The use and reporting of airline passenger data for infectious disease modelling: a systematic review.
airline data
infection, epidemic, passenger data
infectious disease spread
mathematical modelling
outbreaks
travel
Journal
Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin
ISSN: 1560-7917
Titre abrégé: Euro Surveill
Pays: Sweden
ID NLM: 100887452
Informations de publication
Date de publication:
Aug 2019
Aug 2019
Historique:
entrez:
8
8
2019
pubmed:
8
8
2019
medline:
18
7
2020
Statut:
ppublish
Résumé
BackgroundA 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.AimWe 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.MethodsArticles 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.ResultsWe 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.LimitationsBy 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.ConclusionWe 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.
Identifiants
pubmed: 31387671
doi: 10.2807/1560-7917.ES.2019.24.31.1800216
pmc: PMC6685100
doi:
Types de publication
Journal Article
Systematic Review
Langues
eng
Sous-ensembles de citation
IM
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