Partial stratified ranked set sampling scheme for estimation of population mean and median.

Ranked set sampling is an alternative to simple random sampling, which uses the least amount of money and time. The ranked set sampling (RSS) is modified to obtain a more efficient and cost-effective estimator of population parameters. This paper aims to bring a more efficient and cost-effective design than stratified ranked set sampling and simple random sampling. In some distributions, the suggested method used fewer sample units than stratified ranked set sampling and gives a more efficient estimation of population parameters. In symmetric distributions, the proposed design, called "partial stratified ranked set sampling" yields an unbiased estimator of the population mean. The design is illustrated with practical data of COVID-19 confirmed cases.

EFFECT OF TELEREHABILITATION IN FACILITATING UPPER EXTREMITY HOME PROGRAMS AND ASSOCIATED FUNCTIONAL REGAIN AMONG CHRONIC STROKE SURVIVORS: A PILOT STUDY

Background: Stroke is a leading cause of disability in adults, requiring regular patient-therapist contacts to achieve greater functional regain of the affected extremities. Factors such as the recent Covid-19 pandemic have limited access to Rehabilitation services across several communities globally. A proliferation of telerehabilitation to ameliorate these healthcare challenges has been palpable in the recent years across the globe. Purpose: To assess the effect of telerehabilitation in facilitating upper extremity home program and associated functional regain among chronic stroke survivors. Methods: Two groups pretest-posttest study design was employed. Participants were instructed to perform upper extremity home programs three times a week for four weeks. A task-oriented, individually tailored, and intensive home-based telerehabilitation program was administered to the participants using audio calls. Upper extremity functional status was assessed using Fugl-Meyer Motor Assessment, and Wolf Motor Function Test. The Barthel Index was used to assess the extent of activities of daily living. Results: A total number of 14 people were recruited (experimental n=7 age, 58 ± 5.83;control n=7, age 50.71 ± 8.62). Participants showed significant improvement for Fugl-Meyer Motor Assessment changed from 17.57 to 25.86 (p=0.02), whereas Wolf Motor Function Test changed from 28.14 to 43.71 (p=0.03). Conclusions: Amidst situations restricting regular hospital visit among stroke survivors;telerehabilitation could serve as an adjunct therapeutic option for upper extremity rehabilitation. Future studies should employ a randomized controlled trial design with a larger sample size to confirm the utility of telerehabilitation.

A Comprehensive Performance Analysis of Transfer Learning Optimization in Visual Field Defect Classification

Numerous research have demonstrated that Convolutional Neural Network (CNN) models are capable of classifying visual field (VF) defects with great accuracy. In this study, we evaluated the performance of different pre-trained models (VGG-Net, MobileNet, ResNet, and DenseNet) in classifying VF defects and produced a comprehensive comparative analysis to compare the performance of different CNN models before and after hyperparameter tuning and fine-tuning. Using 32 batch sizes, 50 epochs, and ADAM as the optimizer to optimize weight, bias, and learning rate, VGG-16 obtained the highest accuracy of 97.63 percent, according to experimental findings. Subsequently, Bayesian optimization was utilized to execute automated hyperparameter tuning and automated fine-tuning layers of the pre-trained models to determine the optimal hyperparameter and fine-tuning layer for classifying many VF defect with the highest accuracy. We found that the combination of different hyperparameters and fine-tuning of the pre-trained models significantly impact the performance of deep learning models for this classification task. In addition, we also discovered that the automated selection of optimal hyperparameters and fine-tuning by Bayesian has significantly enhanced the performance of the pre-trained models. The results observed the best performance for the DenseNet-121 model with a validation accuracy of 98.46% and a test accuracy of 99.57% for the tested datasets.

Face Mask Detection Using Deep Convolutional Neural Network and MobileNetV2-Based Transfer Learning

The rapid spreading of Coronavirus disease 2019 (COVID-19) is a major health risk that the whole world is facing for the last two years. One of the main causes of the fast spreading of this virus is the direct contact of people with each other. There are many precautionary measures to reduce the spread of this virus;however, the major one is wearing face masks in public places. Detection of face masks in public places is a real challenge that needs to be addressed to reduce the risk of spreading the virus. To address these challenges, an automated system for face mask detection using deep learning (DL) algorithms has been proposed to control the spreading of this infectious disease effectively. This work applies deep convolution neural network (DCNN) and MobileNetV2-based transfer learning models for effectual face mask detection. We evaluated the performance of these two models on two separate datasets, i.e., our developed dataset by considering real-world scenarios having 2500  images (dataset-1) and the dataset taken from PyImage Search Reader Prajna Bhandary and some random sources (dataset-2). The experimental results demonstrated that MobileNetV2 achieved 98% and 99% accuracies on dataset-1 and dataset-2, respectively, whereas DCNN achieved 97% accuracy on both datasets. Based on our findings, it can be concluded that the MobileNetV2-based transfer learning model would be an alternative to the DCNN model for highly accurate face mask detection.

The Impact of Social Media Usage on Students’ Fear during COVID-19: A Study of Postgraduate Students in Pakistan

The purpose of this study was to examine the impact of social media usage on students’ fear during the COVID-19 pandemic. Using a cross-sectional survey approach, a closed-ended questionnaire was administered as a data collection tool among 600 students of 10 public and private sector universities in Pakistan and 438 responses were received. It was found that the respondents’ believed that uploading more information on social media about COVID-19 had spread fear and panic among the students. It was also found males had a high level of psychological fear and physical fears as compared to female respondents. Respondents between the age group of 31 years or more had more psychological fear, followed by respondents between the age group of 24-30 years. However, those whose age was between 18-23 years had fewer psychological fears. The findings of this study could contribute to the body of knowledge on the subject matters. [ FROM AUTHOR] Copyright of Journal of Hospital Librarianship 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.)

Delivering a modified continuous objective structured clinical examination for ophthalmology residents through a hybrid online method.

Since coronavirus disease 2019 was declared a global pandemic by the World Health Organization, it has become a challenging situation to continue medical education, including in Indonesia. The situation prohibited face-to-face (direct) educational activities in clinical settings, therefore also postponing examinations involving especially procedural skills. Adaptations were urgently needed to maintain the delivery of high-stake examinations to sustain the number of ophthalmology graduates and the continuation of eye health service. Objective structured clinical examination (OSCE) has been one of our widely used method to assess clinical competencies for ophthalmology residents, and is the one method that involves gatherings, close contact of examiners, examinees and patients, therefore the most difficult to adjust. Pandemic challenges brought technical changes in our delivering the OSCE to online, maximizing digital platforms of meetings, while still concerned to guarding the safety of candidates, patients and staffs. OSCE scenarios were also made as timely efficient as possible by changing continuous station models to a cascade one. The purpose of this article is to document our experience in conducting a feasible and reproducible OSCE in this pandemic era filled with limitations.

The Impact of COVID-19 on Solid Waste Generation in the Perspectives of Socioeconomic and People’s Behavior: A Case Study in Serdang, Malaysia

Malaysia has enforced several phases of Movement Control Order (MCO) as a quarantine period since 18 March 2020 with the intended purpose of containing the coronavirus disease (COVID-19) outbreak. The quarantine has affected people’s daily lives with frequent job dismissal and retrenchment due to the struggling economic conditions of particularly small and medium businesses. This study aimed to understand the impact of MCO on solid waste management in Serdang, Selangor from the aspects of socioeconomic and people’s behavior. Solid waste generation data in Serdang, Selangor was collected by KDEB Waste Management through waste weighing daily throughout 2019 and 2020. The collection was conducted according to different housing areas of Serdang. The quantitative findings have recorded a decline of 9.94% in solid waste data generation subjected to COVID-19 lockdown. In conjunction with that, an online questionnaire participated by 310 respondents was conducted on understanding the effect of the lockdown on people’s behavior and socioeconomic aspect with respect to solid waste management. This study revealed that June onwards (after MCO Phase 1) generated the most solid waste. Indeed, solid waste generation due to MCO according to the waste refusal behavior is the consensus in favor of Malaysia’s appropriate need for stricter policies.

Hesitant Fuzzy Linear Regression Model for Decision Making

An expert may experience difficulties in decision making when evaluating alternatives through a single assessment value in a hesitant environment. A fuzzy linear regression model (FLRM) is used for decision-making purposes, but this model is entirely unreasonable in the presence of hesitant fuzzy information. In order to overcome this issue, in this paper, we define a hesitant fuzzy linear regression model (HFLRM) to account for multicriteria decision-making (MCDM) problems in a hesitant environment. The HFLRM provides an alternative approach to statistical regression for modelling situations where input–output variables are observed as hesitant fuzzy elements (HFEs). The parameters of HFLRM are symmetric triangular fuzzy numbers (STFNs) estimated through solving the linear programming (LP) model. An application example is presented to measure the effectiveness and significance of our proposed methodology by solving a MCDM problem. Moreover, the results obtained employing HFLRM are compared with the MCDM tool called technique for order preference by similarity to ideal solution (TOPSIS). Finally, Spearman’s rank correlation test is used to measure the significance for two sets of ranking.

Pimenta dioica (L.) Merr. Bioactive Constituents Exert Anti-SARS-CoV-2 and Anti-Inflammatory Activities: Molecular Docking and Dynamics, In Vitro, and In Vivo Studies.

In response to the urgent need to control Coronavirus disease 19 (COVID-19), this study aims to explore potential anti-SARS-CoV-2 agents from natural sources. Moreover, cytokine immunological responses to the viral infection could lead to acute respiratory distress which is considered a critical and life-threatening complication associated with the infection. Therefore, the anti-viral and anti-inflammatory agents can be key to the management of patients with COVID-19. Four bioactive compounds, namely ferulic acid 1, rutin 2, gallic acid 3, and chlorogenic acid 4 were isolated from the leaves of Pimenta dioica (L.) Merr (ethyl acetate extract) and identified using spectroscopic evidence. Furthermore, molecular docking and dynamics simulations were performed for the isolated and identified compounds (1-4) against SARS-CoV-2 main protease (Mpro) as a proposed mechanism of action. Furthermore, all compounds were tested for their half-maximal cytotoxicity (CC50) and SARS-CoV-2 inhibitory concentrations (IC50). Additionally, lung toxicity was induced in rats by mercuric chloride and the effects of treatment with P. dioca aqueous extract, ferulic acid 1, rutin 2, gallic acid 3, and chlorogenic acid 4 were recorded through measuring TNF-α, IL-1ß, IL-2, IL-10, G-CSF, and genetic expression of miRNA 21-3P and miRNA-155 levels to assess their anti-inflammatory effects essential for COVID-19 patients. Interestingly, rutin 2, gallic acid 3, and chlorogenic acid 4 showed remarkable anti-SARS-CoV-2 activities with IC50 values of 31 µg/mL, 108 µg/mL, and 360 µg/mL, respectively. Moreover, the anti-inflammatory effects were found to be better in ferulic acid 1 and rutin 2 treatments. Our results could be promising for more advanced preclinical and clinical studies especially on rutin 2 either alone or in combination with other isolates for COVID-19 management.

Platypnoea-orthodeoxia syndrome in an older patient with COVID-19 pneumonia and orthostatic hypotension-a case of prolonged hospital admission.

An 89-year-old woman was admitted to hospital with a fall, general malaise and low oxygen saturations. She tested positive for SARS-CoV-2 and commenced on standard therapy for COVID-19 pneumonia. She improved initially but reported ongoing dyspnoea exacerbated by position. Following investigations to rule out other causes, she was given a diagnosis of platypnoea-orthodeoxia syndrome (POS). She was treated with gradual verticalization therapy with supplemental oxygen and subsequently discharged to an intermediate care bed (ICB).

Computational Insights on the Potential of Some NSAIDs for Treating COVID-19: Priority Set and Lead Optimization.

The discovery of drugs capable of inhibiting SARS-CoV-2 is a priority for human beings due to the severity of the global health pandemic caused by COVID-19. To this end, repurposing of FDA-approved drugs such as NSAIDs against COVID-19 can provide therapeutic alternatives that could be utilized as an effective safe treatment for COVID-19. The anti-inflammatory activity of NSAIDs is also advantageous in the treatment of COVID-19, as it was found that SARS-CoV-2 is responsible for provoking inflammatory cytokine storms resulting in lung damage. In this study, 40 FDA-approved NSAIDs were evaluated through molecular docking against the main protease of SARS-CoV-2. Among the tested compounds, sulfinpyrazone 2, indomethacin 3, and auranofin 4 were proposed as potential antagonists of COVID-19 main protease. Molecular dynamics simulations were also carried out for the most promising members of the screened NSAID candidates (2, 3, and 4) to unravel the dynamic properties of NSAIDs at the target receptor. The conducted quantum mechanical study revealed that the hybrid functional B3PW91 provides a good description of the spatial parameters of auranofin 4. Interestingly, a promising structure-activity relationship (SAR) was concluded from our study that could help in the future design of potential SARS-CoV-2 main protease inhibitors with expected anti-inflammatory effects as well. NSAIDs may be used by medicinal chemists as lead compounds for the development of potent SARS-CoV-2 (Mpro) inhibitors. In addition, some NSAIDs can be selectively designated for treatment of inflammation resulting from COVID-19.

Analisis Semiotika Meme ‘Profesi Yang Tidak Dapat Work From Home’ Selama Pandemi COVID-19

A meme is capable of picturing a phenomenon which is generally arranged through a picture that is followed by a description that adds up to the representation of a meaning that is intended to be conveyed by a meme creator. A meme may be perceived as unique since it has the ability to express numerous points of view, such as one?s or a group of society?s political view. The COVID-19 pandemic which is currently threatening the world?s public health starting from the end of 2019 introduces an enormous disruption in various fields, including the social aspect in Indonesia. One of the difficulties that the citizens felt is their obligation to do their work from home, as a form of health quarantine, along with physical distancing avoiding interactions that occurred in workplaces. As a government policy, it?s only normal that a pro-contra rises in the society. One of the flaws in the policy is the existence of professions which doesn?t allow their work to be done at home, specifically for professions such as fishermen, farmers, and construction workers that are also found at the memes which this study analysed. To look at how a public discourse is done through a meme, the study uses Barthes? Semiotic Analysis Model in revealing the myth that exists in the meme found in the social media platforms during the COVID-19 pandemic. The study finds how the memes in the analysis represent a perceived flaw in the Work From Home policy when the policy is directed to several types of professions in Indonesia, as well as it is a form of political critique.Keywords: Work From Home, COVID-19, semiotic, meme�ABSTRAKSuatu meme mampu menggambarkan sebuah fenomena yang pada umumnya dirangkai melalui suatu gambar yang diikuti dengan deskripsi yang mendukung representasi suatu makna yang hendak disampaikan seorang pembuat meme. Meme juga dianggap unik oleh karena kemampuannya mengekspresikan berbagai sudut pandang, seperti pandangan politik seseorang atau sekelompok masyarakat. Pandemi COVID-19 yang tengah mengancam kesehatan masyarakat dunia sejak akhir tahun 2019 menghadirkan disrupsi yang besar dalam berbagai sektor, termasuk aspek sosial di Indonesia. Salah satu kesulitan yang dialami masyarakat adalah kewajiban setiap individu untuk melaksanakan pekerjaan mereka dari rumah masing-masing atau yang sering disebut sebagai ?Work From Home?, sebagai bentuk kekarantinaan kesehatan dengan pembatasan fisik dari interaksi yang terjadi di tempat berbagai pekerjaan dilakukan. Selayaknya suatu kebijakan pemerintah, resolusi kesehatan ini menimbulkan pro-kontra bagi masyarakat Indonesia. Salah satu kekurangan dari kebijakan ini adalah keberadaan profesi yang tidak memungkinkan pekerjaannya untuk dikerjakan di rumah, khususnya untuk profesi seperti nelayan, petani, dan tukang bangunan yang juga ditemukan pada ketiga meme yang dianalisis pada penelitian ini. Untuk melihat bagaimana ruang publik dimanfaatkan melalui meme, penelitian menggunakan Model Analisis Semiotika Barthes dalam mengulik mitos yang terdapat pada beberapa meme yang hidup di media sosial selama rangkaian pandemi COVID-19. Studi menemukan keberadaan meme yang menunjukkan ketidaksesuaian perwujudan Work From Home bagi beberapa jenis profesi milik masyarakat Indonesia, sebagai bentuk kritik politis. Selain memenuhi fungsi hiburan, sebuah meme juga memiliki potensi untuk menjadi ruang publik bagi masyarakat melalui berbagai saluran dimana meme dapat hidup, yakni media sosial.Kata Kunci: Bekerja dari Rumah, COVID-19, semiotika, meme

Facilitating SARS CoV-2 RNA-Dependent RNA polymerase (RdRp) drug discovery by the aid of HCV NS5B palm subdomain binders: In silico approaches and benchmarking.

Corona Virus 2019 Disease (COVID-19) is a rapidly emerging pandemic caused by a newly discovered beta coronavirus, called Sever Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2). SARS CoV-2 is an enveloped, single stranded RNA virus that depends on RNA-dependent RNA polymerase (RdRp) to replicate. Therefore, SARS CoV-2 RdRp is considered as a promising target to cease virus replication. SARS CoV-2 polymerase shows high structural similarity to Hepatitis C Virus-1b genotype (HCV-1b) polymerase. Arising from the high similarity between SARS CoV-2 RdRp and HCV NS5B, we utilized the reported small-molecule binders to the palm subdomain of HCV NS5B (genotype 1b) to generate a high-quality DEKOIS 2.0 benchmark set and conducted a benchmarking analysis against HCV NS5B. The three highly cited and publicly available docking tools AutoDock Vina, FRED and PLANTS were benchmarked. Based on the benchmarking results and analysis via pROC-Chemotype plot, PLANTS showed the best screening performance and can recognize potent binders at the early enrichment. Accordingly, we used PLANTS in a prospective virtual screening to repurpose both the FDA-approved drugs (DrugBank) and the HCV-NS5B palm subdomain binders (BindingDB) for SARS CoV-2 RdRp palm subdomain. Further assessment by molecular dynamics simulations for 50 ns recommended diosmin (from DrugBank) and compound 3 (from BindingDB) to be the best potential binders to SARS CoV-2 RdRp palm subdomain. The best predicted compounds are recommended to be biologically investigated against COVID-19. In conclusion, this work provides in-silico analysis to propose possible SARS CoV-2 RdRp palm subdomain binders recommended as a remedy for COVID-19. Up-to-our knowledge, this study is the first to propose binders at the palm subdomain of SARS CoV2 RdRp. Furthermore, this study delivers an example of how to make use of a high quality custom-made DEKOIS 2.0 benchmark set as a procedure to elevate the virtual screening success rate against a vital target of the rapidly emerging pandemic.

Targeting multiple conformations of SARS-CoV2 Papain-Like Protease for drug repositioning: An in-silico study.

Papain-Like Protease (PLpro) is a key protein for SARS-CoV-2 viral replication which is the cause of the emerging COVID-19 pandemic. Targeting PLpro can suppress viral replication and provide treatment options for COVID-19. Due to the dynamic nature of its binding site loop, PLpro multiple conformations were generated through a long-range 1 micro-second molecular dynamics (MD) simulation. Clustering the MD trajectory enabled us to extract representative structures for the conformational space generated. Adding to the MD representative structures, X-ray structures were involved in an ensemble docking approach to screen the FDA approved drugs for a drug repositioning endeavor. Guided by our recent benchmarking study of SARS-CoV-2 PLpro, FRED docking software was selected for such a virtual screening task. The results highlighted potential consensus binders to many of the MD clusters as well as the newly introduced X-ray structure of PLpro complexed with a small molecule. For instance, three drugs Benserazide, Dobutamine and Masoprocol showed a superior consensus enrichment against the PLpro conformations. Further MD simulations for these drugs complexed with PLpro suggested the superior stability and binding of dobutamine and masoprocol inside the binding site compared to Benserazide. Generally, this approach can facilitate identifying drugs for repositioning via targeting multiple conformations of a crucial target for the rapidly emerging COVID-19 pandemic.

Supporting SARS-CoV-2 Papain-Like Protease Drug Discovery: In silico Methods and Benchmarking.

The coronavirus disease 19 (COVID-19) is a rapidly growing pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Its papain-like protease (SARS-CoV-2 PLpro) is a crucial target to halt virus replication. SARS-CoV PLpro and SARS-CoV-2 PLpro share an 82.9% sequence identity and a 100% sequence identity for the binding site reported to accommodate small molecules in SARS-CoV. The flexible key binding site residues Tyr269 and Gln270 for small-molecule recognition in SARS-CoV PLpro exist also in SARS-CoV-2 PLpro. This inspired us to use the reported small-molecule binders to SARS-CoV PLpro to generate a high-quality DEKOIS 2.0 benchmark set. Accordingly, we used them in a cross-benchmarking study against SARS-CoV-2 PLpro. As there is no SARS-CoV-2 PLpro structure complexed with a small-molecule ligand publicly available at the time of manuscript submission, we built a homology model based on the ligand-bound SARS-CoV structure for benchmarking and docking purposes. Three publicly available docking tools FRED, AutoDock Vina, and PLANTS were benchmarked. All showed better-than-random performances, with FRED performing best against the built model. Detailed performance analysis via pROC-Chemotype plots showed a strong enrichment of the most potent bioactives in the early docking ranks. Cross-benchmarking against the X-ray structure complexed with a peptide-like inhibitor confirmed that FRED is the best-performing tool. Furthermore, we performed cross-benchmarking against the newly introduced X-ray structure complexed with a small-molecule ligand. Interestingly, its benchmarking profile and chemotype enrichment were comparable to the built model. Accordingly, we used FRED in a prospective virtual screen of the DrugBank database. In conclusion, this study provides an example of how to harness a custom-made DEKOIS 2.0 benchmark set as an approach to enhance the virtual screening success rate against a vital target of the rapidly emerging pandemic.

Access and Use Experience of Personal Protective Equipment Among Frontline Healthcare Workers in Pakistan During the COVID-19 Emergency: A Cross-Sectional Study.

Healthcare workers are at the highest risk of contracting novel coronavirus disease 2019 (COVID-19) and, therefore, require constant protection. This study assesses access to personal protective equipment (PPE), availability of adequate information about PPE use, self-reported ability to correctly wear and remove (donning and doffing) PPE, and risk perceptions associated with COVID-19 among frontline healthcare workers in Pakistan. Using a structured and validated questionnaire, an online survey was conducted from May 9 to June 5, 2020. Responses were received from 453 healthcare workers. Of these, 218 (48.12%) were doctors, 183 (40.40%) were nurses, and 52 (11.48%) were paramedical staff. Only 129 (28.48%) healthcare workers reported having adequate access to PPE at all times, whereas 156 (34.44%) never had access to PPE and 168 (37.09%) had access to PPE occasionally. Lack of access to PPE led the majority (71.74%) of healthcare workers to use coping strategies such as reuse of N95 and surgical masks. A total of 312 (68.87%) respondents believed that the risk of contracting COVID-19 in the work environment was high and the majority (62.69%) adopted precautionary measures at home to keep their families safe. A significantly high (n = 233, 51.43%, P = .03) number of respondents reported self-medicating. Of all the respondents, only 136 (30.02%) were tested for COVID-19 at least once, of which 32 (23.53%) ever tested positive. These findings suggest that healthcare workers in Pakistan had limited access to PPE. Adequate provision and training is vital to protect the healthcare workforce during the COVID-19 pandemic.

Impact of Movement Control Order (MCO) due to Coronavirus Disease (COVID-19) on Food Waste Generation: A Case Study in Klang Valley, Malaysia

The outbreak of a neurological disorder was first discovered as a new coronavirus (2019-nCoV) in Wuhan, China. The infection spread rapidly in China and throughout the world, including Malaysia. Malaysia recorded its initial case on 25 January 2020 with intensifying numbers since March 2020. Due to this uncertain circumstance, Malaysia has introduced the Movement Control Order (MCO) with the main aim of isolating the source of the COVID-19 outbreak, which was effective from 18 March 2020. The restriction has observed fewer vehicles on the road with industrial and commercial activities being suspended. The objective of the study is to quantify the effects of MCO to food waste generation in town and district areas of Klang Valley, Malaysia. Food waste generation data was derived from the Project Delivery Department, KDEB Waste Management on a daily basis before (19 February–17 March 2020) and during the MCO (18 March–14 April 2020) at 12 local authorities in Selangor, Malaysia. The data was obtained with the limitation of assumption that there is no waste compositional analysis to be conducted in 2020. Despite the stay-at-home order, food waste data showed a descriptive reduction of up to 15.1% during the MCO. Statistical analysis of food waste generation from one-way variance has shown that municipal and district local authorities recorded a significant reduction (p <0.50) during the MCO. The food waste reduction during the MCO will deliver as the evidence-based results to push the need for policies in Malaysia as per the goals outlined in Sustainable Development Goals of global food loss and waste.