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covid-19-reopenings.Rmd
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covid-19-reopenings.Rmd
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---
title: "COVID-19 US State Re-Openings"
output: github_document
---
The ultimate goal here it to see if there's a noticeable impact on COVID-19 case data as the different states start to reopen.
```{r, include=FALSE}
# Load libraries
library(tidyverse)
library(lubridate)
library(data.table) # need this for the "%like%"function
library(wesanderson)
library(scales)
library(ggpubr)
theme_set(theme_pubr())
```
```{r}
# Load John Hopkins USA case data
jhu_latest_raw <- read.csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_US.csv")
jhu_latest_deaths_raw <- read.csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_US.csv")
```
```{r, warning=FALSE}
# do some data cleaning
jhu_latest <- jhu_latest_raw
jhu_latest_deaths <- jhu_latest_deaths_raw
jhu_latest <- jhu_latest %>% filter(iso3 == "USA") %>%
select(-UID, -iso2, -iso3, -code3, -FIPS, -Admin2, -Country_Region, -Lat, -Long_, -Combined_Key)
jhu_latest_deaths <- jhu_latest_deaths %>% filter(iso3 == "USA") %>%
select(-UID, -iso2, -iso3, -code3, -FIPS, -Admin2, -Country_Region, -Lat, -Long_, -Combined_Key)
by_state <- jhu_latest %>%
group_by(Province_State) %>%
summarise_all(funs(sum(.))) %>%
column_to_rownames(var = "Province_State") %>%
t() %>%
as.data.frame() %>%
rownames_to_column() %>%
mutate(date = str_sub(rowname, 2)) %>%
select(date, everything()) %>%
select(-rowname) %>%
mutate(date = mdy(date)) %>%
filter(date >="2020-03-01")
by_state_deaths <- jhu_latest_deaths %>%
group_by(Province_State) %>%
summarise_all(funs(sum(.))) %>%
column_to_rownames(var = "Province_State") %>%
t() %>%
as.data.frame() %>%
rownames_to_column() %>%
mutate(date = str_sub(rowname, 2)) %>%
select(date, everything()) %>%
select(-rowname) %>%
mutate(date = mdy(date)) %>%
filter(date >="2020-03-01")
```
```{r}
# Some US states did not declare an official start date and/or end date of lockdown, and therefore we set default dates for these that are far in the future to prevent them from plotting.
# function for plotting state data
plot_state_reopening <- function(state_name, lockdown_date="2100-12-31", reopen_date="2100-12-31", memorial_day = "2020-05-25", george_floyd_protests_start = "2020-05-27", july_fourth = "2020-07-04") {
state <- by_state %>% select(date, all_of(state_name))
ggplot(state, aes_(x = as.name(names(state)[1]), y = as.name(names(state)[2]))) +
geom_bar(stat= "identity") +
scale_x_date(date_breaks = "3 weeks") +
ylab("Number of Cases") +
xlab("Date") +
scale_y_continuous(labels = comma) +
geom_vline(xintercept = as.Date(lockdown_date), linetype="dotted",
color = "blue", size=1) +
geom_vline(xintercept = as.Date(reopen_date), linetype="dotted",
color = "green", size=1) +
geom_vline(xintercept = as.Date(memorial_day), linetype="dotted",
color = "red", size=1) +
geom_vline(xintercept = as.Date(george_floyd_protests_start), linetype="solid",
color = "orange", size=1) +
geom_vline(xintercept = as.Date(july_fourth), linetype="dotted",
color = "purple", size=1) +
#annotate("rect", xmin = as.Date(lockdown_date), xmax = as.Date(reopen_date), ymin = 0, ymax = Inf,
# alpha = .2) +
theme_light() +
labs(title = "Confirmed Cases (Cumulative)", subtitle = state_name) +
theme(axis.text.x=element_text(angle=60, hjust=1))
}
plot_state_reopening_log <- function(state_name, lockdown_date="2100-12-31", reopen_date="2100-12-31", memorial_day = "2020-05-25", george_floyd_protests_start = "2020-05-27", july_fourth = "2020-07-04") {
state <- by_state %>% select(date, all_of(state_name))
ggplot(state, aes_(x = as.name(names(state)[1]), y = as.name(names(state)[2]))) +
geom_line() +
scale_x_date(date_breaks = "3 weeks") +
ylab("Cases (log scale)") +
xlab("Week") +
scale_y_continuous(trans = "log10", labels = comma) +
geom_vline(xintercept = as.Date(lockdown_date), linetype="dotted",
color = "blue", size=1) +
geom_vline(xintercept = as.Date(reopen_date), linetype="dotted",
color = "green", size=1) +
geom_vline(xintercept = as.Date(memorial_day), linetype="dotted",
color = "red", size=1) +
geom_vline(xintercept = as.Date(george_floyd_protests_start), linetype="solid",
color = "orange", size=1) +
geom_vline(xintercept = as.Date(july_fourth), linetype="dotted",
color = "purple", size=1) +
theme_light() +
labs(title = "Confirmed Cases (Rate of Change)", subtitle = state_name) +
theme(axis.text.x=element_text(angle=60, hjust=1))
}
# deaths
plot_state_deaths_reopening <- function(state_name, lockdown_date="2100-12-31", reopen_date="2100-12-31", memorial_day = "2020-05-25", george_floyd_protests_start = "2020-05-27", july_fourth = "2020-07-04") {
state <- by_state_deaths %>% select(date, all_of(state_name))
ggplot(state, aes_(x = as.name(names(state)[1]), y = as.name(names(state)[2]))) +
geom_bar(stat= "identity") +
scale_x_date(date_breaks = "3 weeks") +
ylab("Number of Cases") +
xlab("Date") +
scale_y_continuous(labels = comma) +
geom_vline(xintercept = as.Date(lockdown_date), linetype="dotted",
color = "blue", size=1) +
geom_vline(xintercept = as.Date(reopen_date), linetype="dotted",
color = "green", size=1) +
geom_vline(xintercept = as.Date(memorial_day), linetype="dotted",
color = "red", size=1) +
geom_vline(xintercept = as.Date(george_floyd_protests_start), linetype="solid",
color = "orange", size=1) +
geom_vline(xintercept = as.Date(july_fourth), linetype="dotted",
color = "purple", size=1) +
#annotate("rect", xmin = as.Date(lockdown_date), xmax = as.Date(reopen_date), ymin = 0, ymax = Inf,
# alpha = .2) +
theme_light() +
labs(title = "Confirmed Deaths (Cumulative)", subtitle = state_name) +
theme(axis.text.x=element_text(angle=60, hjust=1))
}
plot_state_deaths_reopening_log <- function(state_name, lockdown_date="2100-12-31", reopen_date="2100-12-31", memorial_day = "2020-05-25", george_floyd_protests_start = "2020-05-27", july_fourth = "2020-07-04") {
state <- by_state_deaths %>% select(date, all_of(state_name))
ggplot(state, aes_(x = as.name(names(state)[1]), y = as.name(names(state)[2]))) +
geom_line() +
scale_x_date(date_breaks = "3 weeks") +
ylab("Cases (log scale)") +
xlab("Week") +
scale_y_continuous(trans = "log10", labels = comma_format(digits = 0)) +
geom_vline(xintercept = as.Date(lockdown_date), linetype="dotted",
color = "blue", size=1) +
geom_vline(xintercept = as.Date(reopen_date), linetype="dotted",
color = "green", size=1) +
geom_vline(xintercept = as.Date(memorial_day), linetype="dotted",
color = "red", size=1) +
geom_vline(xintercept = as.Date(george_floyd_protests_start), linetype="solid",
color = "orange", size=1) +
geom_vline(xintercept = as.Date(july_fourth), linetype="dotted",
color = "purple", size=1) +
theme_light() +
labs(title = "Confirmed Deaths (Rate of Change)", subtitle = state_name) +
theme(axis.text.x=element_text(angle=60, hjust=1))
}
```
Legend for Vertical Lines:
* Blue dotted: the date when the state first went into lockdown
* Green dotted: the date when the state started to reopen
* Red dotted: Memorial Day (lots of reports in the press about people not observing social distancing)
* Magenta solid: Nationwide anti-racism (BLM) protests erupt across the US (and the world) Protests start after George Floyd is killed by a police man kneeling on his neck and asphyxiating him.
* Purple dotted: Fourth of July
## Alabama
```{r, warning=FALSE}
# call the state_reopen function for individual states
plot_state_reopening("Alabama","2020-04-04", "2020-04-30")
plot_state_reopening_log("Alabama","2020-04-04", "2020-04-30")
AL_cases <- plot_state_reopening("Alabama","2020-04-04", "2020-04-30")
AL_cases_log <- plot_state_reopening_log("Alabama","2020-04-04", "2020-04-30")
AL_deaths <- plot_state_deaths_reopening("Alabama","2020-04-04", "2020-04-30")
AL_deaths_log <- plot_state_deaths_reopening_log("Alabama","2020-04-04", "2020-04-30")
ggarrange(AL_deaths, AL_deaths_log,
ncol = 2, nrow = 1)
```
## Alaska
```{r, warning=FALSE}
# call the state_reopen function for individual states
AK_cases <- plot_state_reopening("Alaska","2020-03-28", "2020-04-24")
AK_cases_log <- plot_state_reopening_log("Alaska","2020-03-28", "2020-04-24")
AK_deaths <- plot_state_deaths_reopening("Alaska","2020-03-28", "2020-04-24")
AK_deaths_log <- plot_state_deaths_reopening_log("Alaska","2020-03-28", "2020-04-24")
AK_cases
AK_cases_log
ggarrange(AK_deaths, AK_deaths_log,
ncol = 2, nrow = 1)
```
## Arizona
```{r, warning=FALSE}
# call the state_reopen function for individual states
AZ_cases <- plot_state_reopening("Arizona","2020-03-31", "2020-05-15")
AZ_cases_log <- plot_state_reopening_log("Arizona","2020-03-31", "2020-05-15")
AZ_deaths <- plot_state_deaths_reopening("Arizona","2020-03-31", "2020-05-15")
AZ_deaths_log <- plot_state_deaths_reopening_log("Arizona","2020-03-31", "2020-05-15")
AZ_cases
AZ_cases_log
ggarrange(AZ_deaths, AZ_deaths_log,
ncol = 2, nrow = 1)
```
## Arkansas
```{r, warning=FALSE}
# call the state_reopen function for individual states
AR_cases <- plot_state_reopening("Arkansas",, "2020-05-06")
AR_cases_log <- plot_state_reopening_log("Arkansas", , "2020-05-06")
AR_deaths <- plot_state_deaths_reopening("Arkansas", , "2020-05-06")
AR_deaths_log <- plot_state_deaths_reopening_log("Arkansas", , "2020-05-06")
AR_cases
AR_cases_log
ggarrange(AR_deaths, AR_deaths_log,
ncol = 2, nrow = 1)
```
## California
```{r, warning=FALSE}
# call the state_reopen function for individual states
CA_cases <- plot_state_reopening("California","2020-03-19", "2020-05-12")
CA_cases_log <- plot_state_reopening_log("California","2020-03-19", "2020-05-12")
CA_deaths <- plot_state_deaths_reopening("California","2020-03-19", "2020-05-12")
CA_deaths_log <- plot_state_deaths_reopening_log("California","2020-03-19", "2020-05-12")
CA_cases
CA_cases_log
ggarrange(CA_deaths, CA_deaths_log,
ncol = 2, nrow = 1)
```
## Colorado
```{r, warning=FALSE}
# call the state_reopen function for individual states
CO_cases <- plot_state_reopening("Colorado","2020-03-26", "2020-04-26")
CO_cases_log <- plot_state_reopening_log("Colorado","2020-03-26", "2020-04-26")
CO_deaths <- plot_state_deaths_reopening("Colorado","2020-03-26", "2020-04-26")
CO_deaths_log <- plot_state_deaths_reopening_log("Colorado","2020-03-26", "2020-04-26")
CO_cases
CO_cases_log
ggarrange(CO_deaths, CO_deaths_log,
ncol = 2, nrow = 1)
```
## Connecticut
```{r, warning=FALSE}
# call the state_reopen function for individual states
CT_cases <- plot_state_reopening("Connecticut","2020-03-23", "2020-05-20")
CT_cases_log <- plot_state_reopening_log("Connecticut","2020-03-23", "2020-05-20")
CT_deaths <- plot_state_deaths_reopening("Connecticut","2020-03-23", "2020-05-20")
CT_deaths_log <- plot_state_deaths_reopening_log("Connecticut","2020-03-23", "2020-05-20")
CT_cases
CT_cases_log
ggarrange(CT_deaths, CT_deaths_log,
ncol = 2, nrow = 1)
```
## Delaware
```{r, warning=FALSE}
# call the state_reopen function for individual states
DE_cases <- plot_state_reopening("Delaware","2020-03-24", "2020-05-31")
DE_cases_log <- plot_state_reopening_log("Delaware","2020-03-24", "2020-05-31")
DE_deaths <- plot_state_deaths_reopening("Delaware","2020-03-24", "2020-05-31")
DE_deaths_log <- plot_state_deaths_reopening_log("Delaware","2020-03-24", "2020-05-31")
DE_cases
DE_cases_log
ggarrange(DE_deaths, DE_deaths_log,
ncol = 2, nrow = 1)
```
## District of Columbia
```{r, warning=FALSE}
# call the state_reopen function for individual states
DC_cases <- plot_state_reopening("District of Columbia","2020-04-01", "2020-06-08")
DC_cases_log <- plot_state_reopening_log("District of Columbia","2020-04-01", "2020-06-08")
DC_deaths <- plot_state_deaths_reopening("District of Columbia","2020-04-01", "2020-06-08")
DC_deaths_log <- plot_state_deaths_reopening_log("District of Columbia","2020-04-01", "2020-06-08")
DC_cases
DC_cases_log
ggarrange(DC_deaths, DC_deaths_log,
ncol = 2, nrow = 1)
```
## Florida
```{r, warning=FALSE}
# call the state_reopen function for individual states
FL_cases <- plot_state_reopening("Florida","2020-04-03", "2020-05-04")
FL_cases_log <- plot_state_reopening_log("Florida","2020-04-03", "2020-05-04")
FL_deaths <- plot_state_deaths_reopening("Florida","2020-04-03", "2020-05-04")
FL_deaths_log <- plot_state_deaths_reopening_log("Florida","2020-04-03", "2020-05-04")
FL_cases
FL_cases_log
ggarrange(FL_deaths, FL_deaths_log,
ncol = 2, nrow = 1)
```
## Georgia
```{r, warning=FALSE}
# call the state_reopen function for individual states
GA_cases <- plot_state_reopening("Georgia","2020-04-03", "2020-04-24")
GA_cases_log <- plot_state_reopening_log("Georgia","2020-04-03", "2020-04-24")
GA_deaths <- plot_state_deaths_reopening("Georgia","2020-04-03", "2020-04-24")
GA_deaths_log <- plot_state_deaths_reopening_log("Georgia","2020-04-03", "2020-04-24")
GA_cases
GA_cases_log
ggarrange(GA_deaths, GA_deaths_log,
ncol = 2, nrow = 1)
```
## Hawaii
```{r, warning=FALSE}
# call the state_reopen function for individual states
HI_cases <- plot_state_reopening("Hawaii","2020-03-25", "2020-05-07")
HI_cases_log <- plot_state_reopening_log("Hawaii","2020-03-25", "2020-05-07")
HI_deaths <- plot_state_deaths_reopening("Hawaii","2020-03-25", "2020-05-07")
HI_deaths_log <- plot_state_deaths_reopening_log("Hawaii","2020-03-25", "2020-05-07")
HI_cases
HI_cases_log
ggarrange(HI_deaths, HI_deaths_log,
ncol = 2, nrow = 1)
```
## Idaho
```{r, warning=FALSE}
# call the state_reopen function for individual states
ID_cases <- plot_state_reopening("Idaho","2020-03-25", "2020-04-30")
ID_cases_log <- plot_state_reopening_log("Idaho","2020-03-25", "2020-04-30")
ID_deaths <- plot_state_deaths_reopening("Idaho","2020-03-25", "2020-04-30")
ID_deaths_log <- plot_state_deaths_reopening_log("Idaho","2020-03-25", "2020-04-30")
ID_cases
ID_cases_log
ggarrange(ID_deaths, ID_deaths_log,
ncol = 2, nrow = 1)
```
## Illinois
```{r, warning=FALSE}
# call the state_reopen function for individual states
IL_cases <- plot_state_reopening("Illinois","2020-03-21", "2020-05-29")
IL_cases_log <- plot_state_reopening_log("Illinois","2020-03-21", "2020-05-29")
IL_deaths <- plot_state_deaths_reopening("Illinois","2020-03-21", "2020-05-29")
IL_deaths_log <- plot_state_deaths_reopening_log("Illinois","2020-03-21", "2020-05-29")
IL_cases
IL_cases_log
ggarrange(IL_deaths, IL_deaths_log,
ncol = 2, nrow = 1)
```
## Indiana
```{r, warning=FALSE}
# call the state_reopen function for individual states
IN_cases <- plot_state_reopening("Indiana","2020-03-24", "2020-05-04")
IN_cases_log <- plot_state_reopening_log("Indiana","2020-03-24", "2020-05-04")
IN_deaths <- plot_state_deaths_reopening("Indiana","2020-03-24", "2020-05-04")
IN_deaths_log <- plot_state_deaths_reopening_log("Indiana","2020-03-24", "2020-05-04")
IN_cases
IN_cases_log
ggarrange(IN_deaths, IN_deaths_log,
ncol = 2, nrow = 1)
```
## Iowa
```{r, warning=FALSE}
# call the state_reopen function for individual states
IA_cases <- plot_state_reopening("Iowa", , "2020-05-01")
IA_cases_log <- plot_state_reopening_log("Iowa", , "2020-05-01")
IA_deaths <- plot_state_deaths_reopening("Iowa", , "2020-05-01")
IA_deaths_log <- plot_state_deaths_reopening_log("Iowa", , "2020-05-01")
IA_cases
IA_cases_log
ggarrange(IA_deaths, IA_deaths_log,
ncol = 2, nrow = 1)
```
## Kansas
```{r, warning=FALSE}
# call the state_reopen function for individual states
KS_cases <- plot_state_reopening("Kansas", "2020-03-30", "2020-05-04")
KS_cases_log <- plot_state_reopening_log("Kansas", "2020-03-30", "2020-05-04")
KS_deaths <- plot_state_deaths_reopening("Kansas", "2020-03-30", "2020-05-04")
KS_deaths_log <- plot_state_deaths_reopening_log("Kansas", "2020-03-30", "2020-05-04")
KS_cases
KS_cases_log
ggarrange(KS_deaths, KS_deaths_log,
ncol = 2, nrow = 1)
```
## Kentucky
```{r, warning=FALSE}
# call the state_reopen function for individual states
KY_cases <- plot_state_reopening("Kentucky", "2020-03-26", "2020-05-20")
KY_cases_log <- plot_state_reopening_log("Kentucky", "2020-03-26", "2020-05-20")
KY_deaths <- plot_state_deaths_reopening("Kentucky", "2020-03-26", "2020-05-20")
KY_deaths_log <- plot_state_deaths_reopening_log("Kentucky", "2020-03-26", "2020-05-20")
KY_cases
KY_cases_log
ggarrange(KY_deaths, KY_deaths_log,
ncol = 2, nrow = 1)
```
## Louisiana
```{r, warning=FALSE}
# call the state_reopen function for individual states
LA_cases <- plot_state_reopening("Louisiana", "2020-03-23", "2020-05-15")
LA_cases_log <- plot_state_reopening_log("Louisiana", "2020-03-23", "2020-05-15")
LA_deaths <- plot_state_deaths_reopening("Louisiana", "2020-03-23", "2020-05-15")
LA_deaths_log <- plot_state_deaths_reopening_log("Louisiana", "2020-03-23", "2020-05-15")
LA_cases
LA_cases_log
ggarrange(LA_deaths, LA_deaths_log,
ncol = 2, nrow = 1)
```
## Maine
```{r, warning=FALSE}
# call the state_reopen function for individual states
ME_cases <- plot_state_reopening("Maine", "2020-04-02", "2020-05-31")
ME_cases_log <- plot_state_reopening_log("Maine", "2020-04-02", "2020-05-31")
ME_deaths <- plot_state_deaths_reopening("Maine", "2020-04-02", "2020-05-31")
ME_deaths_log <- plot_state_deaths_reopening_log("Maine", "2020-04-02", "2020-05-31")
ME_cases
ME_cases_log
ggarrange( ME_deaths, ME_deaths_log,
ncol = 2, nrow = 1)
```
## Maryland
```{r, warning=FALSE}
# call the state_reopen function for individual states
MD_cases <- plot_state_reopening("Maryland", "2020-03-30", "2020-05-15")
MD_cases_log <- plot_state_reopening_log("Maryland", "2020-03-30", "2020-05-15")
MD_deaths <- plot_state_deaths_reopening("Maryland", "2020-03-30", "2020-05-15")
MD_deaths_log <- plot_state_deaths_reopening_log("Maryland", "2020-03-30", "2020-05-15")
MD_cases
MD_cases_log
ggarrange(MD_deaths, MD_deaths_log,
ncol = 2, nrow = 1)
```
## Massachusetts
```{r, warning=FALSE}
# call the state_reopen function for individual states
MA_cases <- plot_state_reopening("Massachusetts", "2020-03-24", "2020-05-18")
MA_cases_log <- plot_state_reopening_log("Massachusetts", "2020-03-24", "2020-05-18")
MA_deaths <- plot_state_deaths_reopening("Massachusetts", "2020-03-24", "2020-05-18")
MA_deaths_log <- plot_state_deaths_reopening_log("Massachusetts", "2020-03-24", "2020-05-18")
MA_cases
MA_cases_log
ggarrange( MA_deaths, MA_deaths_log,
ncol = 2, nrow = 1)
```
## Michigan
```{r, warning=FALSE}
# call the state_reopen function for individual states
MI_cases <- plot_state_reopening("Michigan", "2020-03-24", "2020-05-11")
MI_cases_log <- plot_state_reopening_log("Michigan", "2020-03-24", "2020-05-11")
MI_deaths <- plot_state_deaths_reopening("Michigan", "2020-03-24", "2020-05-11")
MI_deaths_log <- plot_state_deaths_reopening_log("Michigan", "2020-03-24", "2020-05-11")
MI_cases
MI_cases_log
ggarrange( MI_deaths, MI_deaths_log,
ncol = 2, nrow = 1)
```
## Minnesota
```{r, warning=FALSE}
# call the state_reopen function for individual states
MN_cases <- plot_state_reopening("Minnesota", "2020-03-27", "2020-04-27")
MN_cases_log <- plot_state_reopening_log("Minnesota", "2020-03-27", "2020-04-27")
MN_deaths <- plot_state_deaths_reopening("Minnesota", "2020-03-27", "2020-04-27")
MN_deaths_log <- plot_state_deaths_reopening_log("Minnesota", "2020-03-27", "2020-04-27")
MN_cases
MN_cases_log
ggarrange(MN_deaths, MN_deaths_log,
ncol = 2, nrow = 1)
```
## Mississippi
```{r, warning=FALSE}
# call the state_reopen function for individual states
MS_cases <- plot_state_reopening("Mississippi", "2020-04-03", "2020-04-27")
MS_cases_log <- plot_state_reopening_log("Mississippi", "2020-04-03", "2020-04-27")
MS_deaths <- plot_state_deaths_reopening("Mississippi", "2020-04-03", "2020-04-27")
MS_deaths_log <- plot_state_deaths_reopening_log("Mississippi", "2020-04-03", "2020-04-27")
MS_cases
MS_cases_log
ggarrange(MS_deaths, MS_deaths_log,
ncol = 2, nrow = 1)
```
## Missouri
```{r, warning=FALSE}
# call the state_reopen function for individual states
MO_cases <- plot_state_reopening("Missouri", "2020-04-06", "2020-05-03")
MO_cases_log <- plot_state_reopening_log("Missouri", "2020-04-06", "2020-05-03")
MO_deaths <- plot_state_deaths_reopening("Missouri", "2020-04-06", "2020-05-03")
MO_deaths_log <- plot_state_deaths_reopening_log("Missouri", "2020-04-06", "2020-05-03")
MO_cases
MO_cases_log
ggarrange(MO_deaths, MO_deaths_log,
ncol = 2, nrow = 1)
```
## Montana
```{r, warning=FALSE}
# call the state_reopen function for individual states
MT_cases <- plot_state_reopening("Montana", "2020-03-28", "2020-04-26")
MT_cases_log <- plot_state_reopening_log("Montana", "2020-03-28", "2020-04-26")
MT_deaths <- plot_state_deaths_reopening("Montana", "2020-03-28", "2020-04-26")
MT_deaths_log <- plot_state_deaths_reopening_log("Montana", "2020-03-28", "2020-04-26")
MT_cases
MT_cases_log
ggarrange(MT_deaths, MT_deaths_log,
ncol = 2, nrow = 1)
```
## Nebraska
```{r, warning=FALSE}
# call the state_reopen function for individual states
NE_cases <- plot_state_reopening("Nebraska", , "2020-05-04")
NE_cases_log <- plot_state_reopening_log("Nebraska", , "2020-05-04")
NE_deaths <- plot_state_deaths_reopening("Nebraska", , "2020-05-04")
NE_deaths_log <- plot_state_deaths_reopening_log("Nebraska", , "2020-05-04")
NE_cases
NE_cases_log
ggarrange(NE_deaths, NE_deaths_log,
ncol = 2, nrow = 1)
```
## Nevada
```{r, warning=FALSE}
# call the state_reopen function for individual states
NV_cases <- plot_state_reopening("Nevada", "2020-04-01", "2020-05-09")
NV_cases_log <- plot_state_reopening_log("Nevada", "2020-04-01", "2020-05-09")
NV_deaths <- plot_state_deaths_reopening("Nevada", "2020-04-01", "2020-05-09")
NV_deaths_log <- plot_state_deaths_reopening_log("Nevada", "2020-04-01", "2020-05-09")
NV_cases
NV_cases_log
ggarrange(NV_deaths, NV_deaths_log,
ncol = 2, nrow = 1)
```
## New Hampshire
```{r, warning=FALSE}
# call the state_reopen function for individual states
NH_cases <- plot_state_reopening("New Hampshire", "2020-03-27", "2020-05-11")
NH_cases_log <- plot_state_reopening_log("New Hampshire", "2020-03-27", "2020-05-11")
NH_deaths <- plot_state_deaths_reopening("New Hampshire", "2020-03-27", "2020-05-11")
NH_deaths_log <- plot_state_deaths_reopening_log("New Hampshire", "2020-03-27", "2020-05-11")
NH_cases
NH_cases_log
ggarrange(NH_deaths, NH_deaths_log,
ncol = 2, nrow = 1)
```
## New Jersey
```{r, warning=FALSE}
# call the state_reopen function for individual states
NJ_cases <- plot_state_reopening("New Jersey", "2020-03-21", )
NJ_cases_log <- plot_state_reopening_log("New Jersey", "2020-03-21", )
NJ_deaths <- plot_state_deaths_reopening("New Jersey", "2020-03-21", )
NJ_deaths_log <- plot_state_deaths_reopening_log("New Jersey", "2020-03-21", )
NJ_cases
NJ_cases_log
ggarrange(NJ_deaths, NJ_deaths_log,
ncol = 2, nrow = 1)
```
## New Mexico
```{r, warning=FALSE}
# call the state_reopen function for individual states
NM_cases <- plot_state_reopening("New Mexico", "2020-03-24", "2020-05-16")
NM_cases_log <- plot_state_reopening_log("New Mexico", "2020-03-24", "2020-05-16")
NM_deaths <- plot_state_deaths_reopening("New Mexico", "2020-03-24", "2020-05-16")
NM_deaths_log <- plot_state_deaths_reopening_log("New Mexico", "2020-03-24", "2020-05-16")
NM_cases
NM_cases_log
ggarrange( NM_deaths, NM_deaths_log,
ncol = 2, nrow = 1)
```
## New York
```{r, warning=FALSE}
# call the state_reopen function for individual states
NY_cases <- plot_state_reopening("New York", "2020-03-22", "2020-05-15")
NY_cases_log <- plot_state_reopening_log("New York", "2020-03-22", "2020-05-15")
NY_deaths <- plot_state_deaths_reopening("New York", "2020-03-22", "2020-05-15")
NY_deaths_log <- plot_state_deaths_reopening_log("New York", "2020-03-22", "2020-05-15")
NY_cases
NY_cases_log
ggarrange( NY_deaths, NY_deaths_log,
ncol = 2, nrow = 1)
```
## North Carolina
```{r, warning=FALSE}
# call the state_reopen function for individual states
NC_cases <- plot_state_reopening("North Carolina", "2020-03-30", "2020-05-22")
NC_cases_log <- plot_state_reopening_log("North Carolina", "2020-03-30", "2020-05-22")
NC_deaths <- plot_state_deaths_reopening("North Carolina", "2020-03-30", "2020-05-22")
NC_deaths_log <- plot_state_deaths_reopening_log("North Carolina", "2020-03-30", "2020-05-22")
NC_cases
NC_cases_log
ggarrange(NC_deaths, NC_deaths_log,
ncol = 2, nrow = 1)
```
## North Dakota
```{r, warning=FALSE}
# call the state_reopen function for individual states
ND_cases <- plot_state_reopening("North Dakota", , "2020-05-01")
ND_cases_log <- plot_state_reopening_log("North Dakota", , "2020-05-01")
ND_deaths <- plot_state_deaths_reopening("North Dakota", , "2020-05-01")
ND_deaths_log <- plot_state_deaths_reopening_log("North Dakota", , "2020-05-01")
ND_cases
ND_cases_log
ggarrange(ND_deaths, ND_deaths_log,
ncol = 2, nrow = 1)
```
## Ohio
```{r, warning=FALSE}
# call the state_reopen function for individual states
OH_cases <- plot_state_reopening("Ohio", "2020-03-23", "2020-05-29")
OH_cases_log <- plot_state_reopening_log("Ohio", "2020-03-23", "2020-05-29")
OH_deaths <- plot_state_deaths_reopening("Ohio", "2020-03-23", "2020-05-29")
OH_deaths_log <- plot_state_deaths_reopening_log("Ohio", "2020-03-23", "2020-05-29")
OH_cases
OH_cases_log
ggarrange(OH_deaths, OH_deaths_log,
ncol = 2, nrow = 1)
```
## Oklahoma
```{r, warning=FALSE}
# call the state_reopen function for individual states
OK_cases <- plot_state_reopening("Oklahoma", "2020-04-06", "2020-04-24")
OK_cases_log <- plot_state_reopening_log("Oklahoma", "2020-04-06", "2020-04-24")
OK_deaths <- plot_state_deaths_reopening("Oklahoma", "2020-04-06", "2020-04-24")
OK_deaths_log <- plot_state_deaths_reopening_log("Oklahoma", "2020-04-06", "2020-04-24")
OK_cases
OK_cases_log
ggarrange(OK_deaths, OK_deaths_log,
ncol = 2, nrow = 1)
```
## Oregon
```{r, warning=FALSE}
# call the state_reopen function for individual states
OR_cases <- plot_state_reopening("Oregon", "2020-03-23", "2020-05-15")
OR_cases_log <- plot_state_reopening_log("Oregon", "2020-03-23", "2020-05-15")
OR_deaths <- plot_state_deaths_reopening("Oregon", "2020-03-23", "2020-05-15")
OR_deaths_log <- plot_state_deaths_reopening_log("Oregon", "2020-03-23", "2020-05-15")
OR_cases
OR_cases_log
ggarrange(OR_deaths, OR_deaths_log,
ncol = 2, nrow = 1)
```
## Pennsylvania
```{r, warning=FALSE}
# call the state_reopen function for individual states
PA_cases <- plot_state_reopening("Pennsylvania", "2020-04-01", "2020-06-04")
PA_cases_log <- plot_state_reopening_log("Pennsylvania", "2020-04-01", "2020-06-04")
PA_deaths <- plot_state_deaths_reopening("Pennsylvania", "2020-04-01", "2020-06-04")
PA_deaths_log <- plot_state_deaths_reopening_log("Pennsylvania", "2020-04-01", "2020-06-04")
PA_cases
PA_cases_log
ggarrange(PA_deaths, PA_deaths_log,
ncol = 2, nrow = 1)
```
## Rhode Island
```{r, warning=FALSE}
# call the state_reopen function for individual states
RI_cases <- plot_state_reopening("Rhode Island", "2020-03-28", "2020-05-08")
RI_cases_log <- plot_state_reopening_log("Rhode Island", "2020-03-28", "2020-05-08")
RI_deaths <- plot_state_deaths_reopening("Rhode Island", "2020-03-28", "2020-05-08")
RI_deaths_log <- plot_state_deaths_reopening_log("Rhode Island", "2020-03-28", "2020-05-08")
RI_cases
RI_cases_log
ggarrange(RI_deaths, RI_deaths_log,
ncol = 2, nrow = 1)
```
## South Carolina
```{r, warning=FALSE}
# call the state_reopen function for individual states
SC_cases <- plot_state_reopening("South Carolina", "2020-04-07", "2020-05-04")
SC_cases_log <- plot_state_reopening_log("South Carolina", "2020-04-07", "2020-05-04")
SC_deaths <- plot_state_deaths_reopening("South Carolina", "2020-04-07", "2020-05-04")
SC_deaths_log <- plot_state_deaths_reopening_log("South Carolina", "2020-04-07", "2020-05-04")
SC_cases
SC_cases_log
ggarrange(SC_deaths, SC_deaths_log,
ncol = 2, nrow = 1)
```
## South Dakota
```{r, warning=FALSE}
# call the state_reopen function for individual states
SD_cases <- plot_state_reopening("South Dakota", , )
SD_cases_log <- plot_state_reopening_log("South Dakota", , )
SD_deaths <- plot_state_deaths_reopening("South Dakota", , )
SD_deaths_log <- plot_state_deaths_reopening_log("South Dakota", , )
SD_cases
SD_cases_log
ggarrange( SD_deaths, SD_deaths_log,
ncol = 2, nrow = 1)
```
## Tennessee
```{r, warning=FALSE}
# call the state_reopen function for individual states
TN_cases <- plot_state_reopening("Tennessee", "2020-03-31", "2020-04-24")
TN_cases_log <- plot_state_reopening_log("Tennessee", "2020-03-31", "2020-04-24")
TN_deaths <- plot_state_deaths_reopening("Tennessee", "2020-03-31", "2020-04-24")
TN_deaths_log <- plot_state_deaths_reopening_log("Tennessee", "2020-03-31", "2020-04-24")
TN_cases
TN_cases_log
ggarrange(TN_deaths, TN_deaths_log,
ncol = 2, nrow = 1)
```
## Texas
```{r, warning=FALSE}
# call the state_reopen function for individual states
TX_cases <- plot_state_reopening("Texas", "2020-04-02", "2020-04-30")
TX_cases_log <- plot_state_reopening_log("Texas", "2020-04-02", "2020-04-30")
TX_deaths <- plot_state_deaths_reopening("Texas", "2020-04-02", "2020-04-30")
TX_deaths_log <- plot_state_deaths_reopening_log("Texas", "2020-04-02", "2020-04-30")
TX_cases
TX_cases_log
ggarrange(TX_deaths, TX_deaths_log,
ncol = 2, nrow = 1)
```
## Utah
```{r, warning=FALSE}
# call the state_reopen function for individual states
UT_cases <- plot_state_reopening("Utah", "2020-04-01", "2020-05-01")
UT_cases_log <- plot_state_reopening_log("Utah", "2020-04-01", "2020-05-01")
UT_deaths <- plot_state_deaths_reopening("Utah", "2020-04-01", "2020-05-01")
UT_deaths_log <- plot_state_deaths_reopening_log("Utah", "2020-04-01", "2020-05-01")
UT_cases
UT_cases_log
ggarrange(UT_deaths, UT_deaths_log,
ncol = 2, nrow = 1)
```
## Vermont
```{r, warning=FALSE}
# call the state_reopen function for individual states
VT_cases <- plot_state_reopening("Vermont", "2020-03-25", "2020-05-15")
VT_cases_log <- plot_state_reopening_log("Vermont", "2020-03-25", "2020-05-15")
VT_deaths <- plot_state_deaths_reopening("Vermont", "2020-03-25", "2020-05-15")
VT_deaths_log <- plot_state_deaths_reopening_log("Vermont", "2020-03-25", "2020-05-15")
VT_cases
VT_cases_log
ggarrange(VT_deaths, VT_deaths_log,
ncol = 2, nrow = 1)
```
## Virginia
```{r, warning=FALSE}
# call the state_reopen function for individual states
VA_cases <- plot_state_reopening("Virginia", "2020-03-30", "2020-05-15")
VA_cases_log <- plot_state_reopening_log("Virginia", "2020-03-30", "2020-05-15")
VA_deaths <- plot_state_deaths_reopening("Virginia", "2020-03-30", "2020-05-15")
VA_deaths_log <- plot_state_deaths_reopening_log("Virginia", "2020-03-30", "2020-05-15")
VA_cases
VA_cases_log
ggarrange(VA_deaths, VA_deaths_log,
ncol = 2, nrow = 1)
```
## Washington
```{r, warning=FALSE}
# call the state_reopen function for individual states
WA_cases <- plot_state_reopening("Washington", "2020-03-23", "2020-05-11")
WA_cases_log <- plot_state_reopening_log("Washington", "2020-03-23", "2020-05-11")
WA_deaths <- plot_state_deaths_reopening("Washington", "2020-03-23", "2020-05-11")
WA_deaths_log <- plot_state_deaths_reopening_log("Washington", "2020-03-23", "2020-05-11")
WA_cases
WA_cases_log
ggarrange(WA_deaths, WA_deaths_log,
ncol = 2, nrow = 1)
```
## West Virginia
```{r, warning=FALSE}
# call the state_reopen function for individual states
WV_cases <- plot_state_reopening("West Virginia", "2020-03-24", "2020-05-04")
WV_cases_log <- plot_state_reopening_log("West Virginia", "2020-03-24", "2020-05-04")
WV_deaths <- plot_state_deaths_reopening("West Virginia", "2020-03-24", "2020-05-04")
WV_deaths_log <- plot_state_deaths_reopening_log("West Virginia", "2020-03-24", "2020-05-04")
WV_cases
WV_cases_log
ggarrange(WV_deaths, WV_deaths_log,
ncol = 2, nrow = 1)
```
## Wisconsin
```{r, warning=FALSE}
# call the state_reopen function for individual states
WI_cases <- plot_state_reopening("Wisconsin", "2020-03-25", "2020-05-13")
WI_cases_log <- plot_state_reopening_log("Wisconsin", "2020-03-25", "2020-05-13")
WI_deaths <- plot_state_deaths_reopening("Wisconsin", "2020-03-25", "2020-05-13")
WI_deaths_log <- plot_state_deaths_reopening_log("Wisconsin", "2020-03-25", "2020-05-13")
WI_cases
WI_cases_log
ggarrange(WI_deaths, WI_deaths_log,
ncol = 2, nrow = 1)
```
NOTE: Wisconsin stay-at-home order struck down on May 13.
## Wyoming
```{r, warning=FALSE}
# call the state_reopen function for individual states
WY_cases <- plot_state_reopening("Wyoming", "2020-03-28", "2020-05-01")
WY_cases_log <- plot_state_reopening_log("Wyoming", "2020-03-28", "2020-05-01")
WY_deaths <- plot_state_deaths_reopening("Wyoming", "2020-03-28", "2020-05-01")
WY_deaths_log <- plot_state_deaths_reopening_log("Wyoming", "2020-03-28", "2020-05-01")
WY_cases
WY_cases_log
ggarrange(WY_deaths, WY_deaths_log,
ncol = 2, nrow = 1)
```
<!-- ```{r} -->
<!-- # plot select states (initially selecting some of the states where people are protesting, will refine with more precise selection) -->
<!-- states = c("Florida", "Georgia", "Michigan", "California", "Illinois", "Pennsylvania", "Colorado") -->
<!-- states <- by_state %>% -->
<!-- select(date, all_of(states)) %>% -->
<!-- gather(key = "State", value = "value", -date) -->
<!-- ggplot(states, aes(x = date, y = value)) + -->
<!-- geom_line(stat= "identity", aes(color = State)) + -->
<!-- scale_x_date(date_breaks = "1 week") + -->
<!-- ylab("Number of Cases") + -->
<!-- scale_y_continuous(labels = comma) + -->
<!-- geom_vline(xintercept = as.Date("2020-05-04"), linetype="dotted", -->
<!-- color = "blue", size=1.5) + -->
<!-- theme_minimal() + -->
<!-- theme(axis.text.x=element_text(angle=60, hjust=1)) -->
<!-- #+ facet_wrap(~State) -->