Designing the Safe Reopening of US Towns Through High-Resolution Agent-Based Modeling

Agnieszka Truszkowska, Malav Thakore, Lorenzo Zino, Sachit Butail, Emanuele Caroppo, Zhong Ping Jiang, Alessandro Rizzo, Maurizio Porfiri

Research output: Contribution to journalArticlepeer-review


As COVID-19 vaccine is being rolled out in the US, public health authorities are gradually reopening the economy. To date, there is no consensus on a common approach among local authorities. Here, a high-resolution agent-based model is proposed to examine the interplay between the increased immunity afforded by the vaccine roll-out and the transmission risks associated with reopening efforts. The model faithfully reproduces the demographics, spatial layout, and mobility patterns of the town of New Rochelle, NY — representative of the urban fabric of the US. Model predictions warrant caution in the reopening under the current rate at which people are being vaccinated, whereby increasing access to social gatherings in leisure locations and households at a 1% daily rate can lead to a 28% increase in the fatality rate within the next three months. The vaccine roll-out plays a crucial role on the safety of reopening: doubling the current vaccination rate is predicted to be sufficient for safe, rapid reopening.

Original languageEnglish (US)
Article number2100157
JournalAdvanced Theory and Simulations
Issue number9
StatePublished - Sep 2021


  • COVID-19
  • agent-based model
  • epidemiology
  • urban science
  • vaccination

ASJC Scopus subject areas

  • Statistics and Probability
  • Numerical Analysis
  • Modeling and Simulation
  • General


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