Awesome COVID-19 resources
A curated list of awesome data science, analytics and computer programming resources for COVID-19.
- COVID-19 DATABASE: COVID-19: CASISTICA RADIOLOGICA ITALIANA - Italian database with CT images of lungs.
- Coronavirus-Dataset: Dataset of COVID-19 in South Korea - South Korean dataset detailing virus spread routes.
- COVID-19 Open Research Dataset (CORD-19) - dataset with scholarly articles about COVID-19.
- European Centre for Disease Prevention and Control - geographic distribution of COVID-19 cases worldwide
- Data Repository by Johns Hopkins CSSE
- SARS-CoV-2 and COVID-19 Pathway (Homo sapiens) - WikiPathways model
- nCovMemory - Memory of coronavirus: Media Coverage, Non-fiction Writings, and Individual Narratives.
- COVID-19-TweetIDs - Twitter posts related to COVID-19. Described in COVID-19: The First Public Coronavirus Twitter Dataset.
- cord-19-tools - David Josephs' pip-installable python package to load the COVID-19 Open Research Dataset (CORD-19) dataset. A full load take 5 GB of memory.
- Visualization of Covid-19 confirmed cases - Interactive ShinyApp visualization by Felix Schönbrodt (@nicebread) et al. with longitudinal confirmed cumulative cases and deaths. Development from https://github.com/nicebread/corona and data from ECDC and Johns Hopkins University.
- COVID-19 case counts - Interactive visualization by Theo Sanderson of longitudinal COVID-19 cases by country with interactive date offset. Data from Johns Hopkins University.
- EuroMOMO - European monitoring of excess mortality for public health action weekly mortality as deviations from the baseline.
Visualizations on maps
- Visual Dashboard - Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU) described in An interactive web-based dashboard to track COVID-19 in real time.
- Modeling COVID-19 Spread vs Healthcare Capacity - Interactive ShinyApps by Alison Hill with interactive settings of epidemiological parameters and longitudinal visualization.
- Effekten af kontakt restriktioner og rejseforbud på COVID-19 udbrud i DK - Interactive ShinyApps in Danish by Kaare Græsbøll and Elisabeth Ottesen Bangsgaard with various interactive epidemiological variables.
Collections of visualizations
- Observable Topic: "Coronavirus" - A selection of interactive Observable notebooks related to COVID-19 and SARS-CoV-2
- Hierarchical Logistic Growth Curves - Brynjólfur Gauti Jónsson's Bayesian modeling of daily COVID-19 counts with output at https://bgautijonsson.shinyapps.io/Hierarchical_Report/.
- Stochastic epidemic models - Michael Riis Andersen.
- Effective containment explains sub-exponential growth in confirmed cases of recent COVID-19 outbreak in Mainland China - Model that captures both, quarantine of symptomatic infected individuals as well as population wide isolation in response to mitigation policies or behavioral changes.
Lung-CT deep learning
- A deep learning algorithm using CT images to screen for Corona Virus Disease (COVID-19)
- Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography: a prospective study in 27 patients
- Deep Learning-Based Quantitative Computed Tomography Model in Predicting the Severity of COVID-19: A Retrospective Study in 196 Patients
- Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner - Description of recurrent neural network predicting 6 respiratory patterns from depth camera data (Scholia)