Do fear and perceived knowledge of Covid-19 drive sustainable consumption behaviour in Muslims? The mediating role of religiosity

PurposeThis research aims to investigate the impact of fear and perceived knowledge (PK) of Covid-19 on the sustainable consumption behaviour (SCB) of Muslim consumers and to test the mediating role of (intrinsic) religiosity.Design/methodology/approachA total of 417 responses were collected during Covid-19 lockdown through an online structured survey using the snowball technique. A two-step research approach was adopted. In Study 1, an exploratory factor analysis was performed on the SCB measurement scale through SPSS. In Study 2, hypothesised associations were analysed using SmartPLS-SEM.FindingsPK of Covid-19 pandemic directly motivates SCB in Muslim consumers, whereas fear has no direct effect on any factor of SCB. Religiosity is found to be a significant driver of SCB. Indirect effects also depict that religiosity positively mediates the association between fear and SCB as well as PK and SCB.Practical implicationsThe study may guide policymakers and marketers in using the current pandemic as a tool to inspire sustainable consumption. Religious values, teachings and knowledge about the pandemics can be publicised to create awareness and induce desired behaviour to cope with adverse events and adopt sustainable consumption patterns and lifestyles among Muslim consumers.Originality/valueThe article is the pioneer of its kind to present survey research about Covid-19 fear and PK's impact on SCB through religiosity. It adds to the Islamic marketing literature about religiosity, coping theory, PK and fear of pandemics and their role in transitioning Muslim consumers towards SCB. Moreover, the use of partial least squares structural equation modelling in the context of Covid-19 research was extended.

A comprehensive genomic study, mutation screening, phylogenetic and statistical analysis of SARS-CoV-2 and its variant omicron among different countries.

BACKGROUND: With the rapid development of the genomic sequence data for the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants Delta (B.1.617.2) and Omicron (B.1.1.529), it is vital to successfully identify mutations within the genome. OBJECTIVE: The main objective of the study is to investigate the full-length genome mutation analysis of 157 SARS-CoV-2 and its variant Delta and Omicron isolates. This study also provides possible effects at the structural level to understand the role of mutations and new insights into the evolution of COVID-19 and evaluates the differential level analysis in viral genome sequence among different nations. We have also tried to offer a mutation snapshot for these differences that could help in vaccine formulation. This study utilizes a unique and efficient method of targeting the stable genes for the drug discovery approach. METHODS: Complete genome sequence information of SARS-CoV-2, Delta, and Omicron from online resources were used to predict structure domain identification, data mining, and screening; employing different bioinformatics tools. BioEdit software was used to perform their genomic alignments across countries and a phylogenetic tree as per the confidence of 500 bootstrapping values was constructed. Heterozygosity ratios were determined in-silico. A minimum spanning network (MSN) of selected populations was determined by Bruvo's distance role-based framework. RESULTS: Out of all 157 different strains of SARS-CoV-2 and its variants, and their complete genome sequences from different countries, Corona nucleoca and DUF5515 were observed to be the most conserved domains. All genomes obtained changes in comparison to the Wuhan-Hu-1 strain, mainly in the TRS region (CUAAAC or ACGAAC). We discovered 596 mutations in all genes, with the highest number (321) found in ORF1ab (QHD43415.1), or TRS site mutations found only in ORF7a (1) and ORF10 (2). The Omicron variant has 30 mutations in the Spike protein and has a higher alpha-helix shape (23.46%) than the Delta version (22.03%). T478 was also discovered to be a prevalent polymorphism in Delta and Omicron variations, as well as genomic gaps ranging from 45 to 65aa. All 157 sequences contained variations and conformed to Nei's Genetic distance. We discovered heterozygosity (Hs) 0.01, mean anticipated Hs 0.32, the genetic diversity index (GDI) 0.01943989, and GD within population 0.01266951. The Hedrick value was 0.52324978, the GD coefficient was 0.52324978, the average Hs was 0.01371452, and the GD coefficient was 0.52324978. Among other countries, Brazil has the highest standard error (SE) rate (1.398), whereas Japan has the highest ratio of Nei's gene diversity (0.01). CONCLUSIONS: The study's findings will assist in comprehending the shape and kind of complete genome, their streaming genomic sequences, and mutations in various additions of SARS-CoV-2, as well as its different variant strains like Omicron. These results will provide a scientific basis to design the vaccines and understand the genomic study of these viruses.

The impact of COVID-19 pandemic on air pollution: a global research framework, challenges, and future perspectives.

As a result of extreme modifications in human activity during the COVID-19 pandemic, the status of air quality has recently been improved. This bibliometric study was conducted on a global scale to quantify the impact of the COVID-19 pandemic on air pollution, identify the emerging challenges, and discuss the future perspectives during the course of the ongoing COVID-19 pandemic. For this, we have estimated the scientific production trends between 2020 and 2021 and investigated the contributions of countries, institutions, authors, and most prominent journals metrics network analysis on the topic of COVID-19 combined with air pollution research spanning the period between January 01, 2020, and June 21, 2021. The search strategy retrieved a wide range of 2003 studies published in scientific journals from the Web of Sciences Core Collection (WoSCC). The findings indicated that (1) publications on COVID-19 pandemic and air pollution were 990 (research articles) in 2021 with 1870 citations; however, the year 2020 witnessed only 830 research articles with a large number 16,600 of citations. (2) China ranked first in the number of publications (n = 365; 18.22% of the global output) and was the main country in international cooperation network, followed by the USA (n = 278; 13.87% of the global output) and India (n = 216; 10.78 of the total articles). (3) By exploring the co-occurrence and links strengths of keywords "COVID-19" (1075; 1092), "air pollution" (286; 771), "SARS-COV-2" (252; 1986). (4) The lessons deduced from the COVID-19 pandemic provide defined measures to reduce air pollution globally. The outcomes of the present study also provide useful guidelines for future research programs and constitute a baseline for researchers in the domain of environmental and health sciences to estimate the potential impact of the COVID-19 pandemic on air pollution.

Assessing the Impact of COVID-19 on the Mental Health of Healthcare Workers in Three Metropolitan Cities of Pakistan.

PURPOSE: The COVID-19 (coronavirus disease-2019) has been associated with psychological distress during its rapid rise period in Pakistan. The present study aimed to assess the mental health of healthcare workers (HCWs) in the three metropolitan cities of Pakistan. METHODS: A cross-sectional, web-based study was conducted in 276 HCWs from April 10, 2020, to June 5, 2020. Depression, anxiety, and stress scale (DASS-21) were used for the mental health assessment of the HCWs. Multivariable logistic regression analysis (MLRA) was performed to measure the association between the demographics and the occurrence of depression, anxiety, and stress (DAS). RESULTS: The frequency of DAS in the HCWs was 10.1%, 25.4%, and 7.3%, respectively. The MLRA showed that the depression in HCWs was significantly associated with the profession (P<0.001). The anxiety in HCWs was significantly associated with their age (P=0.005), profession (P<0.05), and residence (P<0.05). The stress in HCWs was significantly associated with their age (P<0.05). LIMITATION: This study was conducted in the early phase of the COVID-19 pandemic, when the number of COVID-19 cases was on the rise in Pakistan and it only represents a definite period (April to June 2020). CONCLUSION: The symptoms of DAS are present in the HCWs of Pakistan and to manage the psychological health of HCWs, there is a need for the initiation of psychological well-being programs.

Assessing Barriers Faced by Surgeons While Providing Surgical Care During the COVID-19 Pandemic in Pakistan: An Online Cross-Sectional Study.

BACKGROUND: The COVID-19 pandemic is not only affecting public health, but it is also impairing the specialized surgical care services in the hospitals. The present study aimed to assess the barriers faced by the surgeons while performing surgical procedures during the COVID-19 pandemic. METHODS: A cross-sectional, web-based survey was conducted from September 10 to October 14, 2020. The study population consisted of surgeons practicing in Kpk, Pakistan. Descriptive statistics and binary logistic regression analysis were used to analyze the data. RESULTS: A total of 292, out of 543, surgeons participated in the study (response rate: 59.6%). The younger surgeons (25-30 years) considered the lack of policies and practices regarding exposure to COVID-19 patients as a significant barrier to their practice. The surgeons practicing in private hospitals considered themselves at a higher risk while providing surgical care to the COVID-19 patients. The non-cooperation of the patients was the main barrier in delivering surgical care services. CONCLUSION AND RECOMMENDATION: The current study highlighted the barriers to the surgeons while providing surgical care to patients in the current pandemic. The most pronounced barriers to the surgeons were the lack of policies regarding exposure to COVID-19 and practice and non-cooperation of the patient. To address these barriers, it is recommended that health regulatory agencies of Pakistan should implement strict infection control practices to ensure the safety of surgeons and allied healthcare staff during the COVID-19 pandemic.

Investigating connections between COVID-19 pandemic, air pollution and community interventions for Pakistan employing geoinformation technologies.

Several major cities that witnessed heavy air pollution by particulate matter (PM2.5) concentration and nitrogen dioxide (NO2) have contributed to high rate of infection and severity of the coronavirus disease (COVID-19) pandemic. Owing to the negative impact of COVID-19 on health and economy, it is imperative to predict the pandemic trend of the COVID-19 outbreak. Pakistan is one of the mostly affected countries by recent COVID-19 pandemic in terms of COVID-cases and economic crises. Like other several Asian countries to combat the virus impacts, Pakistan implemented non-pharmacological interventions (NPI), such as national lockdowns. The current study investigates the effect of major interventions across three out of four provinces of Pakistan for the period from the start of the COVID-19 in March 22, 2020 until June 30, 2020, when lockdowns were started to be eased. High-resolution data on NO2 was recorded from Sentinel-5's Precursor spacecraft with TROPOspheric Monitoring Instrument (Sentinel-5P TROPOMI). Similarly, PM2.5 data were collected from sampling sties to investigate possible correlation among these pollutants and COVID-19. In addition, growth and susceptible-infected-recovered (SIR) models utilizing time-series data of COVID-19 from February 26 to December 31, 2020, with- and without NPI that encompass the predicted number of infected cases, peak time, impact on the healthcare system and mortality in Pakistan. Maximum mean PM2.5 concentration of 108 µgm-3 was recorded for Lahore with the range from 51 to 215 µgm-3, during strict lockdown (L), condition. This is three times higher than Pak-EPA and US-EPA and four times for WHO guidelines, followed by Peshawar (97.2 and 58 ± 130), Islamabad (83 and 158 ± 58), and Karachi (78 and 50 ± 140). The majority of sampling sites in Lahore showed NO2 levels higher than 8.75E-5 (mol/m2) in 2020 compared to 2019 during "L" period. The susceptible-infected-recovered (SIR) model depicted a strong correlation (r) between the predicted and reported cases for Punjab (r = 0.79), Sindh (r = 0.91), Khyber Pakhtunkhwa (KPK) (r = 94) and Islamabad (r = 0.85). Findings showed that major NPI and lockdowns especially have had a large effect on minimizing transmission. Continued community intervention should be undertaken to keep transmission of SARS-CoV-2 under control in cities where higher incidence of COVID-19 cases until the vaccine is available. This study provides a methodological framework that if adopted can assist epidemiologist and policy makers to be well-prepared in advance in cities where PM2.5 concentration and NO2 levels are already high in order to minimize the potential risk of further spread of COVID-19 cases.

Spatiotemporal variability of COVID-19 pandemic in relation to air pollution, climate and socioeconomic factors in Pakistan.

Information on the spatiotemporal variability of respirable suspended particulate pollutant matter concentrations, especially of particles having size of 2.5 µm and climate are the important factors in relation to emerging COVID-19 cases around the world. This study aims at examining the association between COVID-19 cases, air pollution, climatic and socioeconomic factors using geospatial techniques in three provincial capital cities and the federal capital city of Pakistan. A series of relevant data was acquired from 3 out of 4 provinces of Pakistan (Punjab, Sindh, Khyber Pakhtunkhwa (KPK) including the daily numbers of COVID-19 cases, PM2.5 concentration (µgm-3), a climatic factors including temperature (°F), wind speed (m/s), humidity (%), dew point (%), and pressure (Hg) from June 1 2020, to July 31 2020. Further, the possible relationships between population density and COVID-19 cases was determined. The generalized linear model (GLM) was employed to quantify the effect of PM2.5, temperature, dew point, humidity, wind speed, and pressure range on the daily COVID-19 cases. The grey relational analysis (GRA) was also implemented to examine the changes in COVID-19 cases with PM2.5 concentrations for the provincial city Lahore. About 1,92, 819 COVID-19 cases were reported in Punjab, Sindh, KPK, and Islamabad during the study period. Results indicated a significant relationship between COVID-19 cases and PM2.5 and climatic factors at p < 0.05 except for Lahore in case of humidity (r = 0.175). However, mixed correlations existed across Lahore, Karachi, Peshawar, and Islamabad. The R2 value indicates a moderate relationship between COVID-19 and population density. Findings of this study, although are preliminary, offers the first line of evidence for epidemiologists and may assist the local community to expedient for the growth of effective COVID-19 infection and health risk management guidelines. This remains to be seen.

Disaster Management Policy Development and Engineering Economics: An Analysis of Game-Changing Impact of COVID 19 on Oil-Power Industry, Environment, and Economy

Dynamics of power are linked with sustainable development goals. These goals are dependent on the resources and management of development economics. The oil industry is the backbone of the economic profile of any country which is directly connected with power generation, industrialization, and the environment as well. In this study, a comparative performance analysis of five major oil-dependent economies has been conducted. The performance of these countries has been analyzed based on economics and the environment during pandemics. A war to piece relationship has also been discussed based on the oil industry. Furthermore, management policy has also been recommended to maintain oil pricing and economic management for sustainable development goals. This study will help to develop a comprehensive disaster management policy for sustainable development and engineering economics.