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Accepted (AM)Open Access (License Unspecified), Open
Journal article
Effect of Adjustment for Case Misclassification and Infection Date Uncertainty on Estimates of COVID-19 Effective Reproduction Number
Epidemiology (Cambridge, Mass.), v 32(6), pp 800-806
01 Nov 2021
PMID: 34310444
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Background: Surveillance data captured during the COVID-19 pandemic may not be optimal to inform a public health response, because it is biased by imperfect test accuracy, differential access to testing, and uncertainty in date of infection. Methods: We downloaded COVID-19 time-series surveillance data from the Colorado Department of Public Health & Environment by report and illness onset dates for 9 March 2020 to 30 September 2020. We used existing Bayesian methods to first adjust for misclassification in testing and surveillance, followed by deconvolution of date of infection. We propagated forward uncertainty from each step corresponding to 10,000 posterior time-series of doubly adjusted epidemic curves. The effective reproduction number (R-t), a parameter of principal interest in tracking the pandemic, gauged the impact of the adjustment on inference. Results: Observed period prevalence was 1.3%; median of the posterior of true (adjusted) prevalence was 1.7% (95% credible interval [CrI]: 1.4%, 1.8%). Sensitivity of surveillance declined over the course of the epidemic from a median of 88.8% (95% CrI: 86.3%, 89.8%) to a median of 60.8% (95% CrI: 60.1%, 62.6%). The mean (minimum, maximum) values of R-t were higher and more variable by report date, 1.12 (0.77, 4.13), compared to those following adjustment, 1.05 (0.89, 1.73). The epidemic curve by report date tended to overestimate R-t early on and be more susceptible to fluctuations in data. Conclusion: Adjusting for epidemic curves based on surveillance data is necessary if estimates of missed cases and the effective reproduction number play a role in management of the COVID-19 pandemic.
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Details
- Title
- Effect of Adjustment for Case Misclassification and Infection Date Uncertainty on Estimates of COVID-19 Effective Reproduction Number
- Creators
- Neal D. Goldstein - Drexel UniversityHarrison Quick - Drexel UniversityIgor Burstyn - Drexel University
- Publication Details
- Epidemiology (Cambridge, Mass.), v 32(6), pp 800-806
- Publisher
- Lippincott Williams & Wilkins
- Number of pages
- 7
- Grant note
- K01AI143356 / National Institute of Allergy and Infectious Diseases of the National Institutes of Health; United States Department of Health & Human Services; National Institutes of Health (NIH) - USA; NIH National Institute of Allergy & Infectious Diseases (NIAID)
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Epidemiology and Biostatistics; Environmental and Occupational Health
- Web of Science ID
- WOS:000702003900006
- Scopus ID
- 2-s2.0-85116823719
- Other Identifier
- 991019168512204721
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- Web of Science research areas
- Public, Environmental & Occupational Health