Author: Norden E Huang; Fangli Qiao; Ka-Kit Tung
Title: A data-driven tool for tracking and predicting the course of COVID-19 epidemic as it evolves Document date: 2020_3_30
ID: mxen3n0k_27
Snippet: This result can be rigorously derived using an age-structured population model (see 163 reference (36)). It is also common sense: the infected eventually recovered after a 164 number of days, or dead after a similar number of days. Of course, the number of 165 days a patient stays in the hospital before discharge depends on the efficacy of 166 treatment and so varies somewhat, and the time it takes for a patient to die may also 167 depend on the .....
Document: This result can be rigorously derived using an age-structured population model (see 163 reference (36)). It is also common sense: the infected eventually recovered after a 164 number of days, or dead after a similar number of days. Of course, the number of 165 days a patient stays in the hospital before discharge depends on the efficacy of 166 treatment and so varies somewhat, and the time it takes for a patient to die may also 167 depend on the age and underlying conditions. T is therefore a statistical quantity. Hubei ( Figure S2 ) and other regions (not shown). This is one of the ways the mean 175 recovery period is determined statistically from data, but it is not practical in the 176 early phase of the epidemic. We will give different methods for the latter purpose. 177
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