Dataset Information

From data to complex network control of airline flight delays.

ABSTRACT: Many critical complex systems and networks are continuously monitored, creating vast volumes of data describing their dynamics. To understand and optimize their performance, we need to discover and formalize their dynamics to enable their control. Here, we introduce a multidisciplinary framework using network science and control theory to accomplish these goals. We demonstrate its use on a meaningful example of a complex network of U.S. domestic passenger airlines aiming to control flight delays. Using the real data on such delays, we build a flight delay network for each airline. Analyzing these networks, we uncover and formalize their dynamics. We use this formalization to design the optimal control for the flight delay networks. The results of applying this control to the ground truth data on flight delays demonstrate the low costs of the optimal control and significant reduction of delay times, while the costs of the delays unabated by control are high. Thus, the introduced here framework benefits the passengers, the airline companies and the airports.

SUBMITTER: Niu X

PROVIDER: S-EPMC8455581 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature

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From data to complex network control of airline flight delays.

Niu Xiang X Jiang Chunheng C Gao Jianxi J Korniss Gyorgy G Szymanski Boleslaw K BK

Scientific reports 20210921 1

Many critical complex systems and networks are continuously monitored, creating vast volumes of data describing their dynamics. To understand and optimize their performance, we need to discover and formalize their dynamics to enable their control. Here, we introduce a multidisciplinary framework using network science and control theory to accomplish these goals. We demonstrate its use on a meaningful example of a complex network of U.S. domestic passenger airlines aiming to control flight delays ...[more]

PMID: 34548546

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Project description:BackgroundIn-flight medical emergencies (IMEs) can have severe outcomes, including the deaths of passengers and aircraft diversions. Information is lacking regarding the incidence rate and characteristics of IMEs in most countries, especially in mainland China.ObjectiveThe objective of this study was to investigate the incidence, patterns, and associated risk factors of IMEs in mainland China and to provide medical suggestions for the evaluation and management of IMEs.MethodsThis population-based retrospective study examined electronic records for all IME reports between January 1, 2018, and December 31, 2022, from a major airline company in mainland China. Outcome variables included the medical category of the IMEs, the outcomes of first aid, and whether or not the IMEs led to a flight diversion. We calculated the incidence rate and death rate of IMEs based on the number of passengers and flights, respectively. A logistic regression model was used to investigate the factors associated with aircraft diversions.ResultsA total of 199 IMEs and 24 deaths occurred among 447.2 million passengers, yielding an incidence rate of 0.44 (95% CI 0.39-0.51) events per million passengers and 66.56 (95% CI 50.55-86.04) events per million flights, and an all-cause mortality rate of 0.05 (95% CI 0.03-0.07) events per million passengers and 7.50 (95% CI 4.81-11.16) events per million flights. From 2018 to 2022, the highest incidence and mortality rates were observed in 2019 and 2020, respectively, while the lowest were in 2020 and 2021, respectively. Additionally, the highest incidence and mortality rates were observed between 6 PM to 6 AM and noon to 6 PM, respectively. There was a higher incidence rate of IMEs in the winter months. Moreover, the highest case-fatality rates were observed in 2019 (12/74, 16.2%), on flights traveling ≥4000 km (9/43, 20.9%), and on wide-body planes (10/52, 19.2%). Seizures (29/199, 14.6%), cardiac symptoms (25/199, 12.6%), and syncope or presyncope (19/199, 9.6%) were the most common medical problems and main reasons for aircraft diversion. The incidence of aircraft diversion was 42.50 (95% CI 37.02-48.12) events per million flights. Narrow-body planes (odds ratio [OR] 5.69, 95% CI 1.05-30.90), flights ≥4000 km (OR 16.40, 95% CI 1.78-151.29), and the months of December to February (OR 12.70, 95% CI 3.09-52.23), as well as the months of March to May (OR 23.21, 95% CI 3.75-143.43), were significantly associated with a higher risk of diversion.ConclusionsThe occurrence of and deaths associated with IMEs are rare in mainland China, but a temporal trend shows higher incidence rates at night and in winter. The leading IMEs are cardiac symptoms, seizures, and syncope. The establishment of a unified reporting system for IMEs and ground-to-air medical support are of great value for reducing IMEs and deaths in the global community.

Dataset Information

From data to complex network control of airline flight delays.

Publications

From data to complex network control of airline flight delays.

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