COVID-19 Mortality Projections for US States

Graphs show both the reported and projected number of COVID-19 deaths per day across the US and for individual states and metropolitan areas. For each US state, we use local data from mobile-phone GPS traces to quantify the changing impact of social-distancing measures on “flattening the curve.”

COVID-19MortalityUS States
  415

Contributor

contributed at 2020-05-01

Authorship

Affiliation:  
University of Texas
Homepage:  
View
Is authorship not correct? Feed back

Classification(s)

Earth System SubjectEarth Surface SystemAnthroposphere

Detailed Description

Use daily data on COVID-19 deaths, together with mobile-phone data that allows us to characterize each state's social-distancing behavior, to form three-week-ahead projections of COVID-19 death rates in all US states and most major metropolitan areas.

Key model assumptions: (1) The observed and projected numbers reflect confirmed COVID-19 deaths only. (2) The model estimates the extent of social distancing using geolocation data from mobile phones and assumes that the extent of social distancing does not change during the period of forecasting. (3) The model is designed to predict deaths resulting from only a single wave of COVID-19 transmission and cannot predict epidemiological dynamics resulting from a possible second wave.

The peak is defined as the day on which our model’s prediction for the average daily death rate stops increasing and begins to decrease.

How to cite

The University of Texas COVID-19 Modeling Consortium (2020). COVID-19 Mortality Projections for US States, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/ea75f95b-3f4d-4008-9132-450d905c286d
Copy

QR Code

Contributor

contributed at 2020-05-01

Authorship

Affiliation:  
University of Texas
Homepage:  
View
Is authorship not correct? Feed back

QR Code

You can link related {{typeName}} from your personal space to this model item, or you can create a new {{typeName.toLowerCase()}}.

Model Content & Service

These authorship information will be submitted to the contributor to review.