Deploying the Minimum Number of Rechargeable UAVs for a Quarantine Barrier

To control the rapid spread of COVID-19, we consider deploying a set of Unmanned Aerial Vehicles (UAVs) to form a quarantine barrier such that anyone crossing the barrier can be detected. We use a charging pile to recharge UAVs. The problem is scheduling UAVs to cover the barrier, and, for any scheduling strategy, estimating theminimum number of UAVs needed to cover the barrier forever. We propose breaking the barrier into subsegments so that each subsegment can be monitored by a single UAV. We then analyze two scheduling strategies, where the first one is simple to implement and the second one requires fewer UAVs. The first strategy divides UAVs into groups with each group covering a subsegment. For this strategy, we derive a closed-form formula for the minimum number of UAVs. In the case of insufficient UAVs, we give a recursive function to compute the exact coverage time and give a dynamic-programming algorithm to allocate UAVs to subsegments to maximize the overall coverage time. The second strategy schedules all UAVs dynamically. We prove a lower and an upper bound on the minimum number of UAVs. We implement a prototype system to verify the proposed coverage model and perform simulations to investigate the performance.

Graph-Based Fusion of Imaging and Non-Imaging Data for Disease Trajectory Prediction

This study proposes a graph convolutional neural networks (GCN) architecture for fusion of radiological imaging and non-imaging tabular electronic health records (EHR) for the purpose of clinical event prediction. We focused on a cohort of hospitalized patients with positive RT-PCR test for COVID-19 and developed GCN based models to predict three dependent clinical events (discharge from hospital, admission into ICU, and mortality) using demographics, billing codes for procedures and diagnoses and chest X-rays. We hypothesized that the two-fold learning opportunity provided by the GCN is ideal for fusion of imaging information and tabular data as node and edge features, respectively. Our experiments indicate the validity of our hypothesis where GCN based predictive models outperform single modality and traditional fusion models. We compared the proposed models against two variations of imaging-based models, including DenseNet-121 architecture with learnable classification layers and Random Forest classifiers using disease severity score estimated by pre-trained convolutional neural network. GCN based model outperforms both imaging-only methods. We also validated our models on an external dataset where GCN showed valuable generalization capabilities. We noticed that edge-formation function can be adapted even after training the GCN model without limiting application scope of the model. Our models take advantage of this fact for generalization to external data. © 2023 IEEE.

[Rapid detection and genotyping of SARS-CoV-2 Omicron BA.4/5 variants using a RT-PCR and CRISPR-Cas12a-based assay].

OBJECTIVE: To establish a rapid detection and genotyping method for SARS-CoV-2 Omicron BA.4/5 variants using CRISPPR-Cas12a gene editing technology. METHODS: We combined reverse transcription-polymerase chain reaction (RT-PCR) and CRISPR gene editing technology and designed a specific CRISPPR RNA (crRNA) with suboptimal protospacer adjacent motifs (PAM) for rapid detection and genotyping of SARS- CoV-2 Omicron BA.4/5 variants. The performance of this RT- PCR/ CRISPPR-Cas12a assay was evaluated using 43 clinical samples of patients infected by wild-type SARS-CoV-2 and the Alpha, Beta, Delta, Omicron BA. 1 and BA. 4/5 variants and 20 SARS- CoV- 2-negative clinical samples infected with 11 respiratory pathogens. With Sanger sequencing method as the gold standard, the specificity, sensitivity, concordance (Kappa) and area under the ROC curve (AUC) of RT-PCR/CRISPPR-Cas12a assay were calculated. RESULTS: This assay was capable of rapid and specific detection of SARS- CoV-2 Omicron BA.4/5 variant within 30 min with the lowest detection limit of 10 copies/µL, and no cross-reaction was observed in SARS-CoV-2-negative clinical samples infected with 11 common respiratory pathogens. The two Omicron BA.4/5 specific crRNAs (crRNA-1 and crRNA-2) allowed the assay to accurately distinguish Omicron BA.4/5 from BA.1 sublineage and other major SARS-CoV-2 variants of concern. For detection of SARS-CoV-2 Omicron BA.4/5 variants, the sensitivity of the established assay using crRNA-1 and crRNA-2 was 97.83% and 100% with specificity of 100% and AUC of 0.998 and 1.000, respectively, and their concordance rate with Sanger sequencing method was 92.83% and 96.41%, respectively. CONCLUSION: By combining RT-PCR and CRISPPR-Cas12a gene editing technology, we successfully developed a new method for rapid detection and identification of SARS-CoV-2 Omicron BA.4/5 variants with a high sensitivity, specificity and reproducibility, which allows rapid detection and genotyping of SARS- CoV-2 variants and monitoring of the emerging variants and their dissemination.

The Application of Biosensors in the Detection of SARS-CoV-2

Since the outbreak of COVID-19, it is becoming important to screen SARS-CoV-2 with high accuracy, high efficiency, and rapidness, for epidemic prevention and control. Conventional detection technologies can not satisfy the requirements of examining massive people in a very short time. Biosensor technology, with the advantages of high sensitivity, good selectivity, low cost, easy miniaturization, and short detection time, is being used to develop real-time detection equipment, thus as a potential alternative for real-time detection of SARS-CoV-2 in clinical diagnosis. In the present study, the authors summarized the construction methods and principles for optical biosensors, electrochemical biosensors, wearable biosensors, magnetic biosensors, gold nanoparticle biosensors, and aptamer biosensors, followed by the introduction of the current application of multiple biosensors in SARS-CoV-2 detection. Conclusively, the technical bottlenecks and future development trends of biosensors in SARS-CoV-2 detection are proposed.

The Application of Biosensors in the Detection of SARS-CoV-2

Since the outbreak of COVID-19, it is becoming important to screen SARS-CoV-2 with high accuracy, high efficiency, and rapidness, for epidemic prevention and control. Conventional detection technologies can not satisfy the requirements of examining massive people in a very short time. Biosensor technology, with the advantages of high sensitivity, good selectivity, low cost, easy miniaturization, and short detection time, is being used to develop real-time detection equipment, thus as a potential alternative for real-time detection of SARS-CoV-2 in clinical diagnosis. In the present study, the authors summarized the construction methods and principles for optical biosensors, electrochemical biosensors, wearable biosensors, magnetic biosensors, gold nanoparticle biosensors, and aptamer biosensors, followed by the introduction of the current application of multiple biosensors in SARS-CoV-2 detection. Conclusively, the technical bottlenecks and future development trends of biosensors in SARS-CoV-2 detection are proposed. © 2023 Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences.

Higher vocational college students' learning burnout during the COVID-19 pandemic: A case study in China

This study examines students' levels of learning burnout during the COVID-19 pandemic. Learning burnout levels were also investigated about students' gender, hometown, family member structure, and field of major. The study employs a random sampling survey method, with 1,098 students from a public higher vocational college in Shandong Province, China. The collected data was analyzed using SPSS 26. The results found that 71.5% of students are at a moderate burnout level, 27.0% are at a low level, and only 1.5% are at a high level, and there was no high level of learning burnout on a single item during the COVID-19 pandemic. The data showed that the levels of learning burnout of male students, students who live in town, non-only child students, and students majoring in science and engineering were higher than the other group of students. There was a statistically significant difference in the level of student learning burnout by gender, but not in the variables of hometown, family structure, or field of major. Although studies show that students' learning burnout level is not affected by COVID-19, students generally have learning burnout. Therefore, three strategies were also put forward to reduce students' learning burnout from school. © 2023, Institute of Advanced Engineering and Science. All rights reserved.

Research and Application of 5G Edge AI in Medical Industry

With the development of 5G and AI technology, the infectious virus detection framework system based on the combination of 5G MEC and medical sensors can effectively assist in the intelligent detection and control of influenza viruses such as COVID-19. Employing the edge computing and 5G+MEC model, the virus AI model is trained for the collected influenza virus data. Then the virus AI model can be used to evaluate the virus patients on the local edge computing service platform. Therefore, this paper introduces an algorithm and resource allocation, which uses 5G functions (especially, low latency, high bandwidth, wide connectivity, and other functions) to achieve local chest X-ray or CT scan images to detect COVID-19. Meanwhile, this paper also compares the computational efficiency of different algorithms in the 5G edge AI-based infectious virus detection framework, in this way to select the best algorithm and resource allocation. © 2022 IEEE.

THE STOCHASTICITY IN ADHERENCE TO NONPHARMACEUTICAL INTERVENTIONS AND BOOSTER DOSES AND THE MITIGATION OF COVID-19

Facing the more contagious COVID-19 variant, Omicron, nonpharmaceutical interventions (NPIs) were still in place and booster doses were proposed to mitigate the epidemic. However, the uncertainty and stochasticity in individuals' behaviours toward the NPIs and booster dose increase, and how this randomness affects the transmission remains poorly understood. We present a model framework to incorporate demographic stochasticity and two kinds of environmental stochasticity (notably variations in adherence to NPIs and booster dose acceptance) to analyze the effects of different forms of stochasticity on transmission. The model is calibrated using the data from December 31, 2021, to March 8, 2022, on daily reported cases and hospitalizations, cumulative cases, deaths and vaccinations for booster doses in Toronto, Canada. An approximate Bayesian computational (ABC) method is used for calibration. We observe that demographic stochasticity could dramatically worsen the outbreak with more incidence compared with the results of the corresponding deterministic model. We found that large variations in adherence to NPIs increase infections. The randomness in booster dose acceptance will not affect the number of reported cases significantly and it is acceptable in the mitigation of COVID-19. The stochasticity in adherence to NPIs needs more attention compared to booster dose hesitancy. © 2023 American Institute of Mathematical Sciences. All rights reserved.

Hira Makes a Sound: Nepali Diasporic Worldviewing through Asian American Studies Praxis during the COVID-19 Anti-Asian Hate Pandemics

In this article, we offer a specific example from our programmatic research and teaching praxis during the COVID-19 anti-Asian hate pandemic period. We demonstrate how Asian American Studies community-centered knowledge coproduction and narrative generational wealth investment can address critical experiences of young learners from underrepresented, religiously-diverse populations through content that supports culturally sustaining child development and challenges disparately impactful realities of racism, misrepresentation, and systemic Western biases which undermine their health and wellbeing. Focusing on religious themes in relation to child development was not an explicit intention of our collaboratively developed storybook project titled, Hira Makes a Sound. Nevertheless, centering a women-led, intergenerational Nepali immigrant story in both our process and final product necessarily led to foregrounding religious, cultural, and spiritual dimensions of diasporic family and community life that are essential to coping and development for the fictional lead character, Hira, and her loved ones. Robust story data themes—paradoxically grounded in the ether of a shared Gurung worldview—provide generative lessons for researchers, educators, artists, and community advocates who work with or need to account for the lived experiences of young learners within religiously diverse, multi-generational immigrant family households and community ecologies. © 2023 by the authors.

Investigation and analysis on the infection control and radiation safety of radiodiagnostic workplace for COVID-19.

Objective: To survey and supervise the risk of infection control and radiation safety in the radiological diagnostic workplace for COVID-19, and provide data support for the safety protection of radiographers and related staff. Method(s): 4 emergency hospitals for COVID-19 including 2 makeshift hospitals, module hospital and brick pattern hospital in Hubei province were performed for testing and evaluation of imaging performance and radiological protection for the 8 new installed CT scanners and places according to the national standards of WS 519-2019 and GBZ 130-2013. The infection control safety factors such as the layout of the equipment room were monitored and investigated. Two COVID-19 designated hospitals including general hospital and infectious disease specialized hospital were selected to carry out field investigation and sampling of environmental biological samples for 4 CT rooms. Then the samples were detected for the nucleic acid of novel coronavirus. The results of radiodiagnostic workplace overall arrangement, infection prevention and the nucleic acid testing were analyzed, and the biological safety reliability and risk point were evaluated. Result(s): The indicators of imaging performance and radiation protection for 8 CT scanners in emergency hospitals could meet the requirements of national standards.Each of 2 makeshift hospitals had 3 CT rooms with the area of 38.8 m2 and 4 mm Pb equivalent thickness of protective shielding. The CT rooms in module hospital and brick pattern hospital were 20.0 m2, and 35.8 m2 in areas, with 4 mm Pb equivalent and 3 mm Pb equivalent thickness of protection shielding, respectively. The 8 radiological diagnostic workplaces of the emergency hospitals were designed and constructed based on " three zones with two passage ways". The result of the nucleic acid test indicated that the positive samples were found at the multiple sites such as scanning bed, internal of gantry and ground touched by patients in CT scanning room. The areas such as console panel and ground were risked of pollution by the virus infected hands and feet of radiographers. In addition, the similar positive samples were found in the areas in scanning room with no touch of patients, such as observation window and air outlet. Conclusion(s): 8 CT scanners and rooms in 4 emergency hospitals basically meet the requirements of imaging performance and radiation protection. The disinfection of COVID-19 radiodiagnostic workplace should be standardized.Copyright © 2020 by the Chinese Medical Association.

Analysis of medication regularities of epidemic disease prescription in Treatise on Febrile Diseases and mechanism of core drugs in treatment of COVID-19

Objective To analyze the medication rules of related epidemic disease prescription in Treatise on Febrile Diseases based on data mining, and the mechanism of "Chaihu (Bupleuri Radix)-Huangqin (Scutellariae Radix)” as the core drugs in the treatment of coronavirus disease 2019 (COVID-19) by network pharmacology, in order to explore the contemporary value of classical prescriptions in the treatment of epidemic diseases. Methods The prescriptions for treating epidemic diseases in Treatise on Febrile Diseases were screened, and the medication rules such as drug frequency, flavor and meridian tropism as well as correlation, apriori algorithm were analyzed by using software such as R language. The mechanism of the core drugs in the medication pattern in the treatment of COVID-19 was explored by the network pharmacology. A "disease-drug-ingredient-target” network was constructed on the selected components and targets with Cytoscape. The key targets were introduced into String database for network analysis of protein-protein interaction (PPI), and gene ontology (GO) functional analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were conducted in R language. Results A total of 61 prescriptions for treating epidemic diseases in Treatise on Febrile Diseases were included, including 52 traditional Chinese medicines (TCMs). In the top 20 high-frequency drugs, warm drugs, spicy drugs and qitonifying drugs were mainly used, mostly in the spleen and lung meridian. Chaihu (Bupleuri Radix) and Huangqin (Scutellariae Radix) herb pair had the strongest correlation. A total of five clusters were excavated: supplemented formula of Xiaochaihu Decoction (小柴胡汤), Sini Decoction (四逆汤), supplemented formule of Maxing Shigan Decoction (麻杏石甘汤), Fuling Baizhu Decoction (茯苓白术汤) and Dachengqi Decoction (大承气汤). A total of 45 active ingredients, 189 action targets of Bupleuri Radix-Scutellariae Radix herb pair, and 543 targets of COVID-19 were obtained from TCMSP and Genecards, and 64 intersection targets were generated. The results of the network analysis showed that the main components of core drugs pair against COVID-19 may be quercetin, wogonin, kaempferol baicalein, acacetin etc., and the core targets may be VEGFA, TNF, IL-6, TP53, AKT1, CASP3, CXCL8, PTGS2, etc. A total of 1871 related entries and 164 pathways were obtained by GO and KEGG enrichment analysis, respectively. Conclusion In Treatise on Febrile Diseases, the treatment of epidemic diseases mainly chose pungent, warm, spleen-invigorating and qi-tonifying herbs, such as Xiaochaihu Decoction, Sini Decoction and Dachengqi Decoction, etc. It was found that Bupleuri Radix-Scutellariae Radix core herb pair prevent and treat COVID-19 through multi-target targets such as PTGS2, IL-6 and TNF. The ancient prescriptions for treating epidemic disease in Treatise on Febrile Diseases may have significant reference value for the prevention and treatment of new epidemic diseases today. © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.

Research Progress and Implication of Wastewater Surveillance of SARS-CoV-2

Since the outbreak of the coronavirus disease 2019 (COVID-19), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been found in wastewater frequently worldwide. Based on the wastewater-based epidemiology (WBE), wastewater surveillance of SARS-CoV-2 can complement population surveillance for COVID-19. Quantification of viral load and genome sequencing of SARS-CoV-2 can help early warning of COVID-19 outbreaks, early identification of asymptomatic cases, assessment of infection scale, prediction of pandemic trend status, and identification of virus sources to provide scientific basis for polices for the prevention and control. Accordingly, here, the sources of SARS-CoV-2 in wastewater at home and abroad and the major factors affecting the survival of virus were reviewed. Common methods to concentrate, detect and quantify SARS-CoV-2 were reviewed, with an overview of global surveillance projects, progresses, and remaining scientific issues. Some shortcomings of the current procedures, including the lack of sufficient information on distribution characteristics and infectivity of SARS-CoV-2 in wastewater and limited development and application of prediction models were also discussed. WBE can provide insight into the scientific prevention and control of COVID-19 in the face of current or future pandemics in China, and enhance China′s ability to deal with the surveillance and early warning, epidemic scale assessment, and accurate policy-making for the infectious and non-infectious diseases. © 2022 Editorial Board, Research of Environmental Sciences. All rights reserved.

Analysis of medication regularities of epidemic disease prescription in Treatise on Febrile Diseases and mechanism of core drugs in treatment of COVID-19

Objective To analyze the medication rules of related epidemic disease prescription in Treatise on Febrile Diseases based on data mining, and the mechanism of "Chaihu (Bupleuri Radix)-Huangqin (Scutellariae Radix)" as the core drugs in the treatment of coronavirus disease 2019 (COVID-19) by network pharmacology, in order to explore the contemporary value of classical prescriptions in the treatment of epidemic diseases. Methods The prescriptions for treating epidemic diseases in Treatise on Febrile Diseases were screened, and the medication rules such as drug frequency, flavor and meridian tropism as well as correlation, apriori algorithm were analyzed by using software such as R language. The mechanism of the core drugs in the medication pattern in the treatment of COVID-19 was explored by the network pharmacology. A "disease-drug-ingredient-target" network was constructed on the selected components and targets with Cytoscape. The key targets were introduced into String database for network analysis of protein-protein interaction (PPI), and gene ontology (GO) functional analysis and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were conducted in R language. Results A total of 61 prescriptions for treating epidemic diseases in Treatise on Febrile Diseases were included, including 52 traditional Chinese medicines (TCMs). In the top 20 high-frequency drugs, warm drugs, spicy drugs and qitonifying drugs were mainly used, mostly in the spleen and lung meridian. Chaihu (Bupleuri Radix) and Huangqin (Scutellariae Radix) herb pair had the strongest correlation. A total of five clusters were excavated: supplemented formula of Xiaochaihu Decoction (), Sini Decoction (), supplemented formule of Maxing Shigan Decoction (), Fuling Baizhu Decoction () and Dachengqi Decoction (). A total of 45 active ingredients, 189 action targets of Bupleuri Radix-Scutellariae Radix herb pair, and 543 targets of COVID-19 were obtained from TCMSP and Genecards, and 64 intersection targets were generated. The results of the network analysis showed that the main components of core drugs pair against COVID-19 may be quercetin, wogonin, kaempferol baicalein, acacetin etc., and the core targets may be VEGFA, TNF, IL-6, TP53, AKT1, CASP3, CXCL8, PTGS2, etc. A total of 1871 related entries and 164 pathways were obtained by GO and KEGG enrichment analysis, respectively. Conclusion In Treatise on Febrile Diseases, the treatment of epidemic diseases mainly chose pungent, warm, spleen-invigorating and qi-tonifying herbs, such as Xiaochaihu Decoction, Sini Decoction and Dachengqi Decoction, etc. It was found that Bupleuri Radix-Scutellariae Radix core herb pair prevent and treat COVID-19 through multi-target targets such as PTGS2, IL-6 and TNF. The ancient prescriptions for treating epidemic disease in Treatise on Febrile Diseases may have significant reference value for the prevention and treatment of new epidemic diseases today. Copyright © 2023 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.

Hierarchical Multi-modal Transformer for Automatic Detection of COVID-19

Automated COVID-19 detection based on analysis of cough recordings has been an important field of study, as efficient and accurate methods are necessary to contain the spread of the global pandemic and relieve the burden on medical facilities. While previous works presented lightweight machine learning models [9], these models may sacrifice accuracy and interpretability to integrate into mobile devices. Besides, the question of how to effectively associate indicators from audio signals to other modality inputs (i.e. patient information) is still largely unexplored, as previous works predominantly relied on simply concatenated features to learn. To tackle these issues, this paper proposes a novel Hierarchical Multi-modal Transformer (HMT) that learns more informative multi-modal representations with a cross attention module during the feature fusion procedure. Besides, the block aggregation algorithm for the HMT provides an efficient and improved solution from the Vanilla Vision Transformer for limited COVID-19 benchmark datasets. Extensive experiments show the effectiveness of our proposed model for more accurate COVID-19 detection, which yield state-of-the-art results on two public datasets, Coswara and COUGHVID. © 2022 Copyright held by the owner/author(s).

An approach combining bioinformatics and machine learning to identify eight autophagy-related biomarkers and construct molecular mechanisms underlying COVID-19 and major depressive disorders.

OBJECTIVE: A lack of objective biomarkers is preventing the screening and diagnosis of COVID-19 combined with major depression disorder (COVID-19-MDD). The purpose of this study was to identify diagnostic biomarkers and gene regulatory mechanisms associated with autophagy; a crucial process significantly involved in the pathogenesis of COVID-19-MDD. MATERIALS AND METHODS: In this study, differentially expressed genes (DEGs) were screened using GSE98793 from the GEO2R analysis (GEO) database, and intersected with the COVID-19-related gene (CRGs) and autophagy-related genes (ARGs) to obtain common genes involved in. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of these common genes were performed. Subsequently, the transcription factor (TF)-gene regulatory network and comorbidity network were constructed. In addition, 10 drug candidates were screened using the DSigDB database. To identify diagnostic markers, we used LASSO regression. RESULTS: In total, 13 common genes were screened, which were primarily enriched in lysosomes, endoplasmic reticulum membranes, and other endomembrane systems also associated with autophagy. Additionally, these genes were involved in neurological cell signaling and have a functional role in pathways related to vascular endothelial growth factor, tyrosine kinase, autophagy, inflammation, immunity, and carcinogenesis. Tumors and psychiatric disorders were the most highly linked diseases to COVID-19. Finally, ten drug candidates and eight diagnostic markers (STX17, NRG1, RRAGD, XPO1, HERC1, HSP90AB1, EPHB2, and S1PR3) were screened. CONCLUSIONS: This is the first study to screen eight diagnostic markers and construct a gene regulatory network for COVID-19-MDD from the perspective of autophagy. The findings of our study provide novel insights into the diagnosis and treatment of COVID-19-MDD.

Detection of the SARS-CoV-2 Delta Variant in the Transboundary Rivers of Yunnan, China

Ruili and Longchuan, two border counties in southwestern China, are facing epidemic control challenges due to the high rate of COVID-19 infections originating from neighboring Myanmar. Here, we aimed to establish the applicability of wastewater and environmental water surveillance of SARS-CoV-2 and conduct whole-genome sequencing (WGS) to trace the possible infection origin. In August 2021, total 72 wastewater and river water samples were collected from 32 sampling sites. SARS-CoV-2 ORF1ab and N genes were measured by RT-qPCR. We found that 19 samples (26.39%) were positive, and the viral loads of ORF1ab and N genes were 6.62 × 102–2.55×105 and 1.86 × 103–2.32 × 105 copies/L, respectively. WGS further indicated the sequences in two transboundary river samples, and one hospital wastewater sample belonged to the delta variant, suggesting that the infection source might be areas with high COVID-19 delta variant incidence in Southeast Asia (e.g., Myanmar). We reported for the first time the detection and quantification of SARS-CoV-2 RNA in the transboundary rivers of Myanmar–China. Our findings demonstrate that wastewater and environmental water may provide independent and nonintrusive surveillance points to monitor the global spread of emerging COVID-19 variants of concern, particularly in high-risk regions or border areas with considerable epidemic challenges and poor wastewater treatment facilities.

Operation within 7 Weeks after Covid-19 Infection Is Safe in Selected Group of Patients with Proper Precaution

Aim: It was recommended that surgery should be delayed for at least 7 weeks following COVID-19 infection to reduce risk of operation. However, for patients undergoing cancer surgery, a delay of 7-week might not be feasible practically. The aim of this case report was to demonstrate that it would be safe to carry out operation during early post-COVID period in selected cases with proper prophylaxis. Method(s): We prospectively collected data for patients undergoing cancer surgery and emergency operation in the hepatobiliary team from Mar 2022 to May 2022. Informed consent for recording and publication of the data was obtained from patients. COVID-19 related data and peri-operative outcome and measures to prevent postoperative complications were recorded. Patients were followed-up in our clinic after 8 weeks post-operatively. Result(s): 4 patients receiving elective hepatobiliary cancer surgery and 1 patient receiving emergency laparotomy for intestinal obstruction were recruited. The time from positive COVID-19 to operation ranged from 23 to 45 days. All patients were asymptomatic for COVID-19 at the time of operation. Prophylaxis for deep vein thrombosis and pneumonia was employed for all cases. All our patients recovered from surgery without pulmonary complication or unexpected ICU admission. There was no mortality in our case series. The patients' length-of-stay ranged from 4 to 12 days. Conclusion(s): It was safe to perform operation in carefully selected patients within 7 weeks after COVID-19 infection with appropriate peri-operative complication prevention measures.