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Tracking COVID-19 in the United States With Surveillance of Aggregate Cases and Deaths

Overview of attention for article published in Public Health Reports, March 2023
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

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62 X users

Citations

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1 Dimensions

Readers on

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7 Mendeley
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Title
Tracking COVID-19 in the United States With Surveillance of Aggregate Cases and Deaths
Published in
Public Health Reports, March 2023
DOI 10.1177/00333549231163531
Pubmed ID
Authors

Diba Khan, Meeyoung Park, Jacqueline Burkholder, Sorie Dumbuya, Matthew D. Ritchey, Paula Yoon, Amanda Galante, Joseph L. Duva, Jeffrey Freeman, William Duck, Stephen Soroka, Lyndsay Bottichio, Michael Wellman, Samuel Lerma, B. Casey Lyons, Deborah Dee, Seghen Haile, Denise M. Gaughan, Adam Langer, Adi V. Gundlapalli, Amitabh B. Suthar

Abstract

Early during the COVID-19 pandemic, the Centers for Disease Control and Prevention (CDC) leveraged an existing surveillance system infrastructure to monitor COVID-19 cases and deaths in the United States. Given the time needed to report individual-level (also called line-level) COVID-19 case and death data containing detailed information from individual case reports, CDC designed and implemented a new aggregate case surveillance system to inform emergency response decisions more efficiently, with timelier indicators of emerging areas of concern. We describe the processes implemented by CDC to operationalize this novel, multifaceted aggregate surveillance system for collecting COVID-19 case and death data to track the spread and impact of the SARS-CoV-2 virus at national, state, and county levels. We also review the processes established to acquire, process, and validate the aggregate number of cases and deaths due to COVID-19 in the United States at the county and jurisdiction levels during the pandemic. These processes include time-saving tools and strategies implemented to collect and validate authoritative COVID-19 case and death data from jurisdictions, such as web scraping to automate data collection and algorithms to identify and correct data anomalies. This topical review highlights the need to prepare for future emergencies, such as novel disease outbreaks, by having an event-agnostic aggregate surveillance system infrastructure in place to supplement line-level case reporting for near-real-time situational awareness and timely data.

X Demographics

X Demographics

The data shown below were collected from the profiles of 62 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 29%
Other 2 29%
Researcher 1 14%
Student > Master 1 14%
Unknown 1 14%
Readers by discipline Count As %
Medicine and Dentistry 3 43%
Unspecified 2 29%
Nursing and Health Professions 1 14%
Unknown 1 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 39. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 April 2023.
All research outputs
#1,078,478
of 25,784,004 outputs
Outputs from Public Health Reports
#213
of 2,964 outputs
Outputs of similar age
#22,868
of 424,376 outputs
Outputs of similar age from Public Health Reports
#3
of 24 outputs
Altmetric has tracked 25,784,004 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,964 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.7. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 424,376 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 94% of its contemporaries.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.