app: Minor copy updates
@@ -54,10 +54,13 @@ Penn_market_share = (
/ 100.0
)
+st.markdown(
+ """This tool was developed by the [Predictive Healthcare team](http://predictivehealthcare.pennmedicine.org/) at Penn Medicine. For questions and comments please see our [contact page](http://predictivehealthcare.pennmedicine.org/contact/)."""
+)
st.title("COVID Hospital Impact Model for Epidemics")
st.subheader("SIR modeling of infections/recovery")
st.markdown(
- """Disrete-time SIR model
+ """Discrete-time SIR model
The model consists of individuals who are either Susceptible ( S ), Infected ( I ), or Recovered ( R ).
@@ -119,7 +122,7 @@ s, i, r = sim_sir(S, I, R, beta, gamma, n_days, beta_decay=0.005)
st.subheader("Projected Hospital Impact")
-st.markdown("The number of individuals requiring hospitalization in a region")
+st.markdown("The number of COVID-19 patients requiring hospitalization in the region")
hosp = i * hosp_rate * Penn_market_share
icu = i * icu_rate * Penn_market_share
@@ -216,7 +219,7 @@ census_table = census_table.dropna()
if st.checkbox("Show Census Data"):
st.dataframe(census_table)
-st.markdown("""**Click the checkbox below to view the raw SIR similation data**""")
+st.markdown("""**Click the checkbox below to view the raw SIR simulation data**""")
if st.checkbox("Show Infection Rate Data"):
fig, ax = plt.subplots(1, 1, figsize=(10, 4))
# ax.plot(s,label='S')
