Comparing and Integrating US COVID-19 Daily Data from Multiple Sources: A County-Level Dataset with Local Characteristics

06/02/2020
by   Guannan Wang, et al.
0

Over the past several months, the outbreak of COVID-19 has been expanding over the world. A reliable and accurate dataset of the cases is vital for scientists to conduct related research and for policy-makers to make better decisions. We collect the COVID-19 daily reported data from four open sources: the New York Times, the COVID-19 Data Repository by Johns Hopkins University, the COVID Tracking Project at the Atlantic, and the USAFacts, and compare the similarities and differences among them. In addition, we examine the following problems which occur frequently: (1) the order dependencies violation, (2) outliers and abnormal observations, and (3) the delay-reported issue on weekends and/or holidays. We also integrate the COVID-19 reported cases with the county-level auxiliary information of the local features from official sources, such as health infrastructure, demographic, socioeconomic, and environment information, which are important for understanding the spread of the virus.

READ FULL TEXT

page 6

page 8

page 9

research
07/19/2020

COVID-19 Data Analysis and Forecasting: Algeria and the World

The novel coronavirus disease 2019 COVID-19 has been leading the world i...
research
04/07/2020

A large-scale COVID-19 Twitter chatter dataset for open scientific research – an international collaboration

As the COVID-19 pandemic continues its march around the world, an unprec...
research
07/04/2020

Excess deaths hidden 100 days after the quarantine in Peru by COVID-19

Objective: To make an estimate of the excess deaths caused by COVID-19 i...
research
12/13/2021

Real-Time Estimation of COVID-19 Infections via Deconvolution and Sensor Fusion

We propose, implement, and evaluate a method to estimate the daily numbe...
research
01/29/2021

The growth of COVID-19 scientific literature: A forecast analysis of different daily time series in specific settings

We present a forecasting analysis on the growth of scientific literature...
research
10/28/2020

Space-Time Covid-19 Bayesian SIR modeling in South Carolina

The Covid-19 pandemic has spread across the world since the beginning of...
research
01/14/2021

Scared into Action: How Partisanship and Fear are Associated with Reactions to Public Health Directives

Differences in political ideology are increasingly appearing as an imped...

Please sign up or login with your details

Forgot password? Click here to reset