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1.
China Biotechnology ; JOUR(8):63-73, 42.
Article in Chinese | Scopus | ID: covidwho-2090952

ABSTRACT

The global pandemic of the COVID-19 has had a major impact on the entire human society, and human beings are facing challenges such as fiscal stimulus, financial stress, and debt restructuring. Before the emergence of specific therapeutic drugs and methods, large-scale population screening and isolation has become the most effective method for epidemic management. However, the new strain of coronavirus this time has shown a very high genetic variability, with a statistical mutation rate of more than 2. 3%c as of March 31st, 2022. So far, new highly infectious virus strains have been emerging, and the number of mutant strains officially warned by the World Health Organization has reached 7. Therefore, in the next virus prevention and control and research, we not only need to detect SARS-CoV-2, but also need to explore accurate and practical single nucleotide variation (SNV) genotyping techniques, especially for large-scale population screening. It is not only necessary to obtain information on the SRAS-CoV-2, but also to accurately and quickly distinguish variant strains with higher infectivity and virulence. This paper briefly introduces the infection and mutation mechanism of the virus, and focuses on the classification and review of the existing main SARS-CoV-2 SNV genotyping techniques, hoping to provide insight into the development of new detection technolooies. © 2022, China Biotechnology Press. All rights reserved.

2.
2022 Portland International Conference on Management of Engineering and Technology, PICMET 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2081373

ABSTRACT

In recent years, with the impact of COVID-19 epidemic, Taiwan's food manufacturing industry needs digital transformation. Faced with such a dynamic enterprise environment, the construction of accurate R&D system becomes very important and urgent. By discussing the market analysis methods and the design of research and development process in literatures, this study further used a combination of natural semantic analysis technology and QFD method to build an integrated model, so as to help food processing companies understand the consumer demand and some issues in product research and development in the terminal market. Proof of Concept(POC) showed that, first, the marketing supervisor or R&D supervisor accurately evaluate the consumer needs of online users on the e-commerce platform, successfully develop products that consumers are satisfied with, and strengthen R&D decisions;second, by analyzing the characteristics of consumer demand through machine learning model, aspects of demands that consumers care the most could further help to formulate product improvement strategies with application value, which would be extremely helpful to the methodology research of incremental innovation;and third, an integrated model of market and R&D analysis would effectively assist the food industry to develop products on the spot to be successfully deliver to Amazon platform, in which this methodology could be applied in the entire food manufacturing industry. © 2022 PICMET.

4.
8th International Conference on E-Business and Mobile Commerce, ICEMC 2022 ; : 77-82, 2022.
Article in English | Scopus | ID: covidwho-2053354

ABSTRACT

Whether to take vaccines or not is a controversial topic on Twitter. This paper will focus on the California, USA and find if there is a relationship between people's attitudes toward vaccines on Twitter and the rate of increase in the number of the primary series administrated. The relationship then can be trained as a model to predict the rate of increase in the number of booster shots administrated in the US by performing sentiment analysis on the current Twitter comments regarding the booster shots. NLP techniques will be applied on tweets, and machine learning techniques will be used to find the relationship and make the prediction. © 2022 ACM.

5.
2022 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2022 ; 2022-July:1213-1218, 2022.
Article in English | Scopus | ID: covidwho-2051931

ABSTRACT

With the increasingly serious aging situation, more and more elderly people are physically disabled. In addition, the current rehabilitation resources have the problems of shortage and uneven distribution, coupled with the impact of COVID-19 in early 2019, most patients have been greatly restricted from going to the rehabilitation center for training. To solve these problems, we propose a "Kinect-based 3D Human Motion Acquisition and Evaluation System for Remote Rehabilitation and Exercise"which uses the Kinect3 camera to obtain human motion with an error rate of only 3% when the body is in front of the camera. Then we use Unity to create a humanoid virtual model and interactive scene and synchronize the real body motion to the virtual model with an average error less than 1%. At the same time, our system provides reliable and highly accurate methods for evaluating actions based on angles and trajectories. What's more, users don't need to wear any wearable devices when using the system. It is a mark-less motion acquisition system, which reduces the cost and improves the usability and scalability of the system. And the interactive virtual scenes also increase the training motivation of users. © 2022 IEEE.

6.
Asia-Pacific Journal of Clinical Oncology ; 18:60, 2022.
Article in English | EMBASE | ID: covidwho-2032339

ABSTRACT

Objectives: In order to provide useful reference information for researchers in the field of pharmacology and toxicology, this paper studies the current research hot spots in this field, as well as the correlation closeness between research topics. Methods: This paper studies on the hot papers of pharmacology and toxicology field based on ESI (Essential Scientific Indicators) database, and the time span of the data is from January 1, 2010 to December 31, 2020. The data about these 110 hot papers are analyzed by the authors from the aspects of published time, country/territory, institution, journal, citation, and so on. The methods of multi-dimension analysis, cluster analysis, Vosviewer visualization are used to analyze these papers. Results: The results shows that United States is in the first place in the ranking of published papers, England is in the second place, and China is in the third place. The research hotspots are COVID-19, anxiety, depression, and mental health. Conclusions: The cluster of hot papers show the correlativity of the topic in the pharmacology and toxicology field. This research provides researchers in the field of pharmacology and toxicology with the current international hot research direction, and helps China researchers to improve their research in the field.

7.
10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022 ; 2022-June:1133-1138, 2022.
Article in English | Scopus | ID: covidwho-2018924

ABSTRACT

Catheter tip misalignment can lead to complications in patients together with serious medical malpractice cases. This article aims at the current surge in COVID-19 patients. Using X-ray imaging datasets from COVID-19 patients, previously published on Kaggle as 'RANZCR CLiP - Catheter and Line Position Challenge' and hosted by the Royal Australian and NZ College of Radiologists, a deep-learning algorithm was utilized to detect the position of the patient's catheter and automatically determine whether the catheter tip is misplaced or otherwise. This study employed U-Net to segment and identify catheter position types, together with employing Efficiency net B7 to determine whether the misaligned catheter is misaligned which scores 0.959(AUC). In addition, results were also compared using Efficiency Net B5, ResNet 200D. © 2022 IEEE.

8.
8th International Conference on Information Management, ICIM 2022 ; : 1-5, 2022.
Article in English | Scopus | ID: covidwho-2018847

ABSTRACT

With the advancement of global aging, the imbalance of informatization leads to the digital divide becoming more evident among the elderly. COVID-19 forces various information services to be transferred to the Internet. The elderly cannot fully integrate into Internet life due to physical and psychological factors, thus making it difficult to enjoy the convenient and efficient services brought by the Internet, which may lead to serious social problems. In recent years, the digital divide among the elderly has been widely concerned by researchers, and the related research publications are increasing. However, there is no review literature at present. This study aims to make a comprehensive and systematic bibliometric analysis of the research topics, including a co-word knowledge map and references co-citation network to focus on the knowledge evolution trend related to research directions of the topic. This study is committed to identifying present research foci and frontier trends that are beneficial to subsequent research. © 2022 IEEE.

9.
25th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2021 ; : 739-740, 2021.
Article in English | Scopus | ID: covidwho-2012740

ABSTRACT

As the SARS-CoV-2 virus continues to mutate, global eradication of infections is unlikely, and COVID-19 is predicted to become a seasonal or endemic disease like influenza. Widespread detection of variant strains will be critical to inform policy decisions to mitigate further spread, and post-pandemic multiplexed screening of respiratory viruses will be necessary to properly manage patients presenting with similar respiratory symptoms. We have developed a portable, magnetofluidic platform for multiplexed PCR testing in <30 min. Cartridges were designed for multiplexed detection of SARS-CoV-2 with either distinctive variant mutations or with Influenza A and B and tested with clinical samples. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

10.
Polymer Reviews ; 2022.
Article in English | Scopus | ID: covidwho-1984894

ABSTRACT

Vaccine development is among the critical issues for ceasing the COVID-19 pandemic. This review discusses the current usage of biomaterials in vaccine development and provides brief descriptions of the vaccine types and their working mechanisms. New types of vaccine platforms (next-generation vaccines and DNA- or mRNA-based vaccines) are discussed in detail. The mRNA vaccine encoding the spike protein viral antigen can be produced in a cell-free system, suggesting that mRNA vaccines are safer than “classic vaccines” using live or inactivated virus. The mRNA vaccine efficacy is typically high at approximately 95%. However, most mRNA vaccines need to be maintained at −20 or −70 degrees for storage for long periods (half a year) and their transportation because of mRNA vaccine instability in general, although mRNA vaccines with unmodified and self-amplifying RNA (ARCT-154, Arcturus), which have a lyophilized form, have recently been reported to be kept at room temperature. mRNA vaccines are typically entrapped in lipid nanoparticles composed of ionizable lipids, polyethylene glycol (PEG)-lipids, phospholipids, and cholesterol. These components and their composition affect mRNA vaccine stability and efficacy and the size of the mRNA vaccine. The development of an improved mRNA vaccine entrapped in sophisticated biomaterials, such as novel lipid nanoparticles, using new types of biopolymers or lipids is necessary for high efficacy, safe transportation and long-term storage of the next generation of mRNA vaccines under mild conditions. © 2022 Taylor & Francis Group, LLC.

11.
Quantitative Biology ; 10(2):172-187, 2022.
Article in English | Scopus | ID: covidwho-1964764

ABSTRACT

Background: In this paper, we conduct an analysis of the COVID-19 data in the United States in 2020 via functional data analysis methods. Through this research, we investigate the effectiveness of the practice of public health measures, and assess the correlation between infections and deaths caused by the COVID-19. Additionally, we look into the relationship between COVID-19 spread and geographical locations, and propose a forecasting method to predict the total number of confirmed cases nationwide. Methods: The functional data analysis methods include functional principal analysis methods, functional canonical correlation analysis methods, an expectation-maximization (EM) based clustering algorithm and a functional time series model used for forecasting. Results: It is evident that the practice of public health measures helps to reduce the growth rate of the epidemic outbreak over the nation. We have observed a high canonical correlation between confirmed and death cases. States that are geographically close to the hot spots are likely to be clustered together, and population density appears to be a critical factor affecting the cluster structure. The proposed functional time series model gives more reliable and accurate predictions of the total number of confirmed cases than standard time series methods. Conclusions: The results obtained by applying the functional data analysis methods provide new insights into the COVID-19 data in the United States. With our results and recommendations, the health professionals can make better decisions to reduce the spread of the epidemic, and mitigate its negative effects to the national public health. © The Author (s) 2022. Published by Higher Education Press.

12.
IEEE Internet of Things Journal ; : 1-1, 2022.
Article in English | Scopus | ID: covidwho-1961407

ABSTRACT

The COVID-19 pandemic has caused a high rate of infection, and thus effective epidemic prevention measures of avoiding the second spread of COVID-19 in hospitals are major challenges for healthcare workers. Hospitals, where medicines are collected, are vulnerable to the rapid spread of COVID-19. Using the remote health monitoring technology of the Internet of Things (IoT) to automatically monitor and record the basic medical information of patients, reduce the workload of healthcare workers, and avoid direct contact with healthcare workers to cause secondary infections is an important research topic. This research proposes a new artificial intelligence solution based on the IoT, replacing existing medicine stations and recognizing medicine bags through the state-of-the-art optical character recognition (OCR) model and PP-OCR v2. The use of optical character recognition in identification of medicine bags can replace healthcare workers in data recording. In addition, this research proposes an administrator management and monitoring system to monitor the equipment and provide a mobile application for patients to check the latest status of medicine bags in real time, and record their medication times. The results of the experiments indicate that the recognition model works very well in different conditions (up to 80.76% in PP-OCR v2 and 94.22% in PGNet), which supports both Chinese and English languages. IEEE

13.
4th International Conference on HCI for Cybersecurity, Privacy and Trust, HCI-CPT 2022 Held as Part of the 24th HCI International Conference, HCII 2022 ; 13333 LNCS:492-501, 2022.
Article in English | Scopus | ID: covidwho-1930312

ABSTRACT

Since early 2020, the COVID-19 pandemic has been significantly changing people’s daily lives as social activities are limited to slow down the spread of the novel coronavirus. New technologies, especially mobiles apps, have been widely applied to help with reducing the spread of the pandemic. However, although these apps bring many benefits, it also raises privacy issues given the amount of user information being collected and shared. The goal of this study is to understand individuals’ attitudes towards the privacy concerns on using COVID-19 apps, and their expectations on the privacy protections. By conducting the survey and collecting responses, results found that majority of the participants expressed privacy concerns on COVID-19 apps, and participants with different socioeconomic status may have different levels of willingness to use the app. Results from this study not only provide guidance for the government and app service providers on the implementation of appropriate safeguards, but also address on the needs of privacy protections for the vulnerable groups. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

14.
Annals of Surgical Oncology ; 29(SUPPL 2):S419, 2022.
Article in English | EMBASE | ID: covidwho-1928245

ABSTRACT

INTRODUCTION: With the pressure to reduce both cost of care and in-patient hospitalizations, particularly in the COVID era, several groups have reported the feasibility of outpatient mastectomies utilizing enhanced recovery after surgery (ERAS) programs. Having converted most mastectomies to the outpatient setting in 2009, we examined our experience sending patients home the same day, including patient selection, unexpected admission and post-operative complications, to better inform institutions considering their own outpatient mastectomy programs. METHODS: With approval from the Institutional Review Board, we performed a retrospective cohort study of patients undergoing mastectomy at a single academic medical center from 2014-2020. Patient population included all patients undergoing mastectomy for malignant disease or risk reduction and excluded patients having immediate breast reconstruction. RESULTS: Of 1678 patients undergoing mastectomy in this time period, 810 did not have immediate reconstruction. Overall, 428 (53%) were planned as outpatient procedures. This was dependent on the type of procedure;unilateral mastectomy (UM) (70%), modified radical mastectomy (MRM) (50%), bilateral simple mastectomies (BSM) (39%) and MRM with contralateral prophylactic mastectomy (MRM/CPM) (25%). The latter two increased over the time course of the study. Admission was associated with ASA status (34% ASA 1/2 vs 51% ASA 3/4, p< 0.001). The most significant predictor was surgeon, with rates ranging from 85% to 46% for UM, 80% to 13% for MRM, 68% to 18% for BSM and 55% to 9% for MRM/CPM. Overall, 16 (3.7%) same-day surgery patients were admitted while 14 (3.8%) 23-hour admission patients were converted to inpatient admissions. Post-operative hematomas requiring a second operation were more common with planned admission compared to those planned for same day discharge (19 (4.9%) vs. 10 (2.3%), p=0.036). CONCLUSIONS: Mastectomies (including bilateral and modified radical mastectomies) without reconstruction can be safely performed on an outpatient basis. Rates of unexpected hospitalizations and post-operative complications are low and there is no difference between those patients planning on same-day discharge and those planned for admission.

15.
Journal of Computer Assisted Learning ; : 19, 2022.
Article in English | Web of Science | ID: covidwho-1927600

ABSTRACT

Background Academic dishonesty (AD) and trustworthy assessment (TA) are fundamental issues in the context of an online assessment. However, little systematic work currently exists on how researchers have explored AD and TA issues in online assessment practice. Objectives Hence, this research aimed at investigating the latest findings regarding AD forms, factors affecting AD and TA, and solutions to reduce AD and increase TA to maintain the quality of online assessment. Methods We reviewed 52 articles in Scopus and Web of Science databases from January 2017 to April 2021 using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses model as a guideline to perform a systematic literature review that included three stages, namely planning, conducting, and reporting. Results and conclusions Our review found that there were different forms of AD among students in online learning namely plagiarism, cheating, collusion, and using jockeys. Individual factors such as being lazy to learn, lack of ability, and poor awareness as well as situational factors including the influence of friends, the pressure of the courses, and ease of access to information were strongly associated with AD. A technology-based approach such as using plagiarism-checking software, multi-artificial intelligence (AI) in a learning management system, computer adaptive tests, and online proctoring as well as pedagogical-based approaches, such as implementing a research ethics course programme, and a re-design assessment form such as oral-based and dynamic assessment to reduce cheating behaviour and also sociocultural and sociotechnical adjustment related to the online assessment are reported to reduce AD and increase TA. Implications Educators should adjust the design of online learning and assessment methods as soon as possible. The identified gaps point towards unexplored study on AI, machine learning, learning analytics tools, and related issues of AD and TA in K12 education could motivated future work in the field.

16.
Acta Medica Mediterranea ; 38(3):1471-1476, 2022.
Article in English | Scopus | ID: covidwho-1912456

ABSTRACT

Objective: To investigate the effect of the coronavirus disease 2019 (COVID-19) pandemic on patients with liver abscess associated with type 2 diabetes mellitus (T2DM). Methods: Data about consecutive cases of T2DM-associated liver abscess diagnosed and treated during the pandemic (January-April 2020) or earlier (January-April in 2017-2019) were compared. Results: A total of 177 patients (122 men;median age, 66 years;124 treated in 2017-2019 and 53 treated in 2020) were included in the study. Antibiotic therapy alone led to abscess resolution in 75 patients;the remaining 102 patients underwent successful abscess aspiration (n=56) or drain placement (n = 46). The mean random plasma glucose (15.9±2.7 vs 12.7±2.7 mmol/L;P<0.001), fasting plasma glucose (11.4±2.0 vs 10.6±2.0 mmol/L;P=0.017), and glycosylated hemoglobin A1c (9.1%±1.5% vs 7.8%±0.9%;P<0.001) levels at the presentation were higher among patients treated in 2020 than among those treated earlier. The mean interval between symptom onset and presentation was shorter for patients treated in 2020 (36.5±7.2 hours) than for those treated earlier (50.4±17.4 hours;P<0.001). The mean interval between presentation and diagnosis was longer among patients treated in 2020 (18.4±9.9 hours) than among those treated earlier (11.3±4.9 hours;P<0.001). Conclusions: The COVID-19 pandemic may have promoted the occurrence of liver abscess among patients with poorly controlled T2DM, and control measures for the pandemic may have led to delays in diagnosis. © 2022 A. CARBONE Editore. All rights reserved.

17.
23rd IEEE International Conference on High Performance Computing and Communications, 7th IEEE International Conference on Data Science and Systems, 19th IEEE International Conference on Smart City and 7th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021 ; : 1845-1850, 2022.
Article in English | Scopus | ID: covidwho-1909208

ABSTRACT

This paper presents an integrated data model based on IFC and SensorML to facilitate the post-COVID facilities management to ensure indoor thermal comfort and human health. This paper identifies the information with the reference to different industry guidelines, including WELL building Standard and Singapore BCA post-COVID regulations, and extracts necessary information for sensor description and identification. New parameters in the BIM environment are recommended in this paper to support model-based data exchange in the future. The information required is clarified with a process map depicting the information flow, and IFC MVD to provide a structured overview of the sensor requirement. Data mapping between IFC and SensorML is performed, the result indicates that missing entities and attributes can be proposed to enrich the sensor description in the IFC schema. The integration of SensorML and IFC provides better data interoperability between both schemas, improving information standardization and openness of data exchange in sensor description. © 2021 IEEE.

18.
Nature Machine Intelligence ; : 17, 2022.
Article in English | Web of Science | ID: covidwho-1886237

ABSTRACT

B-cell receptors (BCRs) and their impact on B cells play a vital role in our immune system;however, the manner in which B cells are activated by BCRs are still poorly understood. Ze Zhang and colleagues present a graph-based method that connects BCR and single B-cell RNA sequencing data and identifies notable coupling between BCR and B-cell expression in COVID-19. B-cell receptors (BCRs) are a crucial player in the development and activation of B cells, and their mature forms are secreted as antibodies, which execute functions such as the neutralization of invading pathogens. All current analytical approaches for BCRs solely investigate the BCR sequences and ignore their correlations with the transcriptomics of the B cells, yielding conclusions of unknown functional relevance regarding the roles of BCRs and B cells, and could generate biased interpretation. Many single-cell RNA-sequencing (scRNA-seq) techniques can now capture both the gene expression and BCR of each B cell, which could potentially address this issue. Here, we investigated 43,938 B cells from 13 scRNA-seq datasets with matched scBCR sequencing, and we observed an association between the BCRs and the B cells' transcriptomics. Motivated by this, we developed the Benisse model (BCR embedding graphical network informed by scRNA-seq) to provide refined analyses of BCRs guided by single-cell gene expression. Benisse revealed a gradient of B-cell activation along BCR trajectories. We discovered a stronger coupling between BCRs and B-cell gene expression during COVID-19 infections. We found that BCRs form a directed pattern of continuous and linear evolution to achieve the highest antigen targeting efficiency, compared with the convergent evolution pattern of T-cell receptors. Overall, a simultaneous digestion of the BCR and gene expression of B cells, viewed through the lens of Benisse, will lead to a more insightful interpretation of the functional relevance of the BCR repertoire in different biological contexts.

19.
2nd International Conference on Big Data and Artificial Intelligence and Software Engineering (ICBASE) ; : 157-161, 2021.
Article in English | English Web of Science | ID: covidwho-1883118

ABSTRACT

Accurate facial recognition can effectively help the population combat the disease by offering risk-free phone usage, access controls, etc. In the era of COVID-19, a mask has become a necessity. However, masks may reduce the accuracy of face recognition to some degree. Thus, it is necessary to use deep learning to increase face recognition accuracy by recovering the face with a mask. For this purpose, this study proposed an AI-based model based on Pix2pix and U-net generator for restoring face mask images using the paired image database. In the training step, we used two adversarial models, including one generator and one discriminator. Then they are extended to a conditional model, which will be piped to the Pix2pix algorithm once again. U-Net was built in the training of the generator. The loss curves of generator and discriminators show that as iteration time increases, the loss of fake discriminator becomes lower stably. In contrast, the loss of real discriminator has the same tendency. In the meantime, the loss of generator shows an increased tendency. The result indicates that our model can help build reliable face mask restoration for daily use, which helps to improve the recognition accuracy of the face with a mask.

20.
Topics in Antiviral Medicine ; 30(1 SUPPL):354-355, 2022.
Article in English | EMBASE | ID: covidwho-1879987

ABSTRACT

Background: Historically, control of HIV infection in young men living with HIV (LWH) has been problematic. We examined the STI/HIV burden in young men with urethral discharge syndrome (UDS) in Kampala, Uganda. Methods: Between Oct 2019-Nov 2020, 250 men with UDS were enrolled at 6 urban sites. All HIV positive men (20%, 50/250) had plasma viral load testing (Abbott m2000 RealTime HIV-1);when VL>1000 copies/mL, resistance and recency testing (Asanté HIV-1 Rapid Recency Assay, Sedia Biosciences) were performed. Penile meatal swabs were retrospectively tested for gonorrhea, chlamydia, trichomoniasis, and Mycoplasma genitalium (Hologic Aptima CT/NG, TV, MG). Descriptive statistical analysis, logistic, and bivariable and multivariable regression were undertaken. Results: Among the men LWH, 92% (46/50) had VL<1000;4 were not suppressed, 1 of whom was previously undiagnosed. Among the viremic individuals, no major resistance mutations were found and none appeared recently infected. Men (median age 24[22;32]) reported sex partners/previous 2 months (median 2[1;2]), 61.6% engaged in transactional sex in the previous 6 months, and 48.4% reported alcohol use. 44.4% reported alcohol use before sex in the previous 6 months. Overall, 0.4% reported 'always' condom use, 21.8% continued condomless sex since onset of UDS symptoms. There was a high burden of active, undiagnosed STIs found in these men (see Table);of the 10% who had syphilis, 80% were previously undiagnosed. Agreement between HIV-and syphilis-POC and lab-based testing was 100% and 95% (19/20), respectively. By multivariable logistic regression, alcohol use (OR, 3.32 (95% CI:1.61, 7.11)), and condomless sexual activity since symptom onset (OR, 2.86 (95% CI:1.20, 6.84)) were significantly associated with HIV;92% had at least one other STI. Conclusion: Among men presenting with UDS, bacterial STIs were very common. 20% had HIV with a surprisingly high level of viral suppression and no evidence of resistance in those with detectable VL. Recency testing results were non-discriminatory;none appeared recently infected. Risk of future HIV acquisition is high in those not LWH. Given the high frequency of bacterial STI, alcohol use and unprotected high-risk sexual behavior in this population, men with UDS who test negative for HIV should be prioritized for PrEP. Future research, evaluating the effect of SARS-CoV-2 on the burden of STI and level of viral suppression in this population, is required.

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