scholarly journals Impact of close interpersonal contact on COVID-19 incidence: Evidence from 1 year of mobile device data

2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Forrest W. Crawford ◽  
Sydney A. Jones ◽  
Matthew Cartter ◽  
Samantha G. Dean ◽  
Joshua L. Warren ◽  
...  
Keyword(s):  
Mobile Device ◽  
Interpersonal Contact

scholarly journals Impact of close interpersonal contact on COVID-19 incidence: evidence from one year of mobile device data

2021 ◽  
Author(s):  
Forrest W. Crawford ◽  
Sydney A. Jones ◽  
Matthew Cartter ◽  
Samantha G. Dean ◽  
Joshua L. Warren ◽  
...  
Keyword(s):  
Mobile Device ◽  
Close Contact ◽  
Population Level ◽  
First Year ◽  
Contact Rate ◽  
Interpersonal Contact ◽  
Location Data ◽  
Frequency Of Contact ◽  
One Year ◽  
Device Location

AbstractClose contact between people is the primary route for transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). We sought to quantify interpersonal contact at the population-level by using anonymized mobile device geolocation data. We computed the frequency of contact (within six feet) between people in Connecticut during February 2020 – January 2021. Then we aggregated counts of contact events by area of residence to obtain an estimate of the total intensity of interpersonal contact experienced by residents of each town for each day. When incorporated into a susceptible-exposed-infective-removed (SEIR) model of COVID-19 transmission, the contact rate accurately predicted COVID-19 cases in Connecticut towns during the timespan. The pattern of contact rate in Connecticut explains the large initial wave of infections during March–April, the subsequent drop in cases during June–August, local outbreaks during August–September, broad statewide resurgence during September–December, and decline in January 2021. Contact rate data can help guide public health messaging campaigns to encourage social distancing and in the allocation of testing resources to detect or prevent emerging local outbreaks more quickly than traditional case investigation.One sentence summaryClose interpersonal contact measured using mobile device location data explains dynamics of COVID-19 transmission in Connecticut during the first year of the pandemic.

Worthy of swift trust? How brief interpersonal contact affects trust accuracy.

2018 ◽  
Vol 103 (11) ◽  
pp. 1181-1197 ◽  
Author(s):  
Oliver Schilke ◽  
Laura Huang
Keyword(s):  
Interpersonal Contact ◽  
Swift Trust

The impact of interpersonal contact on attitudes towards the obese

2011 ◽  
Author(s):  
Jennifer Harman ◽  
Holly Nicewicz
Keyword(s):  
Interpersonal Contact ◽  
The Impact

Serum and MRI Biomarkers in Mobile Device Texting: A Pilot Study

2012 ◽  
Author(s):  
Judith E. Gold ◽  
Feroze B. Mohamed ◽  
Sayed Ali ◽  
Mary F. Barbe
Keyword(s):  
Pilot Study ◽  
Mobile Device

Author response for "Use of passive sensing to quantify adolescent mobile device usage: Feasibility, acceptability, and preliminary validation of the eMoodie application"

2020 ◽  
Author(s):  
Sarah E. Domoff ◽  
Claire Ann Banga ◽  
Aubrey L. Borgen ◽  
Ryan P. Foley ◽  
Chelsea Robinson ◽  
...  
Keyword(s):  
Mobile Device ◽  
Author Response ◽  
Passive Sensing ◽  
Preliminary Validation

Analisis Forensik Smartphone Android Menggunakan Metode NIST dan Tool MOBILedit Forensic Express

2020 ◽  
Vol 5 (1) ◽  
pp. 89
Author(s):  
Nasirudin Nasirudin ◽  
Sunardi Sunardi ◽  
Imam Riadi
Keyword(s):  
Mobile Device ◽  
Rapid Development ◽  
Rapid Progress ◽  
Data Backup ◽  
Technological Advances ◽  
Smartphone Technology ◽  
Case Simulation ◽  
Device Technology

Technological advances are growing rapidly, including mobile device technology, one of which is an Android smartphone that is experiencing rapid progress with a variety of features so that it can spoil its users, with the rapid development of smartphone technology, many users benefit, but many are disadvantaged by the growing smartphone. technology, so that many perpetrators or persons who commit crimes and seek profits with smartphone facilities. Case simulation by securing Samsung Galaxy A8 brand android smartphone evidence using the MOBILedit forensic express forensic tool with the National Institute of Standards and Technology (NIST) method which consists of four stages of collection, examination, analysis and reporting. The results of testing the Samsung Galaxy A8 android smartphone are carried out with the NIST method and the MOBILedit Forensic Express tool obtained by data backup, extraction and analysis so that there are findings sought for investigation and evidence of crimes committed by persons using android smartphone facilities.

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