BOOSTING PUBLIC HEALTH RESILIENCE: HARNESSING AI-DRIVEN PREDICTIVE ANALYSIS TO PREVENT DISEASE OUTBREAKS

Abstract

Despite advances in medical research, infectious illnesses continue to pose a threat to the public's health, demanding creative methods of outbreak prevention. The revolutionary potential of AI-driven predictive analysis as a significant tool for boosting disease outbreak prevention measures is explored in this study. This paper examines how AI's analytical power is used to predict, simulate, and lessen the effects of infectious disease epidemics (Markovic et al., 2022) (Margam, 2023) [1][2]. To stop the spread of these illnesses, healthcare stakeholders and researchers are working together in the United States (Friedman et al., 2021)[3] Preventing disease outbreaks now relies heavily on the use of AI-driven predictive analysis (Gerlee et al., 2022)[4] (Tashman, 2000)[5] Government organisations and public health organisations in the United States are increasingly using AI and machine learning to get insights into the mechanisms of disease transmission and enable preventive interventions (Lu et al., 2020)[6] (Bartoletti, 2019) [7]. Authorities are now able to predict illness trajectories in the setting of the United States thanks to predictive modelling, which is supported by AI (Lidströmer & Ashrafian, 2022) [8]. AI-driven models improve the precision of illness trajectory estimates by taking regional factors like population density, travel patterns, and healthcare facilities into account (khan et al., 2023) [9]. In the context of the United States, integrating big data analytics is essential for preventing disease outbreaks (Kumar et al., 2023) [10]. Authorities acquire a complete picture of how diseases spread by analysing several databases containing medical records, sociodemographic data, and environmental elements (Miller et al., 2023) [11]. Data analysis, for instance, allowed for resource allocation and targeted containment efforts during the COVID-19 pandemic (Dewey & Schlattmann, 2019) [12]. With a focus on the United States, this paper demonstrates how AI-driven predictive analysis is a game-changing factor in the prevention of disease outbreaks. Artificial intelligence (AI) offers a ray of hope in the fight for public health resilience because it can predict disease trends and enable targeted interventions. The integration of artificial intelligence and predictive analysis is emerging as a crucial method for ensuring global well-being as governments deal with the ever-changing landscape of infectious illnesses.