https://doi.org/10.1140/epjp/s13360-024-05647-5
Regular Article
Testing and results of an open-source radiation epidemiology model using the Goiânia accident
1
Department of Industrial Engineering, University of Rome Tor Vergata, Rome, Italy
2
Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy
3
The American University of Rome, Rome, Italy
Received:
15
June
2024
Accepted:
11
September
2024
Published online:
9
October
2024
In the event of dispersed radioactive materials, whether from accidental orphan sources or deliberate use of radiological dispersal devices (RDD) or radiological exposure devices (RED), free open-source modelling codes can greatly assist in forecasting the dispersion of the radiation following the event. Several codes are currently available to quickly calculate the progression of radiological dispersion. However, most of these codes can only simulate the evolution of the threat for limited times after the event and over relatively short distances from the location. In order to predict the transport of radioactive material over long distances and for long times, and thus prevent its expected effects on the exposed population, specific epidemiological codes can be used, taking into account the characteristic of the radiation. If it is considered that radioactive material can be deposited on unsuspecting people who continue their daily activities after exposure, it can be assumed that these people unintentionally carry this radioactive material over long distances. This scenario is comparable to viral vectors of a hypothetical virus designed to mimic the physical characteristics of radiation. In this work, the free open-source spatio-temporal epidemiological modeller (STEM) tool is used to simulate the spread of a chimeric viral agent with specific characteristics of Ebola and COVID-19, designed to replicate the biological conditions caused by exposure to a Cs-137 source for an individual unaware of the risk. The goal is to predict the territorial spread of radioactive material caused by a CBRNe event, such as orphan sources or the use of a RDD or a RED, and its possible effects on the affected population. This supports decision-makers in forecasting the consequences of radioactive material spread and thus helps in reducing the risk. The code was tested comparing its results with the real case of the famous 1987 Goiânia radiological accident. The results show that the developed code was indeed able to accurately represent the number of contaminated individuals and the number of casualties within a month of the initial exposure, with a distribution of radioactive material in the territory similar to that actually caused by the Goiânia accident.
© The Author(s) 2024
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