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01 · ABSTRACT

Abstract

Climate change is no longer a distant threat, but an active occupational health emergency that is silently eroding workforce productivity and health across the globe. While extreme heat and air pollution present immediate risks, these hazards interact synergistically with socioeconomic inequities to disproportionately affect migrants and low-income laborers. This paper argues that traditional, reactive occupational safety models are inadequate for managing the dynamic and the cumulative nature of climate-related risks. We propose a transition toward a predictive resilience framework, exemplified by the "Pocket Ark" model. By harnessing Artificial Intelligence (AI), remote sensing, and longitudinal biometric data, this framework enables a comprehensive occupational health continuum, from pre-deployment risk stratification to long-term post-exposure surveillance. While drawing on the lessons from historical toxic exposures and current infrastructure failures, we highlight the necessity of integrating AI-enabled environmental intelligence with interdisciplinary leadership in Occupational and Environmental Medicine. Ultimately, the future of workforce protection depends on our ability to transform fragmented data into actionable, personalized resilience strategies, evolving the field of OEM into a proactive science of human and systemic adaptation.
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02 · OJS METADATA

Keywords

Climate ChangeOccupational HealthArtificial IntelligenceWorkforce ResilienceWorker Health ProtectionClimate AdaptationEnvironmental HealthFuture of Work
03 · PUBLICATION RECORD

Article details

JournalMedical Research Archives
IssueVol 14 No 6 (2026): Vol.14 Issue 6 June 2026
SectionEditorial
Published01 July 2026
DOI10.18103/mra.2026.0365
ISSN2375-1924
04 · RIGHTS & REUSE

Rights & reuse

This article is published under a Creative Commons Attribution License (CC BY 3.0) and may be shared or distributed by anyone as long as attribution is given to the journal.

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