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SIR_interval.Rmd
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SIR_interval.Rmd
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---
title: "SEIR_intervals"
output: html_document
date: '2022-07-05'
---
```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
###
```{r}
source("israel_functions.R")
```
### Set Date Ranges
```{r}
date0 <- as.Date("2020-12-27")
date1 <- as.Date("2021-01-07")
date2 <- as.Date("2021-02-07")
date3 <- as.Date("2021-03-07")
date4 <- as.Date("2021-04-18")
date_initial = date0
date_final = date4
```
```{r}
israel <- israel_data_only(date_initial, date_final)
israel = israel %>%
mutate(period = ifelse(date < date1, 1,
ifelse(date >= date1 & date < date2, 2,
ifelse(date >= date2 & date < date3, 3,
ifelse(date >= date3, 4, 0)))))
```
```{r}
df1 <- israel %>% filter(period == 1)
df2 <- israel %>% filter(period == 2)
df3 <- israel %>% filter(period == 3)
df4 <- israel %>% filter(period == 4)
# Run algo for each df, using last day of previous as initial for this one
# Add predicted values to df
# Rbind the 4 df into one
# Use geom_smooth to create lines
# tune smoothing parameter
```
```{r}
N=9449000
lambda = mu = 1 / (365 * 82.8)
starting_param_val = list(beta = 1e-2, gamma = 1e-5)
estimates_pois = mle2(minuslogl = logli,
start = lapply(starting_param_val, log), method = "Nelder-Mead",
data=list(dat = df1, N = N, lambda = lambda, mu = mu))
pars_df1 = as.numeric(coef(estimates_pois))
pred_df1 = sir_1(beta = exp(pars_df1[1]), gamma = exp(pars_df1[2]), I0 = df1$I[1],
R0 = df1$R[1], times = df1$day, N = N, lambda = lambda,
mu = mu)
df1 <- df1 %>% mutate(pred_I = pred_df1[3], pred_R = pred_df1[4])
```
```{r}
estimates_pois = mle2(minuslogl = logli,
start = lapply(starting_param_val, log), method = "Nelder-Mead",
data=list(dat = df2, N = N, lambda = lambda, mu = mu))
pars_df2 = as.numeric(coef(estimates_pois))
pred_df2 = sir_1(beta = exp(pars_df2[1]), gamma = exp(pars_df2[2]), I0 = df2$I[1],
R0 = df2$R[1], times = df2$day, N = N, lambda = lambda,
mu = mu)
df2 <- df2 %>% mutate(pred_I = pred_df2[3], pred_R = pred_df2[4])
```
```{r}
estimates_pois = mle2(minuslogl = logli,
start = lapply(starting_param_val, log), method = "Nelder-Mead",
data=list(dat = df3, N = N, lambda = lambda, mu = mu))
pars_df3 = as.numeric(coef(estimates_pois))
pred_df3 = sir_1(beta = exp(pars_df3[1]), gamma = exp(pars_df3[2]), I0 = df3$I[1],
R0 = df3$R[1], times = df3$day, N = N, lambda = lambda,
mu = mu)
df3 <- df3 %>% mutate(pred_I = pred_df3[3], pred_R = pred_df3[4])
```
```{r}
estimates_pois = mle2(minuslogl = logli,
start = lapply(starting_param_val, log), method = "Nelder-Mead",
data=list(dat = df4, N = N, lambda = lambda, mu = mu))
pars_df4 = as.numeric(coef(estimates_pois))
pred_df4 = sir_1(beta = exp(pars_df4[1]), gamma = exp(pars_df4[2]), I0 = df4$I[1],
R0 = df4$R[1], times = df4$day, N = N, lambda = lambda,
mu = mu)
df4 <- df4 %>% mutate(pred_I = pred_df4[3], pred_R = pred_df4[4])
```
```{r}
israel_new <- rbind(df1, df2, df3, df4)
```
```{r}
ci = c("#C79999")
mn = c("#7C0000")
date_breaks = "1 month"
base = ggplot() +
xlab("") +
scale_x_date(
date_breaks = date_breaks,
labels = scales::date_format("%e %b")
) +
theme_bw() +
theme(
axis.text.x = element_text(angle = 45, hjust = 1),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12)
) +
theme(legend.position = "right")
p1 = base +
geom_line(mapping = aes(x = date, y = pred_I$I, color = colour),
data = israel_new, size = 1,color = mn) +
geom_bar(mapping = aes(x = date, y = I), stat = "identity",
data = israel_new, width = 0.5, fill = 'steelblue', alpha = 0.7,
) +
xlim(date_initial, date_final)
p1 = p1 + labs(y = "Removed")
```
```{r}
ci = c("#C79999")
mn = c("#7C0000")
date_breaks = "1 month"
base = ggplot() +
xlab("") +
scale_x_date(
date_breaks = date_breaks,
labels = scales::date_format("%e %b")
) +
theme_bw() +
theme(
axis.text.x = element_text(angle = 45, hjust = 1),
axis.text = element_text(size = 12),
axis.title = element_text(size = 12)
) +
theme(legend.position = "right")
p2 = base +
geom_line(mapping = aes(x = date, y = pred_R$R, color = colour),
data = israel_new, size = 1,color = mn) +
geom_bar(mapping = aes(x = date, y = R), stat = "identity",
data = israel_new, width = 0.5, fill = 'steelblue', alpha = 0.7,
) +
xlim(date_initial, date_final)
p2 = p2 + labs(y = "Removed")
```
```{r}
grid.arrange(p1, p2)
```