Browsing by Author "Rowley, Elizabeth A. K."

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    Early Estimates of Bivalent mRNA Vaccine Effectiveness in Preventing COVID-19–Associated Emergency Department or Urgent Care Encounters and Hospitalizations Among Immunocompetent Adults — VISION Network, Nine States, September–November 2022
    (Center for Disease Control, 2022-12-30) Tenforde, Mark W.; Weber, Zachary A.; Natarajan, Karthik; Klein, Nicola P.; Kharbanda, Anupam B.; Stenehjem, Edward; Embi, Peter J.; Reese, Sarah E.; Naleway, Allison L.; Grannis, Shaun J.; DeSilva, Malini B.; Ong, Toan C.; Gaglani, Manjusha; Han, Jungmi; Dickerson, Monica; Fireman, Bruce; Dascomb, Kristin; Irving, Stephanie A.; Vazquez-Benitez, Gabriela; Rao, Suchitra; Konatham, Deepika; Patel, Palak; Schrader, Kristin E.; Lewis, Ned; Grisel, Nancy; McEvoy, Charlene; Murthy, Kempapura; Griggs, Eric P.; Rowley, Elizabeth A. K.; Zerbo, Ousseny; Arndorfer, Julie; Dunne, Margaret M.; Goddard, Kristin; Ray, Caitlin; Zhuang, Yan; Timbol, Julius; Najdowski, Morgan; Yang, Duck-Hye; Hansen, John; Ball, Sarah W.; Link-Gelles, Ruth; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineering
    During June-October 2022, the SARS-CoV-2 Omicron BA.5 sublineage accounted for most of the sequenced viral genomes in the United States, with further Omicron sublineage diversification through November 2022.* Bivalent mRNA vaccines contain an ancestral SARS-CoV-2 strain component plus an updated component of the Omicron BA.4/BA.5 sublineages. On September 1, 2022, a single bivalent booster dose was recommended for adults who had completed a primary vaccination series (with or without subsequent booster doses), with the last dose administered ≥2 months earlier (1). During September 13-November 18, the VISION Network evaluated vaccine effectiveness (VE) of a bivalent mRNA booster dose (after 2, 3, or 4 monovalent doses) compared with 1) no previous vaccination and 2) previous receipt of 2, 3, or 4 monovalent-only mRNA vaccine doses, among immunocompetent adults aged ≥18 years with an emergency department/urgent care (ED/UC) encounter or hospitalization for a COVID-19-like illness.† VE of a bivalent booster dose (after 2, 3, or 4 monovalent doses) against COVID-19-associated ED/UC encounters was 56% compared with no vaccination, 31% compared with monovalent vaccination only with last dose 2-4 months earlier, and 50% compared with monovalent vaccination only with last dose ≥11 months earlier. VE of a bivalent booster dose (after 2, 3, or 4 monovalent doses) against COVID-19-associated hospitalizations was 57% compared with no vaccination, 38% compared with monovalent vaccination only with last dose 5-7 months earlier, and 45% compared with monovalent vaccination only with last dose ≥11 months earlier. Bivalent vaccines administered after 2, 3, or 4 monovalent doses were effective in preventing medically attended COVID-19 compared with no vaccination and provided additional protection compared with past monovalent vaccination only, with relative protection increasing with time since receipt of the last monovalent dose. All eligible persons should stay up to date with recommended COVID-19 vaccinations, including receiving a bivalent booster dose. Persons should also consider taking additional precautions to avoid respiratory illness this winter season, such as masking in public indoor spaces, especially in areas where COVID-19 community levels are high.
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    Impact of accounting for correlation between COVID-19 and influenza vaccination in a COVID-19 vaccine effectiveness evaluation using a test-negative design
    (Elsevier, 2023) Payne, Amanda B.; Ciesla, Allison Avrich; Rowley, Elizabeth A. K.; Weber, Zachary A.; Reese, Sarah E.; Ong, Toan C.; Vazquez-Benitez, Gabriela; Naleway, Allison L.; Klein, Nicola P.; Embi, Peter J.; Grannis, Shaun J.; Kharbanda, Anupam B.; Gaglani, Manjusha; Tenforde, Mark W.; Link-Gelles, Ruth; VISION Network; Medicine, School of Medicine
    Test-negative-design COVID-19 vaccine effectiveness (VE) studies use symptomatic SARS-CoV-2-positive individuals as cases and symptomatic SARS-CoV-2-negative individuals as controls to evaluate COVID-19 VE. To evaluate the potential bias introduced by the correlation of COVID-19 and influenza vaccination behaviors, we assessed changes in estimates of VE of bivalent vaccines against COVID-19-associated hospitalizations and emergency department/urgent care (ED/UC) encounters when considering influenza vaccination status or including or excluding influenza-positive controls using data from the multi-state VISION vaccine effectiveness network. Analyses included encounters during October 2022 - February 2023, a period of SARS-CoV-2 and influenza cocirculation. When considering influenza vaccination status or including or excluding influenza-positive controls, COVID-19 VE estimates were robust, with most VE estimates against COVID-19-associated hospitalization and ED/UC encounters changing less than 5 percentage points. Higher proportions of influenza-positive patients among controls, influenza vaccination coverage, or VE could impact these findings; the potential bias should continue to be assessed.
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    Methods to Adjust for Confounding in Test-Negative Design COVID-19 Effectiveness Studies: Simulation Study
    (JMIR, 2025-01-27) Rowley, Elizabeth A. K.; Mitchell, Patrick K.; Yang, Duck-Hye; Lewis, Ned; Dixon, Brian E.; Vazquez-Benitez, Gabriela; Fadel, William F.; Essien, Inih J.; Naleway, Allison L.; Stenehjem, Edward; Ong, Toan C.; Gaglani, Manjusha; Natarajan, Karthik; Embi, Peter; Wiegand, Ryan E.; Link-Gelles, Ruth; Tenforde, Mark W.; Fireman, Bruce; Health Policy and Management, Richard M. Fairbanks School of Public Health
    Background: Real-world COVID-19 vaccine effectiveness (VE) studies are investigating exposures of increasing complexity accounting for time since vaccination. These studies require methods that adjust for the confounding that arises when morbidities and demographics are associated with vaccination and the risk of outcome events. Methods based on propensity scores (PS) are well-suited to this when the exposure is dichotomous, but present challenges when the exposure is multinomial. Objective: This simulation study aimed to investigate alternative methods to adjust for confounding in VE studies that have a test-negative design. Methods: Adjustment for a disease risk score (DRS) is compared with multivariable logistic regression. Both stratification on the DRS and direct covariate adjustment of the DRS are examined. Multivariable logistic regression with all the covariates and with a limited subset of key covariates is considered. The performance of VE estimators is evaluated across a multinomial vaccination exposure in simulated datasets. Results: Bias in VE estimates from multivariable models ranged from -5.3% to 6.1% across 4 levels of vaccination. Standard errors of VE estimates were unbiased, and 95% coverage probabilities were attained in most scenarios. The lowest coverage in the multivariable scenarios was 93.7% (95% CI 92.2%-95.2%) and occurred in the multivariable model with key covariates, while the highest coverage in the multivariable scenarios was 95.3% (95% CI 94.0%-96.6%) and occurred in the multivariable model with all covariates. Bias in VE estimates from DRS-adjusted models was low, ranging from -2.2% to 4.2%. However, the DRS-adjusted models underestimated the standard errors of VE estimates, with coverage sometimes below the 95% level. The lowest coverage in the DRS scenarios was 87.8% (95% CI 85.8%-89.8%) and occurred in the direct adjustment for the DRS model. The highest coverage in the DRS scenarios was 94.8% (95% CI 93.4%-96.2%) and occurred in the model that stratified on DRS. Although variation in the performance of VE estimates occurred across modeling strategies, variation in performance was also present across exposure groups. Conclusions: Overall, models using a DRS to adjust for confounding performed adequately but not as well as the multivariable models that adjusted for covariates individually.