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Cell Rep Med
. 2024 Jan 16;5(1):101361.
doi: 10.1016/j.xcrm.2023.101361. Integration of individualized and population-level molecular epidemiology data to model COVID-19 outcomes
Ted Ling-Hu 1 , Lacy M Simons 1 , Taylor J Dean 1 , Estefany Rios-Guzman 1 , Matthew T Caputo 2 , Arghavan Alisoltani 1 , Chao Qi 3 , Michael Malczynski 3 , Timothy Blanke 4 , Lawrence J Jennings 3 , Michael G Ison 5 , Chad J Achenbach 6 , Paige M Larkin 7 , Karen L Kaul 8 , Ramon Lorenzo-Redondo 1 , Egon A Ozer 1 , Judd F Hultquist 9
Affiliations
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with enhanced transmissibility and immune escape have emerged periodically throughout the coronavirus disease 2019 (COVID-19) pandemic, but the impact of these variants on disease severity has remained unclear. In this single-center, retrospective cohort study, we examined the association between SARS-CoV-2 clade and patient outcome over a two-year period in Chicago, Illinois. Between March 2020 and March 2022, 14,252 residual diagnostic specimens were collected from SARS-CoV-2-positive inpatients and outpatients alongside linked clinical and demographic metadata, of which 2,114 were processed for viral whole-genome sequencing. When controlling for patient demographics and vaccination status, several viral clades were associated with risk for hospitalization, but this association was negated by the inclusion of population-level confounders, including case count, sampling bias, and shifting standards of care. These data highlight the importance of integrating non-virological factors into disease severity and outcome models for the accurate assessment of patient risk.
Keywords: COVID-19; SARS-CoV-2; confounders; genomic surveillance; molecular epidemiology; phylogenetics; severity modeling; variants of concern; viral evolution.
. 2024 Jan 16;5(1):101361.
doi: 10.1016/j.xcrm.2023.101361. Integration of individualized and population-level molecular epidemiology data to model COVID-19 outcomes
Ted Ling-Hu 1 , Lacy M Simons 1 , Taylor J Dean 1 , Estefany Rios-Guzman 1 , Matthew T Caputo 2 , Arghavan Alisoltani 1 , Chao Qi 3 , Michael Malczynski 3 , Timothy Blanke 4 , Lawrence J Jennings 3 , Michael G Ison 5 , Chad J Achenbach 6 , Paige M Larkin 7 , Karen L Kaul 8 , Ramon Lorenzo-Redondo 1 , Egon A Ozer 1 , Judd F Hultquist 9
Affiliations
- PMID: 38232695
- DOI: 10.1016/j.xcrm.2023.101361
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with enhanced transmissibility and immune escape have emerged periodically throughout the coronavirus disease 2019 (COVID-19) pandemic, but the impact of these variants on disease severity has remained unclear. In this single-center, retrospective cohort study, we examined the association between SARS-CoV-2 clade and patient outcome over a two-year period in Chicago, Illinois. Between March 2020 and March 2022, 14,252 residual diagnostic specimens were collected from SARS-CoV-2-positive inpatients and outpatients alongside linked clinical and demographic metadata, of which 2,114 were processed for viral whole-genome sequencing. When controlling for patient demographics and vaccination status, several viral clades were associated with risk for hospitalization, but this association was negated by the inclusion of population-level confounders, including case count, sampling bias, and shifting standards of care. These data highlight the importance of integrating non-virological factors into disease severity and outcome models for the accurate assessment of patient risk.
Keywords: COVID-19; SARS-CoV-2; confounders; genomic surveillance; molecular epidemiology; phylogenetics; severity modeling; variants of concern; viral evolution.