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Data Resources for SARS-CoV-2

Models and Projections

COVID-19 Forecasts
https://www.cdc.gov/coronavirus/2019-ncov/covid-data/forecasting-us.html
As part of its collection of resources and data about COVID-19 cases and fatalities, the CDC provides this overview of models and forecasts and the purposes they serve. The site also includes a helpful list of different models, various of which appear on this guide or are used by sources on this guide.

"Where The Latest COVID-19 Models Think We're Headed — And Why They Disagree"
https://projects.fivethirtyeight.com/covid-forecasts/
538 provides this helpful introduction to COVID-19 models, including an overview of many of the available models and how they differ from each other in terms of both their projections and their inner workings.

COVID-19 Hospital Impact Model for Epidemics (CHIME)
https://penn-chime.phl.io/
"This tool was developed by Predictive Healthcare at Penn Medicine to assist hospitals and public health officials with hospital capacity planning. Please read How to Use CHIME to customize inputs for your region."

COVID-19 Projections Using Machine Learning
https://covid19-projections.com/
This model provides predictions for daily and total fatalities and infections for the U.S. as a whole, individual states, and for selected other countries. The model incorporates assumptions about the timing of and variation in social-distancing policies and their effects, as well as estimates of reproduction numbers for different countries and U.S. states. You can download data from the model's projections via the project's GitHub site.

COVID-19 Resources from the Institute for Health Metrics and Evaluation
http://www.healthdata.org/covid
The Institute for Health Metrics and Evaluation at the University of Washington has models for projected hospital use/demand and for fatalities, for the U.S. and for individual states. Note that the model has been critiqued for its assumptions about the extent and intensity of social-distancing measures across the states and for the variability of its projections; see, e.g., https://www.statnews.com/2020/04/17/influential-covid-19-model-uses-flawed-methods-shouldnt-guide-policies-critics-say/. Both current and previous estimates can be downloaded via http://www.healthdata.org/covid/data-downloads.

COVID-19 Mortality Projections for U.S. States
https://covid-19.tacc.utexas.edu/projections/
The University of Texas COVID-19 Modeling Consortium provides daily data for both reported and project deaths from COVID-19. The projections attempt to incorporate the effects of social-distancing policies by amking use of GPS data from mobile phones.

Penn Wharton Budget Model (PWBM) Analysis of the Coronavirus Crisis
https://budgetmodel.wharton.upenn.edu/coronavirus
The Penn Wharton Budget Model from UPenn's Wharton School provides analyses and simulations of the economic effects of public policy and of policy proposals. The PWBM has been producing various analysis of the economic and health effects of the pandemic, including analyses of federal responses to it and a simulator (and data) of the health and economic effects of different scenarios of re-opening and social distancing.

Reich Lab COVID-19 Forecast Hub
https://reichlab.io/covid19-forecast-hub/
The Reich Lab COVID-19 Forecast Hub provides both visualizations and data from a variety of different models for projecting COVID-19 deaths, for the U.S. and for individual states. The geographic coverage and time-frame for projections vary by model. There is also an "ensemble forecast" that aggregates data from different models. See https://github.com/reichlab/covid19-forecast-hub for more information about the models used and for data from them.

Rt Covid-19
https://rt.live/
"The metric being tracked here (Rt) represents the effective reproduction rate of the virus calculated for each locale. It lets us estimate how many secondary infections are likely to occur from a single infection in a specific area. Values over 1.0 mean we should expect more cases in that area, values under 1.0 mean we should expect fewer." The site provides both current and past estimates, to allow for estimating the effects of social-distancting policies. Both the data and the code that produce them are available.

Weather Conditions and COVID-19 Transmission
https://projects.iq.harvard.edu/covid19
This project includes an interactive interface "visualize evidence-based projections of the impact of weather on the potential transmission rate of COVID-19 from May 1, 2020 to April 30, 2021, using 2019-2020 weather data for each location." Projections are available for countries, larger cities, and counties in the U.S. Note that these are "all else being equal" estimates for the effects of weather and pollutants on tranmission and are NOT estimates of the overall risk of transmission. See https://projects.iq.harvard.edu/covid19/Resources for access to data and code.