COVID-19 Flow-Maps an open geographic information system on COVID-19 and human mobility for Spain.
Sci Data
; 8(1): 310, 2021 11 30.
Article
in English
| MEDLINE | ID: covidwho-1545633
Preprint
This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
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This scientific journal article is probably based on a previously available preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
See preprint
ABSTRACT
COVID-19 is an infectious disease caused by the SARS-CoV-2 virus, which has spread all over the world leading to a global pandemic. The fast progression of COVID-19 has been mainly related to the high contagion rate of the virus and the worldwide mobility of humans. In the absence of pharmacological therapies, governments from different countries have introduced several non-pharmaceutical interventions to reduce human mobility and social contact. Several studies based on Anonymized Mobile Phone Data have been published analysing the relationship between human mobility and the spread of coronavirus. However, to our knowledge, none of these data-sets integrates cross-referenced geo-localised data on human mobility and COVID-19 cases into one all-inclusive open resource. Herein we present COVID-19 Flow-Maps, a cross-referenced Geographic Information System that integrates regularly updated time-series accounting for population mobility and daily reports of COVID-19 cases in Spain at different scales of time spatial resolution. This integrated and up-to-date data-set can be used to analyse the human dynamics to guide and support the design of more effective non-pharmaceutical interventions.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Travel
/
Geographic Information Systems
/
COVID-19
Type of study:
Experimental Studies
/
Observational study
/
Randomized controlled trials
Limits:
Humans
Country/Region as subject:
Europa
Language:
English
Journal:
Sci Data
Year:
2021
Document Type:
Article
Affiliation country:
S41597-021-01093-5
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