Cost-effective approach to lung cancer risk for a radiological dispersal device (RDD) scenario

Abstract

Abstract A release of radioactive material into the environment can lead to hazardous exposure of the population and serious future concerns about health issues such as an increased incidence of cancer. In this context, a practical methodology capable of providing useful basic information from the scenario can be valuable for immediate decisions and future risk assessment. For this work, the simulation of a radiological dispersal device (RDD) filled with americium-241 was considered. The radiation dose simulated by the HotSpot code was used as an input to the epidemiological equations from BEIR V producing the data used to assess the risk of lung cancer development. The methodology could be useful in providing training for responders aimed to the initial support addressed to decision-making for emergency response at the early phase of an RDD scenario. The results from the simulation allow estimating (a) the size of the potentially affected population, (b) the type of protection action considering gender and location of the individuals, (c) the absorbed doses, (d) the matrix of lung cancer incidence predictions over a period of 5 years, and (e) the cost-effectiveness in the initial decision environment.