app: Hide some extra things
@@ -59,6 +59,7 @@ 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/).* **If you see any error messages please reload the page.**"""
)
st.title("COVID-19 Hospital Impact Model for Epidemics")
+if st.checkbox("More info about this tool"):
st.subheader(
"[Discrete-time SIR modeling](https://mathworld.wolfram.com/SIRModel.html) of infections/recovery"
)
@@ -67,7 +68,6 @@ st.markdown(
The epidemic proceeds via a growth and decline process. This is the core model of infectious disease spread and has been in use in epidemiology for many years."""
)
-if st.checkbox("More info about this tool"):
st.markdown("""The dynamics are given by the following 3 equations.""")
st.latex("S_{t+1} = (-\\beta S_t I_t) + S_t")
@@ -204,7 +204,9 @@ if st.checkbox("Show Admissions Data"):
st.dataframe(admits_table)
st.subheader("Admitted Patients (Census)")
-st.markdown("Running **census** of COVID-19 patients, accounting for arrivals and discharges at Penn hospitals")
+st.markdown(
+ "Running **census** of COVID-19 patients, accounting for arrivals and discharges at Penn hospitals"
+)
# ALOS for each category of COVID-19 case (total guesses)
@@ -243,7 +245,9 @@ census_table = census_table.dropna()
if st.checkbox("Show Census Data"):
st.dataframe(census_table)
-st.markdown("""**Click the checkbox below to view additional data generated by this simulation**""")
+st.markdown(
+ """**Click the checkbox below to view additional data generated by this simulation**"""
+)
if st.checkbox("Show Additional Data"):
st.subheader("Projected Hospitalization Demand at Penn Medicine Facilities")
st.markdown(
@@ -259,7 +263,6 @@ if st.checkbox("Show Additional Data"):
ax.grid("on")
st.pyplot()
-
impact_table = (projection.iloc[::7, :]).apply(np.floor)
impact_table.index = range(impact_table.shape[0])
