Based on the social exchange theory, the aim of this study is to identify the association between job stress state anger, emotional exhaustion and job turnover intention. This study postulates that job related stress and state anger among nurses during COVID-19 subsequently leads to their job turnover intentions. In addition, the study also aims to see the mediating role of emotional exhaustion between COVID-19-related job stress, state anger, and turnover intentions. The sample of this study is gathered from 335 registered nurses working in Pakistani hospitals dealing with COVID-19-related patients. The interrelationships between variables are checked by using structural equation modeling through AMOS. Key findings confirm that COVID-19-related job stress and state anger had a significant effect on nurses’ turnover intentions. Furthermore, emotional exhaustion mediated the relationship between COVID-19-related job stress, state anger, and turnover intentions. There is a lack of research which has assessed the impact of Novel COVID-19-related job stress and state anger on nurses’ turnover intentions in hospitals, providing empirical evidence from a developing country-Pakistan. This study offers managerial implications for hospital management and health policymakers. Moreover, nursing managers need to pay attention to nurses’ turnover intentions who are facing the issue at the front line as patients receive their initial treatment from nurses in the COVID-19 outbreak.

Extending studies of the adverse effects of SARS-2 coronavirus on general health consequences, this research explores complexities related to the mental health of the elderly as a result of pandemic-related stress. The study addresses this issue by using resilience theory to examine the effects of fear and exposure related to COVID-19 and depression. Besides, our study examines the moderating effects of self-efficacy in order to provide an understanding of how the coping abilities of the elderly may mitigate the effect of stress levels on mental health during pandemics. Our model is tested by analysing the survey data collected from Rawalpindi, a metropolitan city in Pakistan. The main results of the study confirm the positive association of pandemic-related fear and exposure virus with depression. However, self-efficacy shows a negative direct effect on depression, and the findings also confirm the moderation effect of self-efficacy on the fear of COVID-19 and depression, but the moderation effect of self-efficacy on COVID-19 exposure and depression is not supported. Based on the outcomes, some severe geriatric care policies that could weaken the pandemic-related fear, exposure to the virus, and depression are recommended.

This study comprehends how non-pharmaceutical approaches such as "quarantine," "social distancing," and "lockdown" help to impede the extent of the severe COVID-19 pandemic. The abrupt, surfacing, and evolving circumstance of this infection was thought to be defended, imperative, and implemented through these approaches as a core component of the quick response in the arena of a global health emergency. In this pursuit, a logical conceptual framework is developed using a qualitative method by reviewing literature along with analyzing numerous documents and reports. Based on information from some countries, this exploration centers around significant approaches and the embraced socio-health policy used as a preventive framework leading to the quarantine, social distancing, and lockdown for the transmission of the virus headed for the community. Studies have shown that populations flowing from the sources of the outbreak pose a higher level of risk in the destination area than other factors such as topographical vicinity, physical contact, and interaction. This study, therefore, suggests some draconian socio-health policies to be imposed, such as quarantine, social distancing, and lockdown measures to cripple the transmission of the virus. The sooner such measures are implemented, the shorter will be the term of the endemic. Finally, the findings have important implications for the policymaking to be adopted globally as well as nationally preventive strategies.

Environmental degradation has been identified as a major worldwide concern in recent decades, with CO2 emissions considered as one of the primary drivers of this catastrophe. This study creatively analyzes the underlying impact of wind and solar energy generation, economic development, fossil fuel consumption on CO2 emissions to mitigate the environmental degradation in the world’s top three largest energy consumers and CO2 emitters nations namely, China, India, and the USA. To investigate the integrated impact of CO2 emission, a grey relational analysis (GRA) technique is adopted for the year 1990–2017. The Grey technique for order of preference by similarity to ideal solution (G-TOPSIS) technique was employed for further optimization by prioritizing the explanatory factors that have potential influence on CO2 emissions in the selected nations. The outcomes through the GRA technique discovered that India is a major contributor of carbon emission caused by economic development, and China appeared to be the more afflicted nation for raising its carbon emissions owing to fossil fuel consumption. Whereas, the generation of solar and wind energy are grounded factors in the reduction of carbon emissions for China and the USA. In addition, the generation of wind energy showed a considerable impact in the reduction of CO2 emissions, based on the G-TOPSIS analysis. This suggests that reducing CO2 emissions would require a compendious transition from nonrenewable to renewable resources, while the United States and China appear to be on a more promising direction to environmental sustainability than India. As a growing renewable energy pioneer, India should increase the utilization of minimal carbon sources of energy in its electricity grid while limiting its reliance on fossil fuels. The findings of the study potentially aid governments and policymakers in making better decisions and investments to mitigate CO2 emissions while fostering a more environmentally friendly atmosphere.

COVID-19 is a rapidly disseminating infectious disease conferred by the World Health Organization (WHO) as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics data have been identified for patients with COVID-19, but mortality-related risk factors and a comprehensive clinical course of disease in a developing country have not been specifically defined. This retrospective, single-center cohort study involved all successive inpatients having a positive COVID-19 polymerase chain reaction (PCR), with deceased or discharged clinical outcomes from 1 January to 10 May 2021. Data were extracted from electronic medical records on demographic, clinical, radiological, and laboratory findings as well as complications faced and treatment provided during follow-up, involving serial samples for viral RNA identification, and compared between the dead and survivors. To investigate the risk factors associated with in-hospital mortality, we employed the multivariate logistic regression model. In this study, 2048 patients were involved, 1458 of whom were discharged, and 590 died in hospital. More than half of patients were identified as male with old age being the potential risk factor of mortality. Exactly 94.8% of all patients presented with fever at the time of admission. Several comorbidities were present in the study population, with the most frequent comorbidity being cardiovascular diseases (1177 of 2048) and hypertension (975 of 2048) followed by cerebrovascular disease and diabetes mellitus. Mortality rates for infected patients were observed as higher in severe patients (46.3%) compared with non-severe cases (26.1%) during a follow-up. Multivariate regression analysis showed a significant association of in-hospital mortality of patients with older age, presence of hypertension and cardiovascular diseases as underlying comorbidities, increased level of cardiac troponin I and d-dimer concentration on admission, as well as septicemia and ARDS as a complication during illness. To minimize the risk of death in COVID19 patients, as well as the risk of severe complications, urgent public health measures should be properly planned and implemented on those vulnerable populations. To detect early manifestations of clinical problems, thorough and regular follow-up is warranted.

The prime objective of the present study is to test the effect of COVID-19 fear on the mental condition of nurses in the public health sector of Pakistan. This study seeks to measure the psychological distress, anxiety, and psychological well-being of nurses due to fear of COVID-19 and exposure to COVID-19. This research further reveals the moderating role of “social support” in the link between COVID-19 fear, exposure and mental health. Through a convenient sampling technique, 250 sample contributors were chosen from 12 public hospitals. The results were obtained by applying multiple regression and moderation analysis by SPSS and the Hayes process. The outcomes indicated that fear of exposure to COVID-19 affects the mental health of nurses. The findings also discovered that social support is not very constructive in the pandemic. However, we suggested that social support is the best weapon to encourage nurses to relieve their fear and minimize negative emotions.

Air pollution has emerged as a major global concern in recent decades as a result of rapid urbanization and industrialization, leading to a variety of adverse health outcomes. This research aims to investigate the influence of exposure to ambient and household particulate matter pollution (PM2.5), and ground-level ozone (O3) pollution on respiratory and cardiac mortality in Pakistan. We used grey incidence analysis (GIA) methodology to estimate the degree of proximity among selected variables and rank them based on mortality. Hurwicz's criterion is then adopted for further optimization by prioritizing the selected factors with the greatest influence on respiratory and cardiac mortality. The GIA findings revealed that asthma mortality is considerably impacted by exposure to ambient and household PM2.5 concentration while ischemic heart disease (IHD) mortality is potentially influenced by ground-level ozone exposure. Furthermore, results based on Hurwicz's analysis demonstrated that exposure to ambient PM2.5 concentration appeared as the most intensified factor of respiratory and cardiac mortality. This corroboration adds to the growing body of research demonstrating that exposure to ambient PM2.5 adversely leads to respiratory and cardiac risks, emphasizing the demand for further improvement of air quality in Pakistan. Besides, the suggested methodologies provide a valuable tool and additional practical knowledge for policymakers and decision-makers in drawing rational decisions.

The health industry is amongst the most affected systems in terms of multiobjective decision-making, rendering the final solution, vulnerable to errors; however, multicriteria decision analysis (MDCA) emerges as a supportive tool for the process of decision-making. Therefore, the present study seeks to offer an MCDA framework for assessing and identifying the potential influence of socioeconomic risk factors on noncommunicable disease mortality. We adopted a subjective approach of grey-based Step-wise Weight Assessment Ratio Analysis (SWARA) and COmplex PRoportional Assessment (COPRAS) approach to calculate weights of parameters and criteria, respectively, and then rank them based on their degree of significance. The findings reveal that CRD mortality is potentially affected by the selected socioeconomic risk variables followed by IHD and cancer. Implementing MCDA techniques in the present study will assist the public health practitioners and policymakers in drawing decisions on the best strategy to reduce CRD mortality, which contributes significantly to raising overall mortality.