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Statistical Insights

Space-time Forecast of Infectious/Death Count and Risk Analysis

Goal: We aim to provide a user-friendly tool to visualize, track and predict real-time infected/death cases of COVID-19 in the U.S., based on our collected data and proposed methods, and thus further illustrate the spatiotemporal dynamics of the disease spread and guide evidence-based decision making.

Method: We established a new spatiotemporal epidemic modeling (STEM) framework for space-time infected/death count data to study the dynamic pattern in the spread of COVID-19. The proposed methodology can be used to dissect the spatial structure and dynamics of spread, as well as to assess how this outbreak may unfold through time and space. [Click here to read our paper on arXiv]

Shiny Apps: Currently, we offer two main and multiple small R shiny apps in our dashboard.