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In this work, SARS-CoV-2 infectivity after UV-C exposure of porous and non-porous surfaces was assessed under controlled environment conditions. The irradiance of a setup of UV-C lamps, placed indoors was studied in detail as a function of the geometry and the distance to the surface. In the presence of living beings, the external UV-C lamps are turned off, and the UV-C lamps mounted inside the disinfection chamber are kept active, allowing a continuous air disinfection and a decreased risk of indoor transmission. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.
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Arterial dissection is an uncommon complication of reversible cerebral vasocon-striction syndrome (RCVS). We describe the case of a 35-year-old woman with a migraine history who presented with recurrent thunderclap headache and focal neurological signs, including right hemiataxia. She had been diagnosed with COVID-19 disease two weeks earlier. Neuroimaging revealed multifocal stenosis of the posterior circulation arteries and dissection of the right superior cerebellar artery. She improved significantly throughout her one-week hospitalization and maintained only mild ataxia. The interplay between COVID-19 disease, RCVS, and arterial dissection requires further investigation.Copyright © Author(s) (or their employer(s)) and Sinapse 2022.
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Background. Nirmatrelvir with ritonavir (nirmatrelvir/r) is an oral antiviral COVID-19 treatment. We report its efficacy to shorten time to sustained alleviation and resolution of COVID-19 signs/symptoms in nonhospitalized adults with COVID-19 at high risk of severe disease as of primary completion data cut (11 Dec 2021). Methods. In this phase 2/3 double-blind study, eligible adults with confirmed SARS-CoV-2 and <= 5 days (d) of symptoms were randomized 1:1 to nirmatrelvir/r 300 mg/100 mg or placebo (PBO) every 12 hrs for 5 d. Pts logged presence and severity (on 3- or 4-point scales) of prespecified COVID-19 signs/symptoms daily Day 1 (predose) through 28. Times to sustained alleviation and resolution of all targeted signs/ symptoms were assessed, summarized with Kaplan-Meier curves, and compared by treatment by log-rank test. Individual signs/symptoms were compared with descriptive analyses. Results. From Jul-Dec 2021, 2246 pts enrolled;2085 pts (nirmatrelvir/r, n=1039;PBO, n=1046) met criteria for the mITT1 population (<= 5 d of symptom onset, did not/not expected to receive an mAb). More pts achieved sustained alleviation or sustained resolution with nirmatrelvir/r. Shorter median times to sustained alleviation/ resolution were observed with nirmatrelvir/r (13/16 d) vs PBO (15/19 d;Fig 1 & 2). Also, a shorter median time to sustained alleviation was seen in pts treated <= 3 d of symptoms with nirmatrelvir/r (12 d) vs PBO (15 d). The most common symptoms were cough, muscle/body aches, and headache in both groups. The median time to sustained alleviation of cough and headache was 2 d less with nirmatrelvir/r vs PBO. The median time to sustained resolution of muscle aches and shortness of breath was 3 d and 4 d less with nirmatrelvir/r. The proportion of pts with severe signs/symptoms in the nirmatrelvir/r vs PBO group was significantly higher at baseline, but significantly lower after treatment, showing nirmatrelvir/r significantly reduced symptom severity through Day 28 (Fig 3). Pts who were seronegative vs seropositive or had high vs low viral load at baseline achieved faster times to sustained alleviation with nirmatrelvir/r vs PBO. Conclusion. Nirmatrelvir/r treatment reduced duration and severity of COVID-19 symptoms vs PBO in pts at high risk of progressing to severe disease. NCT04960202.
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Background. Nirmatrelvir coadministered with ritonavir (nirmatrelvir/r) is a COVID-19 treatment. This study evaluated nirmatrelvir/r in nonhospitalized, symptomatic adults with COVID-19 at high risk of progressing to severe disease. We report secondary efficacy endpoints associated with COVID-19-related medical visits, including hospitalization details and oxygen support, as of the primary completion data cutoff (Dec 11, 2021). Methods. In this phase 2/3 double-blind, interventional study, adults with confirmed SARS-CoV-2 and symptom onset <= 5 days (d) were randomized 1:1 to receive nirmatrelvir/r 300 mg/100 mg or placebo (PBO) orally every 12 hours for 5 d. COVID-19-related medical visits were collected through Day 28. Oxygen support for COVID-19 and details of COVID-19-related hospitalization, including duration, intensive care unit (ICU) status, and mechanical ventilation, were assessed. Results. Of the 2246 patients (pts) enrolled globally from Jul to Dec2021, 2085 (nirmatrelvir/r, n=1039;PBO, n=1046) started treatment and met criteria for the modified intent-to-treat population (mITT1;<= 5 d of symptom onset, did not/not expected to receive a mAb). Fewer overall COVID-19-related medical visits were reported with nirmatrelvir/r vs PBO (Table 1). In addition to fewer hospitalizations being reported with nirmatrelvir/r (n=8 [0.8%]) vs PBO (n=65 [6.2%]), pts receiving nirmatrelvir/ r had fewer hospitalized d (Table 2), with mean durations of 9.6 (range, 5.0, 16.0) d with nirmatrelvir/r and 11.2 (range, 2.0, 57.0) d with PBO in hospitalized pts. No pts in the nirmatrelvir/r group and 9 pts (0.9%) in PBO group were admitted to the ICU. No pts in the nirmatrelvir/r group received mechanical ventilation vs 3 pts in the PBO group. Fewer other COVID-19-related nonhospital medical visits were reported with nirmatrelvir/r vs PBO (Table 3). In the full analysis set, fewer pts required oxygen therapy for COVID-19 with nirmatrelvir/r (n=9/1120 [0.8%]) vs PBO (n=54/1126 [4.8%]). Conclusion. High-risk adults with symptomatic COVID-19 treated with nirmatrelvir/ r within 5 d of symptom onset had fewer COVID-19-related medical visits and reduced healthcare utilization (no ICU visits, no mechanical ventilation, fewer days in hospital) vs pts receiving PBO. (Table Presented).
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Objective: This study's objective was to know Brazilian university students' social representations regarding the influences on adherence to distancing-social isolation during the new coronavirus pandemic. Methods: The research design of this study was qualitative research, guided by the Theory of Social Representations. The students were selected by convenience by the "snowball" sampling method. The environment for access and invitation to participants consisted of groups on social media. Data were collected through an electronic questionnaire prepared by the authors using the Google Forms platform. For analysis, content analysis was used with the aid of the IraMuTeQ software. Results: Seven hundred and ninety-eight Brazilian university students participated, with a mean age of 23.59 years;71.7% of respondents were female, 28.1% were male, and 0.3% were intersex. As a result, four classes were obtained, organized into two categories, entitled "Reproducing the voice of science: Scientific knowledge as a determinant of conduct" and "Life at home: Risk and fear in everyday life". Conclusions: It appears that the participants structure their representations based on scientific recommendations and assume the position of reproducing the hegemonic discourse on distancing/social isolation;however, the symbolic elaboration process is marked by the fear of infecting close people and the desire to protect them.
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The combination of class imbalance and overlap is currently one of the most challenging issues in machine learning. While seminal work focused on establishing class overlap as a complicating factor for classification tasks in imbalanced domains, ongoing research mostly concerns the study of their synergy over real-word applications. However, given the lack of a well-formulated definition and measurement of class overlap in real-world domains, especially in the presence of class imbalance, the research community has not yet reached a consensus on the characterisation of both problems. This naturally complicates the evaluation of existing approaches to address these issues simultaneously and prevents future research from moving towards the devise of specialised solutions. In this work, we advocate for a unified view of the problem of class overlap in imbalanced domains. Acknowledging class overlap as the overarching problem - since it has proven to be more harmful for classification tasks than class imbalance - we start by discussing the key concepts associated to its definition, identification, and measurement in real-world domains, while advocating for a characterisation of the problem that attends to multiple sources of complexity. We then provide an overview of existing data complexity measures and establish the link to what specific types of class overlap problems these measures cover, proposing a novel taxonomy of class overlap complexity measures. Additionally, we characterise the relationship between measures, the insights they provide, and discuss to what extent they account for class imbalance. Finally, we systematise the current body of knowledge on the topic across several branches of Machine Learning (Data Analysis, Data Preprocessing, Algorithm Design, and Meta-learning), identifying existing limitations and discussing possible lines for future research.
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In this contribution, we explore the plausibility and consequences of treating arguments over what counts as a COVID-19 death as metalinguistic arguments. While unquestionably related to the epidemiological and public health issues, these arguments are also arguments about how a term should be used. As such, they touch upon some of the foundational issues in meta-semantics, discussed in the recent literature on metalinguistic negotiations, conceptual ethics, and conceptual engineering. Against this background, we study official statements (of WHO, governments) and media reports to critically reconstruct the metalinguistic elements of the dispute over what a COVID-19 death is. We analyze in particular how epistemic and practical reasons are intertwined in nuanced and complex ways to produce an interesting type of metalinguistic interventions. © 2022, The Author(s).
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Objective: Coronavirus disease 2019 (COVID-19) pandemic may have indirect consequences in ST-segment elevation myocardial infarction (STEMI) outcomes due to difficulties in healthcare access, but also due to reperfusion delays. The objective of this study was to evaluate the performance indicators in STEMI during the early phase of the lockdown following the COVID-19 pandemic. Methods: The patient delay and the system delay were evaluated in 312 patients with suspected STEMI, in the period of the first State of Emergency in Portugal, through a survey called Moment COVID implemented within 18th March to 2 May 2020, in 18 national centers of Interventional Cardiology where PPCI is carried out 24/7. These patients were compared with a historical cohort of 267 patients from the 5th year after integration of SFL Initiative in Portugal (Moment 2015) in which the same survey was applied. Patients with late presentation of STEMI (>12 hours of symptoms onset) were excluded from this analysis. Results: In Moment COVID there was a trend towards a longer patient delay (incremental median 20 min;p=0.059) and a significant longer system-delay (incremental median 17 min;p=0.033) compared to the historical cohort of Moment 2015. Consequently, times to revascularization tended to be longer (incremental median 26 min;p=0.074). Indeed, in Moment COVID patients were less compliant with the times recommended by the European guidelines: door-to-balloon time <60 min was achieved in 47.6% of patients compared to 57.0% (p=0.052) in Moment 2015 and system-delay <90 min in 13.9% compared to 21.8% (p=0.033). Conclusion: These results from a multicentric national analysis demonstrated a trend to longer time from symptom onset to request healthcare system assistance and a significantly longer time from first medical contact to revascularization among patients with STEMI during COVID-19 pandemic. This delay for treatment could negatively impact the STEMI prognosis at the long-term.
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This study aims to explore the use of force vs. time data obtained from an isometric handgrip test to match a frailty state based on the TFI score. BodyGrip, a novel prototype system, is used for handgrip strength over 10 s time interval tests. A cross-sectional study with a non-probabilistic sample of community-dwelling elderly women was conducted. The force/time data collected from the dominant handgrip strength test, together with the Tilburg Frailty Indicator (TFI) test results, were used to train artificial neural networks. Different models were tested, and the frailty matching of TFI scores reached a minimum accuracy of 75%. Despite the small sample size, the BodyGrip system appears to be a promising tool for exploring new frailty-related features. The adopted strategy foresees ultimately configuring the system to be used as an expedite mode for identifying individuals at risk, allowing an easy, quick, and frequent person-centered care approach. Additionally, it is suitable for following up of the elderly in particular, and it may assume a relevant role in the mitigation of the increase in frailty evolution during and after the imposed isolation of the COVID-19 pandemic. Further use of the system will improve the robustness of the artificial neural network algorithm.
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The COVID-19 pandemic imposes a whole new way for cities to deal with crises. More than ever, in order to protect the citizens, cities need to rely on data to address such a public health emergency. In this sense, the Urban Control and Command Centers (CCCs) are an important governance organism to help the monitoring and the management of the complex dynamic of contemporary cities. These centralized and integrated management structures in the form of a governmental agency can aid the decision makers into a more coordinated, systemic, strategic, and data-driven intervention. In Rio de Janeiro's case, the city Urban CCC-called Rio de Janeiro Operations Center (COR in the Portuguese abbreviation)-is mostly designed to monitor the daily routine of the different systems and infrastructures that compose the city's dynamic, to plan and integrate operations for big events like Rio 2016 Olympic Games and to manage emergency situations. With the monitoring center, Rio is able to identify abnormalities and make sure that any interference in the city can be resolved in a timely manner, in order to ensure that the city comes back to normal in the face of a disruption and runs as smoothly as possible. Regarding the context of the pandemic of the COVID-19, Urban CCCs can also be an important tool to manage health emergencies. In this paper, the case of the COR is presented, showing how this Brazilian city is using its Urban CCC to monitor and assist the authorities with real time data intelligence to respond to this unprecedented emergency. © 2020 IEEE.
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INTRODUCTION: Health planning is required for the control and prevention of severe cases of COVID-19 in children. METHODS: Spatial analysis of severe COVID-19 cases in children of Pernambuco in the first six months of the pandemic and its autocorrelation with the Human Development Index was conducted. RESULTS: A total of 551 severe cases (39.4 cases/100,000 inhabitants) was initially concentrated in the metropolitan area, with later interiorization. The spatial autocorrelation of cases was identified. The bivariate analysis revealed alert regions in less developed municipalities (I=0.341;p=0.001). CONCLUSIONS: Considering the local particularities can assist in directing the priorities for decision making.