template_analysis_report_pdf.Rmd

---
title: "*pfhrp2/3* Planner: Analysis report"
subtitle: "*Downloaded on: `r Sys.Date()`| DRpower interactive app v1.0.0*"
output: 
  pdf_document:
    fig_caption: yes
    number_sections: no
    latex_engine: xelatex
    df_print: kable
    fig_width: 6
    fig_height: 4
header-includes:
  - \usepackage{booktabs}
mainfont: Arial
documentclass: article
links-as-notes: true
geometry: 
  - margin=0.75in
  - top=0.5in
papersize: letter
always_allow_html: true
params:
  analysis_prevthresh: NA
  analysis_nclusters: NA
  analysis_study_data: NA
  analysis_prevoutput: NA
  analysis_iccoutput: NA
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

library(tidyverse)
library(bslib)
library(kableExtra)

set.seed(10)
```

```{r create objects from params, echo=F}
prev_thresh <- params$analysis_prevthresh
nclusters <- params$analysis_nclusters
study_data <- params$analysis_study_data
prev_output <- params$analysis_prevoutput
icc_output <- params$analysis_iccoutput
```

## Background
<!-- \begin{center}\rule{7in}{0.4pt}\end{center} -->
This report presents the results generated by using the [*pfhrp2/3* planner web application](https://github.com/shaziaruybal/DRpower_app). This application was used to analyze data from a *pfhrp2/3* deletion prevalence study and estimate prevalence and determine if it is above a set threshold. For more information on the statistical method used, see the [DRpower R package website](https://mrc-ide.github.io/DRpower).

## Study details 
<!-- \begin{center}\rule{7in}{0.4pt}\end{center} -->

A total of `r params$analysis_nclusters` clusters were surveyed in this *pfhrp2/3* deletion prevalence study. The observed counts of *pfhrp2/3* deletions and the sample sizes in each cluster are shown below:

```{r echo=F}
kable(study_data, 
      format = "latex",
      booktabs = T) %>%
  kable_styling(
    bootstrap_options = "striped",
    position = "left",
    full_width = F)
```

### Estimated prevalence 
<!-- \begin{center}\rule{7in}{0.4pt}\end{center} -->

To estimate the prevalence of *pfhrp2/3* deletions in this study we used the [DRpower R package](https://mrc-ide.github.io/DRpower) to test whether the observed prevalence in this study was above or below a prevalence threshold of `r params$analysis_prevthresh`%. 

We estimate that the prevalence of *pfhrp2/3* deletions is `r round(as.numeric(prev_output$MAP),2)`% (95% CrI: `r round(as.numeric(prev_output$CrI_lower),2)`-`r round(as.numeric(prev_output$CrI_upper),2)`%).

<!-- Add here the rendering of the conclusion text if prob is > or < 95% -->

```{r fig.height=3, fig.width=3, echo=F}
prev_output %>% 
  ggplot() +
        geom_segment(aes(x = " ", xend = " ", y = CrI_lower, yend = CrI_upper),
                     color = "gray20", linewidth = 1) + 
        geom_point(aes(x = " ", y = MAP),
                   size = 2,
                   shape = 21,
                   fill = "mediumpurple") +
        # use the user-entered prev_thresh to plot threshold line
        geom_hline(aes(yintercept = as.numeric(params$analysis_prevthresh)), 
                   color = "darkgrey",
                   linetype = "dashed") +
        # use the user-entered prev_thresh to plot threshold line
        geom_text(aes(x= " ", 
                      y = (as.numeric(params$analysis_prevthresh))+3, 
                      label = paste0(ceiling(as.numeric(params$analysis_prevthresh)),"% threshold")), 
                      color = "darkgrey", size = 3) +
        scale_y_continuous(labels = scales::percent_format(1, scale = 1), limits = c(0,100)) +
        labs(x = "",
             y = "Estimated prevalence") +
        theme_light() +
        theme(text = element_text(size = 12))
```

### Estimated intra-cluster correlation (ICC)

We estimate that the intra-cluster correlation is `r round(as.numeric(icc_output$MAP),2)` (95% CrI: `r round(as.numeric(icc_output$CrI_lower), 2)`-`r round(as.numeric(icc_output$CrI_upper),2)`).

```{r fig.height=3, fig.width=3, echo=F}
icc_output %>% 
  ggplot() +
        geom_segment(aes(x = " ", xend = " ", y = CrI_lower, yend = CrI_upper), 
                     color = "gray20", linewidth = 1) +
        geom_point(aes(x = " ", y = MAP), 
                   size = 2, 
                   shape = 21,
                   fill = "mediumpurple") +
        scale_y_continuous(limits = c(0,1)) +
        labs(x = "",
             y = "Estimated ICC") +
        theme_light() +
        theme(text = element_text(size = 12)) 
```