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Objectives: The coronavirus disease 2019 (COVID-19) pandemic has imposed significant burden on Brazil's health system. The present study aims to describe patients' demographic and clinical characteristics, vaccine uptake and assess healthcare resource utilization (HCRU) and costs associated with acute COVID-19 in Brazil during the Omicron predominant period. Method(s): A population-based retrospective study was conducted using the National Health Data Network (RNDS), National Vaccination Campaign against COVID-19 data and surveillance data in public setting. Individuals with positive COVID-19 test results between January-April 2022 were identified. Patients' demographics, comorbidities, vaccination status, HCRU for those who were admitted to hospitals and their associated costs were described by age groups. Result(s): A total of 8,160,715 COVID-19 cases were identified and 2.7% were aged <5 years, 11.6% were 5-19 years, 76.9% were 20-64 years and 8.7% were >= 65 years. The presence of comorbidity was 23.1% with a higher prevalence of comorbidities in the elderly (61.8% for 65-74 years and 71.2% for >=75 years). Regarding COVID -19 vaccination uptake, among those aged <=19 years, 20-64 years and >=65 years, 40.6%, 86.5% and 92.2% had primary series, respectively. Among adults, the booster uptake was 47.3% and 75.8% for those aged 20-64 years and >= 65 years, respectively. Among those with confirmed COVID-19, regardless of vaccination status, 87% were being symptomatic and 1.7% were hospitalized (3.8% in aged <5 years, 4.2% in 5-19 years, 34.3% in 20-64 years and 57.6% in >= 65 years). Among hospitalized patients, 32,6% were admitted to ICU and 80% required mechanical ventilation support. The average cost per day in normal wards and ICU without ventilation was R$291,89 and R$923,90, respectively. Conclusion(s): Our results quantify the public health and economic burden of COVID-19 in Brazil, suggesting substantial healthcare resources required to manage the COVID-19 pandemic.Copyright © 2023
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Objectives: The COVID pandemic has imposed significant direct medical cost and resource use burden on healthcare systems. This study described the patient demographic and clinical characteristics, healthcare resource utilization and costs associated with acute COVID in adults in England. Method(s): This population-based retrospective study used linked primary care (Clinical Practice Research Datalink, CPRD, Aurum) and secondary care (Hospital Episode Statistics) data to identify: 1) hospitalized (admitted within 12 weeks of a positive COVID-19 PCR test between August 2020 and March 2021) and 2) non-hospitalized patients (positive test between August 2020 and January 2022 and managed in the community). Hospitalization and primary care costs, 12 weeks after COVID diagnosis, were calculated using 2021 UK healthcare reference costs. Result(s): We identified 1,706,368 adult COVID cases. For hospitalized (n=13,105) and non-hospitalized (n=1,693,263) cohorts, 84% and 41% considered high risk for severe COVID using PANORAMIC criteria and 41% and 13% using the UKHSA's Green Book for prioritized immunization groups, respectively. Among hospitalized cases, median (IQR) length of stay was 5 (2-7), 6 (4-10), 8 (5-14) days for 18-49 years, 50-64 years and >= 65 years, respectively;6% required mechanical ventilation support, and median (IQR) healthcare costs (critical care cost excluded) per-finished consultant episode due to COVID increased with age (18-49 years: 4364 (1362-4471), 50-64 years: 4379 (4364-5800), 65-74 years: 4395 (4364-5800), 75-84 years: 4473 (4364-5800) and 85+ years: 5800 (4370-5807). Among non-hospitalized cases, older adults were more likely to seek GP consultations (13% of persons age 85+, 9% age 75-84, 7% age 65-74, 5% age 50-64, 3% age 18-49). Of those with at least 1 GP visit, the median primary care consultation total cost in the non-hospitalized cohort was 16 (IQR 16-31). Conclusion(s): Our results quantify the substantial economic burden required to manage adult patients in the acute phase of COVID in England.Copyright © 2023
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The COVID-19 pandemic has caused substantial damage to global health. Even though three years have passed, the world continues to struggle with the virus. Concerns are growing about the impact of COVID-19 on the mental health of infected individuals, who are more likely to experience depression, which can have long-lasting consequences for both the affected individuals and the world. Detection and intervention at an early stage can reduce the risk of depression in COVID-19 patients. In this paper, we investigated the relationship between COVID-19 infection and depression through social media analysis. Firstly, we managed a dataset of COVID-19 patients that contains information about their social media activity both before and after infection. Secondly, We conducted an extensive analysis of this dataset to investigate the characteristic of COVID-19 patients with a higher risk of depression. Thirdly, we proposed a deep neural network for early prediction of depression risk. This model considers daily mood swings as a psychiatric signal and incorporates textual and emotional characteristics via knowledge distillation. Experimental results demonstrate that our proposed framework outperforms baselines in detecting depression risk, with an AUROC of 0.9317 and an AUPRC of 0.8116. Our model has the potential to enable public health organizations to initiate prompt intervention with high-risk patients. © 2023 ACM.
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The United Nations Secretary-General Mechanism (UNSGM) for investigation of the alleged use of chemical and biological weapons is the only established international mechanism of this type under the UN. The UNGSM may launch an international investigation, relying on a roster of expert consultants, qualified experts, and analytical laboratories nominated by the member states. Under the framework of the UNSGM, we organized an external quality assurance exercise for nominated laboratories, named the Disease X Test, to improve the ability to discover and identify new pathogens that may cause possible epidemics and to determine their animal origin. The "what-if" scenario was to identify the etiological agent responsible for an outbreak that has tested negative for many known pathogens, including viruses and bacteria. Three microbes were added to the samples, Dabie bandavirus, Mammarenavirus, and Gemella spp., of which the last two have not been taxonomically named or published. The animal samples were from Rattus norvegicus, Marmota himalayana, New Zealand white rabbit, and the tick Haemaphysalis longicornis. Of the 11 international laboratories that participated in this activity, six accurately identified pathogen X as a new Mammarenavirus, and five correctly identified the animal origin as R. norvegicus. These results showed that many laboratories under the UNSGM have the capacity and ability to identify a new virus during a possible international investigation of a suspected biological event. The technical details are discussed in this report.Copyright © 2022
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Objectives: To estimate the public health impact of COVID-19 booster vaccination in the UK during Omicron predominance, and to explore the impact in counterfactual scenarios with different booster eligibility or uptake. Method(s): A dynamic transmission model was developed to compare public health outcomes for actual and hypothetical UK Spring and Autumn 2022 booster programs. Outcomes were projected over an extended time horizon from April 2022-April 2023, assuming continued Omicron predominance as in Jan-Mar 2022. Health outcomes included averted cases, hospitalizations, long COVID cases, and deaths. NHS resource use outcomes were averted general ward and intensive care unit bed days and general practitioner visits. Patient productivity loss outcomes considered productive days lost for those in and outside the paid work force. Analyses used publicly available data. Result(s): Model output suggested that actual Spring and Autumn 2022 programs, which offered boosters to older adults and vulnerable populations, would avert approximately 716,000 hospitalizations, 1.9M long COVID cases and 125,000 deaths compared to not offering boosters in Spring and Autumn 2022. In a scenario that broadened eligibility to individuals aged >=5 years, an estimated 1.6M hospitalizations, 8.3M long COVID cases, and 222,000 deaths were averted. A scenario assuming broadened eligibility and increased uptake produced the greatest benefit among scenarios analyzed: 1.6M hospitalizations, 9.2M long COVID cases, and 228,000 deaths averted;and 953M productive days saved. Scenarios offering boosters only to high-risk individuals (aged >=5 years) were also estimated to improve benefit relative to actual programs. High-risk-only programs assuming increased uptake provided about half to two-thirds of the benefit estimated for programs assuming broadened eligibility and increased uptake. Conclusion(s): UK booster vaccination programs were estimated to provide substantial benefit to public health during Omicron predominance. Public health benefits could be maximized by broadening booster eligibility to younger age groups and increasing uptake.Copyright © 2023
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Background: This study aimed to identify the incidence rate of post-coronavirus disease-2019 (COVID-19) conditions in the Republic of Korea (ROK) Army and to investigate the trend of the incidence rate according to changes in dominant variants. Method(s): We used the results of a 19-item, self-completed survey of those who had recovered from COVID-19 in the ROK Army between March 24, 2020, and April 30, 2022. We used both descriptive and multiple logistic regression analyses to identify factors associated with the incidence rate of post-COVID-19 conditions. Result(s): Among the total of 48,623 COVID-19 episodes in the ROK Army, the overall incidence rate of post-COVID-19 conditions was 32.9%. Based on the survey, the incidence of cough was the highest at 15.4%, followed by fatigue (15.1%) and sputum (13.8%). The delta variant had the highest incidence rate of post-COVID-19 conditions at 50.7%, whereas the omicron variant had the lowest at 19.7%. Concerning the type of post-COVID-19 condition, the neuropsychiatric symptoms had the highest incidence at 27.4% when the delta variant was dominant, and the respiratory symptoms were highest at 37.3% when the omicron variant was dominant. In the case of smell and taste symptoms, the incidence rate was high at 21.1% only when the delta variant was predominant. Conclusion(s): The overall incidence rate of post-COVID-19 conditions in the ROK Army was 32.9%. When the delta variant was dominant, the overall incidence as well as the proportion of neuropsychiatric symptoms were high. However, as the omicron variant became dominant, the overall incidence decreased, but the proportion of respiratory symptoms increased.Copyright © Korean Medical Association.
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Objective To explore the core targets and important pathways of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) induced atherosclerosis (AS) progression from the perspective of immune inflammation, so as to predict the potential prevention and treatment of traditional Chinese medicine (TCM). Methods Microarray data were obtained from the Gene Expression Omnibus (GEO) database for coronavirus disease 2019 (COVID-19) patients and AS patients, and the "limmar" and "Venn" packages were used to screen out the common differentially expressed genes (DEGs) genes in both diseases. The gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analyses were performed on the common DEGs to annotate their functions and important pathways. The two gene sets were scored for immune cells and immune function to assess the level of immune cell infiltration. The protein-protein interaction (PPI) network was constructed by STRING database, and the CytoHubba plug-in of Cytoscape was used to identify the hub genes. Two external validation datasets were introduced to validate the hub genes and obtain the core genes. Immuno-infiltration analysis and gene set enrichment analysis (GSEA) were performed on the core genes respectively. Finally the potential TCM regulating the core genes were predicted by Coremine Medical database. Results A total of 7898 genes related to COVID-19, 471 genes related to AS progression;And 51 common DEGs, including 32 highly expressed genes and 19 low expressed genes were obtained. GO and KEGG analysis showed that common DEGs, which were mainly localized in cypermethrin-encapsulated vesicles, platelet alpha particles, phagocytic vesicle membranes and vesicles, were involved in many biological processes such as myeloid differentiation factor 88 (MyD88)-dependent Toll-like receptor signaling pathway transduction, interleukin-8 (IL-8) production and positive regulation, IL-6 production and positive regulation to play a role in regulating nicotinamide adenine dinucleotide phosphate oxidase activity, Toll-like receptor binding and lipopeptide and glycosaminoglycan binding through many biological pathways, including Toll-like receptor signaling pathways, neutrophil extracellular trap formation, complement and coagulation cascade reactions. The results of immune infiltration analysis demonstrated the state of immune microenvironment of COVID-19 and AS. A total of 5 hub genes were obtained after screening, among which Toll-like receptor 2 (TLR2), cluster of differentiation 163 (CD163) and complement C1q subcomponent subunit B (C1QB) genes passed external validation as core genes. The core genes showed strong correlation with immune process and inflammatory response in both immune infiltration analysis and GSEA enrichment analysis. A total of 35 TCMs, including Chuanxiong (Chuanxiong Rhizoma), Taoren (Persicae Semen), Danggui (Angelicae Sinensis Radix), Huangqin (Scutellariae Radix), Pugongying (Taraxaci Herba), Taizishen (Pseudostellariae Radix), Huangjing (Polygonati Rhizoma), could be used as potential therapeutic agents. Conclusion TLR2, CD163 and C1QB were the core molecules of SARS-CoV-2-mediated immune inflammatory response promoting AS progression, and targeting predicted herbs were potential drugs to slow down AS progression in COVID-19 patients.Copyright © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.
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Objectives: Clinical Practice Research Datalink (CPRD) Aurum contains primary care electronic health records, including vaccinations and nearly complete capture of SARS-CoV-2 PCR test results between August 2020-March 2022. Our objective was to build code lists to define a cohort of persons diagnosed with COVID in England using routinely collected health data. Method(s): Persons aged 1 year or older were indexed on first COVID diagnosis from August 1, 2020 - January 31, 2022. We developed SNOMED code lists to define high risk of severe disease: 1) National Health Service's (NHS) list of highest risk conditions;2) PANORAMIC trial inclusion criteria;3) UK Health Security Agency (UKHSA) clinical risk groups. COVID vaccinations were defined as of December 1, 2021 using medical and product codes. Code lists were developed using wildcard search terms which were reviewed by multiple independent reviewers, and inclusion/exclusion was determined by consensus. All lists for diagnoses were reviewed by a UK physician. Result(s): We identified 2,257,907 people diagnosed in primary care with COVID;46% were male and mean age was 34 years, comparable to governmental data for the same period reporting 47% of cases in England were male and mean age was 34 years. We identified 12% at high risk of severe disease using the NHS definition, 31% using the PANORAMIC trial criteria, and 10% using the UKHSA clinical risk groups. Among adults, 86.1% had >=1 and 80.2% had >=2 COVID vaccine doses (2% and 0.2% lower than official reports, respectively). Conclusion(s): This cohort represented the age and sex distribution of COVID cases, and the COVID vaccination coverage, in England through January 2022. Definitions were built using reproducible methods that can be leveraged for future work. The high capture of COVID vaccinations supports the use of this cohort to examine clinical and societal benefits of COVID vaccination in England.Copyright © 2023
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Objectives: Clinical Practice Research Datalink (CPRD) Aurum captures primary care electronic healthcare records for ~28% of the population in England. From August 2020-;March 2022, all SARS-CoV-2 polymerase chain reaction (PCR) tests performed were reported back to the patient's general practitioner (GP), making the CPRD a closed system uniquely positioned to answer COVID research questions. Method(s): We defined persons with COVID as those recorded in primary care with a positive PCR test from August 1, 2020-March 31, 2021. We required continuous registration with their GP practice for >=365 days prior to diagnosis to establish comorbid conditions, and eligibility for linkage to Hospital Episode Statistics (HES) Admitted Patient Care data. Hospitalizations for COVID were defined as persons admitted with a primary diagnosis of COVID (ICD-10-CM U07.1) within 12 weeks of the initial primary care diagnosis record. Result(s): Our cohort included 535,453 persons diagnosed in primary care with COVID, with 2% later hospitalized. The hospitalized group was 57% male, 42% current/former smokers, 35% obese46% with a Charlson Comorbidity Index >1 and 98% had never received any COVID vaccine. Hospitalizations increased with age;<0.1% of patients aged 1-17, 1% aged 18-49, 4% aged 50-64, 9% aged 65-74, 13% aged 74-84, and 11% of COVID cases aged >=85 were hospitalized. Persons living in socially disadvantaged areas were overrepresented in the hospitalized cohort (25% in the Index of Multiple Deprivation's most deprived quintile). Conclusion(s): Consistent with other studies, hospitalized COVID patients were disproportionately those with male sex, smoking history, high body mass index, comorbidity and unvaccinated status. Hospitalizations were more common with age, and for individuals living in socially and economically deprived communities. Understanding the demographic and clinical characteristics of this cohort can help contextualize future work describing healthcare resource utilization and costs, as well as the impact of vaccines, associated with COVID in England.Copyright © 2023
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This paper examines return spillovers across China's bond, stock, and offshore (CNH/USD) and onshore (CNY/USD) exchange rate markets. We find evidence of a major transmitting role of the exchange rate market. Our results suggest that the Renminbi exchange rate market can reflect more market information and transmit it to bond and stock markets. Moreover, macroeconomic factors such as the monetary policy and economic policy uncertainty, the 2015 Renminbi exchange rate reform, and the COVID-19 pandemic are important determinants of the CNY/USD and CNH/USD spillover transmissions. Our results provide practical implications for investors, multinational corporations, and policymakers in China.
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Background: This study aimed to identify the incidence rate of post-coronavirus disease-2019 (COVID-19) conditions in the Republic of Korea (ROK) Army and to investigate the trend of the incidence rate according to changes in dominant variants. Method(s): We used the results of a 19-item, self-completed survey of those who had recovered from COVID-19 in the ROK Army between March 24, 2020, and April 30, 2022. We used both descriptive and multiple logistic regression analyses to identify factors associated with the incidence rate of post-COVID-19 conditions. Result(s): Among the total of 48,623 COVID-19 episodes in the ROK Army, the overall incidence rate of post-COVID-19 conditions was 32.9%. Based on the survey, the incidence of cough was the highest at 15.4%, followed by fatigue (15.1%) and sputum (13.8%). The delta variant had the highest incidence rate of post-COVID-19 conditions at 50.7%, whereas the omicron variant had the lowest at 19.7%. Concerning the type of post-COVID-19 condition, the neuropsychiatric symptoms had the highest incidence at 27.4% when the delta variant was dominant, and the respiratory symptoms were highest at 37.3% when the omicron variant was dominant. In the case of smell and taste symptoms, the incidence rate was high at 21.1% only when the delta variant was predominant. Conclusion(s): The overall incidence rate of post-COVID-19 conditions in the ROK Army was 32.9%. When the delta variant was dominant, the overall incidence as well as the proportion of neuropsychiatric symptoms were high. However, as the omicron variant became dominant, the overall incidence decreased, but the proportion of respiratory symptoms increased.Copyright © Korean Medical Association.
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Background: This study aimed to identify the incidence rate of post-coronavirus disease-2019 (COVID-19) conditions in the Republic of Korea (ROK) Army and to investigate the trend of the incidence rate according to changes in dominant variants.Methods: We used the results of a 19-item, self-completed survey of those who had recovered from COVID-19 in the ROK Army between March 24, 2020, and April 30, 2022. We used both descriptive and multiple logistic regression analyses to identify factors associated with the incidence rate of post-COVID-19 conditions.Results: Among the total of 48,623 COVID-19 episodes in the ROK Army, the overall incidence rate of postCOVID-19 conditions was 32.9%. Based on the survey, the incidence of cough was the highest at 15.4%, followed by fatigue (15.1%) and sputum (13.8%). The delta variant had the highest incidence rate of postCOVID-19 conditions at 50.7%, whereas the omicron variant had the lowest at 19.7%. Concerning the type of post-COVID-19 condition, the neuropsychiatric symptoms had the highest incidence at 27.4% when the delta variant was dominant, and the respiratory symptoms were highest at 37.3% when the omicron variant was dominant. In the case of smell and taste symptoms, the incidence rate was high at 21.1% only when the delta variant was predominant.Conclusion: The overall incidence rate of post-COVID-19 conditions in the ROK Army was 32.9%. When the delta variant was dominant, the overall incidence as well as the proportion of neuropsychiatric symptoms were high. However, as the omicron variant became dominant, the overall incidence decreased, but the proportion of respiratory symptoms increased.
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At the end of 2019, a new kind of coronavirus spread in Wuhan city of Hubei province and other places, seriously endangering people's health. Scientific prediction of the spread trend of the novel coronavirus makes a big difference in epidemic prevention, treatment, and relevant health decisions. The COVID-19 transmission model based on virus dynamics was established. We propose a data-driven dynamic modeling method for infectious disease transmission, which is a sparse identification method for nonlinear dynamic models. Sparse regression and parameter identification are used to accurately find the control equation from the potential dynamic models to simulate the dynamic transmission process of the novel coronavirus in Wuhan at the end of 2019. Through the experiment, we get the results that the model can well describe the spread of COVID-19 in Wuhan and also prove that the model is practical and can be extended to the prediction of related epidemic situations. © 2023 SPIE.
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Americans' concerns about the risks of vaccination are rising in recent years. In the original piece that explicated the psychometric paradigm, vaccinations were rated as less dreaded and less unknown. However, in 2016, vaccinations were more dreaded and more unknown in the public eye. A national survey (N = 1025) conducted in August 2021 reflects this trend in risk perception of the COVID-19 vaccines. Individuals who report different risk perceptions based on the unknown and dread characteristics associated with the COVID-19 vaccines also report different behavioral intent toward the vaccines. Overall, these findings show unknown risk to have a more salient impact on participants' risk perception that influence their vaccine-related decisions. © 2023 Informa UK Limited, trading as Taylor & Francis Group.
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Background: Immunocompromised patients with COVID-19 tend to shed viable virus for a prolonged period. Therefore, for moderately or severely immunocompromised patients with COVID-19, CDC recommends an isolation period of at least 20 days and ending isolation in conjunction with serial testing and consultation with an infectious disease specialist. However, data on viral kinetics and risk factors for prolonged viral shedding in these patients are limited. Method(s): From February 1, 2022 to April 1, 2022, we collected weekly saliva samples from immunocompromised patients with COVID-19 admitted to a tertiary hospital in Seoul, South Korea. Genomic and subgenomic RNAs were measured, and virus culture was performed. Result(s): A total of 41 patients were enrolled;29 (70%) were receiving chemotherapy against hematologic malignancies and the remaining 12 (30%) had undergone solid organ transplantation. Of the 41 patients, 14 (34%) had received 3 doses or more of COVID-19 vaccines. Real-time RT-PCR revealed that 7 (17%) were infected with Omicron BA.1, and 33 (80%) with Omicron BA.2. The median duration of viable virus shedding was 4 weeks (IQR 3-6). Patients undergoing B-cell depleting therapy shed viable virus for longer than the comparator (p=0.01). Multivariable analysis showed that 3-dose or more vaccination (HR 0.33, 95% CI 0.12 - 0.93, p = 0.04) and B-cell depleting therapy (HR 12.50, 95% CI 2.44 - 100.00, p = 0.003) independently affected viable virus shedding of SARS-CoV-2. Conclusion(s): Immunocompromised patients with COVID-19 shed viable virus for median 4 weeks. B-cell depleting therapy increases the risk of prolonged viable viral shedding, while completion of a primary vaccine series reduces this risk. Overall distribution of samples according to genomic viral copy number and culture positivity. Red dot indicates positive culture results, whereas blue dot indicated negative culture results. (Figure Presented).
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Does face-to-face interaction still facilitate information transfer despite proliferating communication technologies? We use the COVID-19 collapse in such interactions to examine their influence on information flow in the stock market around earnings announcements. Using daily, county-level abnormal mobility of U.S. residents to proxy for face-to-face interaction, we find that firms located in counties with lower abnormal mobility experience a weaker immediate price reaction to earnings announcements and a larger post-announcement drift. Our findings suggest that lower face-to-face interactions dampen price discovery in financial markets, and that investor attention is a potential mechanism of this effect.
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Tracking the evolution of clusters in social media streams is becoming increasingly important for many applications, such as early detection and monitoring of natural disasters or pandemics. In contrast to clustering on a static set of data, streaming data clustering does not have a global view of the complete data. The local (or partial) view in a high-speed stream makes clustering a challenging task. In this paper, we propose a novel density peak based algorithm, TStream, for tracking the evolution of clusters and outliers in social media streams, via the evolutionary actions of cluster adjustment, emergence, disappearance, split, and merge. TStream is based on a temporal decay model and text stream summarisation. The decay model captures the decreasing importance of textual documents over time. The stream summarisation compactly represents them with the help of cells (aka micro-clusters) in the memory. We also propose a novel efficient index called shared dependency tree (aka SD-Tree) based on the ideas of density peak and shared dependency. It maintains the dynamic dependency relationships in TStream and thereby improves the overall efficiency. We conduct extensive experiments on five real datasets. TStream outperforms the existing state-of-the-art solutions based on MStream, MStreamF, EDMStream, OSGM, and EStream, in terms of cluster mapping measure (CMM) by up to 17.8%, 18.6%, 6.9%, 16.4%, and 20.1%, respectively. It is also significantly more efficient than MStream, MStreamF, OSGM, and EStream, in terms of response time and throughput.