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Project title:
Harnessing mobility data to inform public health decision making
Principal investigator(s):
Saeed, Sahar Z; Bhatnagar, Sahir; Nguyen, Quoc Dinh
Co-investigator(s):
Her, Peter; Mamiya, Hiroshi; Sun, Shuo; Tram, Khai Hoan
Supervisors:
N/A
Institution paid:
Queen's University (Kingston, Ontario)
Research institution:
Queen's University (Kingston, Ontario)
Department:
Public Health Sciences
Program:
Catalyst Grant: CPHO Report - General Pool
Competition (year/month):
202205
Assigned peer review committee:
Catalyst Grant : Chief Public Health Officer (CPHO) Report 2023
Primary institute:
Population and Public Health
Primary theme:
Social / Cultural / Environmental / Population Health
Term (yrs/mths):
1 yr 0 mth
CIHR contribution:
Contributors:
Inst of Population &Publ Hlth
Amount:
$100,000
Equipment:
$0
External funding partner(s):
Partner Name:
N/A
Amount:
N/A
Equipment:
N/A
External applicant partner(s):
Partner Name:
N/A
Amount:
N/A
Equipment:
N/A
External in-kind partner(s):
Partner Name:
N/A
Amount:
N/A
Equipment:
N/A
Keywords:
Covid-19 Pandemic; Digital Technology; Mobility; Public Health
Abstract/Summary:
Smartphones have become an essential part of our daily lives. Globally it is estimated there are 6.6 billion smartphone users and by 2026 this is expected to increase to 7.5 billion. The unprecedented number of people with access to smartphones has created an opportunity to amass and track population-level mobility patterns through Global Positioning Systems (GPS). When smartphone users download certain application (i.e. weather, navigation or social media) they allow the applications to track and record their locations. The magnitude and value of these analytics are not lost by commercial companies who buy these data, mostly for targeted advertising purposes. The COVID-19 pandemic exposed the capacity of using mobility data as an epidemiological surveillance tool to support public health decision-making. Here we propose expanding on our mobility research which uses aggregated location data collected by smartphones via GPS as a means to evaluate adherence to policies, and identify disparities and the impact of the COVID-19 pandemic at long-term care facilities and hospitals. We have put together a team that brings together expertise in epidemiology, biostatistics, geriatrics, and geospatial analytics using big data to provide new insights on how to optimally leverage anonymous mobility data that can continue to inform public health decision making post-pandemic.
Version:
20250311.1