Sleepiness and fatigue are important risk factors in the transport sector and bio-mathematical sleepiness, sleep and fatigue modeling is increasingly becoming a valuable tool for assessing safety of work schedules and rosters in Fatigue Risk Management Systems (FRMS). The present study sought to validate the inner workings of one such model, Three Process Model (TPM), on aircrews and extend the model with functions to model jetlag and to directly assess the risk of any sleepiness level in any shift schedule or roster with and without knowledge of sleep timings. We collected sleep and sleepiness data from 136 aircrews in a real life situation by means of an application running on a handheld touch screen computer device (iPhone, iPod or iPad) and used the TPM to predict sleepiness with varying level of complexity of model equations and data. The results based on multilevel linear and non-linear mixed effects models showed that the TPM predictions correlated with observed ratings of sleepiness, but explorative analyses suggest that the default model can be improved and reduced to include only two-processes (S+C), with adjusted phases of the circadian process based on a single question of circadian type. We also extended the model with a function to model jetlag acclimatization and with estimates of individual differences including reference limits accounting for 50%, 75% and 90% of the population as well as functions for predicting the probability of any level of sleepiness for ecological assessment of absolute and relative risk of sleepiness in shift systems for safety applications.

Fatigue is a major cause of accidents in transport work, including aviation, according to the National Transportation Safety Board (NTSB, 1999). Because fatigue-related safety is linked to scheduling practice, authorities attempt to prevent fatigue through flight time limitations. The European Aviation Safety Agency (EASA) identifies night flying, early morning starts, long flight duty periods (>13 h during daytime) and a high level of sectors as scheduling characteristics contributing to aircrew fatigue (Commission, 2014).Several of these limitations are founded on experience and on results from circadian and sleep science (Rangan et al., 2020).There is no consensus definition of fatigue, but in aviation research it has a connotation of sleepiness (Caldwell et al., 2009;Weiland et al., 2013), which refers to a drive towards sleep (Dement & Carskadon, 1982). Fatigue in aviation shows a pronounced link with sleep loss, time awake and time of day (Dawson & McCulloch, 2005;

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