To screen or not to screen: an interactive framework for comparing costs of mass malaria treatment interventions
This repository contains the data and R/RShiny code for running the analysis and creating the applications from "To screen or not to screen: an interactive framework for comparing costs of mass malaria treatment interventions", published in BMC Medicine. The article is Open Access, so please refer to the article for information on the underlying models and data.
The core of this repository are the two Shiny applications. The general-app folder contains code for the generalized framework application (Figure 1), which is solely based on user input data for RDT sensitivity and specificity. This app is not reliant on external data, and contained in a single app.R file.
The example-app folder contains the data and R code for the "data-driven" example application based of off DHS/MIS survey data. The Shiny app is contained in app.R, and uses model estimates (as CSV files) for malaria prevalence and diagnostic performance. More details on the contents of this folder are provided below.
The data for this application were collected from recent DHS and MIS surveys (details provided in Table 2), and were aggregated to region-level (Admin1). The example-app\r\ folder contains R code used create the models for prevalence, sensitivity, and specificity. The core scripts are:
brms-models.R: Creates the country-level mixed effect models for malaria prevalence and RDT Sn/Sp, saved as .RDS files.sample-posterior.R: Draws posterior samples from models, which are used for estimates in the Shiny application.
The application, app.R, uses the outputs from these scripts, which are contained in the data subfolder. Finally, additional assets for the application are contained in the shapefiles\ folder and the functions.R scripts.