Exploring a COVID-19 Endemic Scenario: High-Resolution Agent-Based Modeling of Multiple Variants

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

Research output: Contribution to journalArticlepeer-review


Our efforts as a society to combat the ongoing COVID-19 pandemic are continuously challenged by the emergence of new variants. These variants can be more infectious than existing strains and many of them are also more resistant to available vaccines. The appearance of these new variants cause new surges of infections, exacerbated by infrastructural difficulties, such as shortages of medical personnel or test kits. In this work, a high-resolution computational framework for modeling the simultaneous spread of two COVID-19 variants: a widely spread base variant and a new one, is established. The computational framework consists of a detailed database of a representative U.S. town and a high-resolution agent-based model that uses the Omicron variant as the base variant and offers flexibility in the incorporation of new variants. The results suggest that the spread of new variants can be contained with highly efficacious tests and mild loss of vaccine protection. However, the aggressiveness of the ongoing Omicron variant and the current waning vaccine immunity point to an endemic phase of COVID-19, in which multiple variants will coexist and residents continue to suffer from infections.

Original languageEnglish (US)
Article number2200481
JournalAdvanced Theory and Simulations
Issue number1
StatePublished - Jan 2023


  • COVID-19
  • agent-based model
  • epidemiology
  • multiple variants
  • urban science

ASJC Scopus subject areas

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


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