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This work evaluates the potential root causes of fatigue using abiomathematical model and a robust sample of aircrew rosters from the Brazilianregular aviation. The fatigue outcomes derive from the software Sleep,Activity, Fatigue, and Task Effectiveness Fatigue Avoidance Scheduling Tool(SAFTE-FAST). The average minimum SAFTE-FAST effectiveness during criticalphases of flight decreases cubically with the number of shifts that elapsetotally or partially between mid-night and 6 a.m. within a 30-day period($N_{NS}$). As a consequence, the relative fatigue risk increases by 23.3% (95%CI, 20.4-26.2%) when increasing $N_{NS}$ from 1 to 13. The average maximumequivalent wakefulness in critical phases also increases cubically with thenumber of night shifts and exceeds 24 hours for rosters with $N_{NS}$ above 10.The average fatigue hazard area in critical phases of flight variesquadratically with the number of departures and landings within 2 and 6 a.m.($N_{Wocl}$). These findings demonstrate that both $N_{NS}$ and $ N_{Wocl}$should be considered as key performance indicators and be kept as low asreasonably practical when building aircrew rosters. The effectiveness scores at30 minute time intervals allowed a model estimate for the relative fatigue riskas a function of the time of the day, whose averaged values show reasonablequalitative agreement with previous measurements of pilot errors. Tailoredanalyses of the SAFTE-FAST inputs for afternoon naps before night shifts,commuting from home to station and vice-versa, and bedtime before early-startshifts show relevant group effects ($p < 0.001$) comparing the groups with andwithout afternoon naps, with one or two hours of commuting and with or withoutthe advanced bedtime feature of the SAFTE-FAST software, evidencing the need ofa better and more accurate understanding of these parameters when modellingfatigue risk factors.

Evaluating the root causes of fatigue and associated risk factors in the Brazilian regular aviation industry