Skip to content
No description, website, or topics provided.
JavaScript Jupyter Notebook Python Other
Branch: master
Clone or download

README.md

grmds.org/project-coronavirus

In Project Coronavirus we aim to create an end to end data science solution to help guide global response to the spread of COVID-19. RMDS is collaborating with data scientists, engineers, epidemiologists and researchers from Wuhan Unviersity, Harvard Dataverse, amongst other groups. We aim to increase the reproducibility and transparency of our project by documenting our work with ResearchMap analytical workflows.

Currently there are two main parts of the coronavirus project: one is building up a dashboard that displays a up-to-date status of the coronavirus breakout, including a interactive global map of how many cases in each place and where they are. It is interactive so you can hover over or click on each city or province to show further information like historical trend in each place and related news reports, social media trends, and policies implemented. We are trying to make it a comprehensive public portal that everyone can easily keep up to date.

The second part is a alert system that is under construction, we are building data-driven models upon coronavirus-related data that we collected from multiple sources and try to track and predict the spreading trend of the virus. Currently we have developed two data-driven models: a time-series LSMT model which rely on historical number of cases and other factors that have a potential impact on this issue to predict future trends; and a epidemiological SIR model to simulate the development of the virus in different cities. After model establishment, we want to set some threshold criteria and try to alert if there is a high level of risk for some places given the prediction of our models.

You can’t perform that action at this time.