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1.
Journal of Econometrics ; 2022.
Article in English | ScienceDirect | ID: covidwho-1778283

ABSTRACT

This paper provides three results for SVARs under the assumption that the primitive shocks are mutually independent. First, a framework is proposed to accommodate a disaster-type variable with infinite variance into a SVAR. We show that the least squares estimates of the SVAR are consistent but have non-standard asymptotics. Second, the disaster shock is identified as the component with the largest kurtosis. An estimator that is robust to infinite variance is used to recover the mutually independent components. Third, an independence test on the residuals pre-whitened by the Choleski decomposition is proposed to test the restrictions imposed on a SVAR. The test can be applied whether the data have fat or thin tails, and to over as well as exactly identified models. Three applications are considered. In the first, the independence test is used to shed light on the conflicting evidence regarding the role of uncertainty in economic fluctuations. In the second, disaster shocks are shown to have short term economic impact arising mostly from feedback dynamics. The third uses the framework to study the dynamic effects of economic shocks post-covid.

2.
Computers and Education: Artificial Intelligence ; : 100043, 2021.
Article in English | ScienceDirect | ID: covidwho-1588176

ABSTRACT

The AI-driven Fourth Industrial Revolution and the COVID-19 pandemic have one important thing in common: they both have caused significant and rapid changes to the skill set landscape of various industries. These disruptive forces mean that the early identification of the newly rising skills in a labour market — which we call its “emerging skills” — is crucial to its workforce. It is also crucial to the educators who, in order to provide lifelong training to the workforce, need to quickly adapt their curricula to the new skills. We propose a classification methodology that uses the past job ad trends of skills to predict the emerging skills of a future period, defined as the skills that have experienced a surge in hiring demand in said period. This general definition allows for freedom in specifying the criteria for a skill being emerging (through thresholds on hiring demand and its growth), which could be important to educators. Applying our methodology to the Information and Communication Technologies (ICT) labour market in Singapore, we show that we are able to predict future emerging skills with good precision and recall and beat two baseline classifiers for multiple threshold sets. Our methodology also allows us to see where job ads fail to provide sufficient predictive signals, pointing to auxiliary data sources (such as Stack Overflow for ICT) and skill ontologies as potential remedies. The success of our method shows how AI can be used to empower learners and educators in the ICT domain (and potentially other domains) with useful and well-curated insights at a moment’s notice, thus helping speed up the process of curricular change.

3.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-296734

ABSTRACT

The recent emergence of the omicron variant of the SARS-CoV-2 virus with large numbers of mutations has raised concern about a potential new surge in infections. Here we use molecular dynamics to study the biophysics of the interface of the omicron spike protein binding to (i) the ACE2 receptor protein, (ii) antibodies from all known binding regions, and (iii) the furin binding domain. Our simulations suggest that while there is significant reduction of antibody binding strength corresponding to escape, the omicron spike pays a cost in terms of weaker receptor binding. The furin cleavage domain is the same or weaker binding than the alpha variant, suggesting less viral load and disease intensity than the extant delta variant.

4.
Lancet Oncol ; 22(6): 765-778, 2021 06.
Article in English | MEDLINE | ID: covidwho-1531901

ABSTRACT

BACKGROUND: The efficacy and safety profiles of vaccines against SARS-CoV-2 in patients with cancer is unknown. We aimed to assess the safety and immunogenicity of the BNT162b2 (Pfizer-BioNTech) vaccine in patients with cancer. METHODS: For this prospective observational study, we recruited patients with cancer and healthy controls (mostly health-care workers) from three London hospitals between Dec 8, 2020, and Feb 18, 2021. Participants who were vaccinated between Dec 8 and Dec 29, 2020, received two 30 µg doses of BNT162b2 administered intramuscularly 21 days apart; patients vaccinated after this date received only one 30 µg dose with a planned follow-up boost at 12 weeks. Blood samples were taken before vaccination and at 3 weeks and 5 weeks after the first vaccination. Where possible, serial nasopharyngeal real-time RT-PCR (rRT-PCR) swab tests were done every 10 days or in cases of symptomatic COVID-19. The coprimary endpoints were seroconversion to SARS-CoV-2 spike (S) protein in patients with cancer following the first vaccination with the BNT162b2 vaccine and the effect of vaccine boosting after 21 days on seroconversion. All participants with available data were included in the safety and immunogenicity analyses. Ongoing follow-up is underway for further blood sampling after the delayed (12-week) vaccine boost. This study is registered with the NHS Health Research Authority and Health and Care Research Wales (REC ID 20/HRA/2031). FINDINGS: 151 patients with cancer (95 patients with solid cancer and 56 patients with haematological cancer) and 54 healthy controls were enrolled. For this interim data analysis of the safety and immunogenicity of vaccinated patients with cancer, samples and data obtained up to March 19, 2021, were analysed. After exclusion of 17 patients who had been exposed to SARS-CoV-2 (detected by either antibody seroconversion or a positive rRT-PCR COVID-19 swab test) from the immunogenicity analysis, the proportion of positive anti-S IgG titres at approximately 21 days following a single vaccine inoculum across the three cohorts were 32 (94%; 95% CI 81-98) of 34 healthy controls; 21 (38%; 26-51) of 56 patients with solid cancer, and eight (18%; 10-32) of 44 patients with haematological cancer. 16 healthy controls, 25 patients with solid cancer, and six patients with haematological cancer received a second dose on day 21. Of the patients with available blood samples 2 weeks following a 21-day vaccine boost, and excluding 17 participants with evidence of previous natural SARS-CoV-2 exposure, 18 (95%; 95% CI 75-99) of 19 patients with solid cancer, 12 (100%; 76-100) of 12 healthy controls, and three (60%; 23-88) of five patients with haematological cancers were seropositive, compared with ten (30%; 17-47) of 33, 18 (86%; 65-95) of 21, and four (11%; 4-25) of 36, respectively, who did not receive a boost. The vaccine was well tolerated; no toxicities were reported in 75 (54%) of 140 patients with cancer following the first dose of BNT162b2, and in 22 (71%) of 31 patients with cancer following the second dose. Similarly, no toxicities were reported in 15 (38%) of 40 healthy controls after the first dose and in five (31%) of 16 after the second dose. Injection-site pain within 7 days following the first dose was the most commonly reported local reaction (23 [35%] of 65 patients with cancer; 12 [48%] of 25 healthy controls). No vaccine-related deaths were reported. INTERPRETATION: In patients with cancer, one dose of the BNT162b2 vaccine yields poor efficacy. Immunogenicity increased significantly in patients with solid cancer within 2 weeks of a vaccine boost at day 21 after the first dose. These data support prioritisation of patients with cancer for an early (day 21) second dose of the BNT162b2 vaccine. FUNDING: King's College London, Cancer Research UK, Wellcome Trust, Rosetrees Trust, and Francis Crick Institute.


Subject(s)
COVID-19 Vaccines/therapeutic use , COVID-19/immunology , Neoplasms/immunology , Adult , Aged , Aged, 80 and over , Antibodies, Viral/blood , COVID-19/blood , COVID-19/complications , COVID-19/virology , COVID-19 Vaccines/immunology , Dose-Response Relationship, Immunologic , Female , Humans , Immunogenicity, Vaccine/immunology , London/epidemiology , Male , Middle Aged , Neoplasms/blood , Neoplasms/complications , Neoplasms/virology , Prospective Studies , SARS-CoV-2 , Wales
5.
Stat (Int Stat Inst) ; : e369, 2021 Feb 22.
Article in English | MEDLINE | ID: covidwho-1095685

ABSTRACT

We propose a generalized non-linear state-space model for count-valued time series of COVID-19 fatalities. To capture the dynamic changes in daily COVID-19 death counts, we specify a latent state process that involves second order differencing and an AR(1)-ARCH(1) model. These modeling choices are motivated by the application and validated by model assessment. We consider and fit a progression of Bayesian hierarchical models under this general framework. Using COVID-19 daily death counts from New York City's five boroughs, we evaluate and compare the considered models through predictive model assessment. Our findings justify the elements included in the proposed model. The proposed model is further applied to time series of COVID-19 deaths from the four most populous counties in Texas. These model fits illuminate dynamics associated with multiple dynamic phases and show the applicability of the framework to localities beyond New York City.

7.
Cancer Cell ; 39(2): 257-275.e6, 2021 02 08.
Article in English | MEDLINE | ID: covidwho-1009339

ABSTRACT

Given the immune system's importance for cancer surveillance and treatment, we have investigated how it may be affected by SARS-CoV-2 infection of cancer patients. Across some heterogeneity in tumor type, stage, and treatment, virus-exposed solid cancer patients display a dominant impact of SARS-CoV-2, apparent from the resemblance of their immune signatures to those for COVID-19+ non-cancer patients. This is not the case for hematological malignancies, with virus-exposed patients collectively displaying heterogeneous humoral responses, an exhausted T cell phenotype and a high prevalence of prolonged virus shedding. Furthermore, while recovered solid cancer patients' immunophenotypes resemble those of non-virus-exposed cancer patients, recovered hematological cancer patients display distinct, lingering immunological legacies. Thus, while solid cancer patients, including those with advanced disease, seem no more at risk of SARS-CoV-2-associated immune dysregulation than the general population, hematological cancer patients show complex immunological consequences of SARS-CoV-2 exposure that might usefully inform their care.


Subject(s)
COVID-19/immunology , Neoplasms/immunology , Neoplasms/virology , Severe Acute Respiratory Syndrome/immunology , Adult , Aged , Aged, 80 and over , COVID-19/etiology , COVID-19/mortality , Female , Hematologic Neoplasms/immunology , Hematologic Neoplasms/mortality , Hematologic Neoplasms/therapy , Hematologic Neoplasms/virology , Humans , Immunophenotyping , Male , Middle Aged , Nasopharynx/virology , Neoplasms/mortality , Neoplasms/therapy , Severe Acute Respiratory Syndrome/etiology , Severe Acute Respiratory Syndrome/mortality , Severe Acute Respiratory Syndrome/virology , T-Lymphocytes/virology , Virus Shedding , Young Adult
8.
Stem Cell Reports ; 16(3): 385-397, 2021 03 09.
Article in English | MEDLINE | ID: covidwho-970134

ABSTRACT

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) led to the coronavirus disease (COVID-19) outbreak that became a pandemic in 2020, causing more than 30 million infections and 1 million deaths to date. As the scientific community has looked for vaccines and drugs to treat or eliminate the virus, unexpected features of the disease have emerged. Apart from respiratory complications, cardiovascular disease has emerged as a major indicator of poor prognosis in COVID-19. It has therefore become of utmost importance to understand how SARS-CoV-2 damages the heart. Human pluripotent stem cell (hPSC) cardiovascular derivatives were rapidly recognized as an invaluable tool to address this, not least because one of the major receptors for the virus is not recognized by SARS-CoV-2 in mice. Here, we outline how hPSC-derived cardiovascular cells have been utilized to study COVID-19, and their potential for further understanding the cardiac pathology and in therapeutic development.


Subject(s)
COVID-19/pathology , COVID-19/virology , Heart/physiology , Heart/virology , Pluripotent Stem Cells/pathology , Pluripotent Stem Cells/virology , SARS-CoV-2/pathogenicity , Animals , Humans
9.
Nat Med ; 26(10): 1623-1635, 2020 10.
Article in English | MEDLINE | ID: covidwho-717130

ABSTRACT

Improved understanding and management of COVID-19, a potentially life-threatening disease, could greatly reduce the threat posed by its etiologic agent, SARS-CoV-2. Toward this end, we have identified a core peripheral blood immune signature across 63 hospital-treated patients with COVID-19 who were otherwise highly heterogeneous. The signature includes discrete changes in B and myelomonocytic cell composition, profoundly altered T cell phenotypes, selective cytokine/chemokine upregulation and SARS-CoV-2-specific antibodies. Some signature traits identify links with other settings of immunoprotection and immunopathology; others, including basophil and plasmacytoid dendritic cell depletion, correlate strongly with disease severity; while a third set of traits, including a triad of IP-10, interleukin-10 and interleukin-6, anticipate subsequent clinical progression. Hence, contingent upon independent validation in other COVID-19 cohorts, individual traits within this signature may collectively and individually guide treatment options; offer insights into COVID-19 pathogenesis; and aid early, risk-based patient stratification that is particularly beneficial in phasic diseases such as COVID-19.


Subject(s)
Antibodies, Viral/immunology , B-Lymphocytes/immunology , Coronavirus Infections/immunology , Cytokines/immunology , Dendritic Cells/immunology , Pneumonia, Viral/immunology , T-Lymphocytes/immunology , Aged , B-Lymphocyte Subsets/immunology , Basophils/immunology , Betacoronavirus , COVID-19 , Case-Control Studies , Cell Cycle , Chemokine CXCL10/immunology , Chemokines/immunology , Cohort Studies , Coronavirus Infections/blood , Disease Progression , Female , Flow Cytometry , Hospitalization , Humans , Immunologic Memory , Immunophenotyping , Interleukin-10/immunology , Interleukin-6/immunology , Leukocyte Count , Lymphocyte Activation/immunology , Male , Middle Aged , Pandemics , Pneumonia, Viral/blood , Prognosis , SARS-CoV-2 , Severity of Illness Index , T-Lymphocyte Subsets/immunology , Up-Regulation
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