Forecast Analysis of the COVID-19 Incidence in Lebanon: Prediction of Future Epidemiological Trends to Plan More Effective Control Programs
Salah El Falou, Fouad Trad

TL;DR
This study uses an agent-based simulation model to analyze COVID-19 spread in Lebanon, evaluating the impact of interventions like school reopening and vaccination rates to inform better control strategies.
Contribution
It introduces a validated agent-based model tailored for Lebanon to simulate COVID-19 spread and assess intervention effects, including school reopening and NPIs.
Findings
Delaying school reopening reduces infection spread.
Early vaccination rollout is crucial for controlling the pandemic.
Simulation results support delaying school openings until vaccination progresses.
Abstract
Ever since the COVID-19 pandemic started, all the governments have been trying to limit its effects on their citizens and countries. This pandemic was harsh on different levels for almost all populations worldwide and this is what drove researchers and scientists to get involved and work on several kinds of simulations to get a better insight into this virus and be able to stop it the earliest possible. In this study, we simulate the spread of COVID-19 in Lebanon using an Agent-Based Model where people are modeled as agents that have specific characteristics and behaviors determined from statistical distributions using Monte Carlo Algorithm. These agents can go into the world, interact with each other, and thus, infect each other. This is how the virus spreads. During the simulation, we can introduce different Non-Pharmaceutical Interventions - or more commonly NPIs - that aim to limit…
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