Predictive Biomathematical Modeling Compared to Objective Sleep During COVID-19 Humanitarian Flights

Area of Science:

• Aviation Physiology
• Biomathematical Modeling
• Human Factors in Flight Operations

Background:

• Biomathematical models like SAFTE and FAST are used for predicting pilot fatigue risk in planned flight schedules.
• The accuracy of these models during extreme, unforeseen operations, such as COVID-19 humanitarian flights, was previously unknown.
• Azul Cargo Express conducted humanitarian missions to China in 2020, providing an opportunity to test model accuracy.

Purpose of the Study:

• To evaluate the accuracy of the AutoSleep algorithm (within SAFTE-FAST) in predicting in-flight sleep duration and pilot effectiveness.
• To compare AutoSleep predictions with pilot sleep diaries and actigraphy data from actual humanitarian missions.
• To assess the reliability of biomathematical models under extreme operational conditions.

Main Methods:

• Twenty pilots participating in five humanitarian missions provided sleep diary and actigraphy data using Zulu watches.
• Intraclass correlation coefficients (ICC) were used to compare the agreement between AutoSleep predictions, sleep diaries, and actigraphy.
• The R² statistic was employed to evaluate the goodness-of-fit for predicted effectiveness distributions.

Main Results:

• Excellent agreement (ICC > 0.90) was observed between AutoSleep predictions, pilot sleep diaries, and actigraphy data.
• The R² statistic also exceeded 0.90, indicating a strong goodness-of-fit for predicted pilot effectiveness.
• The study found that biomathematical predictions aligned well with actual sleep patterns during these extreme missions.

Conclusions:

• Biomathematical models, such as AutoSleep, maintain predictive accuracy for pilot sleep and effectiveness even during unprecedented humanitarian operations.
• These findings suggest that biomathematical models are robust and reliable tools for fatigue risk management in extreme flight scenarios.
• Pilots may overestimate their sleep during demanding flight duties, highlighting a potential fatigue risk that requires careful management.