Forecast Analysis of the COVID-19 Incidence in Lebanon: Prediction of Future Epidemiological Trends to Plan More Effective Control Programs

Since the beginning of the COVID-19 epidemic, governments have been attempting to mitigate its impact on their citizens and countries, and the main way of doing this was through Non-Pharmaceutical Interventions (NPIs) that ranged from universal masking and social isolation to worldwide lockdowns. Given that the virus is still new, a government does not always know what to expect after applying a specific measure, but ideally, if countries knew beforehand the effect of their actions, they would always choose what works best for their citizens, and this is what we seek from our study. Our goal is to conceptualize a system that helps governments make the right decisions during a pandemic. For this purpose, we built a simulator to simulate the spread of COVID-19 in a virtual country – where we can apply different NPIs at different times – using an Agent-Based Model that runs on top of the Monte Carlo Algorithm. Our Simulator was first validated on concepts (e.g. Flattening the Curve and Second Wave scenario) to make sure it reflects realistic COVID-19 aspects. Then, it was used to simulate the case of Lebanon, and forecast the effect of opening schools and universities on the pandemic situation since the Lebanese Ministry of Education was planning to do so starting from 21 April 2021. Our validations prove that this prototype can be very beneficial for a country like Lebanon to carry a better decision making during the pandemic.