Modeling COVID-19 Dynamics and Patterns Across New Jersey: Assessing Effects of Heterogeneities, Exposure Controls and Social and Environmental Factors.

Presented By: Professor Panos G. Georgopoulos, PhD

COVID-19 has created an unprecedented global public health crisis. Prior exposures to chemical, biological, and psychosocial stressors affect susceptibilities to the disease; data show that outcomes are strongly correlated with individual-level risk factors, such as age, sex and medical history, as well as with multiple, spatially heterogeneous, demographic, environmental and socioeconomic factors. Rutgers Professor Panos Georgopoulous describes a computational framework that combines stochastic epidemic modeling with data science approaches to evaluate factors influencing disease spread and characterizes spatiotemporal patterns and risks of COVID19 that remain important as vaccination efforts are being implemented.

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