About: Estimating COVID-19 outbreak risk through air travel

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Estimating COVID-19 outbreak risk through air travel
Creator	Thompson, R Daon, Authors Obolski, U
topic	covid:07a6bab4dccb5d0d721b144514da2d1b0f520cee#this
Source	MedRxiv
abstract	Background: COVID-19 has spread rapidly across the globe during the first several months of 2020, creating a pandemic. Substantial, non-discriminatory limitations have been imposed on air travel to inhibit this spread. As the disease prevalence and incidence will decrease, more specific control measures will be sought so that commercial air travel can continue to operate yet not impose a high threat of COVID-19 resurgence. Methods: We use modelled global air travel data and population density estimates to analyse the risk posed by 1364 airports to initiate a COVID-19 outbreak. We calculate the risk using a probabilistic approach that considers the volume of air travelers between airports and the R0 of each location, scaled by population density. This exercise is performed globally as well as specifically for two potentially vulnerable locations: Africa and India. Results: We show that globally, many of the airports posing the highest risk are in China and India. An outbreak of COVID-19 in Africa is most likely to originate in a passenger travelling from Europe. On the other hand, the highest risk to India is from domestic travellers. Our results are robust to changes in the underlying epidemiological assumptions. Conclusions: Variation in flight volumes and destinations creates a non-uniform distribution of the risk different airports pose to resurgence of a COVID-19 outbreak. We suggest the method presented here as a tool for the estimation of this risk. Our method can be used to inform efficient allocation of resources, such as tests identifying infected passengers, so that they could be differentially deployed in various locations.
has issue date	2020-04-20(xsd:dateTime)
bibo:doi	10.1101/2020.04.16.20067496
has license	medrxiv
sha1sum (hex)	07a6bab4dccb5d0d721b144514da2d1b0f520cee
schema:url	https://doi.org/10.1101/2020.04.16.20067496
resource representing a document's title	Estimating COVID-19 outbreak risk through air travel
resource representing a document's body	covid:07a6bab4dccb5d0d721b144514da2d1b0f520cee#body_text
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