@@ -207,7 +207,7 @@ def sim_sir(S, I, R, beta, gamma, n_days, beta_decay=None):
207207
208208st .subheader ("Admitted Patients (Census)" )
209209st .markdown (
210- "Running **census** of COVID-19 patients, accounting for arrivals and discharges at Penn hospitals"
210+ "Projected **census** of COVID-19 patients, accounting for arrivals and discharges at Penn hospitals"
211211)
212212
213213# ALOS for each category of COVID-19 case (total guesses)
@@ -251,27 +251,7 @@ def sim_sir(S, I, R, beta, gamma, n_days, beta_decay=None):
251251 """**Click the checkbox below to view additional data generated by this simulation**"""
252252)
253253if st .checkbox ("Show Additional Projections" ):
254- st .subheader ("Projected Hospitalization Demand at Penn Medicine Facilities" )
255- st .markdown (
256- "The number of COVID-19 patients projected to require hospitalization at Penn"
257- )
258- fig , ax = plt .subplots (1 , 1 , figsize = (10 , 4 ))
259- ax .plot (hosp , ".-" , label = "Hospitalized" )
260- ax .plot (icu , ".-" , label = "ICU" )
261- ax .plot (vent , ".-" , label = "Ventilated" )
262- ax .legend (loc = 0 )
263- ax .set_xlabel ("days from today" )
264- ax .set_ylabel ("Patients" )
265- ax .grid ("on" )
266- st .pyplot ()
267-
268- impact_table = (projection .iloc [::7 , :]).apply (np .floor )
269- impact_table .index = range (impact_table .shape [0 ])
270-
271- if st .checkbox ("Show Hospital Impact Data" ):
272- st .dataframe (impact_table )
273-
274- st .subheader ("The number of infected and recovered individuals at any given moment" )
254+ st .subheader ("The number of infected and recovered individuals in the hospital catchment region at any given moment" )
275255 fig , ax = plt .subplots (1 , 1 , figsize = (10 , 4 ))
276256 ax .plot (i , label = "Infected" )
277257 ax .plot (r , label = "Recovered" )
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