Scale-dependent spatial patterns in benthic communities around a tropical island seascape

Understanding and predicting patterns of spatial organization across ecological communities is central to the field of landscape ecology, and a similar line of inquiry has begun to evolve sub-tidally among seascape ecologists. Much of our current understanding of the processes driving marine community patterns, particularly in the tropics, has come from small-scale, spatially-discrete data that are often not representative of the broader seascape. Here we expand the spatial extent of seascape ecology studies and combine spatially-expansive in situ digital imagery, oceanographic measurements, spatial statistics, and predictive modeling to test whether predictable patterns emerge between coral reef benthic competitors across scales in response to intra-island gradients in physical drivers. We do this around the entire circumference of a remote, uninhabited island in the central Pacific (Jarvis Island) that lacks the confounding effects of direct human impacts. We show, for the first time, that competing benthic groups demonstrate predictable scaling patterns of organization, with positive autocorrelation in the cover of each group at scales \u3c ~1 km. Moreover, we show how gradients in subsurface temperature and surface wave power drive spatially-abrupt transition points in group dominance, explaining 48–84% of the overall variation in benthic cover around the island. Along the western coast, we documented ten times more sub-surface cooling-hours than any other part of the coastline, with events typically resulting in a drop of 1–4°C over a period of \u3c 5 h. These high frequency temperature fluctuations are indicative of upwelling induced by internal waves and here result in localized nitrogen enrichment (NO 2 + NO 3 ) that promotes hard coral dominance around 44% of the island\u27s perimeter. Our findings show that, in the absence of confounding direct human impacts, the spatial organization of coral reef benthic competitors are predictable and somewhat bounded across the seascape by concurrent gradients in physical drivers

Risk of death among people with rare autoimmune diseases compared with the general population in England during the 2020 COVID-19 pandemic

Objectives: To quantify the risk of death among people with rare autoimmune rheumatic diseases (RAIRD) during the UK 2020 COVID-19 pandemic compared with the general population, and compared with their pre-COVID risk. Methods: We conducted a cohort study in Hospital Episode Statistics for England from 2003 onwards, and linked data from the NHS Personal Demographics Service. We used ONS published data for general population mortality rates. Results: We included 168 691 people with a recorded diagnosis of RAIRD alive on 1 March 2020. Their median age was 61.7 (IQR 41.5-75.4) years, and 118 379 (70.2%) were female. Our case ascertainment methods had a positive predictive value of 85%. A total of 1815 (1.1%) participants died during March and April 2020. The age-standardized mortality rate (ASMR) among people with RAIRD (3669.3; 95% CI: 3500.4, 3838.1 per 100 000 person-years) was 1.44 (95% CI: 1.42, 1.45) times higher than the average ASMR during the same months of the previous 5 years, whereas in the general population of England it was 1.38 times higher. Age-specific mortality rates in people with RAIRD compared with the pre-COVID rates were higher from the age of 35 upwards, whereas in the general population the increased risk began from age 55 upwards. Women had a greater increase in mortality rates during COVID-19 compared with men. Conclusion: The risk of all-cause death is more prominently raised during COVID-19 among people with RAIRD than among the general population. We urgently need to quantify how much risk is due to COVID-19 infection and how much is due to disruption to health-care services

The incidence of Kawasaki disease using hospital admissions data for England 2006-2021

To describe the incidence of Kawasaki Disease (kDa) between 2006 and 2021 in England. We identified all cases in hospital episode statistics with an ICD-10 diagnostic code M303 (for kDa) between 1 April 2006 - 31 March 2021. We validated 83 diagnoses using hospital medical records and found >97% accuracy. We calculated incidence rate ratios (IRRs) using Poisson regression and assessed the influence of age, sex, ethnicity, and index of multiple deprivation (IMD). We used Office for National Statistics population estimates for England as the denominator. We identified a total of 5908 cases of kDa in all children under the age of 16 (mean age 3.8, SD = 3.2, 95% CI: 3.7-3.9). Incidence in children aged <5 years was 8.9 (95% CI: 8.6-9.2)/100 000 person-years; in children aged 5-9, 2.4 (95% CI: 2.3-2.6)/100 000 person-years; and in children aged 10-15, 0.6 (95% CI: 0.6-0.7). Male: female ratio was 1.5:1. Incidence was higher among non-White than White ethnicities (adjusted IRR 2.1 (2.0-2.2) for Asian, 3.0 (2.8-3.3) for Black and 4.5 (4.2-4.8) for other ethnicities). The incidence increased with socioeconomic deprivation; the adjusted IRR of the least deprived IMD quintile compared with the most deprived quintile was 0.81 (0.77-0.84). Incidence rates of kDa derived from hospital admission data in England were higher than in studies relying on clinician reporting. We confirm previous findings on the influence of sex, and ethnicity on kDa incidence and observe that there was a higher incidence of kDa within more deprived socioeconomic groups