Simulating COVID19 Transmission From Observed Movement

Covid

Simulating COVID19 Transmission From Observed Movement

Simulating COVID19 Transmission From Observed Movement: An Agent-Based Model of Classroom Dispersion

A team of University of Miami researchers has put together an extensive study simulating the spread of COVID-19 based on observed movement using RIFD systems and modeled on classroom dispersion.

Abstract

Current models of COVID-19 transmission predict infection from reported or assumed interactions. Here we leverage high-resolution observations of interaction to simulate infectious processes. Ultra-Wide Radio Frequency Identification (RFID) systems were employed to track the real-time physical movements and directional orientation of children and their teachers in 4 preschool classes over a total of 34 observations.

An agent-based transmission model combined observed interaction patterns (individual distance and orientation) with CDC-published risk guidelines to estimate the transmission impact of an infected patient zero attending class on the proportion of overall infections, the average transmission rate, and the time lag to the appearance of symptomatic individuals. These metrics highlighted the prophylactic role of decreased classroom density and teacher vaccinations.

Reduction of classroom density to half capacity was associated with an 18.2% drop in overall infection proportion while teacher vaccination receipt was associated with a 25.3% drop.
Simulation results of classroom transmission dynamics may inform public policy in the face of COVID-19 and similar infectious threats.

This work was financially supported by the National Science Foundation, IBSS-L1620294; Institute of Education Sciences, R324A180203; Microsoft AI for Health COVID-19 Grant Program and Google Cloud COVID-19 Research Credits Program.

Read the full paper here.

Yi ZhangYudong Tao

 

 

 

 

 

 

 

First author Yi Zhang, Physics Dept. Doctoral Candidate and Co-author Yudong Tao, Research Assistant.

Daniel Messinger

Co-authors from left to right: Mei-Ling Shyu (Associate Chair and Professor at in the Dept. of Electrical & Computer Engineering), Lynn K. Perry (Associate Professor of Psychology), Prem R. Warde (MSIE, former Director, Care Transformation, University of Miami Health System), and Daniel Messinger (Associate Professor in the Child Division of the Dept. of Psychology, Coordinator of the UM Developmental Psychology Program and Director of Social System Informatics at IDSC Data Ethics + Society).

 

Zhang, Y., Tao, Y., Shyu, ML. et al. Simulating COVID19 transmission from observed movementSci Rep 12, 3044 (2022). https://doi.org/10.1038/s41598-022-07043-4