1 Automated Malaria Radar (AMaR)
1.1 Why AMaR?
AMaR (Automated Malaria Radar) is a powerful and user-friendly Shiny web application designed to provide comprehensive insights into malaria trends and facilitate data-driven decision-making in the context of malaria control and prevention. By automating the process of data retrieval, analysis, and visualization, AMaR offers a streamlined solution for health professionals, researchers, and policymakers to monitor and manage malaria cases efficiently.
1.2 How does it work?
AMaR seamlessly integrates with DHIS2 to fetch both historical and current weekly malaria data. The application employs advanced statistical calculations to generate dynamic and visually appealing graphs depicting malaria channels at different administrative levels, including National, Regional, District, and Facility levels. Key features of AMaR include:
Data Integration: AMaR retrieves data from DHIS2, ensuring that the latest weekly malaria data is available for analysis.
Automated analysis: The application automatically computes Upper Limit, Lower Limit, and Alert Line to establish normal malaria channels based on historical data patterns and statistical methodologies.
Interactive visualizations: Users can easily select their preferred administrative level (National, Regional, District, or Facility) and visualize the computed malaria channels through interactive and informative graphs.
PDF and HTML reports: AMaR enables users to generate customized PDF and HTML reports summarizing the malaria channels and insights. These reports can be shared with stakeholders and used for evidence-based decision-making.
An example of a normal malaria channel for Adjumani District
1.3 Reasons for using AMaR
AMaR offers several compelling reasons for health professionals, researchers, and policymakers to adopt this innovative tool:
Efficiency: With AMaR, the process of collecting, analyzing, and visualizing malaria data is automated, saving valuable time and resources.
Accuracy: The application employs statistical methods to calculate normal malaria channels, ensuring that the interpretation of trends is based on robust calculations.
Customization: Users can customize their analysis by selecting the administrative level and generating reports tailored to their needs.
Real-time insights: By incorporating the latest data, AMaR provides real-time insights into malaria trends, enabling timely responses and interventions.
Evidence-based decision-making: The visualizations and reports generated by AMaR serve as evidence for informed decision-making in malaria control and prevention efforts.
1.4 In conclusion
AMaR (Automated Malaria Radar) will be a groundbreaking tool that empowers users with accurate, real-time, and actionable insights into malaria trends. Its integration with DHIS2, automated analysis, interactive visualizations, and report generation capabilities make it an essential asset for anyone involved in malaria management and research.