Utilizing AI for Community Protection: Leveraging Open Data to Monitor and Identify Infectious Disease Outbreaks Instantly

Artificial Intelligence (AI) improves public health safety by providing better monitoring of infectious disease outbreaks.This document analyzes AI outbreak detection solutions based on ML technology that combine NLP and GIS systems to process social media and medical data for monitoring early warning indicators.The technological advances create barriers to public health security by generating algorithmic prejudice as well as incorrect data and privacy worries and complex predictive modeling systems.Earth-tested solutions are needed because they guarantee the reliability of AI health monitoring systems.Research examines contemporary AI frameworks in epidemiology while showing their strengths and evaluating weaknesses followed by a study of AI interventions throughout the COVID-19 outbreak time.The advancement of predictive tools through AI requires immediate establishment of country-based research networks as well as ethical regulations for healthcare AI applications.AI technology ensures worldwide health safety because it joins technological development with ethical principles to build superior detection and response systems for diseases.

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Published
2025-05-18
DOI
https://doi.org/10.63169/gcared2025.p2
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
0.00
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article

Utilizing AI for Community Protection: Leveraging Open Data to Monitor and Identify Infectious Disease Outbreaks Instantly

Diptendu Sinha Roy, Shalini Kushwaha, Sushil Kumar, Swati Suryawanshi et al.
Data-Driven Disease Surveillance
article

Utilizing AI for Community Protection: Leveraging Open Data to Monitor and Identify Infectious Disease Outbreaks Instantly

Diptendu Sinha Roy, Shalini Kushwaha, Sushil Kumar, Swati Suryawanshi, Anushka Singh, Purvesh Kolpe, Manasvi Kalode, Yashodhan Sonwane
article en

Abstract

Artificial Intelligence (AI) improves public health safety by providing better monitoring of infectious disease outbreaks.This document analyzes AI outbreak detection solutions based on ML technology that combine NLP and GIS systems to process social media and medical data for monitoring early warning indicators.The technological advances create barriers to public health security by generating algorithmic prejudice as well as incorrect data and privacy worries and complex predictive modeling systems.Earth-tested solutions are needed because they guarantee the reliability of AI health monitoring systems.Research examines contemporary AI frameworks in epidemiology while showing their strengths and evaluating weaknesses followed by a study of AI interventions throughout the COVID-19 outbreak time.The advancement of predictive tools through AI requires immediate establishment of country-based research networks as well as ethical regulations for healthcare AI applications.AI technology ensures worldwide health safety because it joins technological development with ethical principles to build superior detection and response systems for diseases.

D.Y. Patil University (IN)
Openalex Percentile: Top 81%
Data-Driven Disease Surveillance
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