Evidence map›Paper›PMID 41786631›Full record

ArticleSleep2026

Modeling the effects of flight itinerary on jetlag duration.

Shuzheng Huang, Yu Sun Bin, Corinne Caillaud, Svetlana Postnova

Abstract read
In one paragraph

Article in Sleep, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shuzheng HuangSchool of Physics, University of Sydney, Sydney, NSW, Australia.
Yu Sun BinCharles Perkins Centre, University of Sydney, Sydney, NSW, Australia.ORCID 0000-0002-4954-2658
Corinne CaillaudCharles Perkins Centre, University of Sydney, Sydney, NSW, Australia.
Svetlana PostnovaSchool of Physics, University of Sydney, Sydney, NSW, Australia.

Funding

Faculty of Science Research Stipend Scholarship from the Faculty of ScienceUniversity of Sydney
6 · The paper itself

Abstract

STUDY

objectivesJetlag 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.

methodsWe 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.

resultsFlight 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.

conclusionsFlight 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.

Indexed as

Air TravelCircadian RhythmJet Lag SyndromeHumansSleepTime FactorsWakefulnesscircadian misalignmententrainmentflight itineraryjetlaglightmodelingquantitativesleep

Identifiers

PMID41786631
PMCPMC13267907

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LicenceCC BY-NC
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.