About: Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan

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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	Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan
Creator	Kahn, Rebecca Buckee, Caroline Chang, Hsiao-Han Chang, Meng-Chun Lee, Cheng-Sheng Li, Yu-An
Source	MedRxiv; Medline; PMC
abstract	BACKGROUND: As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. METHODS: In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. RESULTS: We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. CONCLUSIONS: To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.
has issue date	2020-08-12(xsd:dateTime)
bibo:doi	10.1101/2020.04.07.20053439
bibo:pmid	32817972
has license	cc-by
sha1sum (hex)	d7043741123337c06637ea3e19158c4307284b7b
schema:url	https://doi.org/10.1101/2020.04.07.20053439
resource representing a document's title	Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan
has PubMed Central identifier	PMC7430617
has PubMed identifier	32817972
schema:publication	medRxiv
resource representing a document's body	covid:d7043741123337c06637ea3e19158c4307284b7b#body_text
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