Modeling the effects of flight itinerary on jetlag duration

Jetlag affects millions of travelers daily, yet influences of flight schedules on circadian disruption remain unclear. We aimed to quantify the effects of flight itinerary on jetlag duration at the group-average level and to identify underlying physiological mechanisms.

We used biophysical modeling to analyze how flight departure and duration times impacted jetlag across 55 296 simulated flights. Simulated flights spanned time zone differences, ΔT, from -12 to 12 h and departed between 00:30 and 24:00 with durations from 0.5 to 24 h. Two cases were compared: (1) free sleep and (2) forced wakefulness during daytime at the destination. In-flight sleep followed the physiological need for sleep.

Flight itineraries affected jetlag duration for all ΔTs and determined the direction of circadian adaptation for a subset of ΔTs depending on behavior at the destination. The highest variability of jetlag duration was observed for ΔT >0 h, peaking at ΔT = 9 h. Overall, for 1 ≤ ΔT ≤ 9 h, jetlag was shortest for flights departing or arriving around habitual wake time and longest when departing or arriving near habitual sleep onset. When in-flight sleep was restricted, the shortest jetlag for these ΔTs was instead observed for flights arriving during the circadian day. This pattern reversed for other ΔTs.

Flight departure and arrival times contribute to the variability of jetlag duration and can reverse the direction of circadian adaptation post-flight. These dynamics are mainly governed by light exposure and sleep timing during and around flights. Statement of Significance This study provides a quantitative analysis of how flight itineraries interact with circadian and sleep physiology to determine jetlag duration. By simulating over 55 000 flights across all time zone transitions, we reveal systematic patterns linking flight timing with adaptation time and the opportunities to minimize circadian disruption through itinerary design and behaviors during and around flights. These findings advance the mechanistic understanding of jetlag and offer actionable insights for travelers and airlines to reduce jetlag impact through optimized flight schedules and personalized strategies.