The use and reporting of airline passenger data for infectious disease modelling: A systematic review

Margaux Marie Isabelle Meslé, Ian Hall, Robert Matthew Christley, Stephen Leach, Jonathan Michael Read

Research output: Contribution to journalReview articlepeer-review

5 Citations (Scopus)

Abstract

Background: A variety of airline passenger data sources are used for modelling the international spread of infectious diseases. Questions exist regarding the suitability and validity of these sources. Aim: We conducted a systematic review to identify the sources of airline passenger data used for these purposes and to assess validation of the data and reproducibility of the methodology. Methods: Articles matching our search criteria and describing a model of the international spread of human infectious disease, parameterised with airline passenger data, were identified. Information regarding type and source of airline passenger data used was collated and the studies’ reproducibility assessed. Results: We identified 136 articles. The majority (n = 96) sourced data primarily used by the airline industry. Governmental data sources were used in 30 studies and data published by individual airports in four studies. Validation of passenger data was conducted in only seven studies. No study was found to be fully reproducible, although eight were partially reproducible. Limitations: By limiting the articles to international spread, articles focussed on within-country transmission even if they used relevant data sources were excluded. Authors were not contacted to clarify their methods. Searches were limited to articles in PubMed, Web of Science and Scopus. Conclusion: We recommend greater efforts to assess validity and biases of airline passenger data used for modelling studies, particularly when model outputs are to inform national and international public health policies. We also recommend improving reporting standards and more detailed studies on biases in commercial and open-access data to assess their reproducibility.

Original languageEnglish
Article number1800216
JournalEurosurveillance
Volume24
Issue number31
DOIs
Publication statusPublished - 1 Aug 2019

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