With the start of the COVID-19 pandemic, Dr Samer Kharroubi embarked on an endeavor to research the infection by developing a Bayesian statistical model that can be used to predict and explain the spread of COVID-19 in Lebanon over time.
To enable containment measures to be applied and/or relaxed, this Bayesian model can estimate whether contagion has a trend (growing or declining), when the peak is reached, and where exactly on the infection cycle each country stands. A model of this kind, while statistically expressing current practices in modelling the global spread of COVID-19, produces findings that could be beneficial for policy-makers to better plan health policy interventions and take the appropriate actions to contain the spreading of the virus. Model findings are presented for the actual time series of Lebanon but can also be easily reproduced and extended to other countries, adding more time periods as more data becomes available.
For more information see: Kharroubi, S. A. (2020). Modeling the spread of COVID-19 in Lebanon: A Bayesian perspective. Frontiers in Applied Mathematics and Statistics, 6, 40. doi:10.3389/fams.2020.00040