AI Applications in Public Health: A Review of Epidemic Monitoring, Epidemiological Analysis, and Health Management

Abstract

This review explores AI’s applications in public health, focusing on epidemic monitoring, epidemiological analysis, and health management, alongside key challenges and future directions. In epidemic monitoring, AI enables early detection and prediction: social media data powers systems like WHO’s EARS (analyzing multilingual COVID-19 narratives with superior precision); AI processes news articles to spot outbreak signals (while addressing misinformation); mobility data analysis via GPT/GCNs improves disease spread forecasting; and anomaly detection (e.g., Siamese neural networks on ECG data) identifies unusual healthcare patterns signaling outbreaks. For epidemiological analysis, AI advances understanding of disease dynamics: Gaussian Mixture models cluster COVID-19 cases to reveal hotspots; causal inference techniques (aided by XAI) uncover disease-risk factor links; multi-factor AI models personalize risk stratification (e.g., HIV prevention, cardiac plaque assessment); and BRBFNs/neural networks model transmission (e.g., COVID-19, TB) to optimize controls. In health management, AI enhances care delivery: deep learning aids early diagnosis (e.g., graph networks for cervical cancer, retinal analysis for glaucoma); AI integrates multi-omics/clinical data for personalized treatments (e.g., oncology biomarkers, stroke outcome prediction); RPM systems (sensors, voice chatbots) enable remote monitoring; and AI-driven platforms boost public health education (e.g., adolescent behavior interventions). Challenges include data privacy (needing robust cybersecurity), algorithmic bias (requiring diverse datasets/audits), and ethical concerns (upholding equity/transparency). Future directions involve AI in drug development, workforce training, and fostering multidisciplinary collaboration to unlock AI’s full potential for equitable public health improvement.

Keywords

artificial intelligence / public health / epidemiology / health management

References

[1] J. Arslan , K. Benke , Artificial Intelligence and Telehealth may Provide Early Warning of Epidemics, Frontiers in Artificial Intelligence, 2021, 4.

[2] B. White , Arnault Gombert , Tim Nguyen , Brian Yau , A. Ishizumi , Laura Kirchner , Alicia León , Harry Wilson , Giovanna Jaramillo—Gutierrez , J. Cerquides , Marcelo D'agostino , Cristiana Salvi , Ravi Shankar Sreenath , Kimberly Rambaud , D. Samhouri , S. Briand , T. Purnat , Using Machine Learning Technology (Early Artificial Intelligence—Supported Response With Social Listening Platform) to Enhance Digital Social Understanding for the COVID—19 Infodemic: Development and Implementation Study, JMIR Infodemiology, 2023, 3.

[3] Haoze Song , Application of big data and artificial intelligence in mental health prediction and intervention, Interdisciplinary Humanities and Communication Studies, 2024.

[4] Shoaib Shaik , A Review and Analysis on Fake News Detection Based on Artificial Intelligence and Data Science, Tuijin Jishu/Journal of Propulsion Technology, 2023.

[5] Amarachukwu Bernaldine Isiaka , Vivian Nonyelum Anakwenze , Chiamaka Rosemary Ilodinso , Chikodili Gladys Anaukwu , Chukwuebuka Mary—Vin Ezeokoli , Samuel Mensah Noi , Gazali Oluwasegun Agboola , Richard Mensah Adonu , Harnessing Artificial Intelligence for Early Detection and Management of Infectious Disease Outbreaks, International Journal of Innovative Research and Development, 2024.

[6] Riccardo Corrias , M. Gjoreski , Marc Langheinrich , Exploring Transformer and Graph Convolutional Networks for Human Mobility Modeling, Sensors (Basel, Switzerland), 2023, 23.

[7] K. Mangold , Rickey E. Carter , K. Siontis , P. Noseworthy , Francisco Lopez—Jimenez , Samuel J. Asirvatham , Paul A. Friedman , Z. Attia , Unlocking the potential of artificial intelligence in electrocardiogram biometrics: age—related changes, anomaly detection, and data authenticity in mobile health platforms, European Heart Journal. Digital Health, 2024, 5, 314-323.

[8] Marcelo Fabian Guato Burgos , Jorge Morato , Fernanda Paulina Vizcaino Imacaña , A Review of Smart Grid Anomaly Detection Approaches Pertaining to Artificial Intelligence, Applied Sciences, 2024.

[9] Durgesh Samariya , Jiangang Ma , Sunil Aryal , Xiaohui Zhao , Detection and explanation of anomalies in healthcare data, Health Information Science and Systems, 2023, 11.

[10] Benjamin Lieberman , J. Kong , Roy Gusinow , A. Asgary , N. Bragazzi , Joshua Choma , S. Dahbi , Kentaro Hayashi , D. Kar , M. Kawonga , Mduduzi Mbada , Kgomotso Monnakgotla , J. Orbinski , X. Ruan , Finn Stevenson , Jianhong Wu , B. Mellado , Big data— and artificial intelligence—based hot—spot analysis of COVID—19: Gauteng, South Africa, as a case study, BMC Medical Informatics and Decision Making, 2023, 23.

[11] S. Zaidi , Amna Mahfooz , Abdullah Latif , Nainan Nawaz , Razia Fatima , Fazal Ur Rehman , T. Reza , Faran Emmanuel , Geographical targeting of active case finding for tuberculosis in Pakistan using hotspots identified by artificial intelligence software (SPOT—TB): study protocol for a pragmatic stepped wedge cluster randomised control trial, BMJ Open Respiratory Research, 2024, 11.

[12] A. Rawal , Adrienne Raglin , Danda B. Rawat , Brian M. Sadler , J. McCoy , Causality for Trustworthy Artificial Intelligence: Status, Challenges and Perspectives, ACM Computing Surveys, 2024, 57, 1-30.

[13] Mohannad Z. Naser , Causality and causal inference for engineers: Beyond correlation, regression, prediction and artificial intelligence, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2024, 14.

[14] Yelleti Vivek, V. Ravi, A. Mane, Laveti Ramesh Naidu, Explainable Artificial Intelligence and Causal Inference Based ATM Fraud Detection, 2024 IEEE Symposium on Computational Intelligence for Financial Engineering and Economics (CIFEr), 2022, 1-7.

[15] Ezeanya C.U , UkaigweJ.A. , Nwoyibe O.I , ObeaguE.I. , Personalized risk reduction of hiv plans with artificial intelligence: a narrative review, KIU Journal of Health Sciences, 2024.

[16] A. Provera , D. Andreini , Kersten Petersen , E. Gallinoro , E. Conte , Artificial intelligence—powered insights into high—risk, non—obstructive coronary atherosclerosis: a case report, European Heart Journal: Case Reports, 2024, 8.

[17] F. Bardanzellu , V. Fanos , Metabolomics, Microbiomics, Machine learning during the COVID‐19 pandemic, Pediatric Allergy and Immunology, 2022, 33, 86-88.

[18] M. Ivanova , C. Pescia , D. Trapani , K. Venetis , Chiara Frascarelli , Eltjona Mane , Giulia Cursano , E. Sajjadi , C. Scatena , B. Cerbelli , G. d'Amati , F. M. Porta , E. Guerini—Rocco , C. Criscitiello , G. Curigliano , Nicola Fusco , Early Breast Cancer Risk Assessment: Integrating Histopathology with Artificial Intelligence, Cancers, 2024, 16.

[19] A. Raza , D. Baleanu , Tahir Nawaz Cheema , Emad Fadhal , Rashid I. H. Ibrahim , Nouara Abdelli , Artificial intelligence computing analysis of fractional order COVID—19 epidemic model, AIP Advances, 2023.

[20] I. Semianiv , L. Todoriko , Y. Vyklyuk , D. Nevinskyi , Application of geospatial multi—agent system for simulation of different aspects of tuberculosis transmission, Infusion&Chemotherapy, 2024.

[21] Jingxiao Tian , Hanzhe Li , Yaqian Qi , Xiangxiang Wang , Yuan Feng , Intelligent medical detection and diagnosis assisted by deep learning, Applied and Computational Engineering, 2024.

[22] Nur Mohammad Fahad , Sami Azam , Sidratul Montaha , Md. Saddam Hossain Mukta , Enhancing cervical cancer diagnosis with graph convolution network: AI—powered segmentation, feature analysis, and classification for early detection, Multim. Tools Appl., 2024, 83, 75343-75367.

[23] Yan Zhu , Rebecca J. Salowe , Caven Chow , Shuo Li , Osbert Bastani , Joan M. O’Brien , Advancing Glaucoma Care: Integrating Artificial Intelligence in Diagnosis, Management, and Progression Detection, Bioengineering, 2024, 11.

[24] Demilade A. Adedinsewo , A. Pollak , S. Phillips , Taryn Smith , A. Svatikova , S. Hayes , S. Mulvagh , C. Norris , V. Roger , P. Noseworthy , Xiaoxi Yao , R. Carter , Cardiovascular Disease Screening in Women: Leveraging Artificial Intelligence and Digital Tools, Circulation Research, 2022, 130, 673-690.

[25] Jin Liao , Xiaoying Li , Yujie Gan , Shuang Han , Pengfei Rong , Wei Wang , Wei Li , Li Zhou , Artificial intelligence assists precision medicine in cancer treatment, Frontiers in Oncology, 2023, 12.

[26] Theranostics and artificial intelligence: new frontiers in personalized medicine, Theranostics, 2024, 14, 2367-2378.

[27] Farida Mohsen , Balqees Al—Saadi , Nima Abdi , Sulaiman Khan , Zubair Shah , Artificial Intelligence—Based Methods for Precision Cardiovascular Medicine, Journal of Personalized Medicine, 2023, 13.

[28] A. Bonkhoff , C. Grefkes , Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence, Brain, 2021, 145, 457-475.

[29] Timothy Malche , Sumegh Tharewal , P. Tiwari , M. Y. Jabarulla , A. Alnuaim , W. Hatamleh , Mohammad Aman Ullah , Artificial Intelligence of Things— (AIoT—) Based Patient Activity Tracking System for Remote Patient Monitoring, Journal of Healthcare Engineering, 2022, 2022.

[30] T. Jadczyk , W. Wojakowski , M. Tendera , T. Henry , G. Egnaczyk , S. Shreenivas , Artificial Intelligence Can Improve Patient Management at the Time of a Pandemic: The Role of Voice Technology, Journal of Medical Internet Research, 2020, 23.

[31] Sowjanya Patibandla , Rajani Adepu , B. Madhuri , Validation of Artificial Intelligence Based Real Time Multi—Vitals Remote Monitoring Solution — A Clinical Study, International Journal of Health Sciences and Research, 2023.

[32] U. Udoudom , Kufre George , A. Igiri , Impact of Digital Learning Platforms on Behaviour Change Communication in Public Health Education, Pancasila International Journal of Applied Social Science, 2023.

[33] A. Giovanelli , Jonathan P. Rowe , Madelynn Taylor , Mark Berna , K. Tebb , C. Penilla , M. Pugatch , James Lester , E. Ozer , Supporting Adolescent Engagement with Artificial Intelligence—Driven Digital Health Behavior Change Interventions, Journal of Medical Internet Research, 2023, 25.

[34] Blake Murdoch , Privacy and artificial intelligence: challenges for protecting health information in a new era, BMC Medical Ethics, 2021, 22.

[35] Francisca Chibugo Udegbe , Ogochukwu Roseline Ebulue , Charles Chukwudalu Ebulue , Chukwunonso Sylvester Ekesiobi , THE ROLE OF ARTIFICIAL INTELLIGENCE IN HEALTHCARE: A SYSTEMATIC REVIEW OF APPLICATIONS AND CHALLENGES, International Medical Science Research Journal, 2024.

[36] L. Nazer , Razan Zatarah , Shai Waldrip , J. Ke , M. Moukheiber , A. Khanna , Rachel S. Hicklen , Lama Moukheiber , D. Moukheiber , Haobo Ma , P. Mathur , Bias in artificial intelligence algorithms and recommendations for mitigation, PLOS Digital Health, 2023, 2.

[37] D. Ueda , Taichi Kakinuma , S. Fujita , K. Kamagata , Y. Fushimi , Rintaro Ito , Y. Matsui , T. Nozaki , T. Nakaura , N. Fujima , F. Tatsugami , M. Yanagawa , K. Hirata , A. Yamada , T. Tsuboyama , M. Kawamura , Tomoyuki Fujioka , S. Naganawa , Fairness of artificial intelligence in healthcare: review and recommendations, Japanese Journal of Radiology, 2023, 42, 3-15.

[38] C. N. Vorisek , Caroline Stellmach , Paula Josephine Mayer , S. Klopfenstein , D. Bures , Anke Diehl , Maike Henningsen , K. Ritter , S. Thun , Artificial Intelligence Bias in Health Care: Web—Based Survey, Journal of Medical Internet Research, 2023, 25.

[39] A. Al—hwsali , Balqes Alsaadi , Nima Abdi , Shaza Khatab , M. Alzubaidi , Barry Solaiman , Mowafa J Househ , Scoping Review: Legal and Ethical Principles of Artificial Intelligence in Public Health, Studies in health technology and informatics, 2023, 305, 640-643.

[40] Mitul Harishbhai Tilala , Pradeep Kumar Chenchala , Ashok Choppadandi , Jagbir Kaur , Savitha Naguri , Rahul Saoji , Bhanu Devaguptapu , Ethical Considerations in the Use of Artificial Intelligence and Machine Learning in Health Care: A Comprehensive Review, Cureus, 2024, 16.

[41] Renan Gonçalves Leonel da Silva , The advancement of artificial intelligence in biomedical research and health innovation: challenges and opportunities in emerging economies, Globalization and Health, 2024, 20.

[42] Rebecca Asamoah—Atakorah , Shadrach Asamoah—Atakorah , Osei Atakorah Amaniampong , Johnson Mensah Sukah Selorm , Alfred Addy , Maximous Diebieri , George Benneh Mensah , The Impact of Artificial Intelligence on Ghanaian Health Worker Training: Opportunities, Challenges, and Ethical Considerations, International Journal For Multidisciplinary Research, 2024.

[43] Harnessing the Power of Artificial Intelligence in Climate Change Mitigation: Opportunities and Challenges for Public Health, Journal of Current Trends in Computer Science Research, 2024.