103_Country_Half_Year_Reccs.Rmd

---
title: "Quantifiers for Continuous Distribution by country for indicative ITN retention times"
author: "Hannah Koenker"
date: "`r format(Sys.time(), '%d %B, %Y')`"
output:
  pdf_document:
  # html_document:
    toc: yes
    toc_depth: 2
    # toc_float: yes
    fig_width: 7
    fig_height: 6
    fig_caption: yes
    df_print: kable
editor_options:
  chunk_output_type: console
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, message = FALSE)
library(haven)
library(tidyverse)
library(broom)
library(readxl)
library(janitor)
library(flextable)
library(officer) # for setting color of vlines in flextable
library(readxl)
library(writexl)

# ![](images/TH_logo.jpg){width=1.0"}

######################
# Set figure theme and colors
######################

theme_set(theme_classic())

```

```{r readmins}
## Read in the full output appended dataset for checking things

# all <- read_dta("data/gruns_all.dta") %>% 
#   clean_names()

## Read in the recommended quantifiers
s2ming <- read_dta("data/s2_min_npp_gruns_all.dta") %>% 
  clean_names()

s3ming <- read_dta("data/s3_min_npp_gruns_all.dta") %>% 
  clean_names()

t80s2 <- s2ming %>% 
  filter(target==80)

t80s3 <- s3ming %>% 
  filter(target==80)

t90s2 <- s2ming %>% 
  filter(target==90)

t90s3 <- s3ming %>% 
  filter(target==90)
```

```{r graph-check, include=FALSE}
t80s2 %>% 
  mutate(retention=as.factor(retention)) %>% 
  ggplot() +
  geom_jitter(aes(x=retention, y=q, color=retention), alpha=.5, height=0)

t80s3 %>% 
  mutate(retention=as.factor(retention)) %>% 
  ggplot() +
  geom_jitter(aes(x=retention, y=q, color=retention), alpha=.5, height=0)

t90s2 %>% 
  mutate(retention=as.factor(retention)) %>% 
  ggplot() +
  geom_jitter(aes(x=retention, y=q, color=retention), alpha=.5, height=0)

t90s3 %>% 
 mutate(retention=as.factor(retention)) %>% 
  ggplot() +
  geom_jitter(aes(x=retention, y=q, color=retention), alpha=.5, height=0)




# Check for BF:

# all %>%
#   filter(iso_a2=="BF" & retention==2.5 & group==3) %>%
#   ggplot() +
#   geom_line(aes(x=year, y=accrk)) +
#   facet_wrap(~scenario)
```

```{r medians}
## Medians

t80s2med <- t80s2 %>% 
  group_by(retention) %>% 
  summarize(median=median(q)) %>% 
  mutate(retention=as.factor(retention))

t90s2med <- t90s2 %>% 
  group_by(retention) %>% 
  summarize(median=median(q)) %>% 
  mutate(retention=as.factor(retention))

t80s3med <- t80s3 %>% 
  group_by(retention) %>% 
  summarize(median=median(q)) %>% 
  mutate(retention=as.factor(retention))

t90s3med <- t90s3 %>% 
  group_by(retention) %>% 
  summarize(median=median(q)) %>% 
  mutate(retention=as.factor(retention))
```


```{r table-prep}
s280wide <- t80s2 %>% 
  select(-target) %>% 
  pivot_wider(id_cols=iso_a2, names_from=retention, values_from=q)

s380wide <- t80s3 %>% 
  select(-target) %>% 
  pivot_wider(id_cols=iso_a2, names_from=retention, values_from=q) %>% 
  mutate(`3.5`=case_when(`3`==0 & `3.5`==1 ~ 0,
                         TRUE ~ as.numeric(`3.5`))) # replace odd 1%s at 3.5y with zero, when 3y is zero.

s290wide <- t90s2 %>% 
  select(-target) %>% 
  pivot_wider(id_cols=iso_a2, names_from=retention, values_from=q)

s390wide <- t90s3 %>% 
  select(-target) %>% 
  pivot_wider(id_cols=iso_a2, names_from=retention, values_from=q)

## Export all Tables for use in other projects 

# Ghana
gh <- bind_rows(s280wide, s290wide, s380wide, s390wide,.id = "id") %>% 
  filter(iso_a2=="GH") %>% 
  mutate(id=case_when(id==1 ~ "Full CD: 80% target",
                      id==2 ~ "Full CD: 90% target",
                      id==3 ~ "CD between campaigns: 80% target",
                      id==4 ~ "CD between campaigns: 90% target"))

write_xlsx (gh, path = "../Ghana_SBD/data/ghana_halfyear_quants.xlsx")

# DRC
drc <- bind_rows(s280wide, s290wide, s380wide, s390wide,.id = "id") %>% 
  filter(iso_a2=="CD") %>% 
  mutate(id=case_when(id==1 ~ "Full CD: 80% target",
                      id==2 ~ "Full CD: 90% target",
                      id==3 ~ "CD between campaigns: 80% target",
                      id==4 ~ "CD between campaigns: 90% target"))

write_xlsx (drc, path = "output/drc_halfyear_quants.xlsx")


```

\newpage

# Indicative quantifiers for CD as a replacement for mass campaigns

## 80% ITN access target

```{r betweenCD80-violin, fig.cap="Median recommended quantifer for continuous distribution between ITN campaigns, by ITN retention time (80% target for ITN access)", height=4, width=5}
t80s2 %>% 
  mutate(retention=as.factor(retention)) %>% 
  ggplot() +
  geom_violin(aes(x=retention, y=q, color=retention), alpha=.5, width=1) + # , draw_quantiles = c(0.5)
  geom_jitter(aes(x=retention, y=q, color=retention), alpha=.10, width=.15) +
  geom_text(data=t80s2med, aes(x=retention, y=median, color=retention, label=median), fontface="bold") +
  labs(x="ITN retention time in years",
       y="Recommended quantifier (% of population)",
       color="",
       title="Median recommended quantifier for annual large-scale CD, by ITN retention time") +
  theme(legend.position="none")

```

\newpage

```{r table-s280}
set_flextable_defaults(
  border.color = "#AAAAAA", font.family = "Arial", fonts_ignore=TRUE,
  font.size = 10, padding = 2, line_spacing = 1.5)

# std_border = fp_border(color="white") ## set the color of the border needed later down


tables280 <- s280wide %>% 
  flextable() %>% 
  set_header_labels(
   iso_a2 = "Country (ISO2 code)"
  ) %>%
  add_header_row(colwidths = c(1,6),
                 values = c("Country (ISO2 code)", "ITN retention time (years)")) %>%
     add_header_row(
       colwidths = c(7),
       values=c("Minimum quantifier (population x quantifier, annually) to sustain ITN access at or above 80%")
     ) %>% 
  fontsize(size = 9, part = "body") %>%
  fontsize(size=10, part="header") %>% 
  colformat_double(
    j=2:7,
    big.mark = ",",
    digits = 0,
    na_str = "",
    suffix="%"
  ) %>% 
  theme_vanilla %>%
  align(align = "center", part = "all") %>% 
  # vline(j=5, border=std_border, part="all") %>%
  # vline(j=1, border=std_border, part="all") %>%
  set_table_properties(width=.5) %>%
    # autofit(part = "all") %>%
    align(align = "center", part = "all")%>% 
    merge_h(part = "header") %>%
    merge_v(part = "header")

invisible(save_as_image(tables280, path="figs/Table_S280_halfyears_long.png"))

```

\newpage

## 90% ITN access target 

```{r betweenCD90-violin, fig.cap="Median recommended quantifer for annual large-scale continuous distribution, by ITN retention time (90% target for ITN access)", height=4, width=5}
t90s2 %>% 
  mutate(retention=as.factor(retention)) %>% 
  ggplot() +
  geom_violin(aes(x=retention, y=q, color=retention), alpha=.5, width=1) + # , draw_quantiles = c(0.5)
  geom_text(data=t90s2med, aes(x=retention, y=median, color=retention, label=median)) +
  labs(x="ITN retention time in years",
       y="Recommended quantifier (% of population)",
       color="",
       title="Median recommended quantifier for annual large-scale CD, by ITN retention time") +
  theme(legend.position="none")

```

\newpage

```{r table-s290}
s290wide %>% 
  flextable() %>% 
  set_header_labels(
   iso_a2 = "Country (ISO2 code)"
  ) %>%
  add_header_row(colwidths = c(1,6),
                 values = c("Country (ISO2 code)", "ITN retention time (years)")) %>%
     add_header_row(
       colwidths = c(7),
       values=c("Minimum quantifier (population x quantifier, annually) to sustain ITN access at or above 90%")
     ) %>% 
  fontsize(size = 9, part = "body") %>%
  fontsize(size=10, part="header") %>% 
  colformat_double(
    j=2:7,
    big.mark = ",",
    digits = 0,
    na_str = "",
    suffix="%"
  ) %>% 
  theme_vanilla %>%
  align(align = "center", part = "all") %>% 
  # vline(j=5, border=std_border, part="all") %>%
  # vline(j=1, border=std_border, part="all") %>%
  set_table_properties(width=.5) %>%
    # autofit(part = "all") %>%
    align(align = "center", part = "all")%>% 
    merge_h(part = "header") %>%
    merge_v(part = "header")
```

\newpage

# Indicative quantifiers for CD between mass campaigns


## 80% ITN access target

```{r betweencampaign-violin, fig.cap="Median recommended quantifer for continuous distribution between ITN campaigns, by ITN retention time (80% target for ITN access)", height=4, width=5}
t80s3 %>% 
  mutate(retention=as.factor(retention)) %>% 
  ggplot() +
  geom_violin(aes(x=retention, y=q, color=retention), alpha=.5, width=1) + # , draw_quantiles = c(0.5)
    geom_jitter(aes(x=retention, y=q, color=retention), alpha=.10, width=.15) +
  geom_text(data=t80s3med, aes(x=retention, y=median, color=retention, label=median), fontface="bold") +
  labs(x="ITN retention time in years",
       y="Recommended quantifier (% of population)",
       color="",
       title="Median recommended quantifier for between-campaign CD, by ITN retention time") +
  theme(legend.position="none")

```

\newpage


```{r table-s380}
tables380 <- s380wide %>% 
  flextable() %>% 
  set_header_labels(
   iso_a2 = "Country (ISO2 code)"
  ) %>%
  add_header_row(colwidths = c(1,6),
                 values = c("Country (ISO2 code)", "ITN retention time (years)")) %>%
     add_header_row(
       colwidths = c(7),
       values=c("Minimum quantifier (population x quantifier, each year between campaigns) to sustain ITN access at or above 80%")
     ) %>% 
  fontsize(size = 9, part = "body") %>%
  fontsize(size=10, part="header") %>% 
  colformat_double(
    j=2:7,
    big.mark = ",",
    digits = 0,
    na_str = "",
    suffix="%"
  ) %>% 
  theme_vanilla %>%
  align(align = "center", part = "all") %>% 
  # vline(j=5, border=std_border, part="all") %>%
  # vline(j=1, border=std_border, part="all") %>%
  set_table_properties(width=.5) %>%
    # autofit(part = "all") %>%
    align(align = "center", part = "all")%>% 
    merge_h(part = "header") %>%
    merge_v(part = "header")

invisible(save_as_image(tables380, path="figs/Table_S380_halfyears_long.png"))
```

## 90% ITN access target 

```{r betweencampaign90-violin, warning=FALSE, fig.cap="Median recommended quantifer for continuous distribution between ITN campaigns, by ITN retention time (90% target for ITN access)", height=4, width=5}
t90s3 %>% 
  mutate(retention=as.factor(retention)) %>% 
  ggplot() +
  geom_violin(aes(x=retention, y=q, color=retention), alpha=.5, width=1) + # , draw_quantiles = c(0.5)
  geom_text(data=t90s3med, aes(x=retention, y=median, color=retention, label=median)) +
  labs(x="ITN retention time in years",
       y="Recommended quantifier (% of population)",
       color="",
       title="Median recommended quantifier for annual large-scale CD, by ITN retention time") +
  theme(legend.position="none")

```

\newpage

```{r table-s390}
s390wide %>% 
  flextable() %>% 
  set_header_labels(
   iso_a2 = "Country (ISO2 code)"
  ) %>%
  add_header_row(colwidths = c(1,6),
                 values = c("Country (ISO2 code)", "ITN retention time (years)")) %>%
     add_header_row(
       colwidths = c(7),
       values=c("Minimum quantifier (population x quantifier, each year between campaigns) to sustain ITN access at or above 90%")
     ) %>% 
  fontsize(size = 9, part = "body") %>%
  fontsize(size=10, part="header") %>% 
  colformat_double(
    j=2:7,
    big.mark = ",",
    digits = 0,
    na_str = "",
    suffix="%"
  ) %>% 
  theme_vanilla %>%
  align(align = "center", part = "all") %>% 
  # vline(j=5, border=std_border, part="all") %>%
  # vline(j=1, border=std_border, part="all") %>%
  set_table_properties(width=.5) %>%
    # autofit(part = "all") %>%
    align(align = "center", part = "all")%>% 
    merge_h(part = "header") %>%
    merge_v(part = "header")
```