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. 2024 Sep 6;196(10):900.
doi: 10.1007/s10661-024-13052-9.

Use of agent-based modeling to analyze potential non-occupational exposures to asbestos of the general population of Sibaté (Colombia)

Françoise Duraffour  1 , Juan Pablo Ramos-Bonilla  2   3 , Benjamin Lysaniuk  4
Affiliations

Use of agent-based modeling to analyze potential non-occupational exposures to asbestos of the general population of Sibaté (Colombia)

Françoise Duraffour et al. Environ Monit Assess. .

Abstract

Previous studies conducted in the municipality of Sibaté (Colombia) have revealed alarming findings regarding asbestos exposure in the region, as it is the site of the country's first mesothelioma cluster. Non-occupational asbestos exposure events were identified in this population, and the young age of the mesothelioma cases at the time of diagnosis suggests that asbestos exposure occurred during their childhood. The creation of landfilled zones in the 1980s and 1990s, utilizing friable asbestos among other disposed materials, may have been a significant asbestos exposure event contributing to the elevated number of mesothelioma cases. The objective of this study was to model various historical exposure scenarios related to the creation and interaction of the population with asbestos-contaminated landfilled zones, in light of the absence of asbestos monitoring in the region. The models utilized a multi-agent simulation process, focusing on a 10-year period (1986-1995). Various relevant variables were incorporated into the modeling process, including, for example, the number of children playing in the landfilled zones and the percentage of children carrying asbestos fibers on their clothes to their homes. A range of values for input data for the models were utilized, spanning from very conservative numbers to exposure-promoting values. The average number of exposed individuals estimated over 750 simulation runs, considering all scenarios, was 571, with a range between 31 and 3800 exposed individuals. The use of multi-agent simulation models can assist the understanding of past asbestos exposure events, especially when there is a lack of environmental surveillance data.

Keywords: Agent-based modeling; Asbestos; Environmental exposure; Landfilled zones; Sibaté (Colombia).

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