Search

Abstract Vaccination against COVID-19 was integral to controlling the pandemic that persisted with the continuous emergence of SARS-CoV-2 variants. Using a mathematical model describing SARS-CoV-2 within-host infection dynamics, we estimate differences in virus and immunity due to factors of infecting variant, age, and vaccination history (vaccination brand, number of doses and time since vaccination). We fit our model in a Bayesian framework to upper respiratory tract viral load measurements obtained from cases of Delta and Omicron infections in Singapore, of whom the majority only had one nasopharyngeal swab measurement. With this dataset, we are able to recreate similar trends in URT virus dynamics observed in past within-host modelling studies fitted to longitudinal patient data. We found that Omicron had higher R0,within values than Delta, indicating greater initial cell-to-cell spread of infection within the host. Moreover, heterogeneities in infection dynamics across patient subgroups could be recreated by fitting immunity-related parameters as vaccination history-specific, with or without age modification. Our model results are consistent with the notion of immunosenescence in SARS-CoV-2 infection in elderly individuals, and the issue of waning immunity with increased time since last vaccination. Lastly, vaccination was not found to subdue virus dynamics in Omicron infections as well as it had for Delta infections. This study provides insight into the influence of vaccine-elicited immunity on SARS-CoV-2 within-host dynamics, and the interplay between age and vaccination history. Furthermore, it demonstrates the need to disentangle host factors and changes in pathogen to discern factors influencing virus dynamics. Finally, this work demonstrates a way forward in the study of within-host virus dynamics, by use of viral load datasets including a large number of patients without repeated measurements.

Summary: Background: During pandemics, avoiding time delay in diagnosing infection is crucial. We evaluated factors associated with delayed diagnosis of symptomatic SARS-CoV-2 infection in a national cohort of adult Singaporeans, during which emergence of the more transmissible Omicron variant shifted pandemic management towards endemicity. Methods: Retrospective cross-sectional study amongst all adult Singaporeans diagnosed with symptomatic SARS-CoV-2 infection during the transition from Delta to Omicron BA.1 (September 2021–February 2022). SARS-CoV-2 testing was fully subsidised and compulsory for all symptomatic individuals presenting at primary care. Results and demographic information were extracted from national databases. Time to diagnosis was defined as days from symptom-onset to diagnosis (date of first positive SARS-CoV-2 test); dichotomising into no delay (≤24 h from symptom-onset) and delay >24 h. Multivariable logistic regression was utilised to assess factors associated with delay >24 h, and association of delay >24 h with progression to severe COVID-19. Findings: Of 149,063 Singaporean adults presenting with symptomatic SARS-CoV-2 infection, 75.9% (113,195/149,063) were diagnosed within 24 h of symptom-onset. On multivariable analysis, female gender, older age (>60 years), Chinese (vs. Malay) ethnicity, socioeconomic status (housing type), primary care characteristics, presentation during Omicron BA.1 (vs. Delta), symptom-onset on Friday/Saturday (vs. Monday), and not having completed a primary vaccination series were independently associated with higher odds of delay >24 h. Delay >24 h was independently associated with severe COVID-19 (adjusted odds-ratio, aOR = 1.45, 95% CI = 1.27–1.65, p 60 years) had higher odds of delay in diagnosis. Delay >24 h in diagnosis was independently associated with severe COVID-19. Funding: This study was not grant-funded.

This article presents the findings of a study conducted in Singapore that examined the use of oral antivirals (OAVs) among older adults with COVID-19 in primary care during the Omicron waves. The study revealed that a small percentage of older adults received OAVs, with nirmatrelvir-ritonavir being the most commonly prescribed medication. The study also identified factors such as primary care characteristics and socioeconomic status (SES) indicators that influenced the likelihood of receiving OAVs. The authors emphasize the importance of addressing disparities in OAV access among older adults and socioeconomically disadvantaged groups. They recommend targeted efforts to improve access for individuals with lower SES. [Extracted from the article]