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The software should be distinguished from the ICL's COVID-19 Scenario Analysis Tool (currently Version 4 [11]), which is hosted under the domain name https://www.covidsim.org, but according to the research documentation is relying on the model combined with a squire model, which is the underlying transmission model in the absence of vaccination.
COVID-19 simulation models are mathematical infectious disease models for the spread of COVID-19. [1] The list should not be confused with COVID-19 apps used mainly for digital contact tracing . Note that some of the applications listed are website-only models or simulators, and some of those rely on (or use) real-time data from other sources.
Research based on the app was described in papers in Science on 5 May 2020 [23] and in Nature Medicine on 11 May 2020. [16] Using data from the app, researchers were able to identify six distinct types of COVID-19 and forecast which initial symptoms were more likely to lead to severe illnesses. [24] [25]
This category is for mathematical models of infectious disease specific to the COVID-19 pandemic. Pages in category "COVID-19 models" The following 6 pages are in this category, out of 6 total.
In April 2020, the model was called "perhaps the most widely cited coronavirus model" by The Colorado Sun [1] and "America's most influential coronavirus model" by The Washington Post. [2] Its projections were cited during White House briefings in March–April 2020. [3] Critics say the model uses flawed methods and should not guide U.S. policies.
The Imperial College COVID-19 Response Team is led by Professor Neil Ferguson, Director of the Jameel Institute and MRC GIDA. [5] [6] On 16 March 2020 the Imperial College COVID-19 Response Team produced a research forecast of various scenarios for spread of the disease in the United Kingdom and the United States.
"The increased prevalence of outdoor activities and gatherings in a post-COVID-19 world will further expose large numbers of people to potential vulnerabilities within security that place them at ...
The We-Care project is a novel initiative by University of California, Davis researchers that uses anonymity and crowdsourced information to alert infected users and slow the spread of COVID-19. [58] [59] [60] The scientific community has held several machine learning competitions to identify false information related to the COVID-19 pandemic ...