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Abstract
This study develops a framework that integrates digital proxies of human mobility and physical mixing into conventional epidemic models to track COVID-19 transmissibility in near real-time and generate nowcasts and short-term forecasts. Using age-specific digital mobility data from Octopus cards in Hong Kong, the model accurately tracks the local effective reproduction number (Rt) of COVID-19, enabling quick assessment of intervention effectiveness. The findings demonstrate that integrating digital proxies into epidemic models provides accurate nowcasting and forecasting of COVID-19 epidemics.
Publisher
Nature Communications
Published On
Jul 28, 2021
Authors
Kathy Leung, Joseph T. Wu, Gabriel M. Leung
Tags
COVID-19
epidemic models
digital mobility
real-time tracking
nowcasting
predictions
transmissibility
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