An Agent Based Modeling of COVID-19: Validation, Analysis, and Recommendations

Abstract

<jats:p>The Coronavirus disease 2019 (COVID-19) has resulted in an ongoing pandemic worldwide. Countries have adopted Non-pharmaceutical Interventions (NPI) to slow down the spread. This study proposes an Agent Based Model that simulates the spread of COVID-19 among the inhabitants of a city. The Agent Based Model can be accommodated for any location by integrating parameters specific to the city. The simulation gives the number of daily confirmed cases. Considering each person as an agent susceptible to COVID-19, the model causes infected individuals to transmit the disease via various actions performed every hour. The model is validated by comparing the simulation to the real data of Ford county, Kansas, USA. Different interventions including contact tracing are applied on a scaled down version of New York city, USA and the parameters that lead to a controlled epidemic are determined. Our experiments suggest that contact tracing via smartphones with more than 60% of the population owning a smartphone combined with a city-wide lock-down results in the effective reproduction number (R<jats:sub>t</jats:sub>) to fall below 1 within three weeks of intervention. In the case of 75% or more smartphone users, new infections are eliminated and the spread is contained within three months of intervention. Contact tracing accompanied with early lock-down can suppress the epidemic growth of COVID-19 completely with sufficient smartphone owners. In places where it is difficult to ensure a high percentage of smartphone ownership, tracing only emergency service providers during a lock-down can go a long way to contain the spread. No particular funding was available for this project.</jats:p>

To Freeze or Not to Freeze? Epidemic Prevention and Control in the DSGE Model Using an Agent-Based Epidemic Component

“…The course of the COVID-19 pandemic in regions smaller than countries was studied by Shamil et al [ 13 ]. Their agent-based model was validated by comparing the simulation to the actual data from American cities.…”

An Agent Based Model for assessing spread and health systems burden for COVID-19 using a synthetic population in Rangareddy district, Telangana state, India

“…The geographical scope of the study governs the number of agents. For example, 10 million stochastic agents for the State of Delaware, US [39], a scaled-down simulation of New York with 10000 agents [69], synthetic population of NYC with 500,000 [35], 5000 agents in the premises of a University in Italy [20], 24 million agent representing Australia [66], 750,805 agents representing Urmia, Iran [50], etc. In this study, we have scaled-down the synthetic population of Rangareddy district to 10.35% and used for the ABM.…”

Simulation-free estimation of an individual-based SEIR model for evaluating nonpharmaceutical interventions with an application to COVID-19 in the District of Columbia

“…An alternative to equation-based compartmental models are IBMs, which provide a method for capturing heterogeneous mixing by simulating contacts among individual agents. A wide range of IBMs have been developed for COVID-19 [21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40]. IBMs have been developed to evaluate numerous interventions including community lockdowns or closures [22,26,27,31,32,35,36,38,39], contact tracing, isolation and quarantine [22-24, 26, 27], mask wearing [29,32,33,39,40], social distancing [22, 24-26, 29, 35] and travel restrictions [26].…”

“…A wide range of IBMs have been developed for COVID-19 [ 21 – 40 ]. IBMs have been developed to evaluate numerous interventions including community lockdowns or closures [ 22 , 26 , 27 , 31 , 32 , 35 , 36 , 38 , 39 ], contact tracing, isolation and quarantine [ 22 – 24 , 26 , 27 ], mask wearing [ 29 , 32 , 33 , 39 , 40 ], social distancing [ 22 , 24 – 26 , 29 , 35 ] and travel restrictions [ 26 ]. IBMs have also been developed to simulate multiple contact settings (e.g., homes, schools, workplaces, public transportation, etc.)…”