Discovery of Peptidic Ligands against the SARS-CoV-2 Spike Protein and Their Use in the Development of a Highly Sensitive Personal Use Colorimetric COVID-19 Biosensor.

In addition to efficacious vaccines and antiviral therapeutics, reliable and flexible in-home personal use diagnostics for the detection of viral antigens are needed for effective control of the COVID-19 pandemic. Despite the approval of several PCR-based and affinity-based in-home COVID-19 testing kits, many of them suffer from problems such as a high false-negative rate, long waiting time, and short storage period. Using the enabling one-bead-one-compound (OBOC) combinatorial technology, several peptidic ligands with a nanomolar binding affinity toward the SARS-CoV-2 spike protein (S-protein) were successfully discovered. Taking advantage of the high surface area of porous nanofibers, immobilization of these ligands on nanofibrous membranes allows the development of personal use sensors that can achieve low nanomolar sensitivity in the detection of the S-protein in saliva. This simple biosensor employing naked-eye reading exhibits detection sensitivity comparable to some of the current FDA-approved home detection kits. Furthermore, the ligand used in the biosensor was found to detect the S-protein derived from both the original strain and the Delta variant. The workflow reported here may enable us to rapidly respond to the development of home-based biosensors against future viral outbreaks.

Assessment of the WHO non-communicable diseases kit for humanitarian emergencies in South Sudan: a retrospective, prospective, observational study.

BACKGROUND: The WHO Non-Communicable Diseases Kit (NCDK) was developed to support care for non-communicable diseases (NCDs) in humanitarian settings. Targeting primary healthcare, each kit contains medicines and supplies that are forecasted to meet the needs of 10,000 people for 3 months. This study aimed to evaluate the NCDK deployment process, contents, usage and limitations, and to explore its acceptability and effectiveness among healthcare workers (HCWs) in South Sudan. METHODS: This mixed-method observational study captured data from pre-and-post NCDK deployment. Six data collection tools included: (i) contextual analysis, (ii) semi-structured interviews, in addition to surveys measuring/assessing (iii) healthcare workers' knowledge about NCDs, and healthcare workers' perceptions of: (iv) health facility infrastructure, (v) pharmaceutical supply chain, and (vi) NCDK content. The pre- and post-deployment evaluations were conducted in four facilities (October-2019) and three facilities (April-2021), respectively. Descriptive statistics were used for quantitative data and content analysis for open-ended questions. A thematic analysis was applied on interviews findings and further categorized into four predetermined themes. RESULTS: Compared to baseline, two of the re-assessed facilities had improved service availability for NCDs. Respondents described NCDs as a growing problem that is not addressed at a national level. After deployment, the same struggles were intensified with the COVID-19 pandemic. The delivery process was slow and faced delays associated with several barriers. After deployment, poor communications and the "push system" of inventories were commonly perceived by stakeholders, leading to expiry/disposal of some contents. Despite being out-of-stock at baseline, at least 55% of medicines were found to be unused post-deployment and the knowledge surveys demonstrated a need for improving HCWs knowledge of NCDs. CONCLUSIONS: This assessment further confirmed the NCDK role in maintaining continuity of care on a short-term period. However, its effectiveness was dependent on the health system supply chain in place and the capacity of facilities to manage and treat NCDs. Availability of medicines from alternative sources made some of the NCDK medicines redundant or unnecessary for some health facilities. Several learnings were identified in this assessment, highlighting barriers that contributed to the kit underutilization.

Crispr biosensing and Ai driven tools for detection and prediction of Covid-19

Coronaviridae family consists of many virulent viruses with zoonotic properties that can be transmitted from animals to humans. Different strains of these viruses have caused pandemic in the past such as Severe Respiratory Syndrome Coronavirus (SARS-CoV) in 2002, Middle East respiratory syndrome coronavirus (MERS-CoV) in 2012 and recently Severe Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) also known as COVID-19 in December 2019. Scientists utilised different approaches for the detection and characterisation of CoVs using samples such as serum, throat swabs, nose swabs, nasopharyngeal aspirates and bronchoalveolar lavages. The two common approaches include antigen-based approach and molecular diagnostic approach, which are hindered by limitations such as low sensitivity and requirement for high level of biosafety during isolation of the virus from cell culture. Thus, there is a need for developing a more rapid, sensitive, simple and cheap diagnostic kit for diagnosis of different strains of coronavirus. In this article, we overview 2019 novel coronavirus, pandemic, prior epidemics, diagnosis, treatments, identification of drugs detection based on classification and prediction using artificial intelligence-driven tools. We also overview in-lab molecular testing and on-site testing using CRISPR-based biosensing tools. We also outline limitations of laboratory techniques and open-research issues in the current state of CRISPR-based biosensing applications and artificial intelligence for treatment of Coronaviruses. [ FROM AUTHOR] Copyright of Journal of Experimental & Theoretical Artificial Intelligence is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

A real-time monitoring platform of colorimetric LAMP for developing rapid visual detection kits of SARS-CoV-2

Visual detection of nucleic acids is important to diagnose the serious acute infectious diseases such as coronavirus disease 2019 (COVID-19). During this pandemic, reliable visual detection kits have been in high demand for screening and prevention of the virus. While developing these visual detection kits, a real-time monitoring platform is usually applied to study the amplification and detection processes of nucleic acids and optimize the detecting conditions. Herein, we developed a real-time monitoring platform of colorimetric loop-mediated isothermal amplification (LAMP) to investigate the amplification and detection processes of nucleic acids. Using this platform, we could obtain the real-time amplification curves, and optimize the reaction temperature, color change, and detection time. Based on the optimized conditions, a visual detection kit for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was successfully developed with a sensitivity of 102 copies µL−1 in 12 min. This real-time monitoring platform has advantages of simple construction, steady performance, high sensitivity, and outstanding anti-pollution capability, and could replace the traditional colorimetric methods by photographing and reading values. This platform would accelerate the development of visual detection kits for colorimetric LAMP, help to explore the amplification and transcription of nucleic acids, and provide support for the prevention of emerging biological threats. © 2023

Electrochemical lateral-flow device for rapid COVID-19 antigen-diagnostic testing.

Antigen test kits (ATK) are extensively utilized for screening and diagnosing COVID-19 because they are easy to operate. However, ATKs exhibit poor sensitivity and cannot detect low concentrations of SARS-CoV-2. Herein, we present a new, highly sensitive, and selective device obtained by combining the principle of ATKs with electrochemical detection for COVID-19 diagnosis, which can be quantitatively assessed using a smartphone. An electrochemical test strip (E-test strip) was constructed by attaching a screen-printed electrode inside a lateral-flow device to exploit the remarkable binding affinity of SARS-CoV-2 antigen to ACE2. The ferrocene carboxylic acid attached to SARS-CoV-2 antibody acts as an electroactive species when it binds to SARS-CoV-2 antigen in the sample before it flows continuously to the ACE2-immobilization region on the electrode. Electrochemical-assay signal intensity on smartphones increased proportionally to the concentration of SARS-CoV-2 antigen (LOD = 2.98 pg/mL, under 12 min). Additionally, the application of the single-step E-test strip for COVID-19 screening was demonstrated using nasopharyngeal samples, and the results were consistent with those obtained using the gold standard (RT-PCR). Therefore, the sensor demonstrated excellent performance in assessing and screening COVID-19, and it can be used professionally to accurately verify diagnostic data while remaining rapid, simple, and inexpensive.

Recent Advances in Understanding SARS-CoV-2 Infection and Updates on Potential Diagnostic and Therapeutics for COVID-19

A more focused approach is needed to understand the SARS-CoV-2 virulence, structure, and genomics to devise more effective diagnostic and treatment interventions as this virus can evade the immune attack and causes life-threatening complications such as cytokine storm. The spread of the virus is still amplifying and causing thousands of new cases worldwide. It is essential to review current diagnostics and treatment approaches to pave the way to correct or modify our current practices to make more effective interventions against COVID-19. COVID-19 vaccine development has moved at a breakneck pace since the outbreak began, utilizing practically all possible platforms or tactics to ensure the success of vaccines. A total of 42 vaccine candidates have already entered clinical trials, including promising results from numerous vaccine candidates in phase 1 or phase 2 trials. Further, many existing drugs are being explored on broad-spectrum antiviral medications for their use in clinical recovery against COVID-19. The present review attempts to re-examine the SARS-CoV-2 structure, its viral life cycle, clinical symptoms and pathogenesis, mode of transmission, diagnostics, and treatment strategies that may be useful for resorting to more effective approaches for controlling COVID-19. Various antiviral drugs and vaccination strategies with their strengths and weaknesses are also discussed in the paper to augment our understanding of COVID-19 management.Copyright © 2022 Bentham Science Publishers.

Diagnosis of Covid-19 from Chest X-Ray Images Using Wavelet-Based Depth Wise Convolution Network

There is a great need to create and put in place a method of automatic detection as a substitute for conventional diagnosis for COVID-19 detection that can be employed on a commercialscale because there aren't as many COVID-19 test kits availablein medical institutions. In particular, chest X-Ray scans can beexamined to assess whether a patient has COVID. Due to the availability of numerous big annotated picture datasets, convolutional neural networks have achieved remarkable success in image analysis and classification. Input is obtained in the form of chest x-rays images. Output results are acquired instantly in real-time which predicts if the person suffers from Covid or not. Modern technique use the RCNN algorithm, which makes them less precise and time-consuming. We suggest an automated deep learning-base method for extracting COVID-19 from chest X-ray pictures. For analysing the chest X-Ray pictures, suggested method offers enhanced depth-wise convolution neural network. Through wavelet decomposition, multiresolution analysis is incorporatedinto the network. In order to identify the condition, the network is given the frequency sub-bands that were recovered from the input pictures. The network's goal is to determine whether the input image belongs to the Covid-19 class or not. The Advantage of the proposed system are that it could be the very first-of its kind, cost-efficient, and highly accurate application that provide complete and accurate covid - 19 diagnosis. © 2022 IEEE.

Information Systems in Medical Settings: A Covid-19 Detection System Using X-Ray Scans

Beginning in 2020, the new coronavirus began to expand globally. Due to Covid-19, millions of individuals are infected. Initially, the availability of corona test kits was problematic. Researchers examined the present scenario and developed the Covid-19 X-ray scan detection system. In terms of Covid-19 detection, artificial intelligence (AI)-based solutions give superior outcomes. Many AI-based models can not provide optimum results because of the issue of overfitting, which has a direct impact on model efficiency. In this work, we developed the CNN-based classification method based on the pre-trained Inception-v3 for normal, viral pneumonia, lung opacity, and Covid-19 samples. In the suggested model, we employed transfer learning to produce promising results for binary class classification. The presented model attained impressive outcomes with an accuracy of 99.42% for Covid-19 vs. Normal, 99.01% for Covid-19 vs. Lung Opacity, and 99.8% for Covid-19 vs. Viral Pneumonia, and 99.93% for Lung Opacity vs. Viral Pneumonia. Comparing the suggested model to existing deep learning-based systems indicated that ours was better. © 2022 IEEE.

A Framework for Bang Saen Safe Food Avenue Management System

The coronavirus (COVID-19) epidemic has had a significant impact on people's lives and businesses. After the epidemic situation, Saensuk Sub-district, Chonburi is one area that has a need to change its tourism management. Saen Suk Municipality launched a campaign to promote Bang Saen as a "Safe Food Avenue". The pilot project began with production of an application to support a special test for formalin (FA) in sea foods which shows the result to food shops and tourists online. The FA test kit was produced and approved with accurate test results verified by a team of specialists from Burapha university. The application was developed using a responsive website technique. Specialists used the system to upload images of FA test results. Then a machine learning in image processing technique was used to analyze the test results. The Server sends the result through a RESTFUL API in JSON format to the application so that users can see the results online. The experiment using Circular Hough Transform (CHT) algorithm to detect circular shape in two-dimensional space by voting in Hough parameter with 400 data records for training. Based on the FA test result dataset, training accuracy are 100%. The SafeFoodAvenue mobile application using responsive technology FA test result's dataset accuracy is 100%. © 2022 IEEE.

Feasibility and acceptability of at-home play kits for middle school physical activity promotion during the COVID-19 pandemic.

BACKGROUND: Schools are central to providing opportunities for youth physical activity (PA), however such opportunities were limited during the COVID-19 pandemic. Identifying feasible, acceptable, and effective approaches for school-based PA promotion amid pandemic-related barriers can inform resource allocation efforts in future circumstances necessitating remote instruction. The aims of this study were to: (1) describe the pragmatic, stakeholder-engaged and theory-informed approach employed to adapt one school's PA promotion efforts to pandemic restrictions, leading to the creation of at-home "play kits" for students, and (2) assess the feasibility, acceptability, and preliminary effectiveness of this intervention. METHODS: Intervention activities occurred in one middle school (enrollment: 847) located in a Federal Opportunity Zone in the Seattle, WA area, with control data from a nearby middle school (enrollment: 640). Students at the intervention school were eligible to receive a play kit during the quarter they were enrolled in physical education (PE) class. Student surveys were completed across the school year (n = 1076), with a primary outcome of days/week that the student engaged in ≥ 60 min of PA. Qualitative interviews (n = 25) were conducted with students, staff, parents, and community partners, and focused on play kit acceptability and feasibility. RESULTS: During remote learning play kits were received by 58% of eligible students. Among students at the intervention school only, students actively enrolled in PE (versus not enrolled) reported significantly more days with ≥ 60 min of PA in the previous week, however the comparison between schools was not statistically significant. In qualitative interviews, most students reported the play kit motivated them to participate in PA, gave them activity ideas, and made virtual PE more enjoyable. Student-reported barriers to using play kits included space (indoors and outdoors), requirements to be quiet at home, necessary but unavailable adult supervision, lack of companions to play outdoors, and inclement weather. CONCLUSIONS: A pre-existing community organization-school partnership lent itself to a rapid response to meet student needs at a time when school staff and resources were highly constrained. The intervention developed through this collaborative response-play kits-has potential to support middle school PA during future pandemics or other conditions that necessitate remote schooling, however modifications to the intervention concept and implementation strategy may be needed to improve reach and effectiveness.

Relationship between SARS-CoV-2 nucleocapsid protein and N gene and its application in antigen testing kits evaluation.

More than forty antigen testing kits have been approved to response the prevalence of SARS-CoV-2 and its variant strains. However, the approved antigen testing kits are not capable of quantitative detection. Here, we successfully developed a lateral flow immunoassay based on colloidal gold nanoparticles (CGNP-based LFIA) for nucleocapsid (N) protein of SARS-CoV-2 quantitative detection. Delta strain (NMDC60042793) of SARS-CoV-2 have been cultured and analyzed by our developed digital PCR and LFIA methods to explore the relationship between N protein amount and N gene level. It indicated that the linear relationship (y = 47 ×) between N protein molecule number and N gene copy number exhibited very well (R2 = 0.995), the virus titers and N protein amount can be roughly estimated according to nucleic acid testing. Additionally, detection limits (LODs) of nine approved antigen testing kits also have been evaluated according to the Guidelines for the registration review of 2019-nCoV antigen testing reagents. Only three antigen testing kits had LODs as stated in the instructions, the LODs of Kits have been converted into the N gene and N protein levels, according to the established relationships among virus titer vers. N gene and antigen. Results demonstrated that the sensitivity of nucleic acid testing is at least 1835 times higher than that of antigen testing. We expect that the relationship investigation and testing kits evaluation have the important directive significance to precise epidemic prevention.

Accelerating COVID-19 testing: An experimental approach.

The COVID-19 pandemic, ever since its global outbreak in 2020, has continued to wreak havoc. Governments across the world were compelled to enforce strict nation-wide lockdowns, while emphasising on social distancing and quarantining suspected people in order to slow down the spread of the virus. During this time, there was a massive increase in demand for COVID-19 test kits. However, given the limited supply, countries were finding it hard to test enough people. This study proposes an approach called Encoded Blending (EB) to increase the number of tests drastically, without increasing the number of test kits. EB modifies the pooled testing method; this has been followed by countries like Germany, Israel and South Korea for mass testing their citizens. EB has the potential to reduce test kits requirement by up to 85% and 80% in a population with 5% and 10% affected cases, respectively.

Effectiveness and policies analysis of pool testing method for COVID-19

Purpose: This research aims to figure out whether the pool testing method of SARS-CoV-2 for COVID-19 is effective and the optimal sample size is in one bunch. Additionally, since the infection rate was unknown at the beginning, this research aims to propose a multiple sampling approach that enables the pool testing method to be utilized successfully. Design/methodology/approach: The authors verify that the pool testing method of SARS-CoV-2 for COVID-19 is effective under the situation of the shortage of nucleic acid detection kits based on probabilistic modeling. In this method, the testing is performed on several samples of the cases together as a bunch. If the test result of the bunch is negative, then it is shown that none of the cases in the bunch has been infected with the novel coronavirus. On the contrary, if the test result of the bunch is positive, then the samples are tested one by one to confirm which cases are infected. Findings: If the infection rate is extremely low, while the same number of detection kits is used, the expected number of cases that can be tested by the pool testing method is far more than that by the one-by-one testing method. The pool testing method is effective only when the infection rate is less than 0.3078. The higher the infection rate, the smaller the optimal sample size in one bunch. If N samples are tested by the pool testing method, while the sample size in one bunch is G, the number of detection kits required is in the interval (N/G, N). Originality/value: This research proves that the pool testing method is not only suitable for the situation of the shortage of detection kits but also the situation of the overall or sampling detection for a large population. More importantly, it calculates the optimal sample size in one bunch corresponding to different infection rates. Additionally, a multiple sampling approach is proposed. In this approach, the whole testing process is divided into several rounds in which the sample sizes in one bunch are different. The actual infection rate is estimated gradually precisely by sampling inspection in each round. © 2021, Emerald Publishing Limited.

Hybrid Transfer Learning with ECOC Ensemble Configuration for COVID-19 CXR Detection

Coronavirus Disease 2019 (COVID-19) is a viral pneumonia that causes symptoms in the lungs of those infected. The presence of the symptoms must be diagnosed as soon as possible. If no test kits are available, the next best alternative is a computer-aided diagnostic of a patient's chest X-ray scan for a quick and accurate diagnosis. This paper proposes a hybrid transfer learning method with Error-Correction Output Codes (ECOC) by combining networks including GoogLeNet, ResNet-18, and ShuffleNet for feature extraction. X-ray input data are collected from open-source repositories. In this implementations, Support Vector Machine (SVM) as the base classifier. The proposed network attempts to categorize the input data into one of three categories: COVID-19, healthy, and non-COVID-19 pneumonia. The mean accuracy of our method is 96.21%, compared fine tuning existing pre-trained model which yielded 89.1% for GoogLeNet, 88.95% for ResNet-18, and 89.31% for ShuffleNet. © 2022 IEEE.

Deep Learning Methods for Early Detection of Monkeypox Skin Lesion

As the world has not fully recovered from the aftermath of COVID-19, a new pandemic appears on the horizon. Monkey Pox is emerging as a new threat to the health of the world population. With the recorded spread over 40 countries worldwide it might be soon declared a pandemic. Monkey Pox shares common features with chickenpox and measles making it difficult to diagnose. Developing a new test kit at this early stage is a challenging task for the medical fraternity. This paper proposes the use of deep learning models that can be used to make the process of diagnosis automated. This paper tries to come up with a performance comparison of ResNet50, EfficientNetB3 and EfficientNetB7 algorithms. This study suggests a method for early detection of Monkey Pox Skin Lesion. Though an extensive study with other models on a larger dataset containing more images from various countries of the world needs to be carried out but this study gives some promising results on this limited dataset. © 2022 IEEE.

Process Intensification and Increased Safety for the On-Demand Continuous Flow Synthesis of Dithiothreitol, a Crucial Component in Polymerase Chain Reaction Testing Kits

The importance of rapid access to diagnostics tools in the identification of pathogens-including their crucial component, bioreagents-was recently underscored in the COVID-19 pandemic. The currently adopted synthesis of dithiothreitol (DTT) involves four steps in batch with long reaction times and which generates a highly carcinogenic and mutagenic bis-epoxide intermediate. In this work, we have developed an intensified telescoped three-step continuous flow synthesis of DTT involving a base-mediated ring closure epoxidation, a nucleophilic epoxide opening with thioacetic acid, and an acid-mediated deacetylation. One of the key features is that the first two steps are conducted in a telescoped continuous flow fashion, allowing generation and consumption of the hazardous intermediate in situ, suppressing the need for its isolation, and improving the overall safety of the synthesis. The process is completed by an acid-catalyzed deacetylation and a subsequent recrystallization to afford the desired DTT. Flow chemistry allows here to intensify the process by using high temperatures and high pressures while minimizing the number of unit operations and improving the overall safety of the process. Our protocol permits the on-demand production of DTT in case of future outbreaks.

Experimental investigation on the use of covid-19 waste in bituminous concrete.

The COVID-19 pandemic has resulted in unprecedented growth in the production and disposal of PPEs, face masks, gloves, face shields, and disinfectants. Daily consumption of masks and PPE has increased the plastic load on the municipality and very few plastics are taken to the recycling during the complete shut down during Covid-19. Plastic pollution is already a matter of concern that is increasing due to the negligence of humans. COVID-19 health crisis puts extra pressure on the regular waste management systems as increased daily consumption of single-use plastics around the world. It leads to the inappropriate management of waste; including mobile incineration, direct land-filling, and local burning of the waste. As the PPE kits and gowns are made of polypropylene plastic, they are non-biodegradable like any other plastics. Incineration and land-filling of plastics do not help them to degrade, even if it increases the number of pollutants in the form of microparticles. In this paper, we discussed the research procedures to utilize the waste plastic specifically Covid-19 waste which is received from the health care clinics in Bituminous concrete for the construction of flexible roads. The main objective of the study was to investigate the effectiveness of the bituminous mix modified with Polypropylene gowns waste and to compare it with the conventional bituminous mix. This research concentrated on the Maximum Stability and Flow Value of the asphalt mixture with the waste. The measurements of the Plastic of 10%, 12.5%, 15%, 17.5 %, and 20% were utilized as substitutions for the bitumen binder in the mix. From the experimental investigation, it is concluded that the optimum bitumen content is found at 10% Plastic waste with 6.5 bitumen content. Bitumen properties also increase with the addition of PPE waste. [copyright information to be updated in production process].

The Development of Mobile Application for Assisting COVID-19 Antigen Test Kit Results Reading

The antigen test kits or ATKs have been widely used for screening COVID-19 infections because they can detect and give the results quickly and can be done easily by untrained patients. However, reading ATK test results could be difficult for some people and may lead to misinterpretations of the test results. This paper presents a preliminary study for developing a mobile application for helping in reading the results of the COVID-19 ATKs from an image using algorithms based on the YOLO object detection. The results are classified into 3 classes, negative, positive, and invalid. The negative and the invalid results are further refined by using the distances between the visible line and the letters on the test cassette. Experiments were conducted to test the efficiency and accuracy of the developed model with a mean of average precision or mAP of 0.986 and an F1 score of 0.970. The model was developed and put into a prototype mobile application using tools that support cross-platform technology. © 2022 Asia-Pacific of Signal and Information Processing Association (APSIPA).

Process Intensification and Increased Safety for the On-Demand Continuous Flow Synthesis of Dithiothreitol, a Crucial Component in Polymerase Chain Reaction Testing Kits

The importance of rapid access to diagnostics tools in the identification of pathogens-including their crucial component, bioreagents-was recently underscored in the COVID-19 pandemic. The currently adopted synthesis of dithiothreitol (DTT) involves four steps in batch with long reaction times and which generates a highly carcinogenic and mutagenic bis-epoxide intermediate. In this work, we have developed an intensified telescoped three-step continuous flow synthesis of DTT involving a base-mediated ring closure epoxidation, a nucleophilic epoxide opening with thioacetic acid, and an acid-mediated deacetylation. One of the key features is that the first two steps are conducted in a telescoped continuous flow fashion, allowing generation and consumption of the hazardous intermediate in situ, suppressing the need for its isolation, and improving the overall safety of the synthesis. The process is completed by an acid-catalyzed deacetylation and a subsequent recrystallization to afford the desired DTT. Flow chemistry allows here to intensify the process by using high temperatures and high pressures while minimizing the number of unit operations and improving the overall safety of the process. Our protocol permits the on-demand production of DTT in case of future outbreaks. © 2023 American Chemical Society.

An evocative approach to utilize castoff PPE kits (Covid-19): Sustainable approach

Severe acute respiratory syndrome-corona virus-2 (SARS-CoV-2) responsible for causing Covid-19 has taken millions of life. Globally, combating COVID-19 pandemic is the primary aim of all the researchers working in any field of study viz. pharmaceutical, chemistry, physics, economics etc. One of the warrior against Covid-19 is Personal Protection Equipment (PPE), which is an indispensable requirement for healthcare workers and others working closely with Covid-19 patients. The kits are providing protection from direct infection. They are made of different types of plastics and their disposal is going to be a serious menace, if not taken care of properly. The disposal of PPE is being done as per the guidelines provided by World Health Organization. However, the final fate of polymer is yet to be decided. This study is critical suggestive approach to value add the disposed PPE kits by converting them to bio-oil. In addition to environmental advantages, it could also minimize the dependency on non-renewable fossil fuels.