Quantitative Analysis of Group for Epidemiology Architectural Approach

Abstract Epidemiology, the aspect of research focusing on disease modelling is date intensive. Research epidemiologists in different groups played a key role developing data driven model for COVID-19 and monkeypox. The requirement accessing highly accurate useful beneficial but not without having challenges. Currently, task acquisition executed by select individuals groups. This approach experiences drawbacks associated with getting permission to access desired inflexibility change goals due dynamic epidemiological objectives. presented addresses these challenges proposes design use intelligent crawlers acquiring related given goal. In addition, aims quantify how computing entities enhances process studies. done formulating investigating metrics efficiency analytics efficiency. human assisted global information networks found enhance (DAqE) (DAnE). hybrid configuration outperforms case where manual group member efforts are expended enhancing DAqE DAnE up 35% 99% average, respectively.