COVID-19
COVID-19 Pandemic in South America
View the Project on GitHub bgonzalezbustamante/COVID-19-South-America
Early Projections Chile Code
## Early Projections
res_chl <- get_R(past.i.chl, si_mean = mu, si_sd = sigma)
plot(res_chl)
## Range
chl_range <- 1:(which(get_dates(i.chl) == third_week) - pred_days)
## Simulation of Future Epicurves
set.seed(20200225)
R_val_chl <- sample_R(res_chl, 1000)
future_i_chl <- project(i.chl[chl_range], R = R_val_chl, n_sim = 1000,
si = res_chl$si, n_days = (pred_days + 41))
## Cumulative conversion
future_i_chl <- cumulate(future_i_chl)
## Dataframe CI 95%
df_future_i_chl <- as.data.frame(future_i_chl, long = TRUE)
## Lower CI
chl1_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-14")))
$incidence, 0.025)[[1]]
chl2_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-15")))
$incidence, 0.025)[[1]]
chl3_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-16")))
$incidence, 0.025)[[1]]
chl4_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-17")))
$incidence, 0.025)[[1]]
chl5_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-18")))
$incidence, 0.025)[[1]]
chl6_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-19")))
$incidence, 0.025)[[1]]
chl7_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-20")))
$incidence, 0.025)[[1]]
chl8_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-21")))
$incidence, 0.025)[[1]]
chl9_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-22")))
$incidence, 0.025)[[1]]
chl10_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-23")))
$incidence, 0.025)[[1]]
chl11_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-24")))
$incidence, 0.025)[[1]]
chl12_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-25")))
$incidence, 0.025)[[1]]
chl13_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-26")))
$incidence, 0.025)[[1]]
chl14_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-27")))
$incidence, 0.025)[[1]]
chl15_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-28")))
$incidence, 0.025)[[1]]
chl16_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-29")))
$incidence, 0.025)[[1]]
chl17_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-30")))
$incidence, 0.025)[[1]]
chl18_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-31")))
$incidence, 0.025)[[1]]
chl19_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-01")))
$incidence, 0.025)[[1]]
chl20_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-02")))
$incidence, 0.025)[[1]]
chl21_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-03")))
$incidence, 0.025)[[1]]
chl22_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-04")))
$incidence, 0.025)[[1]]
chl23_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-05")))
$incidence, 0.025)[[1]]
chl24_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-06")))
$incidence, 0.025)[[1]]
chl25_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-07")))
$incidence, 0.025)[[1]]
chl26_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-08")))
$incidence, 0.025)[[1]]
chl27_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-09")))
$incidence, 0.025)[[1]]
chl28_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-10")))
$incidence, 0.025)[[1]]
chl29_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-11")))
$incidence, 0.025)[[1]]
chl30_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-12")))
$incidence, 0.025)[[1]]
chl31_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-13")))
$incidence, 0.025)[[1]]
chl32_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-14")))
$incidence, 0.025)[[1]]
chl33_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-15")))
$incidence, 0.025)[[1]]
chl34_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-16")))
$incidence, 0.025)[[1]]
chl35_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-17")))
$incidence, 0.025)[[1]]
chl36_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-18")))
$incidence, 0.025)[[1]]
chl37_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-19")))
$incidence, 0.025)[[1]]
chl38_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-20")))
$incidence, 0.025)[[1]]
chl39_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-21")))
$incidence, 0.025)[[1]]
chl40_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-22")))
$incidence, 0.025)[[1]]
chl41_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-23")))
$incidence, 0.025)[[1]]
chl42_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-24")))
$incidence, 0.025)[[1]]
chl43_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-25")))
$incidence, 0.025)[[1]]
chl44_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-26")))
$incidence, 0.025)[[1]]
chl45_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-27")))
$incidence, 0.025)[[1]]
chl46_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-28")))
$incidence, 0.025)[[1]]
chl47_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-29")))
$incidence, 0.025)[[1]]
chl48_lo <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-30")))
$incidence, 0.025)[[1]]
## Upper CI
chl1_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-14")))
$incidence, 0.975)[[1]]
chl2_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-15")))
$incidence, 0.975)[[1]]
chl3_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-16")))
$incidence, 0.975)[[1]]
chl4_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-17")))
$incidence, 0.975)[[1]]
chl5_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-18")))
$incidence, 0.975)[[1]]
chl6_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-19")))
$incidence, 0.975)[[1]]
chl7_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-20")))
$incidence, 0.975)[[1]]
chl8_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-21")))
$incidence, 0.975)[[1]]
chl9_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-22")))
$incidence, 0.975)[[1]]
chl10_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-23")))
$incidence, 0.975)[[1]]
chl11_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-24")))
$incidence, 0.975)[[1]]
chl12_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-25")))
$incidence, 0.975)[[1]]
chl13_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-26")))
$incidence, 0.975)[[1]]
chl14_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-27")))
$incidence, 0.975)[[1]]
chl15_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-28")))
$incidence, 0.975)[[1]]
chl16_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-29")))
$incidence, 0.975)[[1]]
chl17_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-30")))
$incidence, 0.975)[[1]]
chl18_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-03-31")))
$incidence, 0.975)[[1]]
chl19_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-01")))
$incidence, 0.975)[[1]]
chl20_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-02")))
$incidence, 0.975)[[1]]
chl21_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-03")))
$incidence, 0.975)[[1]]
chl22_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-04")))
$incidence, 0.975)[[1]]
chl23_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-05")))
$incidence, 0.975)[[1]]
chl24_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-06")))
$incidence, 0.975)[[1]]
chl25_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-07")))
$incidence, 0.975)[[1]]
chl26_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-08")))
$incidence, 0.975)[[1]]
chl27_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-09")))
$incidence, 0.975)[[1]]
chl28_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-10")))
$incidence, 0.975)[[1]]
chl29_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-11")))
$incidence, 0.975)[[1]]
chl30_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-12")))
$incidence, 0.975)[[1]]
chl31_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-13")))
$incidence, 0.975)[[1]]
chl32_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-14")))
$incidence, 0.975)[[1]]
chl33_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-15")))
$incidence, 0.975)[[1]]
chl34_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-16")))
$incidence, 0.975)[[1]]
chl35_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-17")))
$incidence, 0.975)[[1]]
chl36_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-18")))
$incidence, 0.975)[[1]]
chl37_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-19")))
$incidence, 0.975)[[1]]
chl38_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-20")))
$incidence, 0.975)[[1]]
chl39_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-21")))
$incidence, 0.975)[[1]]
chl40_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-22")))
$incidence, 0.975)[[1]]
chl41_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-23")))
$incidence, 0.975)[[1]]
chl42_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-24")))
$incidence, 0.975)[[1]]
chl43_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-25")))
$incidence, 0.975)[[1]]
chl44_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-26")))
$incidence, 0.975)[[1]]
chl45_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-27")))
$incidence, 0.975)[[1]]
chl46_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-28")))
$incidence, 0.975)[[1]]
chl47_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-29")))
$incidence, 0.975)[[1]]
chl48_up <- quantile((slice(df_future_i_chl, which(df_future_i_chl$date == "2020-04-30")))
$incidence, 0.975)[[1]]
## Dataframe
chl_pred_growth_median_counts <- future_i_chl %>% as.data.frame() %>%
pivot_longer(-dates, names_to = "simulation", values_to = "incidence") %>%
group_by(dates) %>% summarise(incident_cases = as.integer(median(incidence))) %>%
mutate(data_type = "Early projection")
## Dataframe
chl_proj <- chl_pred_growth_median_counts %>%
bind_rows(tibble(dates = get_dates(i.chl),
incident_cases = cumulate(get_counts(i.chl)), data_type
= "Confirmed cases"))
## Plot of Early Projections
ggplot(chl_proj, aes(x = dates, y = incident_cases, colour = data_type)) +
geom_line() + scale_color_manual(values=c("black", "grey60")) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-14" & data_type
== "Early projection"),
aes(ymin = chl1_lo, ymax = chl1_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-15" & data_type
== "Early projection"),
aes(ymin = chl2_lo, ymax = chl2_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-16" & data_type
== "Early projection"),
aes(ymin = chl3_lo, ymax = chl3_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-17" & data_type
== "Early projection"),
aes(ymin = chl4_lo, ymax = chl4_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-18" & data_type
== "Early projection"),
aes(ymin = chl5_lo, ymax = chl5_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-19" & data_type
== "Early projection"),
aes(ymin = chl6_lo, ymax = chl6_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-20" & data_type
== "Early projection"),
aes(ymin = chl7_lo, ymax = chl7_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-21" & data_type
== "Early projection"),
aes(ymin = chl8_lo, ymax = chl8_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-22" & data_type
== "Early projection"),
aes(ymin = chl9_lo, ymax = chl9_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-23" & data_type
== "Early projection"),
aes(ymin = chl10_lo, ymax = chl10_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-24" & data_type
== "Early projection"),
aes(ymin = chl11_lo, ymax = chl11_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-25" & data_type
== "Early projection"),
aes(ymin = chl12_lo, ymax = chl12_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-26" & data_type
== "Early projection"),
aes(ymin = chl13_lo, ymax = chl13_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-27" & data_type
== "Early projection"),
aes(ymin = chl14_lo, ymax = chl14_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-28" & data_type
== "Early projection"),
aes(ymin = chl15_lo, ymax = chl15_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-29" & data_type
== "Early projection"),
aes(ymin = chl16_lo, ymax = chl16_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-30" & data_type
== "Early projection"),
aes(ymin = chl17_lo, ymax = chl17_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-03-31" & data_type
== "Early projection"),
aes(ymin = chl18_lo, ymax = chl18_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-01" & data_type
== "Early projection"),
aes(ymin = chl19_lo, ymax = chl19_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-02" & data_type
== "Early projection"),
aes(ymin = chl20_lo, ymax = chl20_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-03" & data_type
== "Early projection"),
aes(ymin = chl21_lo, ymax = chl21_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-04" & data_type
== "Early projection"),
aes(ymin = chl22_lo, ymax = chl22_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-05" & data_type
== "Early projection"),
aes(ymin = chl23_lo, ymax = chl23_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-06" & data_type
== "Early projection"),
aes(ymin = chl24_lo, ymax = chl24_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-07" & data_type
== "Early projection"),
aes(ymin = chl25_lo, ymax = chl25_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-08" & data_type
== "Early projection"),
aes(ymin = chl26_lo, ymax = chl26_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-09" & data_type
== "Early projection"),
aes(ymin = chl27_lo, ymax = chl27_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-10" & data_type
== "Early projection"),
aes(ymin = chl28_lo, ymax = chl28_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-11" & data_type
== "Early projection"),
aes(ymin = chl29_lo, ymax = chl29_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-12" & data_type
== "Early projection"),
aes(ymin = chl30_lo, ymax = chl30_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-13" & data_type
== "Early projection"),
aes(ymin = chl31_lo, ymax = chl31_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-14" & data_type
== "Early projection"),
aes(ymin = chl32_lo, ymax = chl32_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-15" & data_type
== "Early projection"),
aes(ymin = chl33_lo, ymax = chl33_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-16" & data_type
== "Early projection"),
aes(ymin = chl34_lo, ymax = chl34_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-17" & data_type
== "Early projection"),
aes(ymin = chl35_lo, ymax = chl35_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-18" & data_type
== "Early projection"),
aes(ymin = chl36_lo, ymax = chl36_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-19" & data_type
== "Early projection"),
aes(ymin = chl37_lo, ymax = chl37_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-20" & data_type
== "Early projection"),
aes(ymin = chl38_lo, ymax = chl38_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-21" & data_type
== "Early projection"),
aes(ymin = chl39_lo, ymax = chl39_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-22" & data_type
== "Early projection"),
aes(ymin = chl40_lo, ymax = chl40_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-23" & data_type
== "Early projection"),
aes(ymin = chl41_lo, ymax = chl41_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-24" & data_type
== "Early projection"),
aes(ymin = chl42_lo, ymax = chl42_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-25" & data_type
== "Early projection"),
aes(ymin = chl43_lo, ymax = chl43_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-26" & data_type
== "Early projection"),
aes(ymin = chl44_lo, ymax = chl44_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-27" & data_type
== "Early projection"),
aes(ymin = chl45_lo, ymax = chl45_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-28" & data_type
== "Early projection"),
aes(ymin = chl46_lo, ymax = chl46_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-29" & data_type
== "Early projection"),
aes(ymin = chl47_lo, ymax = chl47_up), width = .5) +
geom_errorbar(data = subset(chl_proj, dates == "2020-04-30" & data_type
== "Early projection"),
aes(ymin = chl48_lo, ymax = chl48_up), width = .5) +
theme_minimal(base_size = 12) + theme(legend.position = "bottom") +
theme(panel.grid.minor = element_blank()) +
theme(axis.text.x = element_text(angle = 35, hjust = 1, color = "black", size = 9)) +
labs(x = NULL, y = "Cumulative incidence", title = "Chile", subtitle = NULL,
colour = NULL) +
theme(plot.margin = unit(c(0.5,0.5,0.5,0.5), "cm")) +
scale_x_date(date_breaks = "2 weeks", date_minor_breaks = "2 weeks",
date_labels = "%Y-%m-%d") +
scale_y_log10(breaks = 10**(1:10), labels = comma(10**(1:10)),
sec.axis = sec_axis(~ ., labels = NULL, name = "Log-scale")) +
theme(axis.title.y.right = element_text(angle = 90, size = 11),
axis.title.y.left = element_text(size = 11),
plot.caption = element_text(size = 9),
plot.title = element_text(hjust = 0.5)) +
## School Closing
geom_segment(aes(x = as.Date(chl_resp$dates[which(chl_resp$c1_schoolclosing
== 3 & chl_resp$c1_flag == 1, arr.ind = TRUE)[1]]), xend = as.Date
(chl_resp$dates[which(chl_resp$c1_schoolclosing == 3 & chl_resp
$c1_flag == 1, arr.ind = TRUE)[1]]), y = 0, yend = chl_proj
$incident_cases[which(chl_proj$data_type == "Confirmed cases"
& chl_proj$dates == as.Date(chl_resp$dates[which(chl_resp
$c1_schoolclosing == 3 & chl_resp$c1_flag == 1, arr.ind = TRUE)
[1]]))]), linetype = "dotted") +
geom_segment(aes(x = as.Date("2020-02-26"), xend = as.Date(chl_resp$dates
[which(chl_resp$c1_schoolclosing == 3 & chl_resp$c1_flag == 1,
arr.ind = TRUE)[1]]), y = chl_proj$incident_cases[which(chl_proj
$data_type == "Confirmed cases" & chl_proj$dates == as.Date
(chl_resp$dates[which(chl_resp$c1_schoolclosing == 3 & chl_resp
$c1_flag == 1, arr.ind = TRUE)[1]]))], yend = chl_proj$incident_cases
[which(chl_proj$data_type == "Confirmed cases" & chl_proj$dates
== as.Date(chl_resp$dates[which(chl_resp$c1_schoolclosing == 3
& chl_resp$c1_flag == 1, arr.ind = TRUE)[1]]))]), linetype = "dotted") +
annotate("text", y = 0.7 * chl_proj$incident_cases[which(chl_proj$data_type
== "Confirmed cases" & chl_proj$dates == as.Date(chl_resp$dates
[which(chl_resp$c1_schoolclosing == 3 & chl_resp$c1_flag == 1,
arr.ind = TRUE)[1]]))], x = as.Date(chl_resp$dates[which(chl_resp
$c1_schoolclosing == 3 & chl_resp$c1_flag == 1, arr.ind = TRUE)[1]])
- 10, label = "Schools closing", size = 3) +
## Workplace Closing
geom_segment(aes(x = as.Date(chl_resp$dates[which(chl_resp$c2_workplaceclosing
== 3 & chl_resp$c1_flag == 1, arr.ind = TRUE)[1]]), xend = as.Date
(chl_resp$dates[which(chl_resp$c2_workplaceclosing == 3 & chl_resp
$c1_flag == 1, arr.ind = TRUE)[1]]), y = 0, yend = chl_proj
$incident_cases[which(chl_proj$data_type == "Confirmed cases"
& chl_proj$dates == as.Date(chl_resp$dates[which(chl_resp
$c2_workplaceclosing == 3 & chl_resp$c1_flag == 1, arr.ind = TRUE)
[1]]))]), linetype = "dotted") +
geom_segment(aes(x = as.Date("2020-02-26"), xend = as.Date(chl_resp$dates[which
(chl_resp$c2_workplaceclosing == 3 & chl_resp$c1_flag == 1,
arr.ind = TRUE)[1]]), y = chl_proj$incident_cases[which(chl_proj
$data_type == "Confirmed cases" & chl_proj$dates == as.Date
(chl_resp$dates[which(chl_resp$c2_workplaceclosing == 3 & chl_resp
$c1_flag == 1, arr.ind = TRUE)[1]]))], yend = chl_proj$incident_cases
[which(chl_proj$data_type == "Confirmed cases" & chl_proj$dates
== as.Date(chl_resp$dates[which(chl_resp$c2_workplaceclosing == 3
& chl_resp$c1_flag == 1, arr.ind = TRUE)[1]]))]), linetype = "dotted") +
annotate("text", y = 1.35 * chl_proj$incident_cases[which(chl_proj$data_type
== "Confirmed cases" & chl_proj$dates == as.Date(chl_resp$dates[which
(chl_resp$c2_workplaceclosing == 3 & chl_resp$c1_flag == 1, arr.ind=TRUE)
[1]]))], x = as.Date(chl_resp$dates[which(chl_resp$c2_workplaceclosing
== 3 & chl_resp$c1_flag == 1, arr.ind = TRUE)[1]]) - 10, label
= "Workplaces closing", size = 3) +
## Effects
geom_segment(aes(x = 21 + as.Date(chl_resp$dates[which(chl_resp$c1_schoolclosing
== 3 & chl_resp$c1_flag == 1, arr.ind = TRUE)[1]]), xend = 21 + as.Date
(chl_resp$dates[which(chl_resp$c1_schoolclosing == 3 & chl_resp
$c1_flag == 1, arr.ind = TRUE)[1]]), y = 0, yend = chl_proj
$incident_cases[which(chl_proj$data_type == "Confirmed cases"
& chl_proj$dates == 21 + as.Date(chl_resp$dates[which(chl_resp
$c1_schoolclosing == 3 & chl_resp$c1_flag == 1, arr.ind = TRUE)[1]]))]),
linetype = "dotted") +
geom_segment(aes(x = as.Date("2020-02-26"), xend = 21 + as.Date(chl_resp$dates
[which(chl_resp$c1_schoolclosing == 3 & chl_resp$c1_flag == 1,
arr.ind = TRUE)[1]]), y = chl_proj$incident_cases[which(chl_proj
$data_type == "Confirmed cases" & chl_proj$dates == 21 + as.Date
(chl_resp$dates[which(chl_resp$c1_schoolclosing == 3 & chl_resp
$c1_flag == 1, arr.ind = TRUE)[1]]))], yend = chl_proj$incident_cases
[which(chl_proj$data_type == "Confirmed cases" & chl_proj$dates == 21
+ as.Date(chl_resp$dates[which(chl_resp$c1_schoolclosing == 3
& chl_resp$c1_flag == 1, arr.ind = TRUE)[1]]))]), linetype = "dotted") +
annotate("text", y = 1.35 * (chl_proj$incident_cases[which(chl_proj$data_type
== "Confirmed cases" & chl_proj$dates == 21 + as.Date(chl_resp$dates[which
(chl_resp$c1_schoolclosing == 3 & chl_resp$c1_flag == 1, arr.ind = TRUE)
[1]]))]), x = as.Date(chl_resp$dates[which(chl_resp$c1_schoolclosing == 3
& chl_resp$c1_flag == 1, arr.ind = TRUE)[1]]) - 10 + 21, label
= "Possible effects", size = 3)
