2020
DOI: 10.1038/s41467-020-18344-5
|View full text |Cite
|
Sign up to set email alerts
|

Uncovering temporal changes in Europe’s population density patterns using a data fusion approach

Abstract: The knowledge of the spatial and temporal distribution of human population is vital for the study of cities, disaster risk management or planning of infrastructure. However, information on the distribution of population is often based on place-of-residence statistics from official sources, thus ignoring the changing population densities resulting from human mobility. Existing assessments of spatio-temporal population are limited in their detail and geographical coverage, and the promising mobile-phone records … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1
1

Citation Types

0
21
0

Year Published

2021
2021
2024
2024

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 40 publications
(21 citation statements)
references
References 68 publications
(80 reference statements)
0
21
0
Order By: Relevance
“…Multiple studies have indicated that AMR bacteria can be transmitted to humans in public settings including on buses ( Conceição et al, 2013 ); at railway stations ( Lin et al, 2017 ); on subway trains ( Mason et al, 2016 ) and in university classrooms ( Li et al, 2015 ). These areas typically see high population movement and throughput and, at times, high population density ( Batista e Silva et al, 2020 ). Public settings such as mass transport systems (buses and trains) contain surfaces that are frequently touched by multiple people and so too do shops and leisure facilities, all posing a particular challenge to AMR spread.…”
Section: Origins Of Antimicrobial Resistance In the Environmentmentioning
confidence: 99%
“…Multiple studies have indicated that AMR bacteria can be transmitted to humans in public settings including on buses ( Conceição et al, 2013 ); at railway stations ( Lin et al, 2017 ); on subway trains ( Mason et al, 2016 ) and in university classrooms ( Li et al, 2015 ). These areas typically see high population movement and throughput and, at times, high population density ( Batista e Silva et al, 2020 ). Public settings such as mass transport systems (buses and trains) contain surfaces that are frequently touched by multiple people and so too do shops and leisure facilities, all posing a particular challenge to AMR spread.…”
Section: Origins Of Antimicrobial Resistance In the Environmentmentioning
confidence: 99%
“…INSEE used anonymous indicators produced by the data analytics services of the MNOs based on network signaling data in accordance with the Directive 2002//EC (the ePrivacy Directive; EUR-Lex, n.d.). Having no control on the methodology used to construct the indicators, INSEE strategy relied on combining data products already available or easily achievable coming from various MNOs-to mitigate risks of biases, or other consistency issues (Batista e Silva et al, 2020). INSEE chose also to keep in hand the final calibration of the results.…”
Section: Setting the Scenementioning
confidence: 99%
“…Cities constitute complex sociotechnical systems where the needs of citizens, social entities, and governments are combined [ 19 ]. Ideally, a smart city model is based on the integration of different domain-oriented technological developments, under a unique digital context in the form of a platform.…”
Section: Introductionmentioning
confidence: 99%