Title: Near real time monitoring and forecasting for COVID-19 situational awareness

Abstract

In the opening months of the pandemic (March - June), the need for situational awareness was urgent. Traditional forecasting models such as the Susceptible Infectious Recovered (SIR) model were hampered by limited testing data and key data on mobility, contact tracing, local policy variations and so forth would not be available with reliability for months. Reliably available were new case counts from John Hopkins University and the NY Times. Using these data, the challenge was to develop a robust monitoring capability in support of U.S. decision making. The Department of Energy’s National Virtual Biotechnology Laboratory responded by developing the COVID County Situational Awareness Tool (CCSAT). The result is significant in three ways. First, we developed a retrospective 7-day moving window map of county level disease magnitude and acceleration that smoothed daily variations and categorized counties with intuitive labels such as “high but decelerating”. Secondly, we developed a Bayesian model that reliably forecasted county level magnitude and acceleration maps for the upcoming week based on population and new case count data. Together these formed a robust operational update delivered weekly to the U.S. government. In this paper, we provide CCSAT details and apply it to a single week in June 2020.

Authors:

Stewart, Robert ;

• Search DOE PAGES for author "Stewart, Robert"
• Search DOE PAGES for ORCID "0000-0002-8186-7559"

Erwin, Samantha; Piburn, Jesse ;

• Search DOE PAGES for author "Piburn, Jesse"
• Search DOE PAGES for ORCID "0000-0003-4967-7912"

Nagle, Nicholas; Kaufman, Jason; Peluso, Alina ;

• Search DOE PAGES for author "Peluso, Alina"
• Search DOE PAGES for ORCID "0000-0003-2895-0406"

Christian, J. Blair ;

• Search DOE PAGES for author "Christian, J. Blair"
• Search DOE PAGES for ORCID "0000-0002-4658-1635"

Grant, Joshua ;

• Search DOE PAGES for author "Grant, Joshua"
• Search DOE PAGES for ORCID "0000-0001-6347-5060"

Sorokine, Alexandre ;

• Search DOE PAGES for author "Sorokine, Alexandre"
• Search DOE PAGES for ORCID "0000-0001-7993-1534"

Bhaduri, Budhendra

Publication Date:

Thu Sep 01 00:00:00 EDT 2022

Research Org.:

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Org.:

USDOE Office of Science (SC), Biological and Environmental Research (BER)

OSTI Identifier:

1879913

Alternate Identifier(s):

OSTI ID: 1884037; OSTI ID: 1885957

Report Number(s):

PNNL-SA-173905
Journal ID: ISSN 0143-6228; S0143622822001308; 102759; PII: S0143622822001308

Grant/Contract Number:  

AC05-00OR22725; AC05-76RL01830

Resource Type:

Published Article

Journal Name:

Applied Geography

Additional Journal Information:

Journal Name: Applied Geography Journal Volume: 146 Journal Issue: C; Journal ID: ISSN 0143-6228

Publisher:

Elsevier

Country of Publication:

United Kingdom

Language:

English

Subject:

60 APPLIED LIFE SCIENCES; COVID-19; Spatio-temporal; Monitoring; Forecasting; Bayesian