Prehos: Prediction of hospitalized, ICU and ventilated cases.

In cyhsuTN/COVID19: Prediction of Cases Volumne and Hospitalization by SIR Model

Description

Prediction of hospitalized, ICU and ventilated cases based on SIR model.

Usage

Prehos(obj, inihos = 14, iniicu = 0, iniven = 0, hosrate = 2.5,
  icurate = 0.75, venrate = 0.5, outhosdays = 7, outicudays = 9,
  outvendays = 10, hms = 15)

Arguments

obj	Input. Object from function fitSIR.
inihos	Input. Initial number of hospitalized cases.
iniicu	Input. Initial number of ICU cases.
iniven	Input. Initial number of ventilated cases.
hosrate	Input. Hospitalization rate of infected people (percentage between 0 to 100).
icurate	Input. ICU rate of infected people (percentage between 0 to 100).
venrate	Input. Ventilated rate of infected people (percentage between 0 to 100).
outhosdays	Input. Hospital Length of Stay (days).
outicudays	Input. ICU Length of Stay (days).
outvendays	Input. Vent Length of Stay (days).
hms	Input. Hospital market share (percentage between 0 to 100).

Examples

## To predicte 100 days from today (dayFT=100).
casevolumne <- fitSIR(susceptible=4119405, Infected=3733, inihos=14,
     hosrate=2.5, hms=15, inidbt=4, mrt=14, sdis=30, dayFT=100)
hospitalization <- Prehos(casevolumne, inihos=14, iniicu=0, iniven=0,
     hosrate=2.5, icurate=0.75, venrate=0.5, outhosdays=7, outicudays=9,
     outvendays=10, hms=15)
head(hospitalization, 21) ## show the first 20 days

cyhsuTN/COVID19 documentation built on April 3, 2020, 4:19 a.m.