DYVIC: DYnamic VIrus Control in Peru

Area of Science:

• Epidemiology
• Public Health Technology
• Digital Health

Background:

• The COVID-19 pandemic necessitated innovative public health strategies, including digital solutions for disease surveillance.
• Contact tracing applications emerged as key tools for managing virus transmission globally.

Purpose of the Study:

• To present a method for detecting probable COVID-19 infections using the PerúEnTusManos epidemiological tracing application.
• To leverage georeferencing data for individual mobility patterns and crowd detection in Peru.

Main Methods:

• Utilized data from the PerúEnTusManos application, which employs georeferencing for user movement analysis.
• Developed a probabilistic model to assign infection risk to individuals based on contact with confirmed COVID-19 cases.

Main Results:

• Preliminary evaluations demonstrate promising accuracy in identifying individuals with a high probability of COVID-19 infection.
• The system successfully identified districts with the highest prevalence of COVID-19 cases.

Conclusions:

• The PerúEnTusManos application provides a valuable tool for health authorities in Peru.
• Data-driven insights support informed decision-making for clinical test allocation and economic re-activation strategies.