Enhanced Gravity Model of trade: reconciling macroeconomic and network models

The structure of the International Trade Network (ITN), whose nodes and links represent world countries and their trade relations respectively, affects key economic processes worldwide, including globalization, economic integration, industrial production, and the propagation of shocks and instabilities. Characterizing the ITN via a simple yet accurate model is an open problem. The traditional Gravity Model (GM) successfully reproduces the volume of trade between connected countries, using macroeconomic properties such as GDP, geographic distance, and possibly other factors. However, it predicts a network with complete or homogeneous topology, thus failing to reproduce the highly heterogeneous structure of the ITN. On the other hand, recent maximum-entropy network models successfully reproduce the complex topology of the ITN, but provide no information about trade volumes. Here we integrate these two currently incompatible approaches via the introduction of an Enhanced Gravity Model (EGM) of trade. The EGM is the simplest model combining the GM with the network approach within a maximum-entropy framework. Via a unified and principled mechanism that is transparent enough to be generalized to any economic network, the EGM provides a new econometric framework wherein trade probabilities and trade volumes can be separately controlled by any combination of dyadic and country-specific macroeconomic variables. The model successfully reproduces both the global topology and the local link weights of the ITN, parsimoniously reconciling the conflicting approaches. It also indicates that the probability that any two countries trade a certain volume should follow a geometric or exponential distribution with an additional point mass at zero volume

Enhanced Gravity Model of trade: reconciling macroeconomic and network models

The structure of the International Trade Network (ITN), whose nodes and links represent world countries and their trade relations respectively, affects key economic processes worldwide, including globalization, economic integration, industrial production, and the propagation of shocks and instabilities. Characterizing the ITN via a simple yet accurate model is an open problem. The traditional Gravity Model successfully reproduces the volume of trade between connected countries, using macroeconomic properties such as GDP, geographic distance, and possibly other factors. However, it predicts a network with complete or homogeneous topology, thus failing to reproduce the highly heterogeneous structure of the ITN. On the other hand, recent maximum-entropy network models successfully reproduce the complex topology of the ITN, but provide no information about trade volumes. Here we integrate these two currently incompatible approaches via the introduction of an Enhanced Gravity Model (EGM) of trade. The EGM is the simplest model combining the Gravity Model with the network approach within a maximum-entropy framework. Via a unified and principled mechanism that is transparent enough to be generalized to any economic network, the EGM provides a new econometric framework wherein trade probabilities and trade volumes can be separately controlled by any combination of dyadic and country-specific macroeconomic variables. The model successfully reproduces both the global topology and the local link weights of the ITN, parsimoniously reconciling the conflicting approaches. It also indicates that the probability that any two countries trade a certain volume should follow a geometric or exponential distribution with an additional point mass at zero volume

Enhanced Gravity Model of Trade: Reconciling Macroeconomic and Network Models

The structure of the International Trade Network (ITN), whose nodes and links represent world countries and their trade relations, respectively, affects key economic processes worldwide, including globalization, economic integration, industrial production, and the propagation of shocks and instabilities. Characterizing the ITN via a simple yet accurate model is an open problem. The traditional Gravity Model (GM) successfully reproduces the volume of trade between connected countries, using macroeconomic properties, such as GDP, geographic distance, and possibly other factors. However, it predicts a network with complete or homogeneous topology, thus failing to reproduce the highly heterogeneous structure of the ITN. On the other hand, recent maximum entropy network models successfully reproduce the complex topology of the ITN, but provide no information about trade volumes. Here we integrate these two currently incompatible approaches via the introduction of an Enhanced Gravity Model (EGM) of trade. The EGM is the simplest model combining the GM with the network approach within a maximum-entropy framework. Via a unified and principled mechanism that is transparent enough to be generalized to any economic network, the EGM provides a new econometric framework wherein trade probabilities and trade volumes can be separately controlled by any combination of dyadic and country-specific macroeconomic variables. The model successfully reproduces both the global topology and the local link weights of the ITN, parsimoniously reconciling the conflicting approaches. It also indicates that the probability that any two countries trade a certain volume should follow a geometric or exponential distribution with an additional point mass at zero volume

Enhancing the repeatability and sensitivity of low-cost PCB, pH-sensitive field-effect transistors

Discrete, extended gate pH-sensitive field-effect transistors (dEGFETs) fabricated on printed circuit boards (PCBs) are a low-cost, simple to manufacture analytical technology that can be applied to a wide range of applications. Electrodeposited iridium oxide (IrOx) films have emerged as promising pH-sensitive layers owing to their theoretically high pH sensitivity and facile deposition, but typically exhibit low pH sensitivity or lack repro- ducibility. Moreover, to date, a combined IrOx and dEGFET PCB system has not yet been realised. In this study, we demonstrate a dEGFET pH sensor based on an extended gate manufactured on PCB that is rendered pH sensitive through an electrodeposited IrOx film, which can reliably and repeatably display beyond-Nernstian pH response. Using a combination of complementary surface analysis techniques, we show that the high pH sensitivity and repeatability of the dEGFETs are dependent on both the chemical composition and critically the uniformity of the IrOx film. The IrOx film uniformity can be enhanced through electrochemical polishing of the extended gate electrode prior to electrodeposition, leading to dEGFETs that exhibit a median pH sensitivity of 70.7 ± 5 mV/pH (n = 56) compared to only 31.3 ± 14 mV/pH (n = 31) for IrOx electrodeposited on non- polished PCB electrodes. Finally, we demonstrate the applicability of these devices by demonstrating the detection and quantification of ampicillin due to β-Lactamase enzyme activity, thus laying the foundation for cheap and ubiquitous sensors which can be applied to a range of global challenges across healthcare and environmental monitoring

MTG570 AposHealth for osteoarthritis (OA) of the knee: External Assessment Group report

AposHealth (previously AposTherapy) is a non-invasive device worn on the foot to adjust the gait of the user to improve symptoms of knee osteoarthritis (OA), a condition that results in joints becoming stiff and painful. It is proposed as an addition to non-surgical standard care, or as an alternative. The comparators included alternative devices such as supports, splints and braces or intra-articular corticosteroid injections. Clinical evidence primarily from low quality non-comparative, observational studies indicates that users of AposHealth experience improvements in symptoms of knee OA including pain, function and stiffness. Quality of life outcomes also show improvements and both clinical and patient experts supported these findings from their own experience. Two comparative studies, one high quality randomised trial and one prospective comparative study, did report improvements with AposHealth however both studies compared with a sham device rather than standard care. There is a lack of evidence comparing AposHealth to non-surgical standard care treatment options such as manual therapy, walking aids, and intra-articular corticosteroid injections and their respective impacts on pain and function. Additionally, there is a lack of evidence relating to the outcome of TKR surgery delay or avoidance and in general there is a lack of long-term follow-up data (beyond 2 years). This is a key gap in the evidence and has a particular impact on the economic assessment

Dipeptidyl peptidase-1 inhibition in patients hospitalised with COVID-19: a multicentre, double-blind, randomised, parallel-group, placebo-controlled trial

Background Neutrophil serine proteases are involved in the pathogenesis of COVID-19 and increased serine protease activity has been reported in severe and fatal infection. We investigated whether brensocatib, an inhibitor of dipeptidyl peptidase-1 (DPP-1; an enzyme responsible for the activation of neutrophil serine proteases), would improve outcomes in patients hospitalised with COVID-19. Methods In a multicentre, double-blind, randomised, parallel-group, placebo-controlled trial, across 14 hospitals in the UK, patients aged 16 years and older who were hospitalised with COVID-19 and had at least one risk factor for severe disease were randomly assigned 1:1, within 96 h of hospital admission, to once-daily brensocatib 25 mg or placebo orally for 28 days. Patients were randomly assigned via a central web-based randomisation system (TruST). Randomisation was stratified by site and age (65 years or ≥65 years), and within each stratum, blocks were of random sizes of two, four, or six patients. Participants in both groups continued to receive other therapies required to manage their condition. Participants, study staff, and investigators were masked to the study assignment. The primary outcome was the 7-point WHO ordinal scale for clinical status at day 29 after random assignment. The intention-to-treat population included all patients who were randomly assigned and met the enrolment criteria. The safety population included all participants who received at least one dose of study medication. This study was registered with the ISRCTN registry, ISRCTN30564012. Findings Between June 5, 2020, and Jan 25, 2021, 406 patients were randomly assigned to brensocatib or placebo; 192 (47·3%) to the brensocatib group and 214 (52·7%) to the placebo group. Two participants were excluded after being randomly assigned in the brensocatib group (214 patients included in the placebo group and 190 included in the brensocatib group in the intention-to-treat population). Primary outcome data was unavailable for six patients (three in the brensocatib group and three in the placebo group). Patients in the brensocatib group had worse clinical status at day 29 after being randomly assigned than those in the placebo group (adjusted odds ratio 0·72 [95% CI 0·57–0·92]). Prespecified subgroup analyses of the primary outcome supported the primary results. 185 participants reported at least one adverse event; 99 (46%) in the placebo group and 86 (45%) in the brensocatib group. The most common adverse events were gastrointestinal disorders and infections. One death in the placebo group was judged as possibly related to study drug. Interpretation Brensocatib treatment did not improve clinical status at day 29 in patients hospitalised with COVID-19

Investigation of hospital discharge cases and SARS-CoV-2 introduction into Lothian care homes

Background The first epidemic wave of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in Scotland resulted in high case numbers and mortality in care homes. In Lothian, over one-third of care homes reported an outbreak, while there was limited testing of hospital patients discharged to care homes. Aim To investigate patients discharged from hospitals as a source of SARS-CoV-2 introduction into care homes during the first epidemic wave. Methods A clinical review was performed for all patients discharges from hospitals to care homes from 1st March 2020 to 31st May 2020. Episodes were ruled out based on coronavirus disease 2019 (COVID-19) test history, clinical assessment at discharge, whole-genome sequencing (WGS) data and an infectious period of 14 days. Clinical samples were processed for WGS, and consensus genomes generated were used for analysis using Cluster Investigation and Virus Epidemiological Tool software. Patient timelines were obtained using electronic hospital records. Findings In total, 787 patients discharged from hospitals to care homes were identified. Of these, 776 (99%) were ruled out for subsequent introduction of SARS-CoV-2 into care homes. However, for 10 episodes, the results were inconclusive as there was low genomic diversity in consensus genomes or no sequencing data were available. Only one discharge episode had a genomic, time and location link to positive cases during hospital admission, leading to 10 positive cases in their care home. Conclusion The majority of patients discharged from hospitals were ruled out for introduction of SARS-CoV-2 into care homes, highlighting the importance of screening all new admissions when faced with a novel emerging virus and no available vaccine

SARS-CoV-2 Omicron is an immune escape variant with an altered cell entry pathway

Vaccines based on the spike protein of SARS-CoV-2 are a cornerstone of the public health response to COVID-19. The emergence of hypermutated, increasingly transmissible variants of concern (VOCs) threaten this strategy. Omicron (B.1.1.529), the fifth VOC to be described, harbours multiple amino acid mutations in spike, half of which lie within the receptor-binding domain. Here we demonstrate substantial evasion of neutralization by Omicron BA.1 and BA.2 variants in vitro using sera from individuals vaccinated with ChAdOx1, BNT162b2 and mRNA-1273. These data were mirrored by a substantial reduction in real-world vaccine effectiveness that was partially restored by booster vaccination. The Omicron variants BA.1 and BA.2 did not induce cell syncytia in vitro and favoured a TMPRSS2-independent endosomal entry pathway, these phenotypes mapping to distinct regions of the spike protein. Impaired cell fusion was determined by the receptor-binding domain, while endosomal entry mapped to the S2 domain. Such marked changes in antigenicity and replicative biology may underlie the rapid global spread and altered pathogenicity of the Omicron variant