RENEB accident simulation exercise

Abstract

Purpose: The RENEB accident exercise was carried out in order to train the RENEB participants in coordinating and managing potentially large data sets that would be generated in case of a major radiological event. Materials and methods: Each participant was offered the possibility to activate the network by sending an alerting email about a simulated radiation emergency. The same participant had to collect, compile and report capacity, triage categorization and exposure scenario results obtained from all other participants. The exercise was performed over 27 weeks and involved the network consisting of 28 institutes: 21 RENEB members, four candidates and three non-RENEB partners. Results: The duration of a single exercise never exceeded 10 days, while the response from the assisting laboratories never came later than within half a day. During each week of the exercise, around 4500 samples were reported by all service laboratories (SL) to be examined and 54 scenarios were coherently estimated by all laboratories (the standard deviation from the mean of all SL answers for a given scenario category and a set of data was not larger than 3 patient codes). Conclusions: Each participant received training in both the role of a reference laboratory (activating the network) and of a service laboratory (responding to an activation request). The procedures in the case of radiological event were successfully established and tested. ARTICLE HISTORY

RENEB – Running the European Network of biological dosimetry and physical retrospective dosimetry

“…The partners were trained in handling large data sets; in addition, the repeated collection of information gave an important insight about the capacity of each lab to the state of preparedness of the network. Details and outcome of this accident simulation exercise are described in this special issue (Brzozowska et al 2016). Key information about the operational network performance is given in Table 2, based on the findings of the accident simulation exercise (Brzozowska et al 2016) and on a survey amongst RENEB partners .…”

“…Details and outcome of this accident simulation exercise are described in this special issue (Brzozowska et al 2016). Key information about the operational network performance is given in Table 2, based on the findings of the accident simulation exercise (Brzozowska et al 2016) and on a survey amongst RENEB partners .…”

Uncertainty of fast biological radiation dose assessment for emergency response scenarios

“…The mean uncertainty reported in rapid categorization mode in the publications listed above was calculated for the relevant exposure scenarios at doses of 0, 0.5, 1, 1.5,2 and 2.5 Gy and applied to the DIC, MN, gamma-H2AX and PCC assay data (doses only) from the RENEB table top exercise (Brzozowska et al 2016). The standard normal distribution was then used to calculate the probability of correct categorization for each data point (consisting of the mean of the dosimetry results from each of the assays) from the RENEB exercise, in order to test the impact of uncertainty on the success of the rapid dose assessment and categorization procedure.…”

“…Test data for all assays and scenarios were also taken from the RENEB accident simulation (Brzozowska et al 2016), in order to test the impact of including uncertainty estimation on rapid biodosimetry categorization. Uncertainty calculations were based on the number of aberrations observed in 50 cells for all assays, corresponding to the recommended methods for fast dose assessment purposes.…”

“…Where appropriate, the methods have been applied to data from the dicentric, gamma-H2AX, micronucleus and PCC assays. The probability of correct rapid categorization (< 1 Gy; 1-2 Gy; 2þ Gy) given the magnitude of the associated uncertainties was then tested using data from recent MULTIBIODOSE and RENEB inter-comparison exercises and the RENEB 'table-top' rapid biodosimetric categorization exercise, which amongst other things has resulted in the creation of a formal expert consensus for fast assessment (Brzozowska et al 2016). Finally, the potential for and implications of inclusion of an assessment of uncertainty into rapid biodosimetric information provided to emergency responders or other medical professionals is considered.…”