Does environmental quality and weather induce COVID-19: Case study of Istanbul, Turkey

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.

Entrepreneurial Leadership and Employee Wellbeing During COVID-19 Crisis: A Dual Mechanism Perspective

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.

China Pakistan Economic Corridor Digital Transformation.

The China-Pakistan Economic Corridor (CPEC) vision and mission are to improve the people's living standards of Pakistan and China through bilateral investments, trade, cultural exchanges, and economic activities. To achieve this envisioned dream, Pakistan established the China-Pakistan Economic Corridor Authority (CPECA) to further its completion, but Covid-19 slowed it down. This situation compelled the digitalization of CPEC. This article reviews the best practices and success stories of various digitalization and e-governance programs and, in this light, advises the implementation of the Ajman Digital Governance (ADG) model as a theoretical framework for CPEC digitalization. This article concludes that the Pakistani government needs to transform CPEC digitalization by setting up the CPEC Digitalization and Transformation Center (DTC) at the CPECA office to attract more investors and businesses.

Indirect effects of COVID-19 pandemic on reproductive, maternal, newborn and child health services in Pakistan.

Background: COVID-19 is having many impacts on health, economy and social life; some due to the indirect effects of closure of health facilities to curb the spread. Closures were implemented in Pakistan from March 2020, affecting provision of reproductive, maternal, newborn and child health (RMNCH) services. Aims: To appraise the effects of containment and lockdown policies on RMNCH service utilization in order to develop an early response to avoid the catastrophic impact of COVID-19 on RMNCH in Pakistan. Methods: Routine monitoring data were analysed for indicators utilization of RMNCH care. The analysis was based on Period 1 (January-May 2020, first wave of COVID-19); Period 2 (June-September 2020, declining number of cases of COVID-19); and Period 3 (October-December 2020, second wave of COVID-19). We also compared data from May and December 2020 with corresponding months in 2019, to ascertain whether changes were due to COVID-19. Results: Reduced utilization was noted for all RMNCH indicators during Periods 1 and 3. There was a greater decline in service utilization during the first wave, and the highest reduction (~82%) was among children aged < 5 years, who were treated for pneumonia. The number of caesarean sections dropped by 57%, followed by institutional deliveries and first postnatal visit (37% each). Service utilization increased from June to September, but the second wave of COVID-19 led to another decrease. Conclusion: To reinstate routine services, priority actions and key areas include continued provision of family planning services along with uninterrupted immunization campaigns and routine maternal and child services.

Explaining Resistance to the COVID-19 Preventive Measures: A Psychological Reactance Perspective

This paper examines the impact that psychological reactance has on the COVID-19 adherence-related behavior and vaccine motivations of the residents of Saudi Arabia. A cross-sectional, online survey was administered, and 604 usable responses were analyzed to discover the level of psychological reactance, and its impact on adherence to COVID-19 preventive measures and vaccine intentions. Results of the Kruskal–Wallis H test demonstrated statistically significant evidence (p < 0.05) of differences between the mean ranks for four out of seven key COVID-19 preventive measures studied, and four out of five items related to vaccine motivations, as a result of psychological reactance. These results suggest that while the majority of the population is adhering to COVID-19 preventive measures, for the subset of the population that are not fully compliant, psychological reactance is a significant factor in influencing behavior. Governments are, therefore, recommended to ensure that their public health messages are autonomy supporting, and take into consideration psychological and personality-based differences in individuals.

COVID-19 seroprevalence in Pakistan: a cross-sectional study.

OBJECTIVES: This study adapted WHO's 'Unity Study' protocol to estimate the population prevalence of antibodies to SARS CoV-2 and risk factors for developing SARS-CoV-2 infection. DESIGN: This population-based, age-stratified cross-sectional study was conducted at the level of households (HH). PARTICIPANTS: All ages and genders were eligible for the study (exclusion criteria: contraindications to venipuncture- however, no such case was encountered). 4998 HH out of 6599 consented (1 individual per HH). The proportion of male and female study participants was similar. PRIMARY AND SECONDARY OUTCOME MEASURES: Following were the measured outcome measures- these were different from the planned indicators (i.e. two out of the three planned indicators were measured) due to operational reasons and time constraints: -Primary indicators: Seroprevalence (population and age specific).Secondary indicators: Population groups most at risk for SARS-CoV-2-infection. RESULTS: Overall seroprevalence of SARS-CoV-2 antibodies was 7.1%. 6.3% of individuals were IgG positive while IgM positivity was 1.9%. Seroprevalence in districts ranged from 0% (Ghotki) to 17% (Gilgit). The seroprevalence among different age groups ranged from 3.9% (0-9 years) to 10.1% (40-59 years). There were no significant differences in the overall seroprevalence for males and females. A history of contact with a confirmed COVID-19 case, urban residence and mask use were key risk factors for developing SARS-CoV-2 infection. CONCLUSIONS: This survey provides useful estimates for seroprevalence in the general population and information on risk factors for developing SARS-CoV-2 infection in the country. It is premised that similar studies need to be replicated at the population level on a regular basis to monitor the disease and immunity patterns related to COVID-19.

Changes in water use and wastewater generation influenced by the COVID-19 pandemic: A case study of China.

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.

Long-term statistical assessment of meteorological indicators and COVID-19 outbreak in hot and arid climate, Bahrain.

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.

A study on the effects of meteorological and climatic factors on the COVID-19 spread in Canada during 2020.

The Coronavirus (COVID-19) pandemic has infected more than three million people, with thousands of deaths and millions of people into quarantine. In this research, the authors focus on meteorological and climatic factors on the COVID-19 spread, the main parameters including daily new cases of COVID-19, carbon dioxide (CO2) emission, nitrogen dioxide (NO2), Sulfur dioxide (SO2), PM2.5, Ozone (O3), average temperature, and humidity are examined to understand how different meteorological parameters affect the COVID-19 spread in Canada? The graphical quantitative analysis results indicate that CO2 emissions, air quality, temperature, and humidity have a direct negative relationship with COVID-19 infections. Quantile regression analysis revealed that air quality, Nitrogen, and Ozone significantly induce the COVID-19 spread across Canadian provinces. The findings of this study are contrary to the earlier studies, which argued that weather and climate change significantly increase COVID-19 infections. We suggested that meteorological and climatic factors might be critical to reducing the COVID-19 new cases in Canada based on the findings. This work's empirical conclusions can provide a guideline for future research and policymaking to stop the COVID-19 spread across Canadian provinces.

Environmental quality, climate indicators, and COVID-19 pandemic: insights from top 10 most affected states of the USA.

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.

Association of Inflammatory Markers with Mortality in COVID-19 Infection.

OBJECTIVE: To evaluate the association of serum ferritin, lactate dehydrogenase, and C-reactive protein at admission with in-hospital mortality in COVID-19 infection; and to determine best predictive cut-offs. STUDY DESIGN: Cross-sectional study. PLACE AND DURATION OF STUDY: Department of Medicine, Combined Military Hospital, Peshawar Cantt; Pakistan from March to June 2020. METHODOLOGY: Admitted patients with SARS-CoV-2 detectable by polymerase chain reaction (PCR) were included. Patients with suggestive radiological findings but negative PCR for SARS-CoV-2, those with incomplete data or those leaving against medical advice were excluded. Serum C-reactive protein, ferritin and LDH levels were tested on admission. SARS-CoV-2 viral load was checked on nasopharyngeal samples. Disease severity was assessed using World Health Organization guidelines. RESULTS: There were 238 patients, aged 41.18 ± 16.74 years. Disease was mild in 157 (65.97%), moderate in 36 (15.13%), and severe in 45 (18.91%) cases. Twenty-two (9.24%) patients died in the hospital. Serum C-reactive protein, ferritin and lactate dehydrogenase levels were elevated in 122 (51.26%), 83 (34.87%) and 184 (77.31%) patients, respectively; more frequently amongst patients with moderate/severe disease or mortality. Areas under receiver operating characteristic curves  and 95% confidence intervals for serum C-reactive protein, ferritin and LDH were 0.909 (0.854-0.964), 0.915 (0.835-0.995) and 0.863 (0.785-0.942), respectively. C-reactive protein ≥45.5 mg/L had sensitivity 86.36% and specificity 88.89%; serum ferritin ≥723 ng/ml had sensitivity 95.45% and specificity 86.57%, and lactate dehydrogenase ≥428.5 U/L had sensitivity 90.91% and specificity 80.56% for predicting mortality. CONCLUSION: Levels of the three inflammatory markers at admission can predict mortality in COVID-19 infection. Key Words: Coronavirus, Inflammation, Mortality, Outcome, Pakistan.

Investigating the Effects of Meteorological Parameters on COVID-19: Case Study of New Jersey, United States.

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.

Effects of climatological parameters on the outbreak spread of COVID-19 in highly affected regions of Spain.

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.

Co-variance nexus between COVID-19 mortality, humidity, and air quality index in Wuhan, China: New insights from partial and multiple wavelet coherence.

The worldwide outbreak of COVID-19 disease has caused immense damage to our health and economic and social life. This research article helps to determine the impact of climate on the lethality of this disease. Air quality index and average humidity are selected from the family of climate variables, to determine its impact on the daily new cases of COVID-19-related deaths in Wuhan, China. We have used wavelet analysis (wavelet transform coherence (WTC), partial (PWC), and multiple wavelet coherence (MWC), due to its advantages over traditional time series methods, to study the co-movement nexus between our selected data series. Findings suggest a notable coherence between air quality index, humidity, and mortality in Wuhan during a recent outbreak. Humidity is negatively related to the COVID-19-related deaths, and bad air quality leads to an increase in this mortality. These findings are important for policymakers to save precious human lives by better understanding the interaction of the environment with the COVID-19 disease.