COVID-19 Literature Mining and Analysis Research

By 2019 COVID-19, since the epidemic, the number of relevant documents exponentially level rise. Faced with a large amount of literature, this research provides convenience for exploring the connection between research topics and fields and quickly understanding relevant literature information. We pass on the data set after data cleansing using the LDA(Latent Dirichlet allocation) methods, and Berts and K-means modeling method extracting topic keywords. Use knowledge graph tools to output relevant visual graphics and systematically extract adequate information. Through text mining of biomedical research papers related to COVID-19, the improved model is used to analyze and make recommendations to respond to and prevent the COVID-19 pandemic. This research can support the rapid and in-depth analysis of a large number of relevant documents and can be used in future research to support real-time scientific disease research.

A class of anomalous diffusion epidemic models based on CTRW and distributed delay

In recent years, the epidemic model with anomalous diffusion has gained popularity in the literature. However, when introducing anomalous diffusion into epidemic models, they frequently lack physical explanation, in contrast to the traditional reaction-diffusion epidemic models. The point of this paper is to guarantee that anomalous diffusion systems on infectious disease spreading remain physically reasonable. Specifically, based on the continuous-time random walk (CTRW), starting from two stochastic processes of the waiting time and the step length, time-fractional space-fractional diffusion, time-fractional reaction-diffusion and fractional-order diffusion can all be naturally introduced into the SIR (S: susceptible, I: infectious and R: recovered) epidemic models, respectively. The three models mentioned above can also be applied to create SIR epidemic models with generalized distributed time delays. Distributed time delay systems can also be reduced to existing models, such as the standard SIR model, the fractional infectivity model and others, within the proper bounds. Meanwhile, as an application of the above stochastic modeling method, the physical meaning of anomalous diffusion is also considered by taking the SEIR (E: exposed) epidemic model as an example. Similar methods can be used to build other types of epidemic models, including SIVRS (V: vaccine), SIQRS (Q: quarantined) and others. Finally, this paper describes the transmission of infectious disease in space using the real data of COVID-19.

Influencing factors of COVID-19 epidemic on the utilization of Human immunodeficiency virus testing among men who have sex with men

Objective To analyze the utilization of HIV testing services and related influencing factors among men who have sex with men (MSM) on COVID-19. Methods From September to November 2020, an electronic questionnaire survey was conducted on MSM in the AIDS Vct of Longhua CDC and the Third People's Hospital of Shenzhen, The rank sum test was used to compare the changes in the utilization of HIV testing services in different situations of various factors, and ordinal multinomial logistic regression model was established to analyze the influencing factors of the utilization of HIV testing services. Results A total of 30.4% MSM were reported reduction in the use of HIV testing services. Logistic regression analysis showed that highly panic of COVID-19 reducing the frequency of anal sex (OR=0.056, 95% CI: 0.021-0.150, P < 0.001), being advised not going to testing agency (OR=0.538, 95% CI: 0.297-0.975, P=0.041), and being infected of COVID-19 (OR=21.979, 95% CI: 4.369-110.559, P < 0.001) had higher chance of reduction in the used of HIV testing services. Conclusion The HIV testing service utilization is decreased in MSM during COVID-19. It is necessary to pay more attention to this convenience when formulating and implementing epidemic prevention and control measures.

Design and Implementation of a Novel, Intrinsically Safe Rigid-Flexible Coupling Manipulator for COVID-19 Oropharyngeal Swab Sampling

Driven by the SARS-CoV-2 pandemic, demand for oropharyngeal swab sampling (OP-swabs) is surging. However, medical staff can easily become infected by the virus during the sampling process. In an effort to combat this, we developed a novel, intrinsically safe rigid-flexible coupling (RFC) manipulator to improve the safety and reliability of OP-swab sampling to test for COVID-19, which is presented herein. Suitable sampling areas and the necessary contact force for OP-swab sampling tasks are carefully investigated, and three typical sampling paths outlined that could be performed by a robotic system. This is followed by a detailed description of an intrinsically safe bionic micro-pneumatic actuator (MPA) that was designed and fabricated as the main component of the RFC manipulator. The developed RFC manipulator's kinematic modeling, motion planning, and force control capacities were designed for OP-swab sampling scenarios. The system was then validated using both an oral cavity phantom and human volunteers, with comparative experiments on the swab quality of the OP-swab sampling approach conducted in both robotic and manual modes. The results indicate that fully-automated sampling based on this design would be feasible.

A VR-based Training and Intelligent Assessment System Integrated with Multi-modal Sensing for Children with Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) exhibits social communication and social interaction disorders, and abnormal restrictive and repetitive behaviors. However, symptoms of infants less than 1-year-old are difficult to reliably predict subsequent diagnosis. Patients with mild ASD may not be discovered until school age, because schools have more opportunities for social activities. In addition, the therapist also needs to consider the labor cost. To provide effective treatment, it also needs to consume more resources. The current situation in Taiwan is that outlying islands and remote areas often have insufficient manpower for therapists. If VR technology can be applied, some of the problems may be solved. However, due to the global pandemic, COVID-19, early treatments or group treatments in many countries have been forced to stop. If VR technology can provide interpersonal interaction scenes, the training of ASD children can hardly be affected.This research uses Virtual Reality (VR) technology, combined with wearable multi-model sensing technology, including EEG, eye tracking, heart rate variability (HRV), and breath-sensing strap. Physiological signals and game performance data are collected while users are training, and integrate multiple evaluation scales such as ADOS, SRS, and CBCL. Statistical analysis of these data is performed to classify them through machine learning models to develop a VR assistance system that can be used to evaluate the diagnosis, severity, and social behavior treatment of ASD. This system presents assessment and therapy in a game-oriented way. In addition to enhancing the incentives for users to participate, it provides better training results than traditional training. It is also an effective and convenient tool for the therapist to use during evaluation and training. © 2021 IEEE.

[National external quality assessment for molecular detection of severe acute respiratory syndrome coronavirus 2 Delta variant].

Objective: To clarify the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta variant on the performance of existing molecular diagnostic assays, and investigate the detection ability of clinical laboratories across China. Methods: The first nationwide external quality assessment (EQA) for molecular detection of Delta variant was carried out based on the non-infectious phage virus-like particles samples, which were prepared by genetic engineering methods and distributed to 8 488 laboratories nationwide. The EQA panel was composed of three Delta variant samples (7.5×102, 1.5×103 and 6.0×103 copies/ml), one non-variant weak positive sample and one negative sample. The percentage of agreement (PA) of Delta variant samples with different concentration, the PA of Delta variant and non-variant samples with 7.5×102 copies/ml, the PA of assays used by more than 100 laboratories for Delta variant samples with different concentration and the PA of Delta variant and non-variant samples with 7.5×102 copies/ml were calculated and analyzed. Results: The data from 8 127 laboratories were available for evaluation. The testing capability of 98.77% (8 027/8 127) of the participating laboratories was found to be competent in reporting correct results for all samples. The overall percentage of agreement (OPA), negative percentage of agreement (NPA) and positive percentage of agreement (PPA) of the samples were 99.64% (40 490/40 635), 99.73% (8 105/8 127), 99.62% (32 385/32 508), respectively. With the decrease of the concentration of the samples, the PPA of Delta variant samples decreased. The PPAs were 99.41% and 99.51% for Delta variant and non-variant samples with 7.5×102 copies/ml, respectively, with no statistical difference (P=0.392). The OPA, NPA and PPA of the assays used by more than 100 laboratories were all greater than 98%, and no statistical difference of the PPAs was identified between Delta variant and non-variant samples with 7.5×102 copies/ml (P>0.05). Conclusions: Delta variant fails to impair the performance of current molecular diagnostic assays in China. The clinical laboratories have the same detection capabilities for Delta variant and non-variant samples. However, in certain laboratories, further improvement is required to ensure the accurate detection of weak positive samples.