An interactive web-based dashboard to track COVID-19 in real time
Open accessAbstract
In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus,1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020.2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time.
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The statistical analysis includes all countries that enjoy at least some degree of functional and/or formal sovereignty as defined by V-Dem, except 5 excluded for lack of confirmed COVID-19 data.
“efforts have been made to include all countries that enjoy at least some degree of functional and/or formal sovereignty as defined by the V-Dem Institute (Coppedge et al. 2021). Out of these 178 countries, 5 must be excluded since they lack the necessary data on confirmed COVID-19 cases reported by the Johns Hopkins University 3 (Dong et al. 2020).”
From Precaution and proportionality in pandemic politics: democracy, state capacity, and COVID-19-related school closures around the world (2022) · cites this paper as Dong et al. 2020
The paper’s main text (page unavailable) identifies the Johns Hopkins dashboard as a source of confirmed COVID-19 case counts for affected countries. It does not discuss the citing study’s 178-country sample or establish that five countries had to be excluded for lack of data. (LLM, conf=0.86)
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References 1 · Cited by 10,048
- Authors
- Dong, E., Du, H., & Gardner, L.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Gardner, Lauren
- Venue
- The Lancet Infectious Diseases
- Publisher
- Elsevier BV
- Published
- 2020-05
- Volume
- 20
- Issue
- 5
- Pages
- 533-534
- ISSN
- 1473-3099 (ISSN-L)
- PMC
- PMC7159018
- OpenAlex
- W3008443627
- Cited by
- 10,048
- References
- 1
- Citations by year
- 2026: 138 · 2025: 262 · 2024: 607 · 2023: 1270 · 2022: 2155 · 2021: 3166 · 2020: 2430 · 2019: 6 · 2018: 3 · 2016: 1 · 2014: 1 · 2013: 4
- FWCI
- 359.35
- Type
- journal article
- Language
- en
- Update notices
- erratum (2020-09-01)
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The Lancet Infectious Diseases (publishedVersion, other-oa)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Johns Hopkins University
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Epidemiology › Data-Driven Disease Surveillance
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Keywords
- COVID-19 pandemic, SARS-CoV-2, interactive dashboard, data visualization, disease surveillance, outbreak surveillance
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Humans, Patient Identification Systems, Pneumonia, Viral, Time Factors, Coronavirus Infections, Pandemics, Web Browser
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