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1.
American Journal of Respiratory and Critical Care Medicine ; 205:2, 2022.
Article in English | English Web of Science | ID: covidwho-1881007
2.
Linguistics Vanguard ; 0(0):10, 2022.
Article in English | Web of Science | ID: covidwho-1742055

ABSTRACT

The Eastern Massachusetts Life and Language project was in its planning stages when the COVID-19 pandemic began to make headway in the United States in 2020. We contribute to the conversation about conducting linguistic fieldwork during a major social upheaval by providing a description of our shift to virtual methodologies, which include utilizing Instagram for participant recruitment and Zoom for conducting sociolinguistic interviews. Virtual data collection remains underexplored, as there has never been a widespread need for such practices until the recent lockdowns resulting from the pandemic. Likewise, social media appears to be underutilized as a recruitment tool in linguistic fieldwork. Nevertheless, it is effective in producing a heterogeneous participant sample in a short amount of time. We are delighted to engage in discussions about the effects of virtual recruitment and data collection on linguistic fieldwork and the data itself. We offer a description of our pivots to virtual recruitment and interviewing and the racial justice initiatives that become achievable because of these changes. We hope this contribution is beneficial to researchers looking to incorporate virtual methodologies into their research program.

3.
International Journal of Infectious Diseases ; 116:S110-S111, 2022.
Article in English | ScienceDirect | ID: covidwho-1712681

ABSTRACT

Purpose To minimize the impact of the COVID-19 pandemic, local public health authorities are often required to make prompt and informed decisions on anticipated case-loads, resource allocation for surveillance and testing, and public health intervention appropriateness. The objective of this research was to develop a near-term forecasting model to predict COVID-19 cases using real-time human mobility information in Ontario, Canada to assist public health authorities with outbreak response. Methods & Materials We utilized a deep neural network model to generate a short-term forecast of new COVID-19 cases by two weeks from May to August 2021. Variable selection was informed by a recent literature review and our ongoing research associating COVID-19 cases with human mobility, demographic and socio-economic factors. A real-time human mobility statistics consisting of a weekly summary of short and long-distance movement, demographic characteristics, weather, vaccination coverage, geo-location, and reported COVID-19 cases two weeks prior were included as predictors. We considered weeks as temporal and health regions as geographic units to account for population-level variabilities. We used a holdout method for model validation of over 300 iterations. Average mean squared error (MSE) and 95% confidence interval (CI) along with overlaying forecasted COVID-19 cases over the reported were used to evaluate the overall model fit. The model predictions were summarized as means and 95% CIs. Results Our best forecasting model had a mean MSE of 0.53 (95% CI: 0.49 – 0.56). Since May 2021, the overall trend of the reported COVID-19 cases in Ontario closely followed the forecasted cases, about 89% of the reported cases were within 1.5 times the interquartile range (IQR) and all were within the entire range of the distribution of the predictions. Forecasting accuracy also varied by health region characteristics, such a population size and density, remoteness, and reported COVID-19 case volume during the most recent weeks. Conclusion A near-term prediction of new COVID-19 cases with real-time population-level data could help public health authorities anticipate, plan and monitor disease burden in a population. Such predictions also allow the assessment of population-level health interventions to minimize new COVID-19 cases on a real-time basis and inform prompt decision making.

5.
MEDLINE;
Preprint in English | MEDLINE | ID: ppcovidwho-326578

ABSTRACT

Drug repurposing is the only method capable of delivering treatments on the shortened time-scale required for patients afflicted with lung disease arising from SARS-CoV-2 infection. Mucin-1 (MUC1), a membrane-bound molecule expressed on the apical surfaces of most mucosal epithelial cells, is a biochemical marker whose elevated levels predict the development of acute lung injury (ALI) and respiratory distress syndrome (ARDS), and correlate with poor clinical outcomes. In response to the pandemic spread of SARS-CoV-2, we took advantage of a high content screen of 3,713 compounds at different stages of clinical development to identify FDA-approved compounds that reduce MUC1 protein abundance. Our screen identified Fostamatinib (R788), an inhibitor of spleen tyrosine kinase (SYK) approved for the treatment of chronic immune thrombocytopenia, as a repurposing candidate for the treatment of ALI. In vivo , Fostamatinib reduced MUC1 abundance in lung epithelial cells in a mouse model of ALI. In vitro , SYK inhibition by Fostamatinib promoted MUC1 removal from the cell surface. Our work reveals Fostamatinib as a repurposing drug candidate for ALI and provides the rationale for rapidly standing up clinical trials to test Fostamatinib efficacy in patients with COVID-19 lung injury.

6.
MEDLINE;
Preprint in English | MEDLINE | ID: ppcovidwho-326567

ABSTRACT

Since its emergence and detection in Wuhan, China in late 2019, the novel coronavirus SARS-CoV-2 has spread to nearly every country around the world, resulting in hundreds of thousands of infections to date. The virus was first detected in the Pacific Northwest region of the United States in January, 2020, with subsequent COVID-19 outbreaks detected in all 50 states by early March. To uncover the sources of SARS-CoV-2 introductions and patterns of spread within the U.S., we sequenced nine viral genomes from early reported COVID-19 patients in Connecticut. Our phylogenetic analysis places the majority of these genomes with viruses sequenced from Washington state. By coupling our genomic data with domestic and international travel patterns, we show that early SARS-CoV-2 transmission in Connecticut was likely driven by domestic introductions. Moreover, the risk of domestic importation to Connecticut exceeded that of international importation by mid-March regardless of our estimated impacts of federal travel restrictions. This study provides evidence for widespread, sustained transmission of SARS-CoV-2 within the U.S. and highlights the critical need for local surveillance.

7.
Circulation ; 144(SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1636757

ABSTRACT

Introduction: COVID-19 infection is associated with troponin elevation, which is associated with increased mortality. We wanted to evaluate whether troponin levels, GRACE scores, and TIMI scores were independently associated with mortality in COVID-19 patients. Methods: Out of 1500 COVID-19 patients admitted to our hospitals, 217 patients with troponin levels were included. Key variables were collected manually, and survival analysis was done. Results: Mortality was 26.5% in the normal troponin group and 54.6% in the elevated troponin group. Patients with elevated troponins had increased frequency of hypotension (P=0.01), oxygen support (P<0.01), low absolute lymphocyte count (P<0.01), elevated blood urea nitrogen (P<0.01), higher C-reactive protein (P<0.01), higher D-dimer (P<0.01), higher lactic acid (P<0.01), and higher qSOFA, SOFA, TIMI, and GRACE scores (all scores P<0.01). On cox regression, troponin elevation (HR 1.85, 95% CI 1.18-2.88, P<0.01), TIMI score >3 (HR 1.79, 95% CI 1.11-2.75, P=0.01), GRACE score >140 (HR 2.27, 95% CI 1.45-3.55, P<0.01) were highly associated with mortality whereas cardiovascular disease (HR 1.40, 95% CI 0.89-2.21, P=0.129) and cardiovascular risk factors (HR 1.15, 95% CI 0.73-1.81, P=0.52) were not. We created four separate multivariate cox regression models for troponin, GRACE score, TIMI score, and SOFA score while adjusting for age, use of nonrebreather or high flow nasal cannula, hemoglobin<8.5, suspected or confirmed source of infection, and qSOFA score. GRACE (HR 1.02, 95% CI 1.01-1.04, P<0.01) and SOFA scores (HR 1.19, 95% CI 1.08-1.31, P<0.01) were independently associated with mortality whereas Troponin (HR 1.08, 95% CI 0.63-1.85, P=0.76) and TIMI score (HR 1.02, 95% CI 0.99-1.06, P=0.12) were not. SOFA scores are positively correlated with GRACE scores (r=+0.39). Conclusion: Troponin elevation in COVID-19 patients is mostly due to demand ischemia rather than acute coronary syndrome-related. This was shown by the association of troponin with a higher degree of systemic inflammation and end-organ dysfunction. We recommend SOFA scores and GRACE scores in risk stratifying COVID-19 patients with myocardial injury.

8.
Asia-Pacific Journal of Clinical Oncology ; 17(SUPPL 9):156, 2021.
Article in English | EMBASE | ID: covidwho-1598610

ABSTRACT

Background: Cancer patients undergoing systemicanti-cancer therapies (SACT) invariably experience toxicities precipitating presentations to Emergency Departments (ED). With the ongoing COVID-19 pandemic, it is imperative to keep vulnerable immunocompromised patients out of hospital and encourage patients to contact SURC when symptoms develop. This nurse-led SURC model of care has been reported to achieve an investment return of $1.73 for every dollar invested. At Peninsula Health (PH), we recently established SURC supported by the Victorian Government and are evaluating its uptake and effectiveness. Methodology: Episodes of care (Educations, phone, and physical attendances) occurring between 31/08/2020 to 30/06/2021 were captured in the SURC Access Database and analysed. ED presentations pre-and post-SURC commencement were examined if potentially avoidable presentations have reduced. Baseline patient experience and post-SURC implementation surveys were conducted amongst patients and clinicians with local ethics approval. Results : 1923 SURC episodes of care were provided to 540 individuals (educations 28.2%, phone triage 63.3%, and attendances 8.5%). The commonest tumour stream was breast (23.0%), lung (20.1%) and colorectal (17.2%), closely aligning with the local cancer prevalence rates. Most frequent SURC contacts were for gastrointestinal symptoms (16.9%), pain management (9.5%), care-coordination (9.1%) and medication advice (6.5%). Notably, more than one-third indicated they would have done nothing (38.5%) or delayed seeking medical advice (10.9%) without SURC. During the first five months post-SURC commencement we observed a 47.0% decrease in avoidable presentations within SURC operation hours, and a 29.3% decrease in after-hours ED presentations. The results from the patient and clinician surveys will be updated at the meeting. Conclusions : The SURC model of care is an invaluable resource to support cancer patients undergoing SACT which allows prompt access to specialist care while avoiding emergency presentations in the ambulatory setting. Resources permitting, it should be standard of care across all health services providing cancer care.

9.
British Journal of Surgery ; 108:1, 2021.
Article in English | Web of Science | ID: covidwho-1539296
10.
O'Toole, A.; Hill, V.; Pybus, O. G.; Watts, A.; Bogoch, II, Khan, K.; Messina, J. P.; consortium, Covid- Genomics UK, Network for Genomic Surveillance in South, Africa, Brazil, U. K. Cadde Genomic Network, Tegally, H.; Lessells, R. R.; Giandhari, J.; Pillay, S.; Tumedi, K. A.; Nyepetsi, G.; Kebabonye, M.; Matsheka, M.; Mine, M.; Tokajian, S.; Hassan, H.; Salloum, T.; Merhi, G.; Koweyes, J.; Geoghegan, J. L.; de Ligt, J.; Ren, X.; Storey, M.; Freed, N. E.; Pattabiraman, C.; Prasad, P.; Desai, A. S.; Vasanthapuram, R.; Schulz, T. F.; Steinbruck, L.; Stadler, T.; Swiss Viollier Sequencing, Consortium, Parisi, A.; Bianco, A.; Garcia de Viedma, D.; Buenestado-Serrano, S.; Borges, V.; Isidro, J.; Duarte, S.; Gomes, J. P.; Zuckerman, N. S.; Mandelboim, M.; Mor, O.; Seemann, T.; Arnott, A.; Draper, J.; Gall, M.; Rawlinson, W.; Deveson, I.; Schlebusch, S.; McMahon, J.; Leong, L.; Lim, C. K.; Chironna, M.; Loconsole, D.; Bal, A.; Josset, L.; Holmes, E.; St George, K.; Lasek-Nesselquist, E.; Sikkema, R. S.; Oude Munnink, B.; Koopmans, M.; Brytting, M.; Sudha Rani, V.; Pavani, S.; Smura, T.; Heim, A.; Kurkela, S.; Umair, M.; Salman, M.; Bartolini, B.; Rueca, M.; Drosten, C.; Wolff, T.; Silander, O.; Eggink, D.; Reusken, C.; Vennema, H.; Park, A.; Carrington, C.; Sahadeo, N.; Carr, M.; Gonzalez, G.; Diego, Search Alliance San, National Virus Reference, Laboratory, Seq, Covid Spain, Danish Covid-19 Genome, Consortium, Communicable Diseases Genomic, Network, Dutch National, Sars-CoV-surveillance program, Division of Emerging Infectious, Diseases, de Oliveira, T.; Faria, N.; Rambaut, A.; Kraemer, M. U. G..
Wellcome Open Research ; 6:121, 2021.
Article in English | MEDLINE | ID: covidwho-1450989

ABSTRACT

Late in 2020, two genetically-distinct clusters of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with mutations of biological concern were reported, one in the United Kingdom and one in South Africa. Using a combination of data from routine surveillance, genomic sequencing and international travel we track the international dispersal of lineages B.1.1.7 and B.1.351 (variant 501Y-V2). We account for potential biases in genomic surveillance efforts by including passenger volumes from location of where the lineage was first reported, London and South Africa respectively. Using the software tool grinch (global report investigating novel coronavirus haplotypes), we track the international spread of lineages of concern with automated daily reports, Further, we have built a custom tracking website (cov-lineages.org/global_report.html) which hosts this daily report and will continue to include novel SARS-CoV-2 lineages of concern as they are detected.

11.
American Journal of Respiratory and Critical Care Medicine ; 203(9):1, 2021.
Article in English | Web of Science | ID: covidwho-1407361
12.
American Journal of Respiratory and Critical Care Medicine ; 203(9):1, 2021.
Article in English | Web of Science | ID: covidwho-1407360
13.
American Journal of Respiratory and Critical Care Medicine ; 203(9), 2021.
Article in English | EMBASE | ID: covidwho-1277582

ABSTRACT

Rationale. Chronic obstructive Pulmonary Disease (COPD) has been associated with severe coronavirus disease 2019 (COVID-19) in Chinese and European cohorts. To date, no studies have evaluated the outcomes of COVID-19 in a selected cohort of patients with COPD in the United States (USA). We hypothesize that patients with COPD infected with Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV2) will have higher likelihood of 14-day hospitalization, mechanical ventilation use, and mortality compared to non-COPD SARS-CoV2 positive patients. Methods. We performed a retrospective analysis of electronic health records (EHR) from facilities across the 4 geographical regions of the USA (Optum Covid-19 Biweekly Data). We defined COVID-19 positive as having International Classification of Disease-10 (ICD-10) code of U07.1, or positive laboratory test results. COPD patients are defined by having at least 2-outpatient visits or 1- inpatient visit with any COPD diagnosis codes within a year prior to COVID-19 positive date. Results. We studied a cohort of 150,775 patients with COVID-19 between March and August 2020 in the United States. COPD was identified in 6,056 (4%) patients. The baseline characteristics of the cohort are presented in table 1. The percentage of patients with COPD and COVID-19 admitted to the hospital in 14-days for any cause was greater than that for non-COPD COVID-19 patients (28.7% vs 10.42%, p< 0.0001). The mean length of stay was longer for COPD with COVID-19 individuals than that for non-COPD COVID-19 patients (12.3 days vs 9.0 days, p<0.001). Amongst all hospitalized, the percentage of patients who required ICU was greater for COPD patients with COVID-19 than that for non-COPD patients (26.4% vs 16.11%, p<0.001). In addition, mechanical ventilation use was higher in COPD vs non-COPD COVID-19 patients (26.4% vs 16.11%, p<0.001) Moreover, the percentage of patients who died in 30 days was greater for COPD than that for non-COPD COVID-19 patients (13.6% vs 7.25%, p<0.0001). Discussion. Patients with COPD and COVID-19 have worse outcomes compared to non-COPD COVID-19 patients.

14.
American Journal of Respiratory and Critical Care Medicine ; 203(9), 2021.
Article in English | EMBASE | ID: covidwho-1277497

ABSTRACT

Rationale. The association between smoking status and severe Coronavirus Disease-2019 (COVID-19) remains controversial. To assess the risk of 14-day hospitalization, as a marker of severe COVID-19, in patients who are ever-smokers and tested positive for the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) compared to those who are never smokers and tested positive for the virus in a single academic health system in the United States. Methods. We conducted a retrospective cohort study of patients who tested positive for SARS-CoV-2 in the University of Texas Medical Branch Health System between March 1st and October 30th 2020 to identify the risk of 14-day hospitalization in ever-smokers compared to non-smokers. Results. In our study period, we identified 5,738 patients who met the inclusion criteria and had documentation of smoking habits. Out of this group, 636 (11%) were consider to be ever-smokers. One hundred and ninety one patients were current smokers and 445 were former smokers. Of the 5,738 patients, 35.1% were male, average age was 43.8 (SD± 17.6), 37.4% were Caucasian, 51.5% were obese (BMI≥30), 3.19 % had vaping history, and 76.5% had at least one comorbidity. We identified 624 (10.8%) patients who were admitted in 14 days and 49(0.8%) who died in 14 days during hospitalization. The percentage of ever smokers admitted in 14 days was greater than that of never smokers (17.9% vs 10%, p<0.0001). In addition, the percentage of smokers who died in 14 days was greater than that of never smokers (2.8% vs 0.6%, p<0.0001). However, after adjusting for other covariates the odds for 14-day hospitalization among ever smokers with COVID-19 was not significant (OR 0.96, 95% CI 0.7-1.2). Conclusions. In our single center study, smoking status was not associated with severe COVID-19 infection.

15.
Respiratory Medicine ; 182:106414, 2021.
Article in English | MEDLINE | ID: covidwho-1210098

ABSTRACT

RATIONALE: The association between smoking status and severe Coronavirus Disease 2019 (COVID-19) remains controversial. OBJECTIVE: To assess the risk of hospitalization (as a marker of severe COVID-19) in patients by smoking status: former, current and never smokers, who tested positive for the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV2) at an academic medical center in the United States. METHODS: We conducted a retrospective cohort study in patients with SARS-COV2 between March-1-2020 and January-31-2021 to identify the risk of hospitalization due to COVID-19 by smoking status. RESULTS: We identified 10216 SARS-COV2-positive patients with complete documentation of smoking habits. Within 14 days of a SARS-COV2 positive test, 1150 (11.2%) patients were admitted and 188 (1.8%) died. Significantly more former smokers were hospitalized from COVID-19 than current or never smokers (21.2% former smokers;7.3% current smokers;10.4% never smokers, p<0.0001). In univariable analysis, former smokers had higher odds of hospitalization from COVID-19 than never smokers (OR 2.31;95% CI 1.94-2.74). This association remained significant when analysis was adjusted for age, race and gender (OR 1.28;95% CI 1.06-1.55), but became non-significant when analysis included Body Mass Index, previous hospitalization and number of comorbidities (OR 1.05;95% CI 0.86-1.29). In contrast, current smokers were less likely than never smokers to be hospitalized due to COVID-19. CONCLUSIONS: Significantly more former smokers were hospitalized and died from COVID-19 than current or never smokers. This effect is mediated via age and comorbidities in former smokers.

16.
Anaesthesia ; 76(SUPPL 2):46, 2021.
Article in English | EMBASE | ID: covidwho-1093667

ABSTRACT

Anaesthetic gases are potent contributors to the enhanced greenhouse gas effect and ozone depletion. Their use accounts for 5% of acute NHS hospitals' total carbon footprint [1]. The NHS 'Long term plan' 2019 aims to reduce its carbon footprint by 51% by 2025, with 2% of this to be achieved by transforming anaesthetic practices. Desflurane is the most environmentally noxious of the volatiles, with a tropospheric lifetime of 14 years and a global warming potential 19.5 times worse than sevoflurane. Our aim was to investigate the carbon offset within our Trust that resulted from reduced elective surgery and volatile usage during the COVID-19 pandemic. We plan to use this information to raise awareness of the environmental impact of anaesthetic gases to our peers and encourage the adoption of greener anaesthetic strategies. Methods We reviewed the number of bottles of sevoflurane, isoflurane and desflurane consumed during the COVID-19 pandemic from 01/03/2020-30/05/2020 at Princess Royal University Hospital and King's College Hospital, then compared this to the amount consumed in the same time period in 2019. We translated these data into carbon emissions using experimentally derived data for each volatile agent [1] to evaluate the reduction in anaesthetic agent-related carbon emissions during the COVID-19 pandemic period. We also calculated the financial savings. Results Over the period analysed, we saw a 41% reduction in sevoflurane use, a 71% reduction in desflurane use and a 65% reduction in isoflurane use. This was a financial saving of £33,030 and a carbon dioxide equivalent reduction of 229,082 kg, which approximates to the greenhouse gases emitted from a standard car driving 568,442 miles, nearly 23 times around the world. Staggeringly, this amount of carbon would take 1 year for 299 acres of forest to sequester. Discussion We hope to see a reduction in our anaesthetic gas-associated carbon footprint for the same time period next year by presenting our findings to our anaesthetic colleagues, and by highlighting greener anaesthetic strategies such as low-flow anaesthesia and the avoidance of desflurane and nitrous oxide.

17.
Remote Sensing ; 13(1):30, 2021.
Article in English | Web of Science | ID: covidwho-1049051

ABSTRACT

The COVID-19 pandemic has infected almost 73 million people and is responsible for over 1.63 million fatalities worldwide since early December 2019, when it was first reported in Wuhan, China. In the early stages of the pandemic, social distancing measures, such as lockdown restrictions, were applied in a non-uniform way across the world to reduce the spread of the virus. While such restrictions contributed to flattening the curve in places like Italy, Germany, and South Korea, it plunged the economy in the United States to a level of recession not seen since WWII, while also improving air quality due to the reduced mobility. Using daily Earth observation data (Day/Night Band (DNB) from the National Oceanic and Atmospheric Administration Suomi-NPP and NO2 measurements from the TROPOspheric Monitoring Instrument TROPOMI) along with monthly averaged cell phone derived mobility data, we examined the economic and environmental impacts of lockdowns in Los Angeles, California;Chicago, Illinois;Washington DC from February to April 2020-encompassing the most profound shutdown measures taken in the U.S. The preliminary analysis revealed that the reduction in mobility involved two major observable impacts: (i) improved air quality (a reduction in NO2 and PM2.5 concentration), but (ii) reduced economic activity (a decrease in energy consumption as measured by the radiance from the DNB data) that impacted on gross domestic product, poverty levels, and the unemployment rate. With the continuing rise of COVID-19 cases and declining economic conditions, such knowledge can be combined with unemployment and demographic data to develop policies and strategies for the safe reopening of the economy while preserving our environment and protecting vulnerable populations susceptible to COVID-19 infection.

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