Modifying script for additional model run and results storage

.gitignore

@@ -8,6 +8,8 @@
 !data/measles_cases.csv
 !scenarios/*_outbreak_size.csv
 !scenarios/*_hospitalizations.csv
+!scenarios/*_outbreak_size_plus1seed.csv
+!scenarios/*_hospitalizations_plus1seed.csv
 .DS_Store
 scenarios/template.md
-scenarios/template_files/
+scenarios/template_files/

DETAILS.md

@@ -25,6 +25,7 @@ scenarios/
   data/                City-specific data symlinked/copied for rendering
 sensitivity_analyses/
   scaling_analysis.md  Report on why downscaling works in the model   
+  seeds_vs_outbreak_controls.qmd  Seed-vs-outbreak analysis with demographic controls
 Makefile               Targets for data generation and package updates
 ```
 

README.qmd

@@ -26,7 +26,7 @@ The following figure summarizes the simulated measles outbreak size over time fo
 library(data.table)
 library(ggplot2)
 
-fns <- list.files("scenarios/", pattern = "outbreak.*\\.csv", full.names = TRUE)
+fns <- list.files("scenarios/", pattern = "_outbreak_size\\.csv$", full.names = TRUE)
 
 # Reading the datasets in
 outbreaks <- lapply(fns, \(fn) {
@@ -172,4 +172,4 @@ fns <- sprintf("scenarios/%s.md", unique(outbreaks$city)) |>
 
 sprintf("- [%s](%s)", gsub("scenarios/([^_]+).md", "\\1", fns), fns) |>
   cat(sep = "\n")
-```
+```

data/mmr_under5.csv

@@ -0,0 +1,14 @@
+# Data from
+# https://www.cdc.gov/mmwr/volumes/73/wr/mm7338a3.htm
+city,geography_used,vacc_rate
+Los Angeles,California,88.6
+San Francisco,California,88.6
+New York City,New York City,86.7
+Boston,Massachusetts,94.9
+Houston,Houston,87.8
+Dallas,Texas,92.8
+Philadelphia,Philadelphia,89.7
+Atlanta,Georgia,84.3
+Seattle,Washington,91.1
+Miami,Florida,90.8
+Kansas City,Missouri,91.7