Self-Isolation and Testing Behaviour During the COVID-19 Pandemic: An Agent-Based Model

Area of Science:

• Epidemiology
• Computational modeling
• Behavioral science

Background:

• Existing COVID-19 models primarily focus on virus transmission dynamics.
• Limited research addresses how individual behavior adaptation impacts pandemic spread.
• Behavioral responses significantly alter interaction patterns and disease transmission.

Purpose of the Study:

• To develop an agent-based model incorporating behavioral changes in response to COVID-19.
• To investigate the influence of behavioral parameters on virus spread dynamics.
• To understand the role of testing and isolation propensity in pandemic control.

Main Methods:

• Developed an agent-based model (ABM) simulating COVID-19 spread.
• Integrated a behavioral module to represent agent testing and isolation decisions.
• Analyzed the impact of varying behavioral parameters on epidemic trajectories.

Main Results:

• Behavioral responses, specifically testing and isolation, significantly modify COVID-19 transmission.
• The model demonstrates that adaptive agent behavior can alter the course of the pandemic.
• Key behavioral parameters were identified as crucial drivers of epidemic dynamics.

Conclusions:

• Agent-based modeling with behavioral components offers valuable insights into COVID-19 spread.
• Understanding and modeling adaptive human behavior is essential for effective pandemic response strategies.
• Future research should further explore the interplay between behavior and disease dynamics.