Advancements in Predictive Techniques and Effective Management Strategies for Dengue Fever: A Comprehensive Review

The dengue virus is the source of the arboviral illness dengue. Wide-ranging medical symptoms, ranging from mild dengue fever to potentially lethal diseases like dengue shock syndrome (DSS), are caused by symptomatic dengue infection. The term intelligent dengue fever prediction and management describes the application of cutting-edge computational techniques, including data analytics, to forecast outbreaks, pinpoint high-risk regions, and maximize resource allocation for efficient dengue fever treatment and prevention. Dengue fever is a virus spread by mosquitoes, and the effect on public health is minimized. Predicting and managing dengue fever has limitations, poor forecasting models, inadequate public health facilities, difficulties controlling vectors, and restricted access to treatment in areas where endemic diseases are present. In this review to reduce the impact of illness through early identification, efficient vector control techniques are to predict dengue fever. Here This Work utilized, the epidemiology of dengue fever, dengue hemorrhagic fever (DHF), Pathogenesis of dengue hemorrhagic fever, and clinical Manifestations divided into dengue with warning symptoms, dengue without warning symptoms, severe dengue and using system is intelligent systems in dengue prediction, intelligent dengue management strategies. The early diagnosis and efficient mitigation of dengue fever might be significantly enhanced by using proactive management techniques and intelligent prediction models. This might minimize the impact of Dengue Fever on healthcare systems and public health.