Optical conductivity of the one-dimensional dimerized Hubbard model at quarter filling

We investigate the optical conductivity in the Mott insulating phase of the one-dimensional extended Hubbard model with alternating hopping terms (dimerization) at quarter band filling. Optical spectra are calculated for the various parameter regimes using the dynamical density-matrix renormalization group method. The study of limiting cases allows us to explain the various structures found numerically in the optical conductivity of this model. Our calculations show that the dimerization and the nearest-neighbor repulsion determine the main features of the spectrum. The on-site repulsion plays only a secondary role. We discuss the consequences of our results for the theory of the optical conductivity in the Bechgaard salts.Comment: 11 pages and 12 figure

COVID-19 Mortality in Patients with a Ward-Based Ceiling of Care

\ua9 2021 by the authors.Objectives: COVID-19 patients thought unlikely to benefit from organ support, thereby having a ward-based ceiling of care (WBCoC), represent a distinct subgroup. There are no associated studies in mortality. We sought to identify clinical risk factors for inpatient COVID-19 mortality. Design and setting: this was a retrospective observational study of patients admitted to Northumbria Healthcare NHS Foundation Trust. Clinical variables were associated with inpatient mortality via logistic regression. Participants: all patients admitted with COVID-19 infection and who had a WBCoC at point of admission were included (n = 114). Main outcome measures: the outcome measure was inpatient death

Report 50: Hospitalisation risk for Omicron cases in England

To assess differences in the risk of hospitalisation between the Omicron variant of concern (1) and the Delta variant, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England with last test specimen dates between 1st and 14th December inclusive. Variant was defined using a combination of S-gene Target Failure (SGTF) and genetic data. Case data were linked by National Health service (NHS) number to the National Immunisation Management System (NIMS) database, the NHS Emergency Care (ECDS) and Secondary Use Services (SUS) hospital episode datasets. Hospital attendance was defined as any record of attendance at a hospital by a case in the 14 days following their last positive PCR test, up to and including the day of attendance. A secondary analysis examined the subset of attendances with a length of stay of one or more days. We used stratified conditional Poisson regression to predict hospitalisation status, with demographic strata defined by age, sex, ethnicity, region, specimen date, index of multiple deprivation and in some analyses, vaccination status. Predictor variables were variant (Omicron or Delta), reinfection status and vaccination status. Overall, we find evidence of a reduction in the risk of hospitalisation for Omicron relative to Delta infections, averaging over all cases in the study period. The extent of reduction is sensitive to the inclusion criteria used for cases and hospitalisation, being in the range 20-25% when using any attendance at hospital as the endpoint, and 40-45% when using hospitalisation lasting 1 day or longer or hospitalisations with the ECDS discharge field recorded as “admitted” as the endpoint (Table 1). These reductions must be balanced against the larger risk of infection with Omicron, due to the reduction in protection provided by both vaccination and natural infection. A previous infection reduces the risk of any hospitalisation by approximately 50% (Table 2) and the risk of a hospital stay of 1+ days by 61% (95%CI:55-65%) (before adjustments for under ascertainment of reinfections). High historical infection attack rates and observed reinfection rates with Omicron mean it is necessary to correct hazard ratio estimates to accurately quantify intrinsic differences in severity between Omicron and Delta and to assess the protection afforded by past infection. The resulting adjustments are moderate (typically less than an increase of 0.2 in the hazard ratio for Omicron vs Delta and a reduction of approximately 0.1 in the hazard ratio for reinfections vs primary infections) but significant for evaluating severity overall. Using a hospital stay of 1+ days as the endpoint, the adjusted estimate of the relative risk of reinfections versus primary cases is 0.31, a 69% reduction in hospitalisation risk (Table 2). Stratifying hospitalisation risk by vaccination state reveals a more complex overall picture, albeit consistent with the unstratified analysis. This showed an apparent difference between those who received AstraZenca (AZ) vaccine versus Pfizer or Moderna (PF/MD) for their primary series (doses 1 and 2). Hazard ratios for hospital attendance with Omicron for PF/MD are similar to those seen for Delta in those vaccination categories, while Omicron hazard ratios are generally lower than for Delta for the AZ vaccination categories. Given the limited samples sizes to date, we caution about over-interpreting these trends, but they are compatible with previous findings that while protection afforded against mild infection from AZ was substantially reduced with the emergency of Delta, protection against more severe outcomes was sustained (2,3). We emphasise that these are estimates which condition upon infection; net vaccine effectiveness against hospital attendance may not vary between the vaccines, given that PF/MD maintain higher effectiveness against symptomatic infection with Omicron than AZ (4). Our estimates will assist in refining mathematical models of potential healthcare demand associated with the unfolding European Omicron wave. The hazard ratios provided in Table 3 can be translated into estimates of vaccine effectiveness (VE) against hospitalisation, given estimates of VE against infection (4). In broad terms, our estimates suggest that individuals who have received at least 2 vaccine doses remain substantially protected against hospitalisation, even if protection against infection has been largely lost against the Omicron variant (4,5)

What settings have been linked to SARS-CoV-2 transmission clusters?

Background: Concern about the health impact of novel coronavirus SARS-CoV-2 has resulted in widespread enforced reductions in people's movement ("lockdowns"). However, there are increasing concerns about the severe economic and wider societal consequences of these measures. Some countries have begun to lift some of the rules on physical distancing in a stepwise manner, with differences in what these "exit strategies" entail and their timeframes. The aim of this work was to inform such exit strategies by exploring the types of indoor and outdoor settings where transmission of SARS-CoV-2 has been reported to occur and result in clusters of cases. Identifying potential settings that result in transmission clusters allows these to be kept under close surveillance and/or to remain closed as part of strategies that aim to avoid a resurgence in transmission following the lifting of lockdown measures. Methods: We performed a systematic review of available literature and media reports to find settings reported in peer reviewed articles and media with these characteristics. These sources are curated and made available in an editable online database. Results: We found many examples of SARS-CoV-2 clusters linked to a wide range of mostly indoor settings. Few reports came from schools, many from households, and an increasing number were reported in hospitals and elderly care settings across Europe. Conclusions: We identified possible places that are linked to clusters of COVID-19 cases and could be closely monitored and/or remain closed in the first instance following the progressive removal of lockdown restrictions. However, in part due to the limits in surveillance capacities in many settings, the gathering of information such as cluster sizes and attack rates is limited in several ways: inherent recall bias, biased media reporting and missing data

Multi-ancestry fine mapping implicates OAS1 splicing in risk of severe COVID-19

The OAS1/2/3 cluster has been identified as a risk locus for severe COVID-19 among individuals of European ancestry, with a protective haplotype of approximately 75 kilobases (kb) derived from Neanderthals in the chromosomal region 12q24.13. This haplotype contains a splice variant of OAS1, which occurs in people of African ancestry independently of gene flow from Neanderthals. Using trans-ancestry fine-mapping approaches in 20,779 hospitalized cases, we demonstrate that this splice variant is likely to be the SNP responsible for the association at this locus, thus strongly implicating OAS1 as an effector gene influencing COVID-19 severity. Multi-ancestry fine-mapping of the OAS1/2/3 region shows that a splice site variant in OAS1 is likely responsible for the association of this locus with the risk of severe COVID-19.Peer reviewe

The Shapes of Dirichlet Defects

If the vacuum manifold of a field theory has the appropriate topological structure, the theory admits topological structures analogous to the D-branes of string theory, in which defects of one dimension terminate on other defects of higher dimension. The shapes of such defects are analyzed numerically, with special attention paid to the intersection regions. Walls (co-dimension 1 branes) terminating on other walls, global strings (co-dimension 2 branes) and local strings (including gauge fields) terminating on walls are all considered. Connections to supersymmetric field theories, string theory and condensed matter systems are pointed out.Comment: 24 pages, RevTeX, 21 eps figure

Atrial fibrillation is an independent predictor for in-hospital mortality in patients admitted with SARS-CoV-2 infection.

Background Atrial fibrillation (AF) is the most encountered arrhythmia and has been associated with worse in-hospital outcomes. Objective This study was to determine the incidence of AF in patients hospitalized with coronavirus disease 2019 (COVID-19) as well as its impact on in-hospital mortality. Methods Patients hospitalized with a positive COVID-19 polymerase chain reaction test between March 1 and April 27, 2020, were identified from the common medical record system of 13 Northwell Health hospitals. Natural language processing search algorithms were used to identify and classify AF. Patients were classified as having AF or not. AF was further classified as new-onset AF vs history of AF. Results AF occurred in 1687 of 9564 patients (17.6%). Of those, 1109 patients (65.7%) had new-onset AF. Propensity score matching of 1238 pairs of patients with AF and without AF showed higher in-hospital mortality in the AF group (54.3% vs 37.2%; P \u3c .0001). Within the AF group, propensity score matching of 500 pairs showed higher in-hospital mortality in patients with new-onset AF as compared with those with a history of AF (55.2% vs 46.8%; P = .009). The risk ratio of in-hospital mortality for new-onset AF in patients with sinus rhythm was 1.56 (95% confidence interval 1.42-1.71; P \u3c .0001). The presence of cardiac disease was not associated with a higher risk of in-hospital mortality in patients with AF (P = .1). Conclusion In patients hospitalized with COVID-19, 17.6% experienced AF. AF, particularly new-onset, was an independent predictor of in-hospital mortality

Detecting behavioural changes in human movement to inform the spatial scale of interventions against COVID-19

On March 23 2020, the UK enacted an intensive, nationwide lockdown to mitigate transmission of COVID-19. As restrictions began to ease, more localized interventions were used to target resurgences in transmission. Understanding the spatial scale of networks of human interaction, and how these networks change over time, is critical to targeting interventions at the most at-risk areas without unnecessarily restricting areas at low risk of resurgence. We use detailed human mobility data aggregated from Facebook users to determine how the spatially-explicit network of movements changed before and during the lockdown period, in response to the easing of restrictions, and to the introduction of locally-targeted interventions. We also apply community detection techniques to the weighted, directed network of movements to identify geographically-explicit movement communities and measure the evolution of these community structures through time. We found that the mobility network became more sparse and the number of mobility communities decreased under the national lockdown, a change that disproportionately affected long distance connections central to the mobility network. We also found that the community structure of areas in which locally-targeted interventions were implemented following epidemic resurgence did not show reorganization of community structure but did show small decreases in indicators of travel outside of local areas. We propose that communities detected using Facebook or other mobility data be used to assess the impact of spatially-targeted restrictions and may inform policymakers about the spatial extent of human movement patterns in the UK. These data are available in near real-time, allowing quantification of changes in the distribution of the population across the UK, as well as changes in travel patterns to inform our understanding of the impact of geographically-targeted interventions

Pregnancy and neonatal outcomes of COVID-19: co-reporting of common outcomes from PAN-COVID and AAP SONPM registries

OBJECTIVE: Few large cohort studies have reported data on maternal, fetal, perinatal and neonatal outcomes associated with SARS-CoV-2 infection in pregnancy. We report the outcome of infected pregnancies from a collaboration formed early during the pandemic between the investigators of two registries, the UK and global Pregnancy and Neonatal outcomes in COVID-19 (PAN-COVID) study and the US American Academy of Pediatrics Section on Neonatal Perinatal Medicine (AAP SONPM) National Perinatal COVID-19 Registry. METHODS: This was an analysis of data from the PAN-COVID registry (January 1st to July 25th 2020), which includes pregnancies with suspected or confirmed maternal SARS-CoV-2 infection at any stage in pregnancy, and the AAP SONPM National Perinatal COVID-19 registry (April 4th to August 8th 2020), which includes pregnancies with positive maternal testing for SARS-CoV-2 from 14 days before delivery to 3 days after delivery. The registries collected data on maternal, fetal, perinatal and neonatal outcomes. The PAN-COVID results are presented both overall for pregnancies with suspected or confirmed SARS-CoV-2 infection and separately in those with confirmed infection. RESULTS: We report on 4005 pregnant women with suspected or confirmed SARS-CoV-2 infection (1606 from PAN-COVID and 2399 from AAP SONPM). For obstetric outcomes, in PAN-COVID overall, those with confirmed infection in PAN-COVID and AAP SONPM, respectively, maternal death occurred in 0.5%, 0.5% and 0.2% of cases, early neonatal death in 0.2%, 0.3% and 0.3% of cases and stillbirth in 0.5%, 0.6% and 0.4% of cases. Delivery was pre-term (<37 weeks' gestation) in 12.0% of all women in PAN-COVID, in 16.2% of those women with confirmed infection in PAN-COVID and in 15.7% of women in AAP SONPM. Extremely preterm delivery (< 27 weeks' gestation) occurred in 0.5% of cases in PAN-COVID and 0.3% in AAP SONPM. Neonatal SARS-CoV-2 infection was reported in 0.8% of all deliveries in PAN-COVID, in 2.0% in those with confirmed infection in PAN-COVID and in 1.8% in AAP SONPM; the proportions of neonates tested were 9.5%, 20.7% and 87.2%, respectively. The rates of a SGA neonate were 8.2% in PAN-COVID overall, 9.7% in those with confirmed infection and 9.6% in AAP SONPM. Mean gestational age adjusted birth-weight z-scores were -0.03 in PAN-COVID and -0.18 in AAP SONPM. CONCLUSIONS: The findings from the UK and US registries of pregnancies with SARS-CoV-2 infection were remarkably concordant. Preterm delivery affected a higher proportion of women than expected based on historical and contemporaneous national data. The proportions of pregnancies affected by stillbirth, a small for gestational age infant or early neonatal death were comparable to those in historical and contemporaneous UK and US data. Although maternal death was uncommon, the rate was higher than expected based on UK and US population data, which is likely explained by under-ascertainment of women affected by milder or asymptomatic infection in pregnancy in the PAN-COVID study although not in the AAP SONPM study. The data presented support strong guidance for enhanced precautions to prevent SARS-CoV-2 infection in pregnancy, particularly in the context of increased risks of preterm delivery and maternal mortality, and for priority vaccination of women planning pregnancy. This article is protected by copyright. All rights reserved