Pandemic Simulator: An Agent-Based Framework with Human Behavior Modeling for Pandemic-Impact Assessment to Build Sustainable Communities

Abstract

It is crucial to immediately curb the spread of a disease once an outbreak is identified in a pandemic. An agent-based simulator will enable policymakers to evaluate the effectiveness of different hypothetical strategies and policies with a higher level of granularity. This will allow them to identify vulnerabilities and asses the threat level more effectively, which in turn can be used to build resilience within the community against a pandemic. This study proposes a PanDemic SIMulator (PDSIM), which is capable of modeling complex environments while simulating realistic human motion patterns. The ability of the PDSIM to track the infection propagation patterns, contact paths, places visited, characteristics of people, vaccination, and testing information of the population allows the user to check the efficacy of different containment strategies and testing protocols. The results obtained based on the case studies of COVID-19 are used to validate the proposed model. However, they are highly extendable to all pandemics in general, enabling robust planning for more sustainable communities.

Adaptive Learning in Agent-Based Models: An Approach for Analyzing Human Behavior in Pandemic Crowding

“…Another approach for epidemics modeling focuses on the use of ABMS. Many researchers have worked to explain the emergent epidemic behavior of simple interactions within a community [26,[36][37][38][39][40][41]. According to Miksch et al [26], a significant benefit of agent-based epidemic modeling is that it allows exceptional flexibility to design very elaborate epidemic processes.…”

“…Additionally, Crooks and Hailegiorgis [37] performed a set of experiments to determine the effects of geographical interactions and concluded that geospatial setups truly determine the outcomes of an epidemic. Another example is Weligampola et al [41], where the authors introduce the Pandemic Disease Simulation (PDSIM) framework, an innovative ABMS that addresses the impact of the COVID-19 pandemic on diverse communities. PDSIM incorporates attributes like gender, age, ethnicity, and other individual characteristics to assess the susceptibility of different community groups to the COVID-19 pandemic.…”

Adaptive Learning in Agent-Based Models: An Approach for Analyzing Human Behavior in Pandemic Crowding

“…Another approach for epidemics modeling focuses on the use of Agent-based modeling and simulation. Many researchers have worked with agent-based models to explain the emergent epidemic behavior of simple interactions within a community [33,[43][44][45][46][47][48]. According to Miksch et al [33], a significant benefit of agent-based epidemic modeling is that it allows exceptional flexibility to design very elaborate epidemic processes.…”

“…Additionally, Crooks and Hailegiorgis [44] performed a set of experiments to determine the effects of geographical interactions and concluded that geospatial setups truly determine the outcomes of an epidemic. Another example is Weligampola et al [48], where the authors introduce the Pandemic Disease Simulation (PDSIM) framework, an innovative agent-based model that addresses the impact of the COVID-19 pandemic on diverse communities. PDSIM incorporates attributes like gender, age, ethnicity, and other individual characteristics to assess the susceptibility of different community groups to the COVID-19 pandemic.…”