High resolution modeling and optimal interventions to control Covid-19 spread

We developed a detailed individual-based simulation model that mimics the spread of COVID-19 in Israel. Based on city-level data from the Israel Central Bureau of Statistics (ICBS), the model generates a synthetic population of individuals, with characteristics such as age and household, education and workplace memberships. Dynamic population behaviors are created through a process mimicking daily contacts at schools, workplaces etc. Then, a COVID-19 spread is modeled by initially “infecting” a group of individuals and having their infections follow a disease progression model, while infecting others based on estimated contacts and behaviors. Using this framework, we can model and compare explicit quarantine and vaccination strategies and the spread of different viral variants.

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