April 9, 2020 at 01:00PM- April 9, 2020 at 02:30PM
Part I: Spatial Analytics, Presented by Mo Chen
Spatial analysis plays an important role not only in our everyday life and business, but also in the fight against the ongoing coronavirus outbreak. In this webinar we will see how the concept of spatial analysis was sparked due to an epidemic event in history. We will give an overview of spatiotemporal datasets, which serve as the foundation of almost all spatial analysis including RMDS’ Project Coronavirus. Attendees will also have a chance to see how mapping acts as a powerful tool in visualizing and informing the trend of coronavirus worldwide. Lastly, some examples will be shown to illustrate how some further spatial analysis can be done, on top of spatiotemporal datasets and mapping, to give us more confidence in winning this battle.
Part II: Epidemiological Modeling, Presented by Suyeon Ryu
In this webinar, we will discuss how we have built data-driven models upon coronavirus-related data collected from multiple sources in order to track and predict the spreading trend of the virus. Specifically, we will focus on the epidemiological SIR model to simulate the development of the coronavirus in different cities. The stochastic SIR model can estimate the termination date, infection rate, recovery rate, and R0 of the coronavirus. We will discuss how we used MCMC to estimate the distribution of epidemiological parameters, and once we have the distribution of parameters the future predictions come from simulations using the Monte Carlo method.
This sounded interesting, but I didn’t make it.