DeepTrace: Learning to Optimize Contact Tracing in Epidemic Networks with Graph Neural Networks

The goal of digital contact tracing is to diminish the spread of an epidemic or pandemic by detecting and mitigating public health emergencies using digital technologies. Since the start of the COVID-$19$ pandemic, a wide variety of mobile digital apps have been deployed to identify people exposed to the SARS-CoV-2 coronavirus and to stop onward transmission. Tracing sources of spreading (i.e., backward contact tracing), as has been used in Japan and Australia, has proven crucial as going backwards can pick up infections that might otherwise be missed at superspreading events. How should robust backward contact tracing automated by mobile computing and network analytics be designed? In this paper, we formulate the forward and backward contact tracing problem for epidemic source inference as maximum-likelihood (ML) estimation subject to subgraph sampling. Besides its restricted case (inspired by the seminal work of Zaman and Shah in 2011) when the full infection topology is known, the general problem is more challenging due to its sheer combinatorial complexity, problem scale and the fact that the full infection topology is rarely accurately known. We propose a Graph Neural Network (GNN) framework, named DeepTrace, to compute the ML estimator by leveraging the likelihood structure to configure the training set with topological features of smaller epidemic networks as training sets. We demonstrate that the performance of our GNN approach improves over prior heuristics in the literature and serves as a basis to design robust contact tracing analytics to combat pandemics

Energy expenditure of type-specific sedentary behaviors estimated using sensewear mini armband: a metabolic chamber validation study among adolescents

SenseWear Mini Armband, an accelerometer with multiple physiological sensors, could be a practical means to estimate energy expenditure (EE) of children and adolescents, but its validity reported for these age groups has not been consistent within the literature. EE of twenty-six healthy Chinese 12-year-old adolescents was measured simultaneously using both SenseWear Mini Armband (SWMA) and metabolic chamber (MC) during a 16-hour stay in a MC. SWMA systematically underestimated the adolescents’ EE during sedentary behaviors, resting metabolic rate (RMR), basal metabolic rate (BMR), and total EE, with the absolute error rate ranging from 14.85% to 28.65%. The SWMA significantly underestimated EE compared with MC in Chinese adolescents. However, the amount of error can be reduced by applying correction equation proposed in this study

LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity

Heterophily has been considered as an issue that hurts the performance of Graph Neural Networks (GNNs). To address this issue, some existing work uses a graph-level weighted fusion of the information of multi-hop neighbors to include more nodes with homophily. However, the heterophily might differ among nodes, which requires to consider the local topology. Motivated by it, we propose to use the local similarity (LocalSim) to learn node-level weighted fusion, which can also serve as a plug-and-play module. For better fusion, we propose a novel and efficient Initial Residual Difference Connection (IRDC) to extract more informative multi-hop information. Moreover, we provide theoretical analysis on the effectiveness of LocalSim representing node homophily on synthetic graphs. Extensive evaluations over real benchmark datasets show that our proposed method, namely Local Similarity Graph Neural Network (LSGNN), can offer comparable or superior state-of-the-art performance on both homophilic and heterophilic graphs. Meanwhile, the plug-and-play model can significantly boost the performance of existing GNNs. Our code is provided at https://github.com/draym28/LSGNN.Comment: The first two authors contributed equally to this work; IJCAI2

An Ontology-Based Semantic Similarity Measure Considering Multi-Inheritance in Biomedicine

Computation of semantic similarity between words for text understanding is a vital issue in many applications such as word sense disambiguation, document categorization, and information retrieval. In recent years, different paradigms have been proposed to compute semantic similarity based on different ontologies and knowledge resources. In this paper, we propose a new similarity measure combining both superconcepts of the evaluated concepts and their common specificity feature. The common specificity feature considers the depth of the Least Common Subsumer (LCS) of two concepts and the depth of the ontology to obtain more semantic evidence. The multiple inheritance phenomenon in a large and complex taxonomy is taken into account by all superconcepts of the evaluated concepts. We evaluate and compare the correlation obtained by our measure with human scores against other existing measures exploiting SNOMED CT as the input ontology. The experimental evaluations show the applicability of the measure on different datasets and confirm the efficiency and simplicity of our proposed measure

Use of non-steroidal anti-inflammatory drugs and adverse outcomes during the COVID-19 pandemic: A systematic review and meta-analysis.

Background There are concerns that the use of non-steroidal anti-inflammatory drugs (NSAIDs) may increase the risk of adverse outcomes among patients with coronavirus COVID-19. This study aimed to synthesize the evidence on associations between the use of NSAIDs and adverse outcomes. Methods A systematic search of WHO COVID-19 Database, Medline, the Cochrane Library, Web of Science, Embase, China Biology Medicine disc, China National Knowledge Infrastructure, and Wanfang Database for all articles published from January 1, 2020, to November 7, 2021, as well as a supplementary search of Google Scholar. We included all comparative studies that enrolled patients who took NSAIDs during the COVID-19 pandemic. Data extraction and quality assessment of methodology of included studies were completed by two reviewers independently. We conducted a meta-analysis on the main adverse outcomes, as well as selected subgroup analyses stratified by the type of NSAID and population (both positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or not). Findings Forty comparative studies evaluating 4,867,795 adult cases were identified. Twenty-eight (70%) of the included studies enrolled patients positive to SARS-CoV-2 tests. The use of NSAIDs did not reduce mortality outcomes among people with COVID-19 (number of studies [N] = 29, odds ratio [OR] = 0.93, 95% confidence interval [CI]: 0.75 to 1.14, I2  = 89%). Results suggested that the use of NSAIDs was not significantly associated with higher risk of SARS-CoV-2 infection in patients with or without COVID-19 (N = 10, OR = 0.96, 95% CI: 0.86 to 1.07, I2  = 78%; N = 8, aOR = 1.01, 95% CI: 0.94 to 1.09, I2  = 26%), or an increased probability of intensive care unit (ICU) admission (N = 12, OR = 1.28, 95% CI: 0.94 to 1.75, I2  = 82% ; N = 4, aOR = 0.89, 95% CI: 0.65 to 1.22, I2  = 60%), requiring mechanical ventilation (N = 11, OR = 1.11, 95% CI: 0.79 to 1.54, I2  = 63%; N = 5, aOR = 0.80, 95% CI: 0.52 to 1.24, I2  = 66%), or administration of supplemental oxygen (N = 5, OR = 0.80, 95% CI: 0.52 to 1.24, I2  = 63%; N = 2, aOR = 1.00, 95% CI: 0.89 to 1.12, I2  = 0%). The subgroup analysis revealed that, compared with patients not using any NSAIDs, the use of ibuprofen (N = 5, OR = 1.09, 95% CI: 0.50 to 2.39; N = 4, aOR = 0.95, 95% CI: 0.78 to 1.16) and COX-2 inhibitor (N = 4, OR = 0.62, 95% CI: 0.35 to 1.11; N = 2, aOR = 0.73, 95% CI: 0.45 to 1.18) were not associated with an increased risk of death. Interpretation Data suggests that NSAIDs such as ibuprofen, aspirin and COX-2 inhibitor, can be used safely among patients positive to SARS-CoV-2. However, for some of the analyses the number of studies were limited and the quality of evidence was overall low, therefore more research is needed to corroborate these findings. Funding There was no funding source for this study

γδ T Cells Provide Protective Function in Highly Pathogenic Avian H5N1 Influenza A Virus Infection

Given the high mortality rate (>50%) and potential danger of intrapersonal transmission, highly pathogenic avian influenza (HPAI) H5N1 epidemics still pose a significant threat to humans. γδ T cells, which participate on the front line of the host immune defense, demonstrate both innate, and adaptive characteristics in their immune response and have potent antiviral activity against various viruses. However, the roles of γδ T cells in HPAI H5N1 viral infection remain unclear. In this study, we found that γδ T cells provided a crucial protective function in the defense against HPAI H5N1 viral infection. HPAI H5N1 viruses could directly activate γδ T cells, leading to enhanced CD69 expression and IFN-γ secretion. Importantly, we found that the trimer but not the monomer of HPAI H5N1 virus hemagglutinin (HA) proteins could directly activate γδ T cells. HA-induced γδ T cell activation was dependent on both sialic acid receptors and HA glycosylation, and this activation could be inhibited by the phosphatase calcineurin inhibitor cyclosporin A but not by the phosphatidylinositol 3-kinase (PI3-K) inhibitors wortmannin and LY294002. Our findings provide a further understanding the mechanism underlying γδ T cell-mediated innate and adoptive immune responses against HPAI H5N1 viral infection, which helps to develop novel therapeutic strategies for the treatment of H5N1 infection in the future

Analysis of COVID-19 Guideline Quality and Change of Recommendations: A Systematic Review.

Background Hundreds of coronavirus disease 2019 (COVID-19) clinical practice guidelines (CPGs) and expert consensus statements have been developed and published since the outbreak of the epidemic. However, these CPGs are of widely variable quality. So, this review is aimed at systematically evaluating the methodological and reporting qualities of COVID-19 CPGs, exploring factors that may influence their quality, and analyzing the change of recommendations in CPGs with evidence published. Methods We searched five electronic databases and five websites from 1 January to 31 December 2020 to retrieve all COVID-19 CPGs. The assessment of the methodological and reporting qualities of CPGs was performed using the AGREE II instrument and RIGHT checklist. Recommendations and evidence used to make recommendations in the CPGs regarding some treatments for COVID-19 (remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir) were also systematically assessed. And the statistical inference was performed to identify factors associated with the quality of CPGs. Results We included a total of 92 COVID-19 CPGs developed by 19 countries. Overall, the RIGHT checklist reporting rate of COVID-19 CPGs was 33.0%, and the AGREE II domain score was 30.4%. The overall methodological and reporting qualities of COVID-19 CPGs gradually improved during the year 2020. Factors associated with high methodological and reporting qualities included the evidence-based development process, management of conflicts of interest, and use of established rating systems to assess the quality of evidence and strength of recommendations. The recommendations of only seven (7.6%) CPGs were informed by a systematic review of evidence, and these seven CPGs have relatively high methodological and reporting qualities, in which six of them fully meet the Institute of Medicine (IOM) criteria of guidelines. Besides, a rapid advice CPG developed by the World Health Organization (WHO) of the seven CPGs got the highest overall scores in methodological (72.8%) and reporting qualities (83.8%). Many CPGs covered the same clinical questions (it refers to the clinical questions on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir in COVID-19 patients) and were published by different countries or organizations. Although randomized controlled trials and systematic reviews on the effectiveness of treatments of remdesivir, glucocorticoids, hydroxychloroquine/chloroquine, interferon, and lopinavir-ritonavir for patients with COVID-19 have been published, the recommendations on those treatments still varied greatly across COVID-19 CPGs published in different countries or regions, which may suggest that the CPGs do not make sufficient use of the latest evidence. Conclusions Both the methodological and reporting qualities of COVID-19 CPGs increased over time, but there is still room for further improvement. The lack of effective use of available evidence and management of conflicts of interest were the main reasons for the low quality of the CPGs. The use of formal rating systems for the quality of evidence and strength of recommendations may help to improve the quality of CPGs in the context of the COVID-19 pandemic. During the pandemic, we suggest developing a living guideline of which recommendations are supported by a systematic review for it can facilitate the timely translation of the latest research findings to clinical practice. We also suggest that CPG developers should register the guidelines in a registration platform at the beginning for it can reduce duplication development of guidelines on the same clinical question, increase the transparency of the development process, and promote cooperation among guideline developers all over the world. Since the International Practice Guideline Registry Platform has been created, developers could register guidelines prospectively and internationally on this platform

Methodology and experiences of rapid advice guideline development for children with COVID-19: responding to the COVID-19 outbreak quickly and efficiently

BACKGROUND: Rapid Advice Guidelines (RAG) provide decision makers with guidance to respond to public health emergencies by developing evidence-based recommendations in a short period of time with a scientific and standardized approach. However, the experience from the development process of a RAG has so far not been systematically summarized. Therefore, our working group will take the experience of the development of the RAG for children with COVID-19 as an example to systematically explore the methodology, advantages, and challenges in the development of the RAG. We shall propose suggestions and reflections for future research, in order to provide a more detailed reference for future development of RAGs. RESULT: The development of the RAG by a group of 67 researchers from 11 countries took 50 days from the official commencement of the work (January 28, 2020) to submission (March 17, 2020). A total of 21 meetings were held with a total duration of 48 h (average 2.3 h per meeting) and an average of 16.5 participants attending. Only two of the ten recommendations were fully supported by direct evidence for COVID-19, three recommendations were supported by indirect evidence only, and the proportion of COVID-19 studies among the body of evidence in the remaining five recommendations ranged between 10 and 83%. Six of the ten recommendations used COVID-19 preprints as evidence support, and up to 50% of the studies with direct evidence on COVID-19 were preprints. CONCLUSIONS: In order to respond to public health emergencies, the development of RAG also requires a clear and transparent formulation process, usually using a large amount of indirect and non-peer-reviewed evidence to support the formation of recommendations. Strict following of the WHO RAG handbook does not only enhance the transparency and clarity of the guideline, but also can speed up the guideline development process, thereby saving time and labor costs

Methodology and experiences of rapid advice guideline development for children with COVID-19: responding to the COVID-19 outbreak quickly and efficiently.

BACKGROUND Rapid Advice Guidelines (RAG) provide decision makers with guidance to respond to public health emergencies by developing evidence-based recommendations in a short period of time with a scientific and standardized approach. However, the experience from the development process of a RAG has so far not been systematically summarized. Therefore, our working group will take the experience of the development of the RAG for children with COVID-19 as an example to systematically explore the methodology, advantages, and challenges in the development of the RAG. We shall propose suggestions and reflections for future research, in order to provide a more detailed reference for future development of RAGs. RESULT The development of the RAG by a group of 67 researchers from 11 countries took 50 days from the official commencement of the work (January 28, 2020) to submission (March 17, 2020). A total of 21 meetings were held with a total duration of 48 h (average 2.3 h per meeting) and an average of 16.5 participants attending. Only two of the ten recommendations were fully supported by direct evidence for COVID-19, three recommendations were supported by indirect evidence only, and the proportion of COVID-19 studies among the body of evidence in the remaining five recommendations ranged between 10 and 83%. Six of the ten recommendations used COVID-19 preprints as evidence support, and up to 50% of the studies with direct evidence on COVID-19 were preprints. CONCLUSIONS In order to respond to public health emergencies, the development of RAG also requires a clear and transparent formulation process, usually using a large amount of indirect and non-peer-reviewed evidence to support the formation of recommendations. Strict following of the WHO RAG handbook does not only enhance the transparency and clarity of the guideline, but also can speed up the guideline development process, thereby saving time and labor costs

Maritime security : container security shipping and trade current issues (container port security - Singapore)

Singapore has been holding the position as the leading transhipment hub of Asia for many years and recently the development of the new Tuas mega port is in the works. This calls for a need to evaluate the security landscape of the container port in order to adequately protect this ever growing critical infrastructure of Singapore. Thus, the aim of this research paper was to determine the top security threat posed to the container transport chain in the context of Singapore, specifically at the container port. It was achieved through the use of risk assessment matrix, which considered the ratings of both the likelihood of occurrence and the severity of consequences of the security threats that were identified in the literature review section. The ratings were attained through conducting surveys with relevant port industry players and maritime security personnel. The results revealed the ranking according to the risk value of the security threats, where a cybersecurity threat emerged as top. Subsequently, the paper also sought to evaluate the current measures put in place to tackle the identified threat category along with further recommendations focusing on future measures, such as working on the human factor and leveraging on new technology to strengthen container port security.Bachelor of Science (Maritime Studies