Various social policies and strategies have been deliberated and used within many countries to handle the COVID-19 pandemic. Some of those basic ideas are strongly related to understanding of human social interactions and the nature of disease transmission and spread. Here we present an agent-based approach to model epidemiological phenomena as well as the interventions upon it. We elaborate micro-social structures such as social-psychological factors and distributed ruling behaviors to grow an artificial society where the interactions among agents may exhibit the spreading of viruses. Capturing policies and strategies during the pandemic, four types of intervention can be applied in the society. Emerged macro-properties of epidemics are delivered in plots section to enrich observations on each policy/strategy’s effectiveness.
|r||→||reset||s||→||save data (json)||a||→||add an infectious agent at random place||c||→||close attraction points|
|p||→||pause/play||i + click||→||put an infectious agent to clicked region||m||→||mask-wearing||l||→||lockdown|