Enhancing Early Warning Systems for Vaccine-Preventable Diseases in Africa through IDSR, Electronic Active Surveillance and Big Data Analytics

Abstract

Active surveillance and the Integrated Disease Surveillance and Response (IDSR) system are vital tools in detecting vaccine-preventable diseases (VPDs), especially in regions like Africa. Active surveillance provides real-time data, while the IDSR system aggregates reports to give a broader disease overview. This study assesses how integrating active surveillance data with the IDSR system improves the detection of VPDs and enhances early epidemic responses. It also examines the role of big data analytics and GIS technologies in disease forecasting. The study analyzed active surveillance and IDSR data over a specific period. A correlation analysis was performed to determine the relationship between diseases identified by active surveillance and those reported through the IDSR system. Big data analytics, including GIS for spatial integration, was used for epidemic forecasting and trend analysis. A positive correlation was found between active surveillance data and IDSR reports (r = 0.763, p < 0.01). Active surveillance explained 58.3% of the variation in disease reports (R-squared = 0.583). GIS identified disease hotspots, improving resource allocation. Predictive modeling with big data analytics enhanced epidemic forecasting, supporting better vaccine distribution and response strategies. Integrating active surveillance with the IDSR system significantly enhances disease detection and response. The combination of real-time data with traditional reporting, supported by GIS and big data, improves epidemic forecasting, resource allocation, and early interventions for VPDs, especially in Africa.