Are commodity futures a hedge against inflation? A Markov-switching approach

This study examines the inflation hedging ability of various commodity futures using Markov-switching vector error correction models (MS-VECM). We find that total commodity futures fail to provide a hedge against inflation over the sample period between January 1983 and December 2021. However, industrial metals and precious metals are able to hedge against inflation. Other sub-indexes, including energy, agriculture, and livestock, do not have a significant inflation hedging ability. The inflation hedging capacity of industrial metals exhibits substantial variation over time, with most of the inflation hedging power occurring during the relatively longer and more common regimes covering the Great Moderation, the post-subprime crisis, and the periods after the outbreak of the COVID-19 pandemic. We further evaluate the inflation hedge ability of commodity futures by including stocks and bonds in the model. Our results suggest that industrial metals are more reliable inflation hedges.

High-Specificity Targets in SARS-CoV-2 N Protein for Serological Antibody Detection (preprint)

Background The current coronavirus disease (COVID-19) pandemic has created a pressing need to diagnose and screen a large number of close contacts of confirmed and suspected cases. Numerous nucleic acid detection kits are being rapidly developed and approved for viral etiological diagnosis; however, these are limited by the number of false negatives produced in clinical practice. Therefore, there is an urgent need to establish serological detection methods to serve as supplementary diagnostics.Methods We (1) performed a conservation and specificity analysis of the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid (N) protein, which is the main target of serological diagnosis; (2) integrated various B-cell epitope prediction methods to obtain possible dominant epitope regions for the N protein; (3) applied ELISA to analyze differences in the serological antibody levels for different epitopes; and (4) identified N protein epitopes for IgG and IgM with high specificity.Results SARS-CoV-2 strains showed low mutation rates for the N protein, and the construction of a phylogeny was a good characterization of its molecular evolutionary lineage in relation to other coronaviruses. SARS-CoV-2 showed the closest genetic relationship with SARS-CoV, which showed multiple consecutive long conserved regions at the amino acid level, but differed substantially from other coronaviruses. Tests targeting the SARS-CoV-2 N protein produced strong positive results in SARS-CoV patients in recovery. Of the five epitope dominant regions, using N18-39 and N183-197 for IgG and IgM detection, respectively, can effectively overcome the limitations of cross-reactivity.Conclusions The patients infected with both SARS viruses may exhibit cross-reactivity when using the N protein for antibody detection. However, there are regions of the N protein that can be used for antibody detection and some of these regions showed good specificity even between SARS-CoV-2 and SARS-CoV, and the antibody levels detected were consistent with those detected by the complete N protein. These findings provide a basis for serological diagnosis of SARS-CoV-2 patients, and research ideas for developing vaccines.

Comparative analysis of clinical characteristics, imaging and laboratory findings of different age groups with COVID-19.

Objective: This study aims to provide scientific basis for rapid screening and early diagnosis of the coronavirus disease 2019 (COVID-19) through analysing the clinical characteristics and early imaging/laboratory findings of the inpatients. Methods: Three hundred and three patients with laboratory-confirmed COVID-19 from the East Hospital of People's Hospital of Wuhan University (Wuhan, China) were selected and divided into four groups: youth (20-40 years, n = 64), middle-aged (41-60 years, n = 89), older (61-80 years, n = 118) and elderly (81-100 years, n = 32). The clinical characteristics and imaging/laboratory findings including chest computed tomography (CT), initial blood count, C-reactive protein [CRP]), procalcitonin (PCT) and serum total IgE were captured and analysed. Results: (1) The first symptoms of all age groups were primarily fever (76%), followed by cough (12%) and dyspnoea (5%). Beside fever, the most common initial symptom of elderly patients was fatigue (13%). (2) Fever was the most common clinical manifestation (80%), with moderate fever being the most common (40%), followed by low fever in patients above 40 years old and high fever in those under 40 years (35%). Cough was the second most common clinical manifestation and was most common (80%) in the middle-aged. Diarrhoea was more common in the middle-aged (21%) and the older (19%). Muscle ache was more common in the middle-aged (15%). Chest pain was more common in the youth (13%), and 13% of the youth had no symptoms. (3) The proportion of patients with comorbidities increased with age. (4) Seventy-one per cent of the patients had positive reverse transcription-polymerase chain reaction results and 29% had positive chest CT scans before admission to the hospital. (5) Lesions in all lobes of the lung were observed as the main chest CT findings (76%). (6) Decrease in lymphocytes and increase in monocytes were common in the patients over 40 years old but rare in the youth. Eosinophils (50%), red blood cells (39%) and haemoglobin (40%) decreased in all age groups. (7) The proportion of patients with CRP and PCT elevation increased with age. (8) Thirty-nine per cent of the patients had elevated IgE, with the highest proportion in the old (49%). Conclusion: The clinical characteristics and imaging/laboratory findings of COVID-19 patients vary in different age groups. Personalised criteria should be formulated according to different age groups in the early screening and diagnosis stage.

The timeline and risk factors of clinical progression of COVID-19 in Shenzhen, China (preprint)

Background: The novel coronavirus disease 2019(COVID-19) broke out globally. Early prediction of the clinical progression was essential but still unclear. We aimed to evaluate the timeline of COVID-19 development and analyze risk factors of disease progression.Methods In this retrospective study, we included 333 patients with laboratory-confirmed COVID-19 infection hospitalized in the Third People's Hospital of Shenzhen from 10 January to 10 February 2020. Epidemiological feature, clinical records, laboratory and radiology manifestations were collected and analyzed. 323 patients with mild-moderate symptoms on admission were observed to determine whether they exacerbated to severe-critically ill conditions (progressive group) or not (stable group). We used logistic regression to identify the risk factors associated with clinical progression.Results Of all the 333 patients, 70(21.0%) patients progressed into severe-critically ill conditions during hospitalization and assigned to the progressive group, 253(76.0%) patients belonged to the stable group, another 10 patients were severe before admission. we found that the clinical features of aged over 40 (3.80[1.72, 8.52]), males (2.21[1.20, 4.07]), with comorbidities (1.78[1.13, 2.81]) certain exposure history (0.38[0.20, 0.71]), abnormal radiology manifestations (3.56[1.13, 11.40]), low level of T lymphocytes (0.99[0.997, 0.999]), high level of NLR (0.99[0.97, 1.01]), IL-6 (1.05[1.03, 1.07]) and CRP (1.67[1.12, 2.47]) were the risk factors of disease progression by logistic regression.Conclusions the potential risk factors of males, older age, with comorbidities, low T lymphocyte level and high level of NLR, CRP, IL-6 can help to predict clinical progression of COVID-19 at an early stage.