Coronavirus [NEW TOPIC PAGE]

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 Coronavirus

Self-reported COVID-19 Symptoms Show Promise for Disease Forecasts
Carnegie-Mellon University, April 20, 2020

Delphi uses two main approaches to forecasts, both of which have proven effective regarding the flu. One, called Crowdcast, is a "wisdom of the crowds" approach, which bases its predictions on the aggregate judgments of human volunteers who submit weekly estimates. The other uses machine learning to recognize patterns in health care data that relate to past experience.

How the UK is cracking the coronavirus code
Genomics Education Program, April 17,2020

Early prediction of mortality risk among severe COVID-19 patients using machine learning
X Chen et al, MEDRXIV, April 19, 2020

183 severe COVID-19 patients (115 survivors and 68 nonsurvivors) from Tongji Hospital were used to develop predictive models. Baseline characteristics and laboratory tests were significantly different between survivors and nonsurvivors. 4 variables(age, high-sensitivity C-reactive protein level, lymphocyte count, and d-dimer level) were selected by all models.

Trends and prediction in daily incidence and deaths of COVID-19 in the United States: a search-interest based model
X Yuan et al, MEDRXIV, April 20, 2020

There were 555,245 new cases and 22,019 deaths of COVID-19 reported in the U.S. from March 1 to April 12, 2020. The search interest of COVID, COVID pneumonia, and COVID heart were correlated with COVDI-19 daily incidence with about 12-day delay (Pearson r=0.978, 0.978 and 0.979, respectively) and deaths with 19-day delay (Pearson r=0.963, 0.958 and 0.970).