MAP Dar Node ECR Development Program  

About the data

For the purpose of this work we are using routine data from the DHIS2 processed by WHO for the country of Fakeland. Fakeland is a malaria endemic country in sub-Saharan Africa, with an ever improving health system. Despite heavy investment and continual deployment of interventions such as mass campaigns for net, improved case-management - Fakeland still is considered a high burden country with the entire population of 11.3 million people continually at risk for malaria. The main mosquito across the country is Anopheles gambiae s.s., and transmission shows a uni-model seasonal profile with the peaks near the end of the year. The OPD reporting into DHIS2 happened across the 100 health facilities in the country. Data from Community Health Workers (CHWs) are also collated at health facilities. We are provided data disaggregated by age and diagnostic test for our analysis.

Overview of Software

This workshop will require you to install several software programs that are essential for data analysis, programming, and project management. Below is a brief description of each software and its purpose:

• R: A powerful programming language and software environment specifically designed for statistical computing and data analysis. It offers a wide array of packages for data manipulation, statistical modeling, and visualization.
• RStudio (now known as Posit): An integrated development environment (IDE) for R that makes coding easier and more efficient. It provides a user-friendly interface for writing and executing R scripts, managing projects, and visualizing data.
• QGIS: A free and open-source geographic information system (GIS) that enables users to create, edit, visualize, and analyze geospatial data. It is particularly useful for mapping and spatial data analysis.
• Visual Studio Code (VS Code): A lightweight yet powerful source code editor that supports numerous programming languages. It offers features like debugging, task running, and version control, making it ideal for coding projects.
• GitHub: A platform for version control and collaboration that allows you to store and manage your code repositories. It facilitates collaboration on projects and keeps track of changes made to your code.

Understanding the role of each software will help you utilize them effectively throughout the workshop. Make sure to follow the installation instructions carefully to ensure everything is set up correctly!

Install R and RStudio

R and RStudio are two separate pieces of software:

• R is a programming language that is especially powerful for data exploration, visualization, and statistical analysis.
• RStudio (renamed recently to Posit) is an integrated development environment (IDE) that makes using R easier. In this course, we use RStudio to interact with R.

If you don’t already have R and RStudio installed, follow the instructions for your operating system below. You have to install R before you install RStudio.

Installing Rtools (Windows)

Rtools is a collection of tools necessary for building R packages from source on Windows. To install Rtools:

• Download Rtools from the Rtools page on CRAN.
• Run the downloaded installer and follow the instructions.
• Ensure that Rtools is added to your system PATH during installation.
• After installation, open R and run the following command to verify Rtools is correctly installed: Sys.which("make"). It should return the path to the make tool.

Update R and RStudio

If you already have R and RStudio installed, first check if your R version is up to date:

• When you open RStudio your R version will be printed in the console on the bottom left. Alternatively, you can typesessionInfo() into the console. If your R version is 4.0.0 or later, you don’t need to update R for this lesson. If your version of R is older than that, download and install the latest version of R from the R project website for Windows, for MacOS, or for Linux
• It is not necessary to remove old versions of R from your system, but if you wish to do so you can check How do I uninstall R?
• Note: The changes introduced by new R versions are usually backwards-compatible. That is, your old code should still work after updating your R version. However, if breaking changes happen, it is useful to know that you can have multiple versions of R installed in parallel and that you can switch between them in RStudio by going toTools > Global Options > General > Basic.
• After installing a new version of R, you will have to reinstall all your packages with the new version. For Windows, there is a package called installr that can help you with upgrading your R version and migrate your package library.

To update RStudio to the latest version, open RStudio and click onHelp > Check for Updates. If a new version is available follow the instruction on screen. By default, RStudio will also automatically notify you of new versions every once in a while.

Install required R packages

During the course we will need a number of R packages. Packages contain useful R code written by other people. We will use the packagestidyverse, sf and terra mainly for this workshop.

To try to install these packages, open RStudio. If this is your first time opening it you may be prompted to set a CRAN mirror - select any country or even the R global cran. This step is important because CRAN aka Comprehensive R Archive Network is where R stores many useful packages that we may use. If you forgot to set this up or wish to change yours you can go to Tools ->Global Options -> Packages, you will have a screen that looks like this:

You can change CRAN by clicking the change... button. Additionally, make sure that the section circled in red in the image above is not selected

Next, copy and paste the following command into the console window (look for a blinking cursor on the bottom left), then press theEnter (Windows and Linux) or Return (MacOS) to execute the command.

list.of.packages <- c("tidyverse", "sf", "terra", "sp", "raster", "scico", "RColorBrewer", "viridis", "viridisLite", "ggplot2", "tidyr", "dplyr", "readxl")
new.packages <- list.of.packages[!(list.of.packages %in% installed.packages()[,"Package"])]
if(length(new.packages)) install.packages(new.packages)

Alternatively, you can install the packages using RStudio’s graphical user interface by going to Tools > Install Packages and typing the names of the packages separated by a comma.

R tries to download and install the packages on your machine. Tidyverse is a group of packages so it can take some time to load. When the installation has finished, you can try to load the packages by pasting the following code into the console:

library(tidyverse)
library(sf)
library(terra)
#library(rgdal)

If you do not see an error likethere is no package called ‘...’ you are good to go!

Note: The rgdal package was retired in 2023 and other, older R packages might be dependants of this package. For now, we are going to shift to other packages but if you ever really need to use this package, install earlier version of R. 

Also note that when you load a package like tidyverse in for the first time you may see such test in your console:

This text is simply telling you what packages have loaded under tidyverse and also telling you that there were function in base R that had the same names as those in tidyverse and they have been ‘over-written’ by the tidyverse ones. Additionally some of you may see some warning signs:

Warnings are normally ok to ignore. Usually when you see a warning in R, it will still process the command you’ve entered, and just wants to draw your attention that later on you may have issues because of the text in the warning. Please ignore any warnings you may see.

Updating R Packages

Generally, it is recommended to keep your R version and all packages up to date, because new versions bring improvements and important bug fixes. To update the packages that you have installed, click Update in the Packages tab in the bottom right panel of RStudio, or go to Tools > Check for Package Updates....

Sometimes, package updates introduce changes that break your old code, which can be very frustrating. To avoid this problem, you can use a package called renv. It locks the package versions you have used for a given project and makes it straightforward to reinstall those exact package versions in a new environment, for example, after updating your R version or on another computer. However, the details are outside the scope of this lesson.

Installing Visual Studio Code

Visual Studio Code (VS Code) is a powerful code editor that supports various programming languages and comes with numerous extensions to enhance your coding experience.

To install VS Code, follow the instructions below for your operating system:

Windows

1. Visit the Visual Studio Code download page.
2. Download the installer for Windows.
3. Once the download is complete, double-click the installer file to start the installation process.
4. Follow the installation prompts, ensuring to select any additional components you wish to include.
5. After installation, launch VS Code from the Start Menu or desktop shortcut.

macOS

1. Visit the Visual Studio Code download page.
2. Download the installer for macOS.
3. Open the downloaded .zip file and drag the Visual Studio Code app into your Applications folder.
4. Launch VS Code from your Applications folder or the Launchpad.

Linux

1. Visit the Visual Studio Code download page.
2. Select the appropriate package for your Linux distribution (deb or rpm).
3. Install the downloaded package using your package manager. For example, use the following command for .deb files:

sudo dpkg -i .deb

4. After installation, launch VS Code from your application menu.

Once installed, you can customize VS Code with various extensions and settings to suit your programming needs.

Setting Up Live Preview and GitHub Integration

To enhance your coding experience in Visual Studio Code, you can install the "Live Preview" extension, which allows you to see your HTML files in action in real time. Additionally, connecting your GitHub account will enable you to manage your repositories directly from the editor.

Step 1: Installing Live Preview

1. Open Visual Studio Code.
2. Go to the Extensions view by clicking on the Extensions icon in the Activity Bar on the side or by pressing Ctrl + Shift + X.
3. In the search bar, type Live Preview and press Enter.
4. Locate the Live Preview extension by MS-CEINTL and click the Install button.
5. Once installed, open an HTML file and click the Live Preview button in the status bar at the bottom of the window to start previewing your work in real time.

Step 2: Logging into GitHub in VS Code

1. In Visual Studio Code, open the Command Palette by pressing Ctrl + Shift + P.
2. Type GitHub: Sign in and select it from the dropdown.
3. A browser window will open. Log in to your Git

   With Live Preview set up and your GitHub account connected, you are now ready to enhance your coding workflow and easily manage your projects.