Health Data Science / 2022 / Article / Tab 6

Review Article

Mobile Sensing in the COVID-19 Era: A Review

Table 6

Study characteristics of contact tracing literature.

AuthorData typePopulation scaleSensing durationDescription

Dar et al. [49]BluetoothNeighborhoodWeeksProviding an evaluation framework for mobile contact tracing solutions
Ferretti et al. [50]BluetoothNeighborhoodWeeksExploring the feasibility of different contact tracing solutions
Carli et al. [51]BluetoothNeighborhoodWeeksProposing a Bluetooth low energy- (BTE-) based contact tracing approach
Leith and Farrell [52]BluetoothNeighborhoodWeeksReporting the measurements of Bluetooth low energy (LE) in different environments
Brack et al. [53]BluetoothNeighborhoodWeeksPresenting a decentralized peer-to-peer contact tracing system
Bian et al. [54]OtherNeighborhoodWeeksMonitoring social distance at real time by magnetic-based system
Xiao et al. [55]GPS/CDRsNeighborhoodWeeksPredicting risk of the community before the spread of COVID-19 from epicenter
Park et al. [56]GPS/CDRsNeighborhoodWeeksUnderstanding privacy issues in disclosing the personal information of the infected
Berke et al. [57]GPS/CDRsNeighborhoodWeeksProviding a secure approach to evaluate the risk of exposure to infected cases
Ye et al. [58]GPS/CDRsCommunityWeeksEstimating provided risk indices associated with a community based on mobile data
Kielienyu et al. [59]GPS/CDRsCommunityWeeksPredicting COVID-19 risk scores by model based on mobile crowd-sourced data