A Study on accelerating threat of Emerging Infectious Diseases (EIDs) and imperative for a proactive, interdisciplinary Global Health Security Framework

Year : 2026 | Volume : 03 | Issue : 01 | Page : 8 21
    By

    Dr. Kazi Kutubuddin,

  1. Professor & Head, Brahmdevdada Mane Institute of Technology, Solapur, Maharashtra, India

Abstract

Emerging Infectious Diseases (EIDs) represent one of the most critical and persistent threats to global health security in the 21st century. Driven primarily by the synergy of unprecedented human encroachment into wild habitats, climate change-induced ecological disruption, accelerated international travel, and antimicrobial resistance, the frequency and severity of zoonotic spillover events are rapidly increasing. Traditional, reactive public health measures—focused on containment after an emergence—have repeatedly proven insufficient, leading to catastrophic global consequences, as evidenced by recent pandemics and ongoing epidemics. This study argues that mitigating the perpetual threat of EIDs requires a fundamental paradigm shift from response to prediction and prevention. The core strategy must be rooted in the One Health framework, integrating human, animal, and environmental surveillance systems into a single, cohesive, intelligence-driven architecture. Key prerequisites include preemptive pathogen discovery, robust community-level diagnostics, equitable vaccine and therapeutic access, and the immediate prioritization of ecological preservation as a core public health mandate. Failure to adopt this proactive posture guarantees continued cycles of crisis, economic disruption, and avoidable mortality.

Keywords: Emerging Infectious Diseases, Zoonotic Spillover, One Health, Global Health Security, Climate Change, Predictive Epidemiology, Surveillance.

[This article belongs to International Journal of Tropical Medicines ]

How to cite this article:
Dr. Kazi Kutubuddin. A Study on accelerating threat of Emerging Infectious Diseases (EIDs) and imperative for a proactive, interdisciplinary Global Health Security Framework. International Journal of Tropical Medicines. 2026; 03(01):8-21.
How to cite this URL:
Dr. Kazi Kutubuddin. A Study on accelerating threat of Emerging Infectious Diseases (EIDs) and imperative for a proactive, interdisciplinary Global Health Security Framework. International Journal of Tropical Medicines. 2026; 03(01):8-21. Available from: https://journals.stmjournals.com/ijtm/article=2026/view=236617


References

1. McArthur DB. Emerging infectious diseases. Nurs Clin North Am. 2019;54(2):297–311. doi:
10.1016/j.cnur.2019.02.006.
2. Petersen E, Petrosillo N, Koopmans M, ESCMID Emerging Infections Task Force Expert Panel.
Emerging infections: An increasingly important topic. Clin Microbiol Infect. 2018;24(4):369–75.
doi: 10.1016/j.cmi.2017.10.035.
3. Fauci AS, Morens DM. The perpetual challenge of infectious diseases. N Engl J Med. 2012;366(5):454–
61. doi: 10.1056/NEJMra1108296.
4. Morens DM, Fauci AS. Emerging infectious diseases: Threats to human health and global stability.
PLoS Pathog. 2013;9(7):e1003467. doi: 10.1371/journal.ppat.1003467.
5. Wolfe ND, Dunavan CP, Diamond J. Origins of major human infectious diseases. Nature.
2007;447:279–83. doi: 10.1038/nature05775.
6. Rosenberg R, Lindsey NP, Fischer M, et al. Vital signs: Trends in reported vector-borne disease
cases—United States and territories, 2004–2016. MMWR Morb Mortal Wkly Rep. 2018;67(17):496–
501. doi: 10.15585/mmwr.mm6717e1.
7. Rathore MH, Runyon J, Haque TU. Emerging infectious diseases. Adv Pediatr. 2017;64:27–71.
doi: 10.1016/j.yapd.2017.04.002.
8. Tamboli DA, Sawant VA, Sathe S. AI-driven IoT (AIIoT)-based decision-making KSK approach
in drones for climate change study. In: Proc 4th Int Conf Ubiquitous Comput Intell Inf Syst (ICUIS).
Gobichettipalayam, India; 2024. p. 1735–44. doi: 10.1109/ICUIS64676.2024.10866450.
9. Liyakat KKS. Explainable AI in healthcare. In: Kamaraj AA, Acharjya DP, editors. Explainable Artificial
Intelligence in Healthcare Systems. 2024. ISBN: 979-8-89113-598-7. doi: 10.52305/GOMR8163.
10. Liyakat KK. Heart health monitoring using IoT and machine learning methods. In: Shaik A, editor.
AI-Powered Advances in Pharmacology. Hershey (PA): IGI Global; 2025. p. 257–82. doi:
10.4018/979-8-3693-3212-2.ch010.
11. Mahant MA. Machine learning-driven Internet of Things (MLIoT)-based healthcare monitoring
system. In: Wickramasinghe N, editor. Digitalization and the Transformation of the Healthcare
Sector. Hershey (PA): IGI Global Scientific Publishing; 2025. p. 205–36. doi: 10.4018/979-8-3693-
9641-4.ch007.
12. Mulani AO, Liyakat KKS, Warade NS, et al. ML-powered Internet of Medical Things structure for
heart disease prediction. J Pharmacol Pharmacother. 2025;0(0). doi: 10.1177/0976500X241306184.

13. Khadake SB, Chounde AB, Suryagan AA, Khadatare MR. AI-driven IoT (AIIoT)-based decision-
making system for high blood pressure patient healthcare monitoring. In: Proc Int Conf Sustain

Commun Netw Appl (ICSCNA); 2024; Theni, India. p. 96–102. doi: 10.1109/ICSCNA63714.
2024.10863954.

Regular Issue Subscription Review Article
Volume 03
Issue 01
Received 10/10/2025
Accepted 24/10/2025
Published 20/01/2026
Publication Time 102 Days
133

Login


My IP

PlumX Metrics