Search Results (5)

Background: Modeling tools should be tested against real-world outcomes to confirm their predictive ability compared to random chance. Insights is an analytical tool within the biomathematical modeling software SAFTE-FAST that identifies work patterns that consistently result in elevated fatigue risk. This study investigated the ability of Insights to correctly identify duties with an associated fatigue report using previously collected flight schedule and report data. Methods: Planned and completed flight roster schedules were analyzed using SAFTE-FAST Insights after the rosters had been flown. Fatigue reports were independently linked to planned and completed schedules at the duty level. Odds ratio (OR) analysis investigated the ability of Insights to predict which duties would be linked to a fatigue report. Differences in duties were compared using a one-way analysis of variance (ANOVA) and a two-sample t-test. Results: There were 157 fatigue reports out of 78,061 planned duties and 235 fatigue reports out of 82,612 completed duties. Insights had 3.04 odds of correctly identifying fatigue reports in planned duties but 0.41 odds for completed duties. Discussion: Insights showed good odds of correctly identifying a fatigue report duty using planned schedules but poor odds of identifying a fatigue report duty from completed schedules. Completed duties started later in the day and were shorter in duration than planned duties. Day-of-operations schedule changes may have reduced the fatigue risk in response to the fatigue reports. Full article

The routine assessment of pilot fatigue is paramount to ensuring aviation safety. However, current designs of pilot fatigue factors often lack the comprehensiveness needed to fully account for the dynamic and cumulative nature of fatigue. To bridge this gap, this study introduces a biomathematical fatigue model (BFM) that leverages system dynamics theory, integrating a dynamic feedback mechanism for fatigue information. The novelty of this approach lies in its capability to continuously capture and model fatigue fluctuations driven by varying operational demands. A comparative analysis with international methodologies for evaluating cumulative fatigue on weekly and monthly scales demonstrates that the proposed BFM effectively reproduces variations in pilot fatigue characteristics. Moreover, the pilot fatigue coefficient derived from the model provides a robust differentiation of fatigue profiles across diverse work types, making it particularly suitable for estimating cumulative fatigue over monthly intervals. This BFM-based approach offers valuable insights for the strategic planning of flight schedules and establishes an innovative framework for utilizing BFMs in fatigue management. By employing a scientifically grounded evaluation method rooted in system dynamics and the BFM, this study rigorously assesses cumulative pilot fatigue, confirming the model’s accuracy in replicating fatigue patterns and validating the efficiency and reliability of the derived fatigue coefficient. Full article

During the COVID-19 pandemic, the question of how to reduce the risk of viral infection for international airline pilots without increasing the risk of fatigue was a novel and urgent theoretical and practical problem, which had never been encountered in the world civil aviation industry. A new scheduling method implemented by the Civil Aviation Administration of China (CAAC) is the extra augmented crew (EAC) schedule, which avoids crew layover in another country on international flights by extending the maximum duty time and adding two additional crew members to such long-haul flights. In this study, a multi-day flight crew fatigue assessment was conducted to evaluate the impact of EAC flight. We recruited 71 pilots as participants, and their fatigue during EAC flights was measured using a multimodality approach integrating a subjective fatigue report, a psychomotor vigilance task, sleep monitoring, and biomathematical model predictions. The results showed that the subjective fatigue level increased during duty time compared to off-duty time, but still with acceptable levels of under 7, as measured by the Karolinska Sleepiness Scale; objective secondary task performance, as measured by the classic psychomotor vigilance task, showed no differences; pilots were able to get around 6 h of sleep, although they slept less during duty time compared to off-duty time. Model fitting using the FAID biomathematical model of fatigue confirmed that the EAC scheduling was compliant with the FAID tolerance level 91.3% of the time. The results suggest that the EAC flight created some moderate level of increased fatigue but no severe fatigue to cross-continent long-haul flight crews. This research can inform current and future scheduling and fatigue risk control during the pandemic or for future time-sensitive periods. Full article

Background: Permanent Daylight Savings Time (DST) may improve road safety by providing more daylight in the evening but could merely shift risk to morning commutes or increase risk due to fatigue and circadian misalignment. Methods: To identify how potential daylight exposure and fatigue risk could differ between permanent DST versus permanent Standard Time (ST) or current time arrangements (CTA), generic work and school schedules in five United States cities were modeled in SAFTE-FAST biomathematical modeling software. Commute data were categorized by morning (0700–0900) and evening (1600–1800) rush hours. Results: Percent darkness was greater under DST compared with ST for the total waking day (t = 2.59, p = 0.03) and sleep periods (t = 2.46, p = 0.045). Waketimes occurred before sunrise 63 ± 41% percent of the time under DST compared with CTA (42 ± 37%) or ST (33 ± 38%; F(_2,74) = 76.37; p < 0.001). Percent darkness was greater during morning (16 ± 31%) and lower during evening rush hour (0 ± 0%) in DST compared with either CTA (morning: 7 ± 23%; evening: 7 ± 14%) or ST (morning: 7 ± 23%; evening: 7 ± 15%). Discussion: Morning rush hour overlaps with students’ commutes and shift workers’ reverse commutes, which may increase traffic congestion and risk compared with evening rush hour. Switching to permanent DST may be more disruptive than either switching to ST or keeping CTA without noticeable benefit to fatigue or potential daylight exposure. Full article

Neurobehavioral task performance is modulated by the circadian and homeostatic processes of sleep/wake regulation. Biomathematical modeling of the temporal dynamics of these processes and their interaction allows for prospective prediction of performance impairment in shift-workers and provides a basis for fatigue risk management in 24/7 operations. It has been reported, however, that the impact of the circadian rhythm—and in particular its timing—is inherently task-dependent, which would have profound implications for our understanding of the temporal dynamics of neurobehavioral functioning and the accuracy of biomathematical model predictions. We investigated this issue in a laboratory study designed to unambiguously dissociate the influences of the circadian and homeostatic processes on neurobehavioral performance, as measured during a constant routine protocol preceded by three days on either a simulated night shift or a simulated day shift schedule. Neurobehavioral functions were measured every 2 h using three functionally distinct assays: a digit symbol substitution test, a psychomotor vigilance test, and the Karolinska Sleepiness Scale. After dissociating the circadian and homeostatic influences and accounting for inter-individual variability, peak circadian performance occurred in the late biological afternoon (in the “wake maintenance zone”) for all three neurobehavioral assays. Our results are incongruent with the idea of inherent task-dependent differences in the endogenous circadian impact on performance. Rather, our results suggest that neurobehavioral functions are under top-down circadian control, consistent with the way they are accounted for in extant biomathematical models. Full article