County-level map: This map shows forecasts for the number of deaths at the county-level.
County-level map: Click this map to access cases/deaths time series of specific counties.
COVID pandemic severity index (CPSI): this index is designed to help aid the distribution of medical resources to hospitals.
It takes on three values (3: High, 2: Medium, 1: Low), indicating the severity of the covid-19 outbreak for a hospital on a certain day. It is calculated in three steps (more details here):
1. county-level predictions for number of deaths are modeled
2. county-level predictions are allocated to hospitals within counties proportional the their total number of employees
3. final value is decided by thresholding the mean of two numbers: (i) percentile of cumulative deaths so far (ii) percentile of predicted new deaths in the next few days
Google sheets with our daily updated predictions:
We have compiled and cleaned a large corpus of county-level and hospital-level data from a variety of public sources to aid data science efforts to combat COVID-19. At the county level, our data include COVID-19 cases/deaths from USA Facts and NYT, automatically updated every day, along with demographic information, health resource availability, COVID-19 health risk factors, and social mobility information. At the hospital level, our data include the location of the hospital, the number of ICU beds, the total number of employees, and the hospital type.
Feature correlations: This heatmap shows correlations between some of the features we have collected at the county-level.
Combined Linear and Exponential Predictors (CLEP)
Calculate a weighted average of the predictions: higher weight to the models with better historical performance
We develop simple, interpretable models for predicting the trajectory of COVID-19-related deaths at the county-level in the United States (updated daily). Our models show that most counties are experiencing exponential growth that can be accurately modeled several days into the future. However, we also find that some counties are starting to experience sub-exponential growth, possibly due to the “flattening-the-curve” impacts of interventions such as social distancing and shelter in place orders. Details are in our paper.
7-day forecasts for selected counties: Prediction intervals are based on the historical performance of our predictors (narrower for counties where the forecasts were accurate). If we denote err as the largest normalized absolute error for a given county in the past five days, then our prediction interval has the form [prediction * (1 - err), prediction * (1 + err)].
Predictive accuracy: Accuracy of our 3-day predictions (predicting today from 3 days ago). Bubble size corresponds to county size (this plot omits counties which have no recorded deaths as of today).