Real-time estimation of the effective reproduction number of COVID-19 from behavioral data.

Publication date: Dec 05, 2023

Monitoring the effective reproduction number [Formula: see text] of a rapidly unfolding pandemic in real-time is key to successful mitigation and prevention strategies. However, existing methods based on case numbers, hospital admissions or fatalities suffer from multiple measurement biases and temporal lags due to high test positivity rates or delays in symptom development or administrative reporting. Alternative methods such as web search and social media tracking are less directly indicating epidemic prevalence over time. We instead record age-stratified anonymous contact matrices at a daily resolution using a longitudinal online-offline survey in Hungary during the first two waves of the COVID-19 pandemic. This approach is innovative, cheap, and provides information in near real-time for estimating [Formula: see text] at a daily resolution. Moreover, it allows to complement traditional surveillance systems by signaling periods when official monitoring infrastructures are unreliable due to observational biases.

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Concepts Keywords
Daily Behavioral
Hospital Biases
Hungary Covid
Matrices Data
Pandemic Effective


Type Source Name
disease VO time
disease VO effective
pathway REACTOME Reproduction
disease MESH COVID-19
disease IDO symptom
drug DRUGBANK Coenzyme M
disease VO population
disease MESH emergencies
disease MESH influenza
disease MESH infections
disease IDO contact tracing
disease MESH secondary infection
disease IDO susceptible population
disease IDO infection
disease VO frequency
disease IDO host
disease VO organization
disease IDO country
drug DRUGBANK Pentaerythritol tetranitrate
disease MESH education level
disease VO vaccination
disease VO monthly
disease IDO susceptibility

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