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The United States COVID-19 Forecast Hub dataset
Estee Y Cramer1, Yuxin Huang1, Yijin Wang1
1Department of Biostatistics and Epidemiology, University of Massachusetts Amherst, Amherst, MA, 01003, USA.
Scientific Data
|August 1, 2022
Summary
The US COVID-19 Forecast Hub provides standardized, short-term COVID-19 forecasts for cases, hospitalizations, and deaths. This open-source dataset aids in developing ensemble models and informing public health policy.
Area of Science:
- Epidemiology
- Public Health
- Data Science
Background:
- The COVID-19 pandemic generated numerous forecasts from diverse groups.
- A need existed for standardized, comparable COVID-19 forecasting data.
- The United States Centers for Disease Control and Prevention (CDC) initiated a project to address this need.
Purpose of the Study:
- To create a centralized, open-source dataset of COVID-19 forecasts.
- To provide standardized, short-term predictions for key COVID-19 metrics.
- To facilitate the comparison and utilization of forecasts for public health decision-making.
Main Methods:
- Partnering academic researchers with the CDC to establish the US COVID-19 Forecast Hub.
- Aggregating point and probabilistic forecasts for incident cases, hospitalizations, and deaths.
- Ensuring data accessibility through GitHub, an API, and R packages.
Main Results:
- The US COVID-19 Forecast Hub was launched in April 2020.
- The dataset includes forecasts at county, state, and national levels.
- Forecasts encompass various modeling approaches and data sources.
Conclusions:
- The Forecast Hub offers a valuable resource for understanding and utilizing COVID-19 predictions.
- Standardized data enables ensemble modeling, public communication, and policy development.
- Open-source availability promotes broad accessibility and application of forecasting data.
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