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In the event of a radiation accident, biological dosimetry is essential for the timely determination of the radiation dose received by an exposed individual. The dose is estimated quantifying the amount of damage induced by radiation at a cellular level, for instance by counting the number of chromosome aberrations like dicentrics or micronuclei. The theory of count data distributions is essential for this aim. In this talk we introduce the standard statistical methodology for dose estimation described in the manual of the International Atomic Energy Agency (IAEA, 2011), and we also summarize the recent research led by our team. We present some models based on compound Poisson processes that are suitable to describe high-LET radiation exposures like those presented in the accident of Fukushima, models based on weighted Poisson distributions to integrate low and high doses and some Bayesian-type methods for Poisson inverse regression which have been implemented in the R package RADIR.
-Higueras M, Puig P, Ainsbury, EA, Rothkamm, K (2015). A new Inverse Regression Model Applied to Radiation Biodosimetry. Proceedings of the Royal Society A, 471:2174 , DOI: 10.1098/rspa.2014.0588
-IAEA (2011). Cytogenetic Dosimetry: Applications in Preparedness for and Response to Radiation Emergencies. International Atomic Energy Agency: Vienna.
-Moriña, D, Higueras M, Puig P, Ainsbury, EA, Rothkamm, K (2015). radir package: an R implementation for cytogenetic biodosimetry dose estimation. Journal of Radiological Protection, 35, p. 557–569.
-Puig, P., Barquinero, F. (2011). An Application of Compound Poisson Modelling to Biological Dosimetry. Proceedings of the Royal Society A, 467, 897-910.
-Pujol M, Barquinero JF, Puig P, Puig R, Caballín MR, Barrios L (2014). A New Model of Biodosimetry to Integrate Low and High Doses, PlosOne, 1-19, DOI: 10.1371/journal.pone.0114137.


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