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Updated: Oct 12, 2025

Trajectory Data Analyses for Pedestrian Space-time Activity Study

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Published on: February 25, 2013

An Automated Contact Tracing Approach for Controlling Covid-19 Spread Based on Geolocation Data From Mobile Cellular

Md Tanvir Rahman¹, Risala T Khan², Muhammad R A Khandaker³

¹Department of Information and Communication TechnologyMawlana Bhashani Science and Technology University Tangail 1902 Bangladesh.

IEEE Access : Practical Innovations, Open Solutions

|November 23, 2021

Summary

This summary is machine-generated.

This study introduces a novel COVID-19 contact tracing method using geolocation data, bypassing smartphone apps. It identifies infected individuals and high-risk zones effectively, offering a privacy-preserving alternative for pandemic control.

Keywords:

Coronavirus Covid-19 contact tracing geolocation pandemic

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Area of Science:

Epidemiology
Public Health
Mobile Technology

Background:

The COVID-19 pandemic presents a significant global health challenge due to the virus's rapid spread and evolution.
Traditional containment strategies like social distancing and quarantine are difficult to implement effectively in densely populated regions.
Existing digital solutions, such as smartphone applications for contact tracing, raise privacy concerns and rely on advanced technology.

Purpose of the Study:

To propose a new method for COVID-19 contact tracing utilizing mobile phone geolocation data.
To enable authorities to identify potential COVID-19 cases and at-risk areas without relying on smartphone applications.
To empower individuals with information about potential exposure for timely medical assistance.

Main Methods:

Leveraging mobile phone users' geolocation data for contact tracing.
Developing an algorithm to identify probable infected individuals based on location patterns.
Analyzing numerical examples to validate the proposed method's efficacy.

Main Results:

The proposed geolocation-based method effectively identifies probable COVID-19 infected persons.
The system can delineate high-risk zones, aiding in targeted isolation and lockdown measures.
Numerical simulations indicate superior performance compared to smartphone app-based solutions.

Conclusions:

The developed method offers a viable, privacy-conscious alternative for COVID-19 contact tracing.
Geolocation data analysis provides a scalable solution for pandemic management, especially in crowded areas.
This approach enhances public health initiatives by improving the accuracy and accessibility of contact tracing.