Differences in virus and immune dynamics for SARS-CoV-2 Delta and Omicron infections by age and vaccination histories.

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.

Association of depression with all-cause and cancer-specific mortality in older adults with cancer: Systematic review, meta-analysis, and meta-regression.

INTRODUCTION: The incidence and mortality of cancer is increasing worldwide with studies reporting that cumulative risk of cancer rises as age increases. Against the backdrop of the increasing prevalence of cancer amongst older patients, we conducted a systematic review and meta-analysis examining the depression-mortality relationship in older adults with cancer (OAC). MATERIALS AND METHODS: This PRISMA-adherent systematic review involved a systematic search of PubMed, Medline, EMBASE, and PsycINFO for prospective and retrospective cohort studies comparing the risk of all-cause and cancer-related mortality among OAC with depression. Random effects meta-analyses and meta-regressions were used for the primary analysis. RESULTS: From 5,280 citations, we included 14 cohort studies. Meta-analyses of hazard ratios (HRs) showed an increased incidence of all-cause mortality in OAC with depression (pooled HR: 1.40; 95% confidence interval [CI]: 1.25, 1.55). Subgroup analyses of other categorical study-level characteristics were insignificant. While risk of cancer-related mortality in OAC with depression was insignificantly increased with a pooled HR of 1.21 (95% CI: 0.98, 1.49), subgroup analysis indicated that risk of cancer-related mortality in OAC with depression significantly differed with cancer type. Our systematic review found that having fewer comorbidities, a higher education level, greater socioeconomic status, and positive social supportive factors lowered risk of all-cause mortality in OAC with depression. DISCUSSION: Depression in OAC significantly increases risk of all-cause mortality and cancer-related mortality among different cancer types. It is imperative for healthcare providers and policy makers to recognize vulnerable subgroups among older adults with cancer to individualize interventions.

Factors associated with delayed diagnosis of symptomatic adult COVID-19 cases presenting to primary care: a population-wide study during transition from Delta to Omicron BA.1 in Singapore.

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 < 0.001). Interpretation: At-risk populations (unvaccinated, age >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.