7, 2020 to March 7, 2021. This dataset includes official values reported by each state on each day of antigen, antibody, and PCR test result totals; the total number of probable and confirmed cases of COVID-19; the number of people currently hospitalized, in intensive care, and on a ventilator; the total number of confirmed and probable COVID-19 deaths; and more.

opencc-by-4.0Jul 2021View details →

Surveys reporting feedback from families attending Early Childhood Services during 5-month school closure due to COVID-19: an Italian experience

This dataset reports results of two surveys distributed by Cooperativa Sociale Aeris during Covid19 pandemic to families attending its Early Childhood Services dedicated to 0-3 aged children. Aeris is a social enterprise based in northern Italy that deals with socio-educational and welfare services. One of Aeris activities deals with the management of the ten Early Childhood Services located in the northern Italy  which are dedicated to 0-3 aged children. After the school closure occurred the 24th of February 2020, Aeris organized online activities to keep contacts with families, to support children as well as their parents. With the aim of assessing if the adopted organization and proposed activities had positive feedback on families, a first survey was distributed in May 2020 and a second survey was distributed in October 2020 to families attending the Early Childhood Services. Survey results are reported in this dataset. Even if several worldwide actions have been implemented to guarantee educational continuity during Covid19 pandemic, most of these actions targeted 3-18 years old children/adolescents, while the subgroup 0-3 was rarely included.

opencc-by-4.0Sep 2020View details →

Chest CT Computerized Aided Quantification of PNEUMONIA Lesions in COVID-19 Infection: A Comparison among Three Commercial Software.

We uploaded the complete database of the manuscript: Grassi R, Cappabianca S, Urraro F, Feragalli B, Montanelli A, Patelli G, Granata V, Giacobbe G, Russo GM, Grillo A, De Lisio A, Paura C, Clemente A, Gagliardi G, Magliocchetti S, Cozzi D, Fusco R, Belfiore MP, Grassi R, Miele V. Chest CT Computerized Aided Quantification of PNEUMONIA Lesions in COVID-19 Infection: A Comparison among Three Commercial Software. Int J Environ Res Public Health. 2020 Sep 22;17(18):6914. doi: 10.3390/ijerph17186914. PMID: 32971756; PMCID: PMC7558768.

opencc-by-4.0Feb 2021View details →

Coronavirus Disease 2019 (COVID-19) in Italy: features on Chest Computed Tomography using a structured report system

We uploaded a dataset including the presence of GGO and its distribution for each patient presented in the manuscript: Grassi R, Fusco R, Belfiore MP, Montanelli A, Patelli G, Urraro F, Petrillo A, Granata V, Sacco P, Mazzei MA, Feragalli B, Reginelli A, Cappabianca S. Coronavirus disease 2019 (COVID-19) in Italy: features on chest computed tomography using a structured report system. Sci Rep. 2020 Oct 14;10(1):17236. doi: 10.1038/s41598-020-73788-5. Erratum in: Sci Rep. 2021 Feb 15;11(1):4231. PMID: 33057039; PMCID: PMC7566610.

opencc-by-4.0Aug 2021View details →

No More Dance Floors: COVID-19 and the Dance Music Industry

This dataset contains values for the social media growth of 75 selected house music artists between April 2020 and April 2021 as part of the author's masters thesis submission for Berklee Online.

openother-openDec 2020View details →

Data and code underpinning: "The association of smoking status with SARS-CoV-2 infection, hospitalisation and mortality from COVID-19: A living rapid evidence review with Bayesian meta-analyses (version 12)"

No description provided.

opencc-zeroAug 2021View details →

DATASET: Forecast made on January 11, 2021 for the second Covid-19 wave based on the improved SIR model with a constant ratio of recovery to infection rate

The temporal evolution of second and subsequent waves of the Covid-19 pandemic is investigated. Analytic expressions for the peak time and asymptotic behaviors, early doubling time, late half decay time, and a half-early peak law, characterizing the dynamical evolution of number of cases and fatalities are derived, where the pandemic evolution exhibiting multiple waves is described by the semi-time SIR model. The asymmetry of the epidemic wave and its exponential tail are affected by the initial conditions; a feature that has no analogue in the all-time SIR model. Our analysis reveals that the immunity is very strongly increasing during the 2nd wave. Wave-specific SIR parameters describing infection and recovery rates we find to behave in a similar fashion. Still, an apparently moderate change of their ratio can have significant consequences. As we show, the probability for an additional wave is however low in several countries due to the fraction of immune inhabitants at the end of the 2nd wave, irrespective the currently ongoing vaccination efforts. We compare with alternate approaches and data available at the time of submission. Most recent data serves to demonstrate the successful forecast and high accuracy of the SIR-model in predicting the evolution of pandemic outbreaks.