Clinician satisfaction and experience using teleconsultation during the COVID-19 pandemic in Pakistan: A cross-sectional study

Aims: During the pandemic of COVID-19, the sudden change in traditional health-care providing systems, clinicians experience some positive and negative aspects of the approach. This study evaluates the clinician's satisfaction and experience with the use of teleconsultation provided during the pandemic of novel coronavirus and their willingness to continue telehealth after the pandemic. Materials and Methods: A cross-sectional survey was conducted online during the peak pandemic of COVID-19 in Pakistan through Google Forms questionnaire from 115 health consultants on different disciplines and recruited through social media. The questionnaire contains 15 questions regarding clinician's satisfaction, quality of treatment, and intention to continue providing telehealth services after the pandemic. Descriptive and inferential statistics were obtained by analyzing the data using SPSS software version 20, USA. Results: One hundred and fifteen consultants, 28 males and 87 females participated in the study, in which 62% were found to have an average and 34% at a high level of satisfaction. The Kruskal-Wallis test showed a significant difference among different medical specialists in the continuation of telehealth services after the pandemic of COVID-19 (P = 0.003) and its recommendation to friends and family (P = 0.02) with high mean rank in endocrinologist and dermatologist. Conclusions: A great number of participants reported a good response for the continuation in telemedicine services in their daily routine even after the pandemic situation. However, there is an urgent need to find the solution for the difficulties and drawbacks faced by health-care providers.

Assessment of changes in air quality in Bangalore, India, during the Covid-19 pandemic lockdown: Statistical modelling

COVID-19 pandemic has resulted in a halt to the daily lifestyle of people around the world and bound them to abide by the lockdown measures enforced to prevent the disease from further spreading. In India also, lockdown has been enforced from March 2020. As a result, the level of air pollutants in the atmosphere goes on decreasing. To know the air quality pattern of Bangalore city, ten stations around the city were selected. Air quality data of these stations has been availed from the Central Pollution Control Board (CPCB) of India website. Box chart concept of graphical representation has been applied to show the range of temporal variation of the air pollutants selected (CO, NO2, Ozone, PM2.5, PM10 and SO2) for the study area over two distinct periods (pre-lockdown and post-lockdown). It has been observed that all the pollutants level were drastically or significantly reduced except for SO2 which showed mixed behavior during the entire study period probably due to no restriction on the operation of power plants. GIS based contour mapping is done for each pollutant over the entire study area and separately for two distinct periods (pre-lockdown and post-lockdown). It was found that, change in CO level over the entire study area was significant and the reason behind it was complete restriction on vehicular movement which is the primary reason for CO emission in atmosphere. Reduction in PMs and ozone was also noticeable, but change in SO2 over the entire study area was almost insignificant. To find out the probable sources of pollution during the lockdown and before the lockdown period and the most significant parameters statistical approach has been adopted. The whole data set has been grouped based on similarity and divided into three distinct clusters for both pre-lockdown and post-lockdown period separately using Hierarchical Agglomerative Cluster Analysis (HACA) concept. Principal Component Analysis (PCA) was done for each of the clusters and each time period considered. From the results of PCA it can be confirmed that the most significant parameters were PM10, PM2.5, ozone and SO2. Results suggest that the probable sources of pollution during pre-lockdown period were vehicular emissions, power plants, industrial activities etc. In contrast, during post-lockdown period the sources of pollution were power plants, construction sites and household pollution only. MLR (Multiple Linear Regression) models were developed to predict Air Quality Index (AQI). Most of the models showed good fit with adjusted R2 value more than 0.9. Regression coefficient (R2) values for PM10 followed PM2.5 were highest in each cluster. © 2023 Author(s).

Ensemble Deep Learning Framework for Situational Aspects-Based Annotation and Classification of International Student's Tweets during COVID-19

As the COVID-19 pandemic swept the globe, social media plat-forms became an essential source of information and communication for many. International students, particularly, turned to Twitter to express their struggles and hardships during this difficult time. To better understand the sentiments and experiences of these international students, we developed the Situational Aspect-Based Annotation and Classification (SABAC) text mining framework. This framework uses a three-layer approach, combining baseline Deep Learning (DL) models with Machine Learning (ML) models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset. Using the pro-posed aspect2class annotation algorithm, we labeled bulk unlabeled tweets according to their contained aspect terms. However, we also recognized the challenges of reducing data's high dimensionality and sparsity to improve performance and annotation on unlabeled datasets. To address this issue, we proposed the Volatile Stopwords Filtering (VSF) technique to reduce sparsity and enhance classifier performance. The resulting Student-COVID Twitter dataset achieved a sophisticated accuracy of 93.21% when using the random forest as a meta-classifier. Through testing on three benchmark datasets, we found that the SABAC ensemble framework performed exceptionally well. Our findings showed that international students during the pandemic faced various issues, including stress, uncertainty, health concerns, financial stress, and difficulties with online classes and returning to school. By analyzing and summarizing these annotated tweets, decision-makers can better understand and address the real-time problems international students face during the ongoing pandemic.

Spectrum of echocardiographic findings in patients with severe and critical COVID-19: a single center experience

Introduction: Information on the cardiac manifestations of coronavirus disease 2019 (COVID-19) is scarce. In this study we assessed the echocardiogram of consecutive patients with COVID-19 infection to assess the frequency of cardiac abnormalities. Materials and Methods: This retrospective descriptive study examined the echocardiographic study of 43 patients with severe and critical COVID-19 infection admitted at the ICU of Chitwan Medical College from May 16, 2021 to June 05, 2021. The study focused on left ventricle (LV) and right ventricle (RV) function. The results were then compared between severe and critical infections to examine if any differences exist between them. Results: The mean age of the study population was 54 years and predominately males. One-third were classified as critical COVID-19 while the remaining were severe COVID-19. Majority(83.7%) had a normal echocardiogram. Among the patients with abnormal reports, the distribution of echocardiographic pattern were biventricular dilation with biventricular dysfunction in two patients (4.6%), LV dialtion with LV dysfunction in two patients (4.6%) and isolated LV dysfunction (diastolic and systolic) in three patients (6.9%). None of the echocardiographic parameters were significantly different between the severe and the critical infection. Conclusion: COVID-19 in primarily a respiratory disease and the cardiac complications is largely attributed to the critical nature of the illness than the specific infection. Considering the risk of infection spread, routine echocardiography for all patients with COVID-19 infection is not advisable.

Impact of Covid-19 on the Prevalence of Intrahepatic Cholestasis of Pregnancy

Background: The virulent pathogen SARS-CoV-2 first appeared in the Chinese province of Hubei in December 2019. Pregnant women were a high-risk population in the pandemic because immune system alterations that occur during pregnancy make them more vulnerable to foreign infections. Late-pregnancy cholestasis is a dangerous liver condition that can cause the foetus to experience potentially fatal problems like early birth and stillbirth. In the present study we were testing the Bile acid level during pregnancy patients after covid pandemic. Objective(s): To evaluate the prevalence of intrahepatic cholestasis in pregnant patients after Covid -19 pandemic. Material(s) and Method(s): This cross-sectional study was conducted at department of Dr.fida painless and General Hospital Peshawar from jan 2022 to Dec 2022. We enrolled 186 pregnant patients after fulfilling the inclusion criteria. 5 ml blood sample were also taken from the patients. Serum was extracted and Bile acid test were performed in clinical laboratory. Data were collected in predesign questionnaire. Result(s): Total 186 patients were enrolled in the study with mean age of 37.18+/-6.39 years (Range 18-45 years). The mean value of all enrolled patients was 31.38+/-5.79 with minimum and maximum value of bile acids 20 micromol/L and 40.6.00 micromol/L. In our study 95 (56.5%) of patients belongs to 36 to 45 years of age group followed by age group of 26 to 35 years in which 60 (35.7%) patients and 13 (7.7%) patients were belongs to age group of 18 to 25 years. Practical implication: This study will help the clinical practitioner to take care of pregnant patients in order to avoid the prevalence of intrahepatic cholestasis. Conclusion(s): It is concluded from this research study that prevalence of intrahepatic cholestasis in pregnancy has increased after Covid-19 pandemic.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

Comparison of Knowledge and Practices among University Students of Allied Health Sciences and Engineering Departments in University of Lahore, Pakistan about Corona Virus Disease

Background: Corona Viruses is a group of viruses that cause diseases in both humans and mammals and are known to cause chronic respiratory diseases. The viruses among them include SARS, MERS and COVID-19. The most recent pandemic was a result of COVID-19. Older people and those with underlying medical problems are more likely to develop serious illness. Objective(s): To compare the knowledge and practices of Allied Health and Engineering students of the University of Lahore about Corona Virus Disease. Methodology: A cross-sectional questionnaire based survey was conducted on 326 students studying in Allied health Sciences and Engineering departments of UOL. The data was compiled in SPSS, version 24 for analysis. Result(s): The students of Allied Health Sciences had a better understanding and were more aware of COVID-19, its percussions and the methods to prevent its spread than of the Engineering Students. More than half of the Engineering students have found to have less understanding about the causative agent of the COVID-19 and similar trend was found in other categories. Health sciences students showed higher tendency towards hands hygiene practices than engineering students. Practical implication: Lessons learned from different outbreaks of infectious diseases suggested that knowledge and practices towards infectious diseases are associated with level of panic emotion among the population, which can further complicate attempts to prevent the spread of the disease. To facilitate outbreak management of COVID-19 in Lahore, Pakistan, there is an urgent need to understand the public's awareness of COVID-19. Keeping these considerations in mind this research was kicked-off to gauge the knowledge and practices of these medical and engineering students about Corona virus disease. Conclusion(s): The study shows that educational background plays a vital role in disease control and it will help in successful uptake of control interventions for prevention of COVID-19.Copyright © 2023 Lahore Medical And Dental College. All rights reserved.

Large-Scale Urban Heating and Pollution Domes over the Indian Subcontinent

The unique geographical diversity and rapid urbanization across the Indian subcontinent give rise to large-scale spatiotemporal variations in urban heating and air emissions. The complex relationship between geophysical parameters and anthropogenic activity is vital in understanding the urban environment. This study analyses the characteristics of heating events using aerosol optical depth (AOD) level variability, across 43 urban agglomerations (UAs) with populations of a million or more, along with 13 industrial districts (IDs), and 14 biosphere reserves (BRs) in the Indian sub-continent. Pre-monsoon average surface heating was highest in the urban areas of the western (42 degrees C), central (41.9 degrees C), and southern parts (40 degrees C) of the Indian subcontinent. High concentration of AOD in the eastern part of the Indo-Gangetic Plain including the megacity: Kolkata (decadal average 0.708) was noted relative to other UAs over time. The statistically significant negative correlation (-0.51) between land surface temperature (LST) and AOD in urban areas during pre-monsoon time illustrates how aerosol loading impacts the surface radiation and has a net effect of reducing surface temperatures. Notable interannual variability was noted with, the pre-monsoon LST dropping in 2020 across most of the selected urban regions (approx. 89% urban clusters) while it was high in 2019 (for approx. 92% urban clusters) in the pre-monsoon season. The results indicate complex variability and correlations between LST and urban aerosol at large scales across the Indian subcontinent. These large-scale observations suggest a need for more in-depth analysis at city scales to understand the interplay and combined variability between physical and anthropogenic atmospheric parameters in mesoscale and microscale climates.

Drug Repurposing in COVID-19 and Cancer: How Far Have We Come?

Drug repurposing is a strategy for ascertaining new implications for already approved drugs. Historically, this field started with the serendipitous and inadvertent findings of a drug that was found to have an effect other than its original indication that was previously unrecognized and that had potential application in an entirely different disease. The fact that the rate of failure associated with the development of new drugs is high and the funds needed are enormous, it has compelled the scientific fraternity to look for alternatives and thus the drug repurposing approach has gained traction in the scientific community. The havoc that COVID-19 wreaked is unprecedented and till date it has led to the death of around 5.7 million people worldwide. The scientific fraternity, the world over, has embarked on the journey of getting a sure shot treatment for this deadly disease and till date many studies have been published discussing the role of various repurposed drug candidates in COVID-19 treatment. A majority of these studies have been carried out using structural bioinformatics and have not been validated by in vitro experiments. There is a pressing need for the treatment of COVID-19 disease using repurposed drugs by experimental validation and clinical testing, and augmented by the modern Machine Learning (ML)-and Artificial Intelligence (AI)-based approaches. A number of drug candidates have been investigated for their potential applications in cancer therapy, however the conundrum about the utility of either repurposed drug candidates or only active anti-cancer drugs for cancer therapy is to be pursued thoroughly so that mankind gets the most out of whatever potential the drug candidates, whether old or new, have in store for us. This chapter discusses the utility of drug repurposing approach as an alternative strategy for drug discovery that is intended to find treatment for new and emerging infectious diseases, viz. COVID-19 and cancer. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Is Remdesivir-Induced Symptomatic Bradycardia Persistent? A Two Case Report of COVID-19 Infection

As of May 2022, a total of over 528 million cases of coronavirus 19 disease (COVID-19) worldwide with over 6 million deaths. Remdesivir is a broad-spectrum antiviral medication approved worldwide;it acts by inhibiting the RNA-dependent RNA polymerase, used for moderate-to-severe COVID-19 which requires supplemental oxygen but not intubation. Not shown to improve mortality but shorten the recovery time, especially if given within the first 10 days of symptom initiation. Despite its worldwide use, its cardiovascular safety profile has not been determined as yet. Herein, we report two cases of COVID-19 infection who develop symptomatic bradycardia on a 5-day course of remdesivir.Copyright © 2022 Annals of Clinical Cardiology Published by Wolters Kluwer - Medknow.

Cellular Therapy Applications for COVID-19

COVID-19 is caused by infection with the novel coronavirus SARS-CoV2, which in turn precipitates severe acute respiratory distress syndrome (ARDS) due to being associated with a cytokine release syndrome (CRS). Inflammatory endothelialitis is also implicated in disease pathophysiology. Cell-based therapy (CBT) is undergoing testing in numerous mechanistic and pivotal clinical trials due to its known immunomodulatory properties. Culture-expanded mesenchymal stem cells (CD105+ cells) may be safely administered as an allograft and can suppress exuberant immune responses, improve endothelial function, and boost T- and B-cell responses. Early-stage open-label trials have reported potential clinical responses, and pivotal trials have been rapidly initiated. Coupled with the known safety profile, CBT may emerge as a valuable addition to the therapeutic armamentarium for SARS-CoV2. © Springer Nature Switzerland AG 2009, 2022, Corrected Publication 2022.

A Rare Case of Congenital Choledochal Cyst (CCC) Resulting in Recurrent Acute Pancreatitis in an Otherwise Healthy Young Woman

Introduction: Congenital choledochal cyst (CCC) is a rare cystic dilatation of intrahepatic or extrahepatic biliary ducts. We present a case of a type IVb choledochal cyst presenting as recurrent acute pancreatitis in a young healthy female with initial negative screenings. Case Description/Methods: An 18-year-old-female with a history of COVID-19 presented to the emergency department with one month of persistent abdominal pain, nausea, and vomiting. She was hospitalized once prior for similar symptoms and was diagnosed with acute pancreatitis. This admission, blood work showed elevated lipase, elevated liver enzymes, mild bilirubinemia with a normal lipid panel and urine was significant for infection. She received fluids, antiemetics and was started on prophylactic antibiotics for ascending cholangitis. A right upper quadrant ultrasound ruled out cholelithiasis or acute cholecystitis, but showed dilation of the common bile duct. MRCP confirmed dilation with bulbous termination in the periampullary region diagnosed as type IVb choledochal cyst. Discussion(s): CCCs are rare in Western countries with an incidence between 1 in 100,000 to 150,000. 80% of these cysts are diagnosed in patients under the age of 10. They are difficult to diagnose due to variable clinical presentations. A study of 214 CCC patients demonstrated the most common symptom was abdominal pain, followed by jaundice and fever. When cysts are found in adults, symptoms resemble atypical acute biliary tract disease. Surgical cyst removal may be needed for patients with significant risk factors such as older age and age of symptom onset, due to increased risk of malignant transformation. Longer periods of observation have been documented to be associated with an increased chance of developing late complications, such as anastomotic stricture, biliary calculi and recurrent cholangitis. Type IVb CCCs, as seen in this case, consist of multiple extrahepatic cysts and hepaticojejunostomy is the treatment. This patient's young age and recurrent acute pancreatitis combined with her lab and imaging findings strongly suggest the diagnosis of CCC. The anatomical location of the CCC impeded flow of pancreatic enzymes through the ampulla of vater, leading to recurrent pancreatitis in an otherwise healthy young female. CCC, although very rare, should be considered in the differential of acute pancreatitis when other causes such as gallstones and heavy alcohol consumption cannot be identified, as prompt diagnosis and surgical removal is imperative.

A Shuffling Building Block and Augmentation Parameter Tuning Techniques to Handle Small Medical Dataset

The recent COVID-19 outbreak showed us the importance of faster disease diagnosis using medical image processing as it is considered the most reliable and accurate diagnostic tool. In a CNN architecture, performance improves with the increasing number of trainable parameters at the cost of processing time. We have proposed an innovative approach of combining efficient novel architectures like Inception, ResNet, and ResNet-Xt and created a new CNN architecture that benefits Extreme Cardinal dimensions. We have also created four variations of the same base architecture by varying the position of each building block and used X-Ray, Microscopic, MRI, and pathMNIST datasets to train our architecture. For learning curve optimization, we have applied learning rate changing techniques, tuned image augmentation parameters, and chose the best random states value. For a specific dataset, we reduced the validation loss from 0.22 to 0.18 by interchanging the architecture's building block position. Our results indicate that image augmentation parameters can help to decrease the validation loss. We have also shown rearrangement of the building blocks reduces the number of parameters, in our case, from 5,689,008 to 3,876,528. © 2023 IEEE.

A Fractional Order Covid-19 Epidemic Model with Mittag–Leffler Kernel

We consider a nonlinear fractional-order Covid-19 model in a sense of the Atagana–Baleanu fractional derivative used for the analytic and computational studies. The model consists of six classes of persons, including susceptible, protected susceptible, asymptomatic infected, symptomatic infected, quarantined, and recovered individuals. The model is studied for the existence of solution with the help of a successive iterative technique with limit point as the solution of the model. The Hyers–Ulam stability is also studied. A numerical scheme is proposed and tested on the basis of the available literature. The graphical results predict the curtail of spread within the next 5000 days. Moreover, there is a gradual increase in the population of protected susceptible individuals. [ FROM AUTHOR] Copyright of Journal of Mathematical Sciences is the property of Springer Nature 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.)

Incidence of COVID-19 Infection in Nurses and their Families: A Prospective Cohort Study in Lahore

Background: Nurses, as frontline workers, are at a higher risk of contracting COVID19 and serve as a potential source of transmitting this infection to their family members. Estimating risk in this population is critical for controlling the rate of secondary attack rate among their families.Objective: To measure the incidence of COVID-19 in nurses and their families with associated risk factors for transmission of infection.Methods: A prospective cohort study was conducted in Akhtar Saeed Medical and Dental college, Lahore and associated three hospitals. A cohort of 176 nurses was identified in March 2020 by using non-probability convenience sampling technique and was followed till September 2021. During this tenure of one and a half year, incidence was observed by following the cohort and using a self-structured questionnaire. With SPSS 23, Chi square test was applied and p value of < 0.05 was considered significant.Results: In a cohort of 176 nurses, followed for one and a half year, incidence of COVID-19 was 37(21%). Secondary attack rate among household members of these nurses was 3%. A significant association was observed between the nursing staff and exposure to their family members (p = 0.002). Vaccination rate in nurses at the start of the study was only 26%. Nurses who worked directly with COVID-19 patients reported high incidence (p = 0.009). Nurses who used Personal protective equipment (PPE) were less affected (p = 0.003). Nurses with comorbidities showed higher incidence (p =0.02). Rate of psychological distress was high (p =0.007).Conclusion: Incidence of COVID-19 among nurses was 21% with secondary attack rate of 3% in families. Protective use of N 95 mask and comorbidities were associated with incidence.

Study of Covid-19-Related Ecological Habitat of College Students: A Survey

In recent years, the interaction of people with the surrounding ecological environment has become increasingly unsafe for health, namely the person' physical and mental capabilities. This is especially true of the younger generation, like students of higher educational institutions, who have weakened immunity due to a busy study schedule, constant mental overload and stress. That is, health, as a sign of the quality of life of a student, is associated with the ecological situation and lifestyle, therefore, is one of the main concepts of human ecology. The influence of additional negative factors, such as stress and restrictions associated with the Covid-19 pandemic, greatly increases the risk of developing students' mental health problems. Unexpected isolation related to Covid-19 has caused disruption to daily routines, especially in students. The sudden change in the learning environment and limited social interactions and activities posed an unusual situation for children's developing brains. The study aim is to investigate and identify the psychological threats posed by students of different ages (under 20, between 21-25, and 26-32) in this pandemic of COVID-19. It was found that 28.0% of students were often nervous and stressed in the age group under 20, in contrast to 26.5% and 11.1% in groups 21 to 25 and over 26, respectively. In the younger group of students, 10.2% of students never felt upset, in the group of 21-25 years old - 8.3% and over 26 years old - 5.6%. It was concluded that it is mandatory to assess the student's psychological health and to plan for necessary support mechanisms, mainly during the recovery phase, because depression, stress, fear of getting infected, fear of losing a loved one, fear about getting jobs and related academic issues, disturbance in sleeping pattern, increase in duration of screen time, etc., were found to be common among students of all age groups.

COVID-19 Versus Diabetes Mellitus: Whom Affect the Other?

Diabetes is considered as a precipitating factor for the poor outcomes of COVID-19. Patients with diabetes had a 2.5-3.9 times higher odds of being infected. Viral infection in diabetic patients could be harder to treat due to fluctuations in blood glucose levels. Their compromised immune system leads to a longer duration of recovery. Furthermore, poorly controlled diabetes impairs the immune response to viral infections. C-reactive protein, IL-6, and D-dimer are inflammatory biomarkers elevated among diabetic patients infected with COVID-19.Many scenarios could explain;how could COVID-19 induce Type 1 diabetes? and how COVID-19 brings out Type 2 diabetes? There is lack of data regarding pancreatic abnormalities and manifestation in COVID-19 patients. Hence, further investigations are required to stand on the consequences of COVID-19 in subjects with prediabetes and patients with diabetes. Losing at least 15 pounds, regular physical exercise, control diet and regular checkup are the most important measures for prevention of diabetes after COVID-19. Regular monitoring of blood sugar levels after COVID-19 illness and control of hyperglycemia as early as possible are essential to avoid development of severe complications and poor outcome. Appropriate management of comorbidities is of great significance in mitigating the COVID-19 pandemic. Diabetic patients must have priority for vaccination against COVID-19. CDC recommends that people with underlying medical conditions including diabetes should receive a third dose of COVID-19 Vaccine at least 3-6 months after completion of their second dose series.

Knowledge of Antibiotic Use and Antibiotic Resistance During the COVID-19 Pandemic Among Healthcare Professionals

Infections can be treated with antibiotics, which have also saved countless lives. But whenever antibiotics are administered, they run the risk of having negative side effects and fueling antibiotic resistance that was a significant public health issue. The current study aimed to describe healthcare workers' knowledge of antibiotic use and resistance during the COVID-19 epidemic in the city of Riyadh and included an online survey that was disseminated on social media. About 78% of the healthcare providers in the present study had an average knowledge score of more than 75%, so most of them had good knowledge. Most of the healthcare professionals in the present study had good knowledge about bacterial resistance and antibiotic use, but there was still a knowledge gap on antibiotic use. Therefore, it is crucial to raise their awareness by attending conferences, lectures, and workshops.

Using Landfill Sites and Marginal Lands for Socio-Economically Sustainable Biomass Production through Cultivation of Non-Food Energy Crops: An Analysis Focused on South Asia and Europe

Food security and energy transition are among the current major global environmental challenges. Although these issues individually are significant in their own right, they are connected to each other in a nexus with different interrelationships and dependencies. In the quest for non-fossil alternatives for energy, cultivation of bioenergy crops has become an important part of the energy policy in many countries. In this regard, the use of fertile agricultural land for growing crops for energy production rather than for food supply affects the global food security. Recent conflicts and the geopolitical crisis in Europe, leading to increased food, fuel, and fertiliser prices, the existing climate crisis, and the crisis caused due to the COVID-19 pandemic, have further reinforced the understanding of this nexus, with certain countries mulling limiting biofuel production from agricultural land and others banning food grain exports to safeguard food supply. The idea of growing non-food energy crops on marginal lands in general and closed landfill sites in particular is hence ever more relevant, to avoid land-use concurrence between food needs and energy needs. Landfilling has been the dominant waste management strategy until recently in European countries and is still the dominant mode of waste management in low-income regions like South Asia. This paper provides a review of the economic as well as environmental benefits of growing Ricinus communis L., Jatropha curcas L., and Populus deltoides as energy crops on closed landfill sites in the South Asian context. While as the cultivation of Miscanthus X Giganteus, Silphium perfoliatum L., and Panicum virgatum (Switchgrass) is reviewed in the European context. The cultivation of non-food energy crops like these on closed landfill sites and marginal lands is presented as a potential component of an integrated food-energy policy, with an increased relevance in the current times. In the current times of multiple crises, this measure is of increasing relevance as a part of the overall strategy to achieve resilience and environmental sustainability.