Name: Intro to Spatial Analytics and Epidemiological Modeling for COVID-19
Start: 2020-04-09T13:00:00-07:00
End: 2020-04-09T14:30:00-07:00

THIS IS A FREE ONLINE EVENT; TO JOIN THE EVENT PLEASE VISIT THE LINK AT THE BOTTOM OF THE PAGE
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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.

Webinar Highlights:

> Spatiotemporal datasets and mapping as spatial representation of coronavirus trends
> Application of spatial analysis in combating epidemic events
> Epidemiological terms and parameters like infection rate, recovery rate, R0, quarantine coefficient
> SIR model, Bayesian statistics, Markov Chain Monte Carlo (MCMC) methods

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http://grmds.org/webinar_april_2020

Alex Liu

Jaden Yocom

Sabine Francois

Katherine H.

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Intro to Spatial Analytics and Epidemiological Modeling for COVID-19

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Intro to Spatial Analytics and Epidemiological Modeling for COVID-19

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