Circulation of Respiratory Viruses in the City: Towards an Agent-Based Ecosystem model

Bull Math Biol. 2023 Sep 10;85(10):100. doi: 10.1007/s11538-023-01203-x.

Abstract

Mathematical models play an important role in management of outbreaks of acute respiratory infections (ARI). While such models are generally used to study the spread of a solitary virus, in reality multiple viruses co-circulate in the population. These viruses have been studied in detail, including the course of infection and immune defense mechanisms. We developed an agent-based model, called ABM-ARI, assimilating heterogeneous data and theoretical knowledge into a biologically motivated system, that allows to reproduce the seasonal patterns of ARI incidence and simulate interventions. ABM-ARI uses city-specific data to create a synthetic population and to construct realistic contact networks in different activity settings. Characteristics of infection, immune protection and non-specific resistance were varied between individuals to account for the population heterogeneity. For the calibration, we minimised the normalised mean absolute error between simulated and observed epidemic curves. ABM-ARI was built based on the quantitative assessment of features of predominant respiratory viruses and epidemiological characteristics of the population. It provides a good fit to the observed epidemic curves for different age groups and viruses. We also simulated one-week school closures when student absences were at or above 10%, 20% or 30% and found that only 10% and 20% thresholds resulted in a reduction of the incidence. ABM-ARI has a great potential in tackling the challenge of emerging infections by simulating and evaluating the effectiveness of various interventions.

Keywords: Acute respiratory infection; Agent-based model; Contact network; Epidemiology; Respiratory virus.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Calibration
  • Disease Outbreaks
  • Ecosystem*
  • Humans
  • Mathematical Concepts
  • Models, Biological
  • Respiratory Tract Infections* / epidemiology
  • Respiratory Tract Infections* / prevention & control