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Objectives. The emergence of COVID-19 has drastically changed the safety outlook of how the work world is viewed by leaders and followers. In this backdrop, the current study aimed at extending the safety leadership literature in the context of organizations operating in crisis situations by investigating the impact of safety-specific transformational leadership on the followers' extra-role behaviors through the mediation of psychological contract fulfillment. Methods. Using a time-lagged and multisource design, data were collected from 384 frontline rescue and healthcare workers dealing with COVID-19-related situations. Results. Results revealed that safety-specific transformational leadership behavior positively affects extra-role behaviors of frontline employees by enhancing their innovative work behavior, knowledge sharing behavior and organizational citizenship behavior. Also, psychological contract fulfillment plays a bridging role in translating the impact of safety-specific transformational leadership behavior on extra-role behaviors. Conclusion. The followers working in an unsafe context view the safety concern of their leader as a fulfillment of their unwritten expectations from their employers. Implications of these findings along with limitations and future research directions are also delineated. [ABSTRACT FROM AUTHOR]

The primary aim of this study was to explore the repercussions of the COVID-19 pandemic on developing nations, with a specific focus on Pakistan, Bangladesh, and India. To accurately portray the pandemic's impact on these economies, our research employed a model incorporating fixed effects. The findings revealed a notable decline in the per capita income of the countries affected by the COVID-19 pandemic. The existing economic downturn can be attributed to various factors, with a significant contributor being the reduced availability of labor. The prevalence of illnesses and adherence to public health guidelines led to a noticeable shortage of labor for active participation in economic activities. As a consequence, there was a decline in both productivity and economic output. Moreover, our analysis yielded a thought-provoking finding: a notable increase in fatalities had a discernible effect on the populace. The population experienced a significant decline as a result of the fatalities caused by the pandemic, an event that had complex economic ramifications. This decline in population paradoxically resulted in a rise in GDP per capita. By employing a fixed effects model, our research gains greater resilience, rendering it a valuable asset for policymakers, economists, and scholars endeavoring to navigate the intricate landscape of the effects of pandemics on emerging economies. In summary, the findings of this research stand to make a significant contribution to the wider comprehension of the repercussions of COVID-19 on these particular countries. [ABSTRACT FROM AUTHOR]

We looked at the prompt effects of the COVID-19 pandemic in the Pakistani neighborhood, in the Liaoning Province, on the psychological well-being and the personal happiness of Pakistani citizens for 19 years. An online review was dispersed through a web-based media stage between January what's more, February 2020. Members finished an altered approved poll that evaluated the Effect of Event Scale (IES), pointers of negative psychological well-being effects, social and family uphold, also, emotional wellness related way of life changes. Our current research was conducted at BVH, Bahawalpurfrom March 2020 to August 2020. A sum of 267 members (108 guys and 159 females) finished the investigation. The mean age of the members was 39.8 15.1 years, and 75.8% had a high level of instruction. The mean IES score in the members was 14.7 8.8, mirroring a mellow distressing sway. Just 7.6% of members had an IES score 27. Most of members (56.4%) did not feel vulnerable because of the pandemic. Then again, 54.2% of members felt sickened and uneasy because of the pandemic. Moreover, most of members (58.9-78.7%) got expanded help from loved ones, expanded imparted feeling and minding to family individuals and others. Taking everything into account, the COVID-19 pandemic was related with gentle distressing sway in our example, despite the fact that the COVID-19 pandemic is as yet continuous. These discoveries would should be checked in bigger populace contemplates. [ABSTRACT FROM AUTHOR]

The coronavirus pandemic has infected more than 100 million people worldwide with COVID-19, with millions of deaths across the globe. In this research, we explored the effects of environmental and weather variables with daily COVID-19 cases and COVID-19 fatalities in Istanbul, Turkey. Turkey has the 8th highest number of COVID-19 cases globally, with the highest infections and deaths in Istanbul. This may be the first study to conduct a comprehensive investigation for environmental quality (air quality pollutants, e.g., PM2.5 and PM10, ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide, etc.), weather parameters (temperature, humidity) and COVID-19 in Turkey. The authors collected meteorological data from 11 March 2020 to 8 February 2021 and COVID-19 data from Istanbul and other regions. The results from empirical estimations, correlation analysis, and quantile on quantile techniques support that air quality and temperature significantly influence COVID-19 deaths in Istanbul. This research may help policymakers and health scientists to take specific measures to reduce the spread of coronavirus across different global cities. The effects of air quality on COVID-19 in Istanbul was investigated. The study applied correlation and quantile on quantile techniques over daily data. Temperature significantly induces the spread of COVID-19 in Istanbul at all quantiles. Air quality and Nitrogen are positively linked with COVID-19 new cases. [ABSTRACT FROM AUTHOR]

This study examined the potential impacts of entrepreneurial leadership on followers’ psychological wellbeing and proactive work behavior through sustainable employability and work uncertainty in a sample of 218 employees employed in SMEs of Pakistan. Hierarchical regression results demonstrated that entrepreneurial leadership was positively connected with sustainable employability and negatively linked with work uncertainty. Sequentially, sustainable employability was positively correlated with proactive work behavior and employees’ psychological wellbeing, and work uncertainty was negatively associated with proactive work behavior and employees’ psychological wellbeing during the COVID-19 crisis. Furthermore, bootstrapping confirmed the mediation effects of work uncertainty and sustainable employability on proactive work behavior and the psychological wellbeing of employees. Sustainable employability did not mediate the relationship between entrepreneurial leadership and psychological wellbeing. Mediators, sustainable employability, and work uncertainty positively linked employees’ psychological wellbeing and proactive work behavior. The results highlighted the significant roles of sustainable employability and work uncertainty and interpreted why entrepreneurial leadership may affect employees’ positive behaviors. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has significantly impacted the global lifestyle, and the spreading of the virus is unprecedented. This study is aimed at assessing the association between the meteorological indicators such as air temperature (°C), relative humidity (%), wind speed (w/s), solar radiation, and PM2.5 with the COVID-19 infected cases in the hot, arid climate of Bahrain. Kendall and Spearman rank correlation coefficients and quantile on quantile regression were used as main econometric analysis to determine the degree of the relationship between related variables. The dataset analysis was performed from 05 April 2020, to 10 January 2021. The empirical findings indicate that the air temperature, humidity, solar radiation, wind speed indicators, and PM2.5 have a significant association with the COVID-19 newly infected cases. The current study findings allow us to suggest that Bahrain's relatively successful response to neighboring GULF economies can be attributed to the successful environmental reforms and significant upgrades to the health care facilities. We further report that a long-term empirical analysis between meteorological factors and respiratory illness threats will provide useful policy measures against future outbreaks. [ABSTRACT FROM AUTHOR]

In the current context of the COVID-19 pandemic, researchers are working with health professionals to inform governments on how to formulate health strategies. In this study, we examine the correlation between environmental and climate indicators and COVID-19 outbreak in the top 10 most affected states of the USA. In doing so, PM2.5, temperature, humidity, environmental quality index, and rainfall are included as crucial meteorological and environmental factors. Kendall and Spearman rank correlation coefficients, quantile regression, and log-linear negative binominal analysis are employed as an estimation strategy. The empirical estimates conclude that temperature, humidity, environmental quality index, PM2.5, and rainfall are significant factors related to the COVID-19 pandemic in the top 10 most affected states of the USA. The empirical findings of the current study would serve as key policy input to mitigate the rapid spread of COVID-19 across the USA. [ABSTRACT FROM AUTHOR]

The coronavirus (COVID-19) pandemic is infecting the human population, killing people, and destroying livelihoods. This research sought to explore the associations of daily average temperature (AT) and air quality (PM2.5) with the daily new cases of COVID-19 in the top four regions of Spain (Castilla y Leon, Castilla-La Mancha, Catalonia, and Madrid). To this end, the authors employ Pearson correlation, Spearman correlation, and robust panel regressions to quantify the overall co-movement between temperature, air quality, and daily cases of COVID-19 from 29 February to 17 July 2020. Overall empirical results show that temperature may not be a determinant to induce COVID-19 spread in Spain, while the rising temperature may reduce the virus transmission. However, the correlation and regression findings illustrate that air quality may speed up the transmission rate of COVID-19. Our findings are contrary to the earlier studies, which show a significant impact of temperature in raising the COVID-19 spread. The conclusions of this work can serve as an input to mitigate the rapid spread of COVID-19 in Spain and reform policies accordingly. [ABSTRACT FROM AUTHOR]

This paper examines and projects the water use and wastewater generation during and after the SARS-CoV-2 (COVID-19) in China, and discussed the water use/wastewater generation pattern changes among different sectors. Existing studies on the impact of pandemic spread-prevention measures on water consumption and wastewater treatment during the pandemic are reviewed. The water use and wastewater discharge in China through the COVID-19 period are then projected and analyzed using Multivariate Linear Regression. The projection is carried out for years 2019–2023 and covers an (estimated) full process of pre-pandemic, pandemic outbreak, and recovery phase and provides essential information for determining the complete phase impact of the COVID-19. Two scenarios, i.e. the recovery scenario and the business as usual scenario, are set to investigate the water use and wastewater generation characteristics after the pandemic. The results imply that in both scenarios, the water use in China shows a V-shaped trend from 2019 to 2023 and reached a low point in 2020 of 5,813✕108 m3. The wastewater discharge shows an increasing trend throughout the COVID period in both scenarios. The results are also compared with the water consumption and wastewater generation during the SARS-CoV-1 period. The implication for policymakers is the possible increase of water use and wastewater discharge in the post COVID period and the necessity to ensure the water supply and control of water pollution and wastewater discharge. • The impact of the SARS-CoV-2 pandemic on the water sector are reviewed. • Water use and wastewater discharge throughout the COVID-19 period are projected. • Water use in China shows a V-shaped trend from 2019 to 2023. • Wastewater discharge shows an increasing trend throughout the COVID period. • Water use and wastewater discharge during the SARS and the COVID-19 are compared. [ABSTRACT FROM AUTHOR]

A Correction to this paper has been published: 10.1007/s11356-021-15990-0 [ABSTRACT FROM AUTHOR]

The accuracy of oil production predictions is crucial in the field of petroleum engineering. However, due to the time series characteristics of oil production and the complex relationship among multiple influencing factors, traditional methods, and time series prediction techniques have limitations in fully extracting time series features and exploring the internal relationships between variables. Deep learning techniques possess unique advantages in solving nonlinear problems and time-series problems but require a significant amount of data and can only conduct short-term oil production predictions due to the nonlinear and chaotic nature of yield. Therefore, this work aims to establish a model that can overcome these limitations. A modified GRU (M-GRU) is proposed to extract time series features of variables and external economic information. Then, the autoregressive (AR) model is integrated into importing priori knowledge to enhance the model's capability in extracting time series information. In addition, feature mapping is used to improve convergence performance. Finally, A loss function that can dynamically adjust the weights is proposed, which can enhance the model's ability to fit from error-prone samples. By validating the proposed model using oil production data, it has been proven that the model can predict oil production accurately and outperform other models with a correlation coefficient reaching 0.99874. Further tests show that the model can provide accurate prediction results even with limited sample sizes and during coincidental events such as financial crises and COVID-19 epidemics, providing strong support for decision-making for reservoir engineers. • Feature mapping can enhance the convergence performance of the model. • An extraction module of time-series priori knowledge is designed to improve the accuracy of the model. • A modified GRU is proposed to extract external economic information. • A loss function with dynamic weight is proposed for time-series information fusion. [ABSTRACT FROM AUTHOR]

This research aims to explore the correlation between meteorological parameters and COVID-19 pandemic in New Jersey, United States. The authors employ extensive correlation analysis including Pearson correlation, Spearman correlation, Kendall's rank correlation and auto regressive distributed lag (ARDL) to check the effects of meteorological parameters on the COVID new cases of New Jersey. In doing so, PM 2.5, air quality index, temperature (°C), humidity (%), health security index, human development index, and population density are considered as crucial meteorological and non-meteorological factors. This research work used the maximum available data of all variables from 1st March to 7th July 2020. Among the weather indicators, temperature (°C) was found to have a negative correlation, while humidity and air quality highlighted a positive correlation with daily new cases of COVID-19 in New Jersey. The empirical findings illustrated that there is a strong positive association of lagged humidity, air quality, PM 2.5, and previous infections with daily new cases. Similarly, the ARDL findings suggest that air quality, humidity and infections have lagged effects with the COVID-19 spread across New Jersey. The empirical conclusions of this research might serve as a key input to mitigate the rapid spread of COVID-19 across the United States. • The study examines the effects of air pollutants on the COVID-19 spread in New Jersey. • Air quality and humidity significantly enhance new COVID-19 cases. • Air quality, humidity and COVID-19 has lagged effects with new infections. • Temperature may not be a significant determinant of COVID-19. [ABSTRACT FROM AUTHOR]