VA County COVID-19 Daily Case Total Forecaster
As COVID-19 approaches its forecast peak in Virginia, researchers at Old Dominion University's Virginia Modeling, Analysis and Simulation Center (VMASC) have developed a real-time platform that predicts the spread of the disease down to the city and county level.
ABOUT PROJECT—
Dr. Ross Gore and Dr. Christopher Lynch have developed a real-time platform for the public that explores four COVID-19-related model forecasts, which predict the spread of the disease down to the city and county level within Virginia. The model utilizes existing data sets from the New York Times, American Communities Survey (ACS), Centers for Disease Control (CDC), and Twitter.
The New York Times updates and publishes daily the number of reported cases down to a county-level. Dr. Gore and Dr. Lynch created a model based off this dataset that allows the public to explore, at a county-level, how the number of reported cases is increasing or decreasing in different areas of the state, while predicting the amount of future case. They also created a model to compare the historical accuracy of their model to actual data published and updated daily.
The ACS dataset includes age-range demographics at the county level, which the VMASC researchers used to create a model that correlates the CDC hospitalization datasets to estimate an outcome for each age-specific case.
The platform also provides a machine learning model which identifies tweets from individuals within each county who are reporting symptoms. Tweets that mention certain terms are collected daily, then ran through a machine-learning algorithm to classify only those tweets of individuals self-reporting symptoms.
The researchers also hope that the platform can aid other COVID-19 modeling efforts, featuring a section that points to more than 130 publicly accessible external data and modeling resources.
Platform
This is a research platform for exploring models. We believe the information provided by the platforms can be useful to the public, but our goal is to explore and explain how different models make predictions and forecasts.
Dr. Ross Gore
VA County COVID-19 Daily Case Total Forecaster
VA COUNTY COVID FORECASTER
Dr. Ross Gore and Dr. Christopher Lynch have developed a real-time platform for the public that explores four COVID-19-related model forecasts, which predict the spread of the disease down to the city and county level within Virginia. The model utilizes existing data sets from the New York Times, American Communities Survey (ACS), Centers for Disease Control (CDC), and Twitter.
The New York Times updates and publishes daily the number of reported cases down to a county-level. Dr. Gore and Dr. Lynch created a model based off this dataset that allows the public to explore, at a county-level, how the number of reported cases is increasing or decreasing in different areas of the state, while predicting the amount of future case. They also created a model to compare the historical accuracy of their model to actual data published and updated daily.
The ACS dataset includes age-range demographics at the county level, which the VMASC researchers used to create a model that correlates the CDC hospitalization datasets to estimate an outcome for each age-specific case.
The platform also provides a machine learning model which identifies tweets from individuals within each county who are reporting symptoms. Tweets that mention certain terms are collected daily, then ran through a machine-learning algorithm to classify only those tweets of individuals self-reporting symptoms.
The researchers also hope that the platform can aid other COVID-19 modeling efforts, featuring a section that points to more than 130 publicly accessible external data and modeling resources.
This is a research platform for exploring models. We believe the information provided by the platforms can be useful to the public, but our goal is to explore and explain how different models make predictions and forecasts.
Dr. Ross Gore
