Announcement: This readme page will be removed on 23 March 2020. Visit the MIDAS Online COVID-19 Portal to navigate and search software tools. This GitHub repository will be used to share the computable (CSV format) software catalog only.
| Contents |
|---|
| Visualizations and Dashboards |
| Data processing |
| Modeling |
- Curation status: published
- Created by: HealthMap
- Description: Map with alerts of 2019 nCoV occurrence extracted from online news reports; a saved search for 2019 Novel Coronavirus from the larger HealthMap disease altert collection.
- Last updated: 2020-02-11
- Curation status: published
- Created by: Brownstein J (John.Brownstein@childrens.harvard.edu), Cohn E (Emily.Cohn@childrens.harvard.edu), Goodwin L(Lauren.Goodwin@childrens.harvard.edu), Gutierrez B (bernanrdo.gutierrez@zoo.ox.ac.uk), Hill S (sarah.hill@zoo.ox.ac.uk), Hulland E(ehulland@uw.edu), Kraemer M(moritz.kraemer@zoo.ox.ac.uk), Li S (sabrina.li@ouce.ox.ac.uk), loskill A (aloskill@bu.edu), Mekaru S(srmekaru@gmail.com), Morgan J (morgaj5@uw.edu), O'Brien K (katelynn.obrien@childrens.harvard.edu), Pigott D (pigottdm@uw.edu), Pybus O (oliver.pybus@zoo.ox.ac.uk), Scarpino S (s.scarpino@northeastern.edu), Sewalk K (Kara.Sewalk@childrens.harvard.edu), Wu J (chiehhsi.wu@gmail.com), Xu B (xu-b15@mails.tsinghua.edu.cn), Zabreski A(aezarebski@gmail.com).
- Description: Map with case counts of cases at point coordinates at centroid of reporting location, cases exclusively collected from publicly available news and media. Data taken from line listing format entered data and stored in Github repository.
- Last updated: 2020-02-11
- Curation status: published
- Created by: China Centers for Disease Control
- Description: Dashboard showing spatial distribution of confirmed and suspected cases, and deaths as new cases per day and cumulative case numbers.
- Last updated: 2020-02-11
- Curation status: published
- Created by: Lai R KK, Wu J, McCann A, Watkins D, Patel J K, Harris R
- Description: Dashboard showing spatial distribution of confirmed and suspected cases, and deaths as new cases per day and cumulative case numbers.
- Last updated: 2020-02-11
- Curation status: published
- Created by: Gardner L, Zlojutro A, Rey D, Dong E.
- Description: Dashboard showing case counts by province/city in China and globally, as total confirmed cases and deaths, and total recovered cases. A related Github repository lists daily snapshots of the case data and a time series compilation of new cases per day for provinces in China and locations outside of China. All data are derived from publicly available data from WHO, CDC, ECDC, NHC, and DXY.
- Last updated: 2020-02-11
- Curation status: published
- Created by: Network Systems Science and Advanced Computing (NSSAC) division of Biocomplexity Institute and Initiative at the University of Virignia.
- Description: Visualization tool that provides an alternate way of examining data curated by JHU and NSSAC: A visualization of all reported Coronavirus incidence data, filtered by date; A heatmap of selected attributes on an interactive map; A Query tool that allows users to focus on regions of interest; The ability to select regions by clicking on the map; Users can export subsets of the data for analysis on external tools.
- Last updated: 2020-02-19
- Curation status: published
- Created by: Network Systems Science and Advanced Computing (NSSAC) division of Biocomplexity Institute and Initiative at the University of Virignia.
- Description: Visualization tool that takes NSSAC-curated data from the Harvard public line list in order to display a dashboard view of imported COVID-19 cases (cases in countries outside of China). Users can click on countries on the dashboard’s interactive map to see more information. the COVID-19 Imported Cases Dashboard includes Imported Case Cluster Figures (where applicable) generated from the BeOutbreakPrepared nCoV 2019 public line list.
- Last updated: 2020-02-19
- Curation status: published
- Created by: European Centre for Disease Prevention and Control
- Description: The interactive situation dashboard shows the latest available data on COVID-19. The interface allows users to explore, interact with data and switch chart to tables view for details. The number of cases and deaths can be shown within a specific date range and by country.
- Last updated: 2020-03-11
- Curation status: published
- Created by: Zhao B, Xu F, Kang L, Ji J, Bao S.
- Description: The online interactive map enables users to track both the global and local trends of Novel Coronavirus infection since Jan 21st, 2020. The supporting dataset is timely collected from multiple official sources and then plotted onto the map.
- Last updated: 2020-03-11
- Curation status: published
- Created by: The Center for the Ecology of Infectious Diseases (CEID) at the University of Georgia
- Description: Public facing website for dissemination of analysis by the UGA CEID Coronavirus Working Group. This website provides analysis and tracking of the 2019 novel Coronavirus oubreak (COVID-19) which began in Wuhan, China, in 2019.
- Last updated: 2020-03-11
- Curation status: published
- Created by: Italian Department of Civil Protection
- Description: To inform citizens and make the collected data available, useful only for communication and information purposes, the Department of Civil Protection has developed an interactive geographic dashboardthe following information updated daily at 18:30 (after the Head of Department press conference): National trend, Json data, Provinces data, Regions data, Summary cards and Areas.
- Last updated: 2020-03-11
- Curation status: published
- Created by: Yu G (guangchuangyu@gmail.com),Wu T (wutimze@gmail.com), Hu E (13766876214@163.com),Tung P (tung_patrick@yahoo.com),Ge X (Xijin.Ge@sdstate.edu)
- Description: R package, nCov2019, to provide convenient access to epidemiological data on the coronavirus outbreak. Besides detailed real-time statistics, it offers access to three data sources with detailed daily statistics from December 1, 2019, for 43 countries and more than 500 Chinese cities.
- Last updated: 2020-03-11
- Curation status: published
- Created by: Kucharski A (adam.kucharski@lshtm.ac.uk)
- Description: R package to extract data from PDF figures
- Last updated: 2020-03-11
- Curation status: published
- Created by: McGough S (sfm341@mail.harvard.edu), Johansson M (mjohansson@cdc.gov), Lipsitch M (mlipsitc@hsph.harvard.edu), Menzies N (nmenzies@hsph.harvard.edu)
- Description: NobBS is Bayesian approach to estimate the number of occurred-but-not-yet-reported cases from incomplete, time-stamped reporting data for disease outbreaks. NobBS learns the reporting delay distribution and the time evolution of the epidemic curve to produce smoothed nowcasts in both stable and time-varying case reporting settings.
- Last updated: 2020-03-11
- Curation status: published
- Created by: The Center for the Ecology of Infectious Diseases (CEID) at the University of Georgia
- Description: Stochastic model to better understand the transmission of 2019-nCov in Hubei (primarily Wuhan). The model includes several features of the Wuhan outbreak that are absent from most compartmental models that otherwise confound the interpretation of data, including time-varying rates of case detection, patient isolation, and case notification.
- Last updated: 2020-03-11
- Curation status: published
- Created by: The Center for the Ecology of Infectious Diseases (CEID) at the University of Georgia
- Description: Estimation of effective reproduction number outside China. Estimates of the effective reproduction number outside China are calculated from the fraction of known exported cases that have led to secondary chains of transmission.
- Last updated: 2020-03-11
- Curation status: published
- Created by: Song Lab, University of Michigan
- Description: An implementation of extended state-space SIR models developed by Song Lab at UM school of Public Health
- Last updated: 2020-03-11