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Korchevskiy, A.A. and Wylie, A.G. (2022) Asbestos Exposure, Lung Fiber Burden, and Mesothelioma Rates: Mechanistic Modelling for Risk Assessment. Computational Toxicology, 24, Article 100249.
https://doi.org/10.1016/j.comtox.2022.100249
https://www.sciencedirect.com/science/article/pii/S2468111322000378

has been cited by the following article:

• TITLE: Asbestos Exposure and Mesothelioma: Historical Insights and Modern Technological Impacts in the USA

  AUTHORS: Robb Shawe

  KEYWORDS: Asbestos Exposure, Mesothelioma, Retrospective Cohort, Case-Control Studies, Dose-Response, AI, Regulatory Frameworks, Occupational Health, Epidemiology, Digital Archives, Biomarker Discovery, Industrial Hygiene, Risk Assessment, Exposure Reconstruction, Latency Period, Public Health Policy

  JOURNAL NAME: Open Journal of Safety Science and Technology, Vol.15 No.4, October 22, 2025

  ABSTRACT: Asbestos exposure remains a critical public health concern in the United States due to its well-established link with mesothelioma. Understanding how risk is estimated and how modern advancements are improving exposure assessment is essential for prevention and policy. Researchers rely on retrospective cohort and case-control study designs to reconstruct past exposures and analyze the dose-response relationship between asbestos and mesothelioma. Significant challenges include missing records, the long latency period of asbestos-related diseases, and the complexity of reconstructing both occupational and non-occupational exposures. Modern tools such as electronic archives and artificial intelligence now help fill data gaps and make exposure assessments more reliable. By combining expertise from medicine, data science, and policy, collaborative approaches are shaping exposure limits and regulations. Studying the past with new technologies is guiding future prevention of mesothelioma and enhancing public health protection.