From bb9fc68aea7a6eeadd412747439ebf5d4b8e8b4a Mon Sep 17 00:00:00 2001
From: holysheets <47127171+holysheets@users.noreply.github.com>
Date: Sat, 21 Mar 2020 20:01:08 -0600
Subject: [PATCH] implimented potential SK simulation fix

---
 scenarios/NPI_Scenario3_SouthKorea.R | 8 ++------
 1 file changed, 2 insertions(+), 6 deletions(-)

diff --git a/scenarios/NPI_Scenario3_SouthKorea.R b/scenarios/NPI_Scenario3_SouthKorea.R
index edd8ea5..d393d01 100644
--- a/scenarios/NPI_Scenario3_SouthKorea.R
+++ b/scenarios/NPI_Scenario3_SouthKorea.R
@@ -1,16 +1,12 @@
 ## create matrix for counties starting social distancing based on South Korea R0 reductions
+##we're actually hardcoding this, but here's a dummy file. 
 ## R0 in SK .6-1.3, mid 2-3
-
 library(dplyr)
 
+# West coast
 county.status <- read.csv(paste0(foldername,'geodata.csv'))
 dates <- seq.Date(as.Date(ti_str), as.Date(tf_str), 1)
 
 NPI <- as.data.frame(matrix(0, dim(county.status)[1],length(dates)))
 colnames(NPI) <- as.Date(dates)
 rownames(NPI) <- county.status$geoid
-
-## Introducing NPI: randomly assign a pc value to each county based on Bootsma paper values
-NPI[ , colnames(NPI) >= as.Date("2020/03/19") & colnames(NPI) <= as.Date("2020/05/14") ] <- 1
-county.status$pc <- replicate(dim(county.status)[1], runif(dim(county.status)[1], 1.4, 1.7))
-NPI <- NPI * county.status$pc