Weekly Viral Load Data Analysis
This repository contains scripts and resources for analyzing Viral Load data collected from multiple molecular labs and hub labs in Malawi. The data is collected by data clerks using mobile devices through platforms like ODK or Kobo Collect. The collected data is then pushed to the central server of KoboToolbox every Friday by 12pm. The analysis of the data is performed using R, where an ETL process is employed to extract data from KoboToolbox, manipulate and aggregate it, and then push it to Power BI for visualization. Table of Contents
Data Collection
Data Analysis
Setup
ETL Process
Power BI Visualization
Contributing
License
Data Collection
The data for Viral Load analysis is collected from various molecular labs and hub labs in Malawi. Data clerks are responsible for collecting the data using mobile devices, employing data collection platforms such as ODK or Kobo Collect. The collected data is then pushed to the central server of KoboToolbox every Friday by 12pm. The data includes relevant information such as patient demographics, viral load test results, lab information, and other related attributes. Data Analysis
The data analysis is performed using the R programming language. The analysis aims to extract valuable insights and patterns from the collected Viral Load data. This may involve various statistical techniques, data manipulation, aggregation, and visualization. Setup
To set up the environment for data analysis, follow these steps:
Clone the repository: git clone https://github.com/konli90/Weekly-VL-analysis.git
Install the required dependencies. You can use the provided requirements.txt file to install the necessary packages: pip install -r requirements.txt
Configure access to KoboToolbox API by providing the necessary credentials or API keys.
Configure access to the Power BI service by providing the required credentials or API keys.
Ensure you have R and the necessary R packages installed for data analysis and visualization.
ETL Process
The ETL (Extract, Transform, Load) process is a crucial step in the data analysis workflow. It involves extracting the data from the KoboToolbox server, transforming and manipulating it to meet the analysis requirements, and then loading the processed data into Power BI for visualization.
The ETL process may include the following steps:
Connect to the KoboToolbox API and retrieve the relevant Viral Load data.
Perform necessary data cleaning and preprocessing, such as handling missing values, removing duplicates, and standardizing formats.
Apply transformations and aggregations based on the analysis requirements, such as calculating summary statistics, grouping data, or creating derived variables.
Load the processed data into Power BI for visualization purposes.
Power BI Visualization
Power BI is utilized for visualizing and exploring the Viral Load data. Power BI provides a range of tools and features to create interactive and insightful visualizations, dashboards, and reports.
To visualize the data in Power BI:
Connect Power BI to the data source, either by importing the processed data or establishing a live connection to the data.
Design interactive visualizations, such as charts, graphs, tables, and maps, to represent the Viral Load data.
Create dashboards and reports to present the analyzed data in a coherent and meaningful manner.
Utilize Power BI's features for filtering, slicing, and drilling down into the data to gain deeper insights.
Contributing
Contributions to this project are welcome. If you have any suggestions, improvements, or bug