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Biomedical

Using Nonprobabilistic Surveys to Measure COVID-19 Incidence

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Jacob E. Simmering

Jacob E. Simmering

Department of Internal Medicine, Carver College of Medicine, University of Iowa, Iowa City


  Peer Reviewed

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© attribution CC-BY

  • 0

rating
490 Views

Added on

2024-10-20

Doi: http://dx.doi.org/10.1001/jamanetworkopen.2024.35407

Related Subjects
Anatomy
Biochemistry
Epidemiology
Genetics
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Oncology
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Musculoskeletal science
Pediatrics
Pathology
Pharmacology
Physiology
Psychiatry
Primary care
Women and reproductive health

Abstract

Summary:

The article discusses the potential of nonprobability online surveys as an efficient and timely method for measuring COVID-19 incidence. These surveys, when integrated with wastewater surveillance data, provide useful estimates of disease spread, particularly in the absence of precise official case counts. They offer demographic insights and can be rapidly deployed, but they face challenges such as increased sampling noise in state-level data. The study highlights the importance of these surveys in public health decision-making and pandemic response.

Key Questions

How do nonprobability online surveys compare to traditional COVID-19 case counts?

Nonprobability surveys correlate well with official case counts and wastewater data, particularly when traditional case counts became less reliable due to widespread home testing.

What are the advantages of using online surveys for disease monitoring?

Online surveys can be quickly deployed, provide demographic insights, and help identify affected populations more precisely than wastewater surveillance or clinical case counts.

What challenges are associated with using online surveys for public health data collection?

Survey data faces challenges such as sampling noise, particularly at state levels, and the need for strategies to maintain accurate demographic subgroup analysis.

How can nonprobability surveys enhance public health decision-making?

These surveys allow for real-time insights into disease spread and the identification of specific high-risk populations, informing timely public health interventions.

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ARTICLE USAGE


Article usage: Oct-2024 to May-2025
Show by month Manuscript Video Summary
2025 May 102 102
2025 April 67 67
2025 March 64 64
2025 February 47 47
2025 January 74 74
2024 December 55 55
2024 November 51 51
2024 October 30 30
Total 490 490
Show by month Manuscript Video Summary
2025 May 102 102
2025 April 67 67
2025 March 64 64
2025 February 47 47
2025 January 74 74
2024 December 55 55
2024 November 51 51
2024 October 30 30
Total 490 490
Related Subjects
Anatomy
Biochemistry
Epidemiology
Genetics
Neuroscience
Psychology
Oncology
Medicine
Musculoskeletal science
Pediatrics
Pathology
Pharmacology
Physiology
Psychiatry
Primary care
Women and reproductive health
copyright icon

© attribution CC-BY

  • 0

rating
490 Views

Added on

2024-10-20

Doi: http://dx.doi.org/10.1001/jamanetworkopen.2024.35407

Related Subjects
Anatomy
Biochemistry
Epidemiology
Genetics
Neuroscience
Psychology
Oncology
Medicine
Musculoskeletal science
Pediatrics
Pathology
Pharmacology
Physiology
Psychiatry
Primary care
Women and reproductive health

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