raunakdune / vis-movement-covid-final

Use data from SafeGraph to idetify pattersn of movement that lead to increased COVID-19 infection.

Visualizing Multi-modal Spatio-temporal Movement Data

Raunak Sarbajna

1956665 [email protected]

PhD Candidate, Dept. of Computer Science, University of Houston

COSC 6344 Visualization Final Project

We present here a visualization system to identify patterns of movement that lead to increased COVID-19 infection rates from a combination of individual location/movement data and infection data.

The visualization is used to aid an epidemiological simulation model. The data is from the continental United States, but allow limiting to a defined area-of-interest (such as the city of Houston) in order to make the results be comprehensible.

The system tackles the challenge of combining the data of visitation rates of various Points of Interest (PoI) with the COVID infection rates.

The main purpose visually identify associations and trends of how visiting these different types of PoIs affect infection rates in various regions of Houston. This will help further investigation and mining of the data.

Getting Started

Running the app locally

venv\Scripts\activate

To install all of the required packages to this environment, simply run:

pip install -r requirements.txt

and all of the required pip packages, will be installed.

To run the app:

python app.py