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Abstract Urban nature—such as greenness and parks—can alleviate distress and provide space for safe recreation during the COVID-19 pandemic. However, nature is often less available in low-income populations and communities of colour—the same communities hardest hit by COVID-19. In analyses of two datasets, we quantified inequity in greenness and park proximity across all urbanized areas in the United States and linked greenness and park access to COVID-19 case rates for ZIP codes in 17 states. Areas with majority persons of colour had both higher case rates and less greenness. Furthermore, when controlling for sociodemographic variables, an increase of 0.1 in the Normalized Difference Vegetation Index was associated with a 4.1% decrease in COVID-19 incidence rates (95% confidence interval: 0.9–6.8%). Across the United States, block groups with lower income and majority persons of colour are less green and have fewer parks. Our results demonstrate that the communities most impacted by COVID-19 also have the least nature nearby. Given that urban nature is associated with both human health and biodiversity, these results have far-reaching implications both during and beyond the pandemic. 

With lowering costs of sequencing and genetic profiling techniques, genetic drivers can now be detected readily in tumors but current prognostic models for Natural‐killer/T cell lymphoma (NKTCL) have yet to fully leverage on them for prognosticating patients. Here, we used next‐generation sequencing to sequence 260 NKTCL tumors, and trained a genomic prognostic model (GPM) with the genomic mutations and survival data from this retrospective cohort of patients using LASSO Cox regression. The GPM is defined by the mutational status of 13 prognostic genes and is weakly correlated with the risk‐features in International Prognostic Index (IPI), Prognostic Index for Natural‐Killer cell lymphoma (PINK), and PINK‐Epstein–Barr virus (PINK‐E). Cox‐proportional hazard multivariate regression also showed that the new GPM is independent and significant for both progression‐free survival (PFS, HR: 3.73, 95% CI 2.07–6.73;p < .001) and overall survival (OS, HR: 5.23, 95% CI 2.57–10.65;p = .001) with known risk‐features of these indices. When we assign an additional risk‐score to samples, which are mutant for the GPM, the Harrell's C‐indices of GPM‐augmented IPI, PINK, and PINK‐E improved significantly (p < .001, χ²test) for both PFS and OS. Thus, we report on how genomic mutational information could steer toward better prognostication of NKTCL patients.