appendix update: Death data from WHO - not OWID

docs/tex/tex_descriptions/projects/sm_covid/agespec_table.tex

@@ -1,4 +1,8 @@
 \begin{table}
+   \begin{tikzpicture}[overlay,remember picture]
+      \node [yshift=-50ex,rotate=45] at ( $(pic cs:A) !.5! (pic cs:B)$ ){ \fontsize{30} 
+            {6}\selectfont\textbf{\color{black!40}DRAFT ONLY} };
+      \end{tikzpicture}
 \centering
 \caption{Age-specific parameters for wild-type COVID-19}
 \label{agespec_table}

docs/tex/tex_descriptions/projects/sm_covid/calibration_description.tex

@@ -19,16 +19,18 @@ \subsection{Parameters varied during calibration}
 The parameters varied during calibration along with their associated prior distributions 
 are listed in Table \ref{param_table} and indicated with the superscript \textsuperscript{C}.
 We used uniform prior distributions for all calibrated parameters. The primary parameters varied during calibration are 
-the unadjusted risk of transmission per contact ($\beta$), the IFR multiplier ($m_C$), the infection seeding times of 
-each strain and the proportion of students on-site during ``Partially open'' periods. Note that the values of the random 
-process $W_t$ described in Section \ref{random_process} are also treated as calibrated parameters by the MCMC. The Gaussian 
+the unadjusted risk of transmission per contact ($\beta$), the IFR multiplier ($m_C$), the original infection seeding time,
+the proportion of students on-site during ``Partially open'' periods, and the uncertainty multiplier modifying the school 
+contacts' contribution ($m_S$). 
+
+Note that the values of the random process $W_t$ described in Section \ref{random_process} are also treated as calibrated parameters by the MCMC. The Gaussian 
 auto-regressive component described in Equation \ref{eq:random_process} is incorporated in the posterior likelihood 
 computation (Section \ref{likelihood}).
 
 \subsection{Calibration targets}
 \label{targets}
 Model calibration was performed independently for each country. All models were fitted to the reported number of COVID-19 deaths over time.
-We used the daily number of COVID-19 deaths reported by Our World in Data and applied a 7-day moving average to the observed data. 
+We used the daily number of COVID-19 deaths reported by WHO and applied a 7-day moving average to the observed data. 
 
 \input{../../tex_descriptions/projects/sm_covid/serodata.tex}
 

docs/tex/tex_descriptions/projects/sm_covid/param_table.tex

@@ -1,4 +1,11 @@
+
+
+
 \begin{table}
+   \begin{tikzpicture}[overlay,remember picture]
+      \node [yshift=-30ex,rotate=45] at ( $(pic cs:A) !.5! (pic cs:B)$ ){ \fontsize{30} 
+            {6}\selectfont\textbf{\color{black!40}DRAFT ONLY} };
+      \end{tikzpicture}
 \centering
 \caption{Model parameters}
 \label{param_table}

docs/tex/tex_descriptions/projects/sm_covid/serodata.tex

@@ -24,7 +24,7 @@
 \begin{enumerate}
     \item Lowest risk of bias (according to SeroTracker),
     \item Latest sampling start date (when a greater number of infections have occurred, and to avoid bias due to early geographic heterogeneity),
-    \item Largest sample size.
+    % \item Largest sample size.
 \end{enumerate}
 
 The estimates used to inform the models are summarised in Table \ref{tab:sero_national}, with the associated original reports accessible by clicking on the countries' names.

docs/tex/user/rragonnet/sm_covid.tex

@@ -14,6 +14,10 @@
 \usepackage{amsmath}
 \usepackage{bbm}
 \usepackage{booktabs}  % for compatibility with table generated by pandas.to_latex()
+
+\usepackage{tikz, lmodern}
+\usetikzlibrary{calc,tikzmark}
+
 \renewcommand{\thefigure}{S\arabic{figure}}
 \renewcommand{\thetable}{S\arabic{table}}
 

notebooks/user/rragonnet/project_specific/School_Closure/remote/sb_full_analysis.ipynb

@@ -36,20 +36,20 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "ISO3 = \"PHL\"\n",
+    "ISO3 = \"FRA\"\n",
     "ANALYSIS = \"main\"\n",
     "\n",
     "N_CHAINS = 32\n",
-    "N_OPTI_SEARCHES = 32\n",
-    "N_BEST_RETAINED = 16\n",
+    "N_OPTI_SEARCHES = 4\n",
+    "N_BEST_RETAINED = 1\n",
     "OPTI_BUDGET = 10000\n",
     "\n",
-    "METROPOLIS_TUNE = 20   #2000\n",