ABSTRACT
Simplicial neural networks (SNN) have recently emerged as the newest direction in graph learning which expands the idea of convolutional architectures from node space to simplicial complexes on graphs. Instead of pre-dominantly assessing pairwise relations among nodes as in the current practice, simplicial complexes allow us to describe higher-order interactions and multi-node graph structures. By building upon connection between the convolution operation and the new block Hodge-Laplacian, we propose the first SNN for link prediction. Our new Block Simplicial Complex Neural Networks (BScNets) model generalizes the existing graph convolutional network (GCN) frameworks by systematically incorporating salient interactions among multiple higher-order graph structures of different dimensions. We discuss theoretical foundations behind BScNets and illustrate its utility for link prediction on eight real-world and synthetic datasets. Our experiments indicate that BScNets outperforms the state-of-the-art models by a significant margin while maintaining low computation costs. Finally, we show utility of BScNets as the new promising alternative for tracking spread of infectious diseases such as COVID-19 and measuring the effectiveness of the healthcare risk mitigation strategies.
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Irrespective of the success of the deep learning-based mixed-domain transfer learning approach for solving various Natural Language Processing tasks, it does not lend a generalizable solution for detecting misinformation from COVID-19 social media data. Due to the inherent complexity of this type of data, caused by its dynamic (context evolves rapidly), nuanced (misinformation types are often ambiguous), and diverse (skewed, fine-grained, and overlapping categories) nature, it is imperative for an effective model to capture both the local and global context of the target domain By conducting a systematic investigation, we show that: (i) the deep Transformer-based pre-trained models, utilized via the mixed-domain transfer learning, are only good at capturing the local context, thus exhibits poor generalization, and (ii) a combination of shallow network-based domain-specific models and convolutional neural networks can efficiently extract local as well as global context directly from the target data in a hierarchical fashion, enabling it to offer a more generalizable solution.
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Aim: To discuss and share experiences in implementing Family centered care (FCC) models in Hong Kong - Shenzhen Hospital (HKU-SZH). Met hods: At present, FCC has not been wel l implemented in China and most NICU adopt closed management. Since December 2013, our department has introduced the FCC concept and implemented 24-hour opening ward, providing family members with a series of services including ward rounds, progressive health education, palliative care, breast-feeding, cold chain support of breast milk, breast milk bank, family visit, followup after discharge, and mutual support group for family members. The above services were maintained during the COVID-19 period. Results: 10,615 newborns were treated from December 2013 to December 2020, the minimum gestational age of preterm infants treated successfully was 22+6 weeks and the minimum weight was 500g. The patient satisfaction rate in 2020 was 99.9%, and the average breastfeeding rate in 2020 was 84% while 83.4% of full-term infants and 90.2% of premature infants were breast-fed. (A multi-center survey of 974 cases of nutrition-related status of preterm infants in NICU in China reported that 13.6% of preterm infants were breast-fed during 2005-2006) The nosocomial infection rate from 2014 to 2020 was controlled between 0.41% and 2.02%. Literature showed that the incidence rate of nosocomial infection in neonatal care units of 17 grade A general hospitals in China from 2013 to 2014 was 3.35%. Conclusion: An open NICU based on the FCC concept is feasible and contributes to increased breastfeeding rates and patient satisfaction without increasing the incidence of nosocomial infections.
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Infectious diseases are caused by pathogenic microorganisms, such as bacteria, viruses, parasites or fungi, which can be spread, directly or indirectly, from one person to another. Infectious diseases pose a serious threat to human health, especially COVID-19 that has became a serious worldwide health concern since the end of 2019. Contact tracing is the process of identifying, assessing, and managing people who have been exposed to a disease to prevent its onward transmission. Contact tracing can help us better understand the transmission link of the virus, whereby better interrupting its transmission. Given the worldwide pandemic of COVID-19, contact tracing has become one of the most critical measures to effectively curb the spread of the virus. This paper presents a comprehensive survey on contact tracing, with a detailed coverage of the recent advancements the models, digital technologies, protocols and issues involved in contact tracing. The current challenges as well as future directions of contact tracing technologies are also presented.
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An epidemiological investigation was carried out on a local cluster of outbreak caused by imported cases of Coronavirus Disease 2019 (COVID-19) in rural areas of Chengdu in December 2020, to find out the source of infection and the chain of transmission. According to Prevention and Control Protocol for COVID-19 (Version 7), field epidemiological investigation was adopted, combined with big data technology, video image investigation, gene sequencing and other methods to carry out investigation into COVID-19 cases and infections source tracing, analyze the epidemiological association, and map the chain of transmission. From December 7 to 17, 2020, 13 local COVID-19 confirmed cases and 1 asymptomatic case were diagnosed in Chengdu, of which 12 cases (85.71%) had a history of residence and activity in the village courtyard of Taiping (TP), Pidu (P) District, Chengdu. From November 8, 2020 to November 28, 2020, a group of inbound people form Nepal were transferred to the designated entry personnel quarantine hotel of P District which was adjacent to the TP village. During quarantine, there were 5 cases who tested positive for COVID-19. Through gene sequencing alignment, genes of local cases and Nepalese imported cases from the same period are homologous, all belong to the lineage of L2.2.3 (B.1.36 according to Pangolin lineage typing method). According to the results of field epidemiological investigation and gene sequencing analysis, the index case was most likely infected by contact with household waste of quarantine site. Under the situation of normalization prevention and control of COVID-19, sentinel monitoring of fever clinics in primary medical institutions is the key to early detection of the epidemic. The multi-department joint epidemiological investigation and the application of gene technology are the core links of the investigation and traceability of modern infectious diseases. The allocation of public health resources in rural areas needs to be strengthened. We need to improve the capacity for early surveillance and early warning of the epidemic in rural areas.
Subject(s)
COVID-19 , Epidemics , Disease Outbreaks , Humans , Quarantine , SARS-CoV-2ABSTRACT
Massive and rapid testing is crucial for containing the spread of COVID-19. Health and policy planners must ensure that access to and uptake of SARS-CoV-2 testing is adequate and equitable. This study measures the spatial accessibility to testing sites in Florida at the census tract level at the end of May 2020, using the 2-step floating catchment area method that integrates both driving and walking modes. Accessibility scores were found to be heterogeneous across geographic regions and among different groups of people. In particular, many rural areas were in a testing desert. While people in larger cities tended to have better accessibility to testing, many did not have adequate accessibility at that time due to both capacity limitations and spatial factors. In particular, people without access to private vehicles and the elderly faced disadvantages in accessibility to testing sites even in urban areas. However, Black and low-income groups were disproportionally concentrated in neighbourhoods with above-average accessibility due to their closer proximity to testing sites. These results suggest that increased efforts are needed to reach vulnerable populations, including the elderly and those without private vehicles.
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Background: The outbreak of COVID-19 caused by SARS-CoV-2 has been a pandemic. The objective of our study was to explore the association between sex and clinical outcomes in patients with COVID-19. Methods: Detailed clinical data including clinical characteristics, laboratory tests, imaging features and treat-ments of 1190 cases of adult patients with confirmed COVID-19 were retrospectively analyzed. Associations between sex and clinical outcomes were identified by multivariable Cox regression analysis. Results: There were 635 (53.4%) male and 555 (46.6%) female patients in this study. Higher rates of acute kidney injury (5.5% vs. 2.9%, p = 0.026), acute cardiac injury (9.1% vs. 4.3%, p = 0.001), and disseminated intravascular coagulation (2.5% vs. 0.7%, P = 0.024) were observed in males. Compared with female patients, male patients with COVID-19 had a higher inhospital mortality rate (15.7% vs. 10.3%, p = 0.005). However, Cox regression analysis showed that sex did not influence inhospital mortality of COVID-19 patients. Conclusions: Male sex was associated with a worse prognosis of COVID-19, but it seems not to be an independent prognostic factor.
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OBJECTIVE: This study aims to survey medical staff's acceptance of online Mindfulness-Based Stress Reduction (MBSR) during the Novel Coronavirus Pneumonia (NCP), and to know some information of physical and emotional response of those medical staff who worked at the forefront of COVID-19, through the playback amount of the online MBSR training. MATERIALS AND METHODS: Considering the working environment of medical staff in forefront of NCP, we designed and recorded MBSR audio album including 13 sessions, covering 24 hours of a day, then sent the album to medical staff who had been working in Wuhan, Hubei province, China. We collected the playback amount in each session on February 10th and February 24th, which were one week and three weeks after the album was finished. RESULTS: On February 10th and February 24th, there were separately 5778 and 10640 times of broadcasting. The highest broadcasting frequency session was at 5:00 am, followed by 7:00 am. The least broadcasting frequency sessions were 17:00 pm and 19:00 pm. The broadcasting amount in the 6 periods of the night (from 21:00 pm to 7:00 am) was significantly higher than those in the daytime (from 9:00 am to 19:00 pm), with a statistical difference. The tendency of the amount of playback was consistent, which was not affected by the specific content of the mindfulness exercises. CONCLUSIONS: Online MBSR exercises were well accepted by medical staff in the COVID-19. It may help them relax and reduce the risk of stress reactions. During the NCP, medical staff may have different degrees of sleep and emotional problems, which need to be paid more attention to.