An AI-enabled Bias-Free Respiratory Disease Diagnosis Model using Cough Audio: A Case Study for COVID-19 (preprint)

Cough-based diagnosis for Respiratory Diseases (RDs) using Artificial Intelligence (AI) has attracted considerable attention, yet many existing studies overlook confounding variables in their predictive models. These variables can distort the relationship between cough recordings (input data) and RD status (output variable), leading to biased associations and unrealistic model performance. To address this gap, we propose the Bias Free Network (RBFNet), an end to end solution that effectively mitigates the impact of confounders in the training data distribution. RBFNet ensures accurate and unbiased RD diagnosis features, emphasizing its relevance by incorporating a COVID19 dataset in this study. This approach aims to enhance the reliability of AI based RD diagnosis models by navigating the challenges posed by confounding variables. A hybrid of a Convolutional Neural Networks (CNN) and Long-Short Term Memory (LSTM) networks is proposed for the feature encoder module of RBFNet. An additional bias predictor is incorporated in the classification scheme to formulate a conditional Generative Adversarial Network (cGAN) which helps in decorrelating the impact of confounding variables from RD prediction. The merit of RBFNet is demonstrated by comparing classification performance with State of The Art (SoTA) Deep Learning (DL) model (CNN LSTM) after training on different unbalanced COVID-19 data sets, created by using a large scale proprietary cough data set. RBF-Net proved its robustness against extremely biased training scenarios by achieving test set accuracies of 84.1%, 84.6%, and 80.5% for the following confounding variables gender, age, and smoking status, respectively. RBF-Net outperforms the CNN-LSTM model test set accuracies by 5.5%, 7.7%, and 8.2%, respectively

Impression management and leadership in failing or failed business-to-business firms during and post-COVID-19: Empirical insights from Africa

This paper is one of the pioneering studies to specifically link COVID-19 pandemic with business failures in African B2B firms and the role of leadership and impression management in mitigating business failures. Based on the qualitative data from Ghana and Nigeria, our findings show that although B2B firms in emerging markets are agile and proactive, the COVID-19 pandemic triggered the process of business decline leading to failure in some cases. Particularly, the lack of technological know-how and the absence of online business activities made it difficult for B2B firms to continue operations. Further, we found that case B2B African firms needed a balance of market and non-market strategies to avoid failure caused by the pandemic. Study findings also indicate that despite the challenges, the COVID-19 pandemic presented opportunities to B2B firms in emerging markets. Flexible working and employee management are found to be instrumental in avoiding business failure. Finally, our findings show that, despite the absence of institutional support in African emerging markets, several case B2B firms quickly adopted digital technologies to communicate with partners and manage online business operations.

Crowd Control, Planning, and Prediction Using Sentiment Analysis: An Alert System for City Authorities

Modern means of communication, economic crises, and political decisions play imperative roles in reshaping political and administrative systems throughout the world. Twitter, a micro-blogging website, has gained paramount importance in terms of public opinion-sharing. Manual intelligence of law enforcement agencies (i.e., in changing situations) cannot cope in real time. Thus, to address this problem, we built an alert system for government authorities in the province of Punjab, Pakistan. The alert system gathers real-time data from Twitter in English and Roman Urdu about forthcoming gatherings (protests, demonstrations, assemblies, rallies, sit-ins, marches, etc.). To determine public sentiment regarding upcoming anti-government gatherings (protests, demonstrations, assemblies, rallies, sit-ins, marches, etc.), the alert system determines the polarity of tweets. Using keywords, the system provides information for future gatherings by extracting the entities like date, time, and location from Twitter data obtained in real time. Our system was trained and tested with different machine learning (ML) algorithms, such as random forest (RF), decision tree (DT), support vector machine (SVM), multinomial naïve Bayes (MNB), and Gaussian naïve Bayes (GNB), along with two vectorization techniques, i.e., term frequency–inverse document frequency (TFIDF) and count vectorization. Moreover, this paper compares the accuracy results of sentiment analysis (SA) of Twitter data by applying supervised machine learning (ML) algorithms. In our research experiment, we used two data sets, i.e., a small data set of 1000 tweets and a large data set of 4000 tweets. Results showed that RF along with count vectorization performed best for the small data set with an accuracy of 82%;with the large data set, MNB along with count vectorization outperformed all other classifiers with an accuracy of 75%. Additionally, language models, e.g., bigram and trigram, were used to generate the word clouds of positive and negative words to visualize the most frequently used words.

Achieving resilience through knowledge management practices and risk management culture in agri-food supply chains

PurposeGiven the increasingly turbulent business landscape and unprecedented incidents (e.g. Covid-19), firms must achieve supply chain resilience (SCRes) as a dynamic capability to bounce back from adversities and ensure continuity of operations. The purpose of this study is to integrate the three interrelated [knowledge management, risk management culture (RMC) and resilience] but often separately discussed concepts to advance the understanding of their intertwined influence on SCRes in the agri-food supply chains.Design/methodology/approachThis study uses a cross-sectional survey approach where quantitative data is collected from 349 participants from the Australian agri-food supply chains to test the proposed hypotheses.FindingsExposure to supply chain risks triggers the deployment of specific knowledge management practices in the agri-food supply chains. Further, the analysis on serial mediation suggests that firms' knowledge management practices work sequentially (knowledge acquisition, assimilation and application) and develop a RMC to achieve SCRes amid supply chain risks.Practical implicationsThe findings of this study inform practitioners and policymakers who seek to understand the key mechanisms that facilitate the development of SCRes when facing supply chain risks, particularly in the Australian agri-food supply chains.Social implicationsThe growth of the food industry through more resilient food supply chains could ensure sustained food supply and more employment opportunities.Originality/valueUsing dynamic capability theory, the authors devise a novel empirical model that explicates how knowledge management practices and RMC instigate the dynamic capability of SCRes amid supply chain risks facing agri-food supply chains.

Healthcare providers' experiences of continuing care for older adults with cancer during the COVID-19 pandemic.

PURPOSE: The COVID-19 pandemic has caused great strain on older adults with cancer and their healthcare providers. This study explored healthcare providers' reported changes in cancer care, clinical barriers to care, patient questions, and the overall experiences of caring for older adults with cancer during the COVID-19 crisis. METHODS: The Advocacy Committee of the Cancer and Aging Research Group and the Association of Community Cancer Centers developed a survey for healthcare providers of adults with cancer, inquiring about their experiences during the pandemic. Responses from the survey's four open-ended items were analyzed by four independent coders for identification of common themes using deductive and inductive methods. RESULTS: Participants (n = 137) represented a variety of demographic and clinical experiences. Six overall themes emerged, including (1) telehealth use, (2) concerns for patient mental health, (3) patient physical and social isolation, (4) patient fear of contracting COVID-19, (5) continued disruptions to cancer care, and (6) patients seeking guidance, particularly regarding COVID-19 vaccination. Questions fielded by providers focused on the COVID-19 vaccination's safety and efficacy during older adults' cancer treatment. CONCLUSIONS: Additional resources (e.g., technology support, established care guidelines, and sufficient staffing) are needed to support older adults with cancer and healthcare providers during the pandemic. Future research should explore universally effective in-person and virtual treatment strategies for older adults with cancer. IMPLICATIONS FOR CANCER SURVIVORS: Persistence of telehealth barriers, particularly a lack of infrastructure to support telehealth visits, social isolation, and restrictive visitor policies as a result of COVID-19, negatively impacted the mental health of older adults with cancer.

Clinical characteristics and outcomes of critically ill coronavirus disease 2019 patients in Malaysia during the first wave: A multi-center observational study (COVIDICU-MY).

Background: Coronavirus disease 2019 (COVID-19) emerged with a wide range of clinical presentations; Malaysia was not spared from its impact. This study describes the clinical characteristics of COVID-19 patients admitted to intensive care unit, their clinical course, management, and hospital outcomes. Methods: COVIDICU-MY is a retrospective analysis of COVID-19 patients from 19 intensive care units (ICU) across Malaysia from 1 March 2020 to 31 May 2020. We collected epidemiological history, demographics, clinical comorbidities, laboratory investigations, respiratory and hemodynamic values, management, length of stay and survival status. We compared these variables between survival and non-survival groups. Results: A total of 170 critically ill patients were included, with 77% above 50 years of age [median age 60, IQR (51-66)] and 75.3% male. Hypertension, diabetes mellitus, hyperlipidemia, chronic cardiac disease, and chronic kidney disease were most common among patients. A high Simplified Acute Physiology Score (SAPS) II score [median 45, IQR (34-49)] and Sequential Organ Failure Assessment (SOFA) score [median 8, IQR (6-11)] were associated with mortality. Patients were profoundly hypoxic with a median lowest PaO2/FiO2 ratio of 150 (IQR 99-220) at admission. 91 patients (53.5%) required intubation on their first day of admission, out of which 38 died (73.1% of the hospital non-survivors). Our sample had more patients with moderate Acute Respiratory Distress Syndrome (ARDS), 58 patients (43.9%), compared to severe ARDS, 33 patients (25%); with both ARDS classification groups contributing to 25 patients (54.4%) and 11 patients (23.9%) of the non-survival group, respectively. Cumulative fluid balance over 24 h was higher in the non-survival group with significant differences on Day 3 (1,953 vs. 622 ml, p < 0.05) and Day 7 of ICU (3,485 vs. 830 ml, p < 0.05). Patients with high serum creatinine, urea, lactate dehydrogenase, aspartate aminotransferase and d-dimer, and low lymphocyte count throughout the stay also had a higher risk of mortality. The hospital mortality rate was 30.6% in our sample. Conclusion: We report high mortality amongst critically ill patients in intensive care units in Malaysia, at 30.6%, during the March to May 2020 period. High admission SAPS II and SOFA, and severe hypoxemia and high cumulative fluid balance were associated with mortality. Higher creatinine, urea, lactate dehydrogenase, aspartate aminotransferase and d-dimer, and lymphopenia were observed in the non-survival group.

Clinical characteristics and outcomes of critically ill coronavirus disease 2019 patients in Malaysia during the first wave: A multi-center observational study (COVIDICU-MY)

Background Coronavirus disease 2019 (COVID-19) emerged with a wide range of clinical presentations;Malaysia was not spared from its impact. This study describes the clinical characteristics of COVID-19 patients admitted to intensive care unit, their clinical course, management, and hospital outcomes. Methods COVIDICU-MY is a retrospective analysis of COVID-19 patients from 19 intensive care units (ICU) across Malaysia from 1 March 2020 to 31 May 2020. We collected epidemiological history, demographics, clinical comorbidities, laboratory investigations, respiratory and hemodynamic values, management, length of stay and survival status. We compared these variables between survival and non-survival groups. Results A total of 170 critically ill patients were included, with 77% above 50 years of age [median age 60, IQR (51–66)] and 75.3% male. Hypertension, diabetes mellitus, hyperlipidemia, chronic cardiac disease, and chronic kidney disease were most common among patients. A high Simplified Acute Physiology Score (SAPS) II score [median 45, IQR (34–49)] and Sequential Organ Failure Assessment (SOFA) score [median 8, IQR (6–11)] were associated with mortality. Patients were profoundly hypoxic with a median lowest PaO2/FiO2 ratio of 150 (IQR 99–220) at admission. 91 patients (53.5%) required intubation on their first day of admission, out of which 38 died (73.1% of the hospital non-survivors). Our sample had more patients with moderate Acute Respiratory Distress Syndrome (ARDS), 58 patients (43.9%), compared to severe ARDS, 33 patients (25%);with both ARDS classification groups contributing to 25 patients (54.4%) and 11 patients (23.9%) of the non-survival group, respectively. Cumulative fluid balance over 24 h was higher in the non-survival group with significant differences on Day 3 (1,953 vs. 622 ml, p < 0.05) and Day 7 of ICU (3,485 vs. 830 ml, p < 0.05). Patients with high serum creatinine, urea, lactate dehydrogenase, aspartate aminotransferase and d-dimer, and low lymphocyte count throughout the stay also had a higher risk of mortality. The hospital mortality rate was 30.6% in our sample. Conclusion We report high mortality amongst critically ill patients in intensive care units in Malaysia, at 30.6%, during the March to May 2020 period. High admission SAPS II and SOFA, and severe hypoxemia and high cumulative fluid balance were associated with mortality. Higher creatinine, urea, lactate dehydrogenase, aspartate aminotransferase and d-dimer, and lymphopenia were observed in the non-survival group.

Healthcare providers' attitudes towards delay in cancer treatment during COVID-19 pandemic.

INTRODUCTION: The COVID-19 pandemic has created unprecedented obstacles leading to delays in treatment for older adults with cancer. Due to limited resources at the height of the pandemic, healthcare providers were constantly faced with ethical dilemmas regarding postponing or rescheduling care for their patients. MATERIALS AND METHODS: Two survey-based studies were conducted at different time-points during the pandemic looking at factors affecting oncology care providers' attitudes towards delay in treatment for older adults with cancer. Eligible participants were recruited by email sent through professional organizations' listservs, email blasts, and social media. Change in provider attitude over time was analyzed by comparing responses from the 2020 and 2021 surveys. Data analysis included descriptive statistics and chi-squares. RESULTS: In 2020, 17.5% of respondents were strongly considering/considering postponing cancer treatment for younger patients (age 30 and below), while 46.2% were considering delaying treatment for patients aged >85. These responses were in stark contrast to the results of the 2021 survey, where only 1.4% of respondents strongly considered postponing treatment for younger patients, and 13.5% for patients aged >85. DISCUSSION: All recommendations to postpone treatment for older adults with cancer must be made after mutual discussion with the patient. Throughout the COVID-19 pandemic, oncology care providers had to consider multiple factors while treating patients, frequently making most decisions without appropriate institutional support.

Efficient, accurate and fast pupil segmentation for pupillary boundary in iris recognition

Iris recognition is a robust biometric system—user-friendly, accurate, fast, and reliable. This biometric system captures information in a contactless manner, making it suitable for use during the COVID-19 pandemic. Despite its advantages such as high security and high accuracy, iris recognition still suffers from pupil deformation, motion blur, eyelids blocking, reflection occlusion and eyelashes obscure. If the pupillary boundary is not accurately segmented, iris recognition may suffer tremendously. Moreover, reflections in iris image may lead to an incorrect pupillary boundary segmentation. The segmentation accuracy can also be affected and reduced because of the presence of an unwanted noise created by the motion blur effect in iris image. Additionally, the pupillary boundary might change from circular shape to uneven or irregular shape because of the interference and obstruction in pupil region. Therefore, this work is carried out to determine an accurate, efficient and fast algorithm for the segmentation of pupillary boundary. First, the iris image is pre-processed with Wiener filter. Next, the respective iris image is assigned with a specific threshold. After that, the pixel property in iris image is computed to determine the pupillary boundary coordinates which are acquired from the measured pixel list and area in iris image. Finally, morphological closing is used to remove reflections in the inner region of pupil boundary. All experiments are implemented with CASIA v4 database and Matlab R2020a.

The role of dynamic capabilities and strategic agility of B2B high-tech small and medium-sized enterprises during COVID-19 pandemic: Exploratory case studies from Finland

This paper focuses on the critical role of business-to-business (B2B) high-tech small and medium-sized enterprises' (SMEs) dynamic capabilities and strategic agility during the COVID-19 pandemic. Based on the exploratory case studies of 5 Finnish high-tech SMEs, we find that the case SMEs enacted different processes and utilized resources and capabilities creatively to mitigate the impact of COVID-19 and leverage it as an opportunity. Findings indicate that agile adaptation and new opportunity utilization were the primary means of dealing with the disruptions the COVID-19 pandemic brought about. These findings indicate effective utilization of sensing and seizing capabilities and engagement with opportunity recognition and discovery to capture opportunities and deal with the impact of the pandemic on their businesses. The results further suggest that the outbreak of COVID-19 triggered a fight-or-flight survival instinct among B2B SMEs due to unprecedented levels of market uncertainty. As such, the sensing capability of B2B SMEs allowed them to identify the market threats and opportunities and understand the prevailing market situation. Accordingly, B2B SMEs seized the identified threats and opportunities by reconfiguring their business models and face-to-face and online operations. The digital technologies facilitated the online presence and promoted communication with existing and new customers. Interesting implications emerge from these findings.

Mapping research on healthcare operations and supply chain management: a topic modelling-based literature review.

The literature on healthcare operations and supply chain management has seen unprecedented growth over the past two decades. This paper seeks to advance the body of knowledge on this topic by utilising a topic modelling-based literature review to identify the core topics, examine their dynamic changes, and identify opportunities for further research in the area. Based on an analysis of 571 articles published until 25 January 2022, we identify numerous popular topics of research in the area, including patient waiting time, COVID-19 pandemic, Industry 4.0 technologies, sustainability, risk and resilience, climate change, circular economy, humanitarian logistics, behavioural operations, service-ecosystem, and knowledge management. We reviewed current literature around each topic and offered insights into what aspects of each topic have been studied and what are the recent developments and opportunities for more impactful future research. Doing so, this review help advance the contemporary scholarship on healthcare operations and supply chain management and offers resonant insights for researchers, research students, journal editors, and policymakers in the field.

Vulnerability of weather on COVID-19 pandemic in West Java Indonesia

COVID-19 is a pandemic that spreads very fast. Until now COVID-19 has spread in 207 countries. This study aimed to analyze the correlation between weather factors and COVID-19 in West Java Indonesia. This study used a secondary data analysis of weather data from the Meteorological Department of the Republic of Indonesia and surveillance of COVID-19 from the Ministry of Health of the Republic of Indonesia. The weather has five components including minimum temperature (0C) maximum temperature (0C) temperature average (0C) humidity (%) amount of rainfall (mm) and wind speed (m/s). Data were analyzed using Spearman’s rank correlation test. Result: Of the weather components only temperature average (r = 0.545;p 0.001) and humidity (r = -0.500;p 0.001) significantly correlated with COVID-19. The results can be used to decrease the pandemic of COVID-19 in Indonesia.

Reimagining global food value chains through effective resilience to COVID-19 shocks and similar future events: A dynamic capability perspective.

The restructuring of global value/supply chains gained increasing attention as the unprecedented COVID-19 echoed around the world. Yet, the COVID-19 related theory-driven, large scale quantitative, and empirical studies are relatively scarce. This study advances the extant literature by empirically investigating how do firms in the global food value chains (GFVCs) re-imagine their businesses structure in response to the COVID-19-becoming more resilient and competitive to the current pandemic and similar future events. We leverage a unique data of 231 senior managers of the Australian GFVCs and examine their firms' response strategies. Drawing upon key insights from the dynamic capability view, we find that GFVCs' competitiveness is achieved when exposure to COVID-19 shocks elicits dynamic capabilities-readiness, response, recovery-and these capabilities work jointly and sequentially to cultivate resilience. A key finding of this study is that firms with domestic plus global value chain partners are more resilient than those having only global business partners. This finding implies that excessive reliance on offshoring sometimes becomes lethal, especially amid unexpected and prolonged global shocks and, therefore, companies should strike a balance between domestic and global business partners to remain competitive. These findings offer important contributions to theory, practice, and UN sustainable development goals.

Bronchopleural Fistula as a Complication in a COVID-19 Patient Managed With Endobronchial Valves.

Bronchopleural fistula (BPF) is associated with high morbidity if left untreated. Although rare, the frequency of BPF in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is becoming recognized in medical literature. We present a case of a 64-year-old male with BPF with persistent air leak due to SARS-CoV-2 pneumonia treated with Spiration Valve System endobronchial valve (EBV). An EBV was placed in the right middle lobe with successful cessation of air leak. In conclusion, the use of EBVs for BPF with persistent air leaks in SARS-CoV-2 patients who are poor surgical candidates is effective and safe.

Antiviral Strategies Using Natural Source-Derived Sulfated Polysaccharides in the Light of the COVID-19 Pandemic and Major Human Pathogenic Viruses.

Only a mere fraction of the huge variety of human pathogenic viruses can be targeted by the currently available spectrum of antiviral drugs. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak has highlighted the urgent need for molecules that can be deployed quickly to treat novel, developing or re-emerging viral infections. Sulfated polysaccharides are found on the surfaces of both the susceptible host cells and the majority of human viruses, and thus can play an important role during viral infection. Such polysaccharides widely occurring in natural sources, specifically those converted into sulfated varieties, have already proved to possess a high level and sometimes also broad-spectrum antiviral activity. This antiviral potency can be determined through multifold molecular pathways, which in many cases have low profiles of cytotoxicity. Consequently, several new polysaccharide-derived drugs are currently being investigated in clinical settings. We reviewed the present status of research on sulfated polysaccharide-based antiviral agents, their structural characteristics, structure-activity relationships, and the potential of clinical application. Furthermore, the molecular mechanisms of sulfated polysaccharides involved in viral infection or in antiviral activity, respectively, are discussed, together with a focus on the emerging methodology contributing to polysaccharide-based drug development.

A Bra Monitoring System Using a Miniaturized Wearable Ultra-Wideband MIMO Antenna for Breast Cancer Imaging

This paper represents a miniaturized, dual-polarized, multiple input–multiple output (MIMO) wearable antenna. A vertically polarized, leaf-shaped antenna and a horizontally polarized, tree-shaped antenna are designed, and the performance of each antenna is investigated. After designing the MIMO antenna, it is loaded with stubs, parasitic spiral, and shorting pins to reduce the coupling effects and remove the unwanted resonances. Afterward, the two-port MIMO cells are spaced by 2 mm and rotated by 90° to create three more cells. The antennas are designed using two layers of denim and felt substrates with dielectric constants of 1.2 and 1.8, and thicknesses of 0.5 mm and 0.9 mm, respectively, along with the ShieldIt™ conductive textile. The antenna covers a bandwidth of 4.8–30 GHz when the specific absorption rate (SAR) meets the 1 g and 10 g standards. Isolation greater than 18 dB was obtained and mutual coupling was reduced after integrating shorting pins and spiral parasitic loadings. A maximum radiation efficiency and directive gain of 96% and 5.72 dBi were obtained, respectively, with the relatively small size of 11 × 11 × 1.4 mm3 for the single element and final dimensions of 24 × 24 × 1.4 mm3 for the full assembly. The antenna’s performance was examined for both on-body (breast) and free space conditions using near-field microwave imaging. The achieved results such as high fidelity, low SAR, and accuracy in localization of the tumour indicate that the MIMO antenna is a decent candidate for breast cancer imaging.

Effect of viral infection on brain functions and Psychological Impact of the COVID-19 on our thinking and mood (preprint)

Background: Viral infections such as measles virus (MV), herpes virus, and human immunodeficiency virus (HIV) can lead to transient or permanent neurological or psychiatric dysfunction. However, respiratory system affecting viruses have appeared as an unbeatable challenge to the modern world. They include the human respiratory syncytial virus (hRSV), the influenza virus (IV), and the coronavirus (CoV). They cause acute respiratory infections mainly children under 5 years old and also the elderly. The most frequent clinical manifestations are febrile or afebrile seizures, status epilepticus, encephalopathies, and encephalitis. Objective: The objective of this review is to assess the effect of COVID-19 on our mood and thinking during this pandemic. Method: We reviewed the literature using different databases e.g., Google Scholar, PubMed, and Science direct etc. Results: Viral Infections badly affect the nervous system functions and ultimate can lead to the onset of neurological and psychological illnesses. Conclusion: COVID-19 is somehow causing depression, anxiety, panic attacks, and stress. As a consequence, social distancing has increased that has ultimately modified our thinking style, mood and has lead to the psychological, emotional and behavioral changes. Review Criteria We reviewed the literature using different databases e.g., Google Scholar, PubMed, etc. from 1997 to 2021 without language limitations. Message for the clinic It is clear that COVID-19 causes cardiac, respiratory, renal, and gastrointestinal dysfunctions and has also a direct effect on brain functioning resulting in psychological and behavioral changes. Along with other dysfunctions, it has severely affected the living style of people and brought depression, anxiety, panic attacks, loneliness, and self-deprecation. It is highly recommended that while treating such patients, all these aspects should be kept in mind. Hence, not only medication can ameliorate the side impacts of this infection but counseling is another tool to bring positive impact in those respondents.

Innovative method used in modern time for the treatment of hospital wastewater

With the advent of technologies in many countries, pharmaceutically active compounds (PhAC), personal care products (PPCPs), and other medicines have been treated by particular facilities. Although the overall rate of PhACs extraction from hospital wastewater (HWW) through different secondary wastewater treatment plants (WWTPs) has been high equal to 79–99%, activity and proliferation of neurotransmitters are inhibited by antiseptics due to the low removal rate of some elements, such as naproxen, excellent-performance technologies are still needed. Venlafaxine and citalopram are the most used antidepressants associated with 10–12% removal value through WWTPs. While HWW contains various types of antibiotics, they improve biocides’ bacterial tolerance against treatment. Ozonation is one of the methods to enhance biodegradability, whereas biofilm reactors have effectively removed emerging contaminants (ECs). Combined activate sludge (CAS) and membrane filtration bioreactors will potently exclude compounds, but previous studies show that membrane filtration bioreactors are around 30%-55% more efficient. ECs elimination in tertiary treatment has shown its great ability rather than conventional treatment sectors. Moreover, ozone treatment can decrease in PPCPs value as 90–98% through activated carbon beds. Activated carbon (NAC) has shown its full capability for micropollutants removal from PAC and membrane bioreactors as well as PPCP reside removal from treated effluents. The ratio of infect COVID-19 in one area was directly proportional, as revealed by SARS-CoV-2 detection in both HWW and wastewater in almost all countries. In this research study, multiple treatment techniques are evaluated in order to offer great-performance technology. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Environmental Analytical Chemistry 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 abstract 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 abstract. (Copyright applies to all Abstracts.)