ARTICLE | doi:10.20944/preprints202305.1783.v1
Subject: Public Health And Healthcare, Health Policy And Services Keywords: Covid-19; Pandemic; Agent-Based Models (ABM); Human Movement Modeling; Envi-ronment modeling; Disease Propagation and Containment
Online: 25 May 2023 (09:01:44 CEST)
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 the policymakers to evaluate the effectiveness of different hypothetical strategies and policies with a higher level of granularity. This will allow them to identify the 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 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, it is highly extendable to all pandemics in general, enabling robust planning for more sustainable communities.