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In this paper, we report the results obtained from one year of real-time measurement (i.e., from December 2019 to November 2020) of atmospheric black carbon (BC) under a rural environment in Qingdao of Northeastern China. The annual average concentration of BC was 1.92 ± 1.89 μg m−3. The highest average concentration of BC was observed in winter (3.65 ± 2.66 μg m−3), followed by fall (1.73 ± 1.33 μg m−3), spring (1.53 ± 1.33 μg m−3), and summer (0.83 ± 0.56 μg m−3). A clear weekend effect was observed in winter, which was characterized by higher BC concentration (4.60 ± 2.86 μg m−3) during the weekend rather than that (3.22 ± 2.45 μg m−3) during weekdays. The influence of meteorological parameters, including surface horizontal wind speed, boundary layer height (BLH), and precipitation, on BC, was investigated. In particular, such BLH influence presented evidently seasonal dependence, while there was no significant seasonality for horizontal wind speed. These may reflect different roles of atmospheric vertical dilution on affecting BC in different seasons. The △BC/△CO ratio decreased with the increase of precipitation, indicative of the influence of below-cloud wet removal of BC, especially during summertime where rainfall events more frequently occurred than any of other seasons. The bivariate-polar-plot analysis showed that the high BC concentrations were mainly associated with low wind speed in all seasons, highlighting an important BC source originated from local emissions. By using concentration-weighted trajectory analysis, it was found that regional transports, especially from northeastern in winter, could not be negligible for contributing to BC pollution in rural Qingdao. In the coronavirus disease 2019 (COVID−19) case analysis, we observed an obvious increase in the BC/NO2 ratio during the COVID-19 lockdown, supporting the significant non-traffic source sector (such as residential coal combustion) for BC in rural Qingdao. [ABSTRACT FROM AUTHOR]

The Novel Coronavirus Disease 2019 (COVID-19) has swept the world and caused a global pandemic. SARS-CoV-2 seems to have originated from bats as their reservoir hosts over time. Similar to SARS-CoV, this new virus also exerts its action on the human angiotensin-converting enzyme 2. This action causes infections in cells and establishes an infectious disease, COVID-19. Against this viral invasion, the human body starts to activate the innate immune system in producing and releasing proinflammatory cytokines such as IL-6, IL-1β, IL-8, TNF-α, and other chemokines, such as G-CSF, IP10 and MCPl, which all develop and increase the inflammatory response. In cases of COVID-19, excessive inflammatory responses occur, and exaggerated proinflammatory cytokines and chemokines are detected in the serum, resulting in cytokine release syndrome or cytokine storm. This causes coagulation abnormalities, excessive oxidation developments, mitochondrial permeability transition, vital organ damage, immune system failure and eventually progresses to disseminated intravascular coagulation and multiple organ failure. Additionally, the excessive inflammatory responses also cause mitochondrial dysfunction due to progressive and persistent stress. This damages cells and mitochondria, leaving products containing mitochondrial DNA and cell debris involved in the excessive chronic inflammation as damage-associated molecular patterns. Thus, the respiratory infection progressively leads to disseminated intravascular coagulation from acute respiratory distress syndrome, including vascular endothelial cell damage and coagulation-fibrinolysis system disorders. This condition causes central nervous system disorders, renal failure, liver failure and, finally, multiple organ failure. Regarding treatment for COVID-19, the following are progressive and multiple steps for mitigating the excessive inflammatory response and subsequent cytokine storm in patients. First, administering of favipiravir to suppress SARS-CoV-2 and nafamostat to inhibit ACE2 function should be considered. Second, anti-rheumatic drugs (monoclonal antibodies), which act on the leading cytokines (IL-1β, IL-6) and/or cytokine receptors such as tocilizumab, should be administered as well. Finally, melatonin may also have supportive effects for cytokine release syndrome, resulting in mitochondrial function improvement. This paper will further explore these subjects with reports mostly from China and Europe. [ABSTRACT FROM AUTHOR]

With the coronavirus pandemic wreathing havoc around the world, power industry has been hit hard due to the proposal of lockdown policies. However, the impact of lockdowns and shutdowns on the power system in different regions as well as periods of the pandemic can hardly be reflected on the foundation of current studies. In this paper, a prediction-based analysis method is developed to point out the electricity consumption gap resulted from the pandemic situation. The core of this method is a novel optimized grey prediction model, namely Rolling IMSGM(1,1) (Rolling Mechanism combined with grey model with initial condition as Maclaurin series), which achieves better prediction results in the face of long-term emergencies. A novel initial condition is adopted to track data with various characteristics in the form of higher-order polynomials, which are then determined by intelligent algorithms to realize accurate fitting. Historical power consumption data in China are utilized to carry out the monthly forecasts during COVID-19. Compared with other competitive models' prediction results, the superiority of IMSGM(1,1) are demonstrated. Through analyzing the gap between predicted consumption values and the actual data, it can be found that the impact of the pandemic on electricity varies in different periods, which is related to its severity and the local lockdown policies. This study helps to understand the impact on power industry in the face of such an emergency intuitively so as to respond to possible future events. [ABSTRACT FROM AUTHOR]

Since December 2019, a new form of coronavirus, SARS-CoV-2, has spread from China to the whole word, raising concerns regarding Coronavirus Disease 2019 (COVID-19) endangering public health and life. Over 1.5 million deaths related with COVID-19 have been recorded worldwide, with wide variations among countries affected by the pandemic and continuously growing numbers. The aim of this paper was to provide an overview of the literature cases of deaths involving COVID-19 and to evaluate the application of the COVID-19 Significance Score (CSS) in the classification of SARS CoV-2-related fatalities, comparing it with the Hamburg rating scale. The results obtained allowed us to highlight that CSS used after a complete accurate post-mortem examination, coupled to the retrieval of in vivo data, post-mortem radiology, histology and toxicology, as well as to additional required analyses (e.g., electronic microscopy) is a useful and concise tool in the assessment of the cause of death and the role played by this virus. A shared use of this scale might hopefully lower the inhomogeneities in forensic evaluation of SARS CoV-2-related fatalities. [ABSTRACT FROM AUTHOR]

With the outbreak of COVID-19 (Corona Virus Disease, 2019), China adopted traffic restrictions to reduce the spread of COVID-19. Using daily data before and after the outbreak of COVID-19, an exogenous shock, this paper analyzes the effects of private vehicle restriction policies on air pollution. We find that the private vehicle restriction policies reduce the degree of air pollution to a certain extent. However, their effect varies with other policies implemented in the same period and the economic development of the city itself. Through the analysis of different categories of restrictions, we find that restriction policy for local fuel vehicles and the restriction policy based on the last digit of license plate numbers have the best effect in reducing air pollution. Under the background of COVID-19 epidemic and the implementation of private vehicle restriction policies and other traffic control policies during this period, we have also obtained other enlightenment on air pollution control. • The causal relationship between air pollution and restriction is analyzed. • An exogenous shock from COVID-19 is used to identify this relationship. • The private vehicle restriction reduces the degree of air pollution. • The restriction policies have heterogeneous effects. • The effects of restriction are affected by other policies against COVID-19. [ABSTRACT FROM AUTHOR]

Introduction: The 2019 coronavirus disease (COVID-19) is a global health crisis that originated in China. As an adjacent city to the origin of COVID-19, Hong Kong has been facing different public health challenges raised by the epidemic. Objectives: This paper examined the prevalence of common physical symptoms, psychological symptoms, somatic symptoms, and health anxiety among the Hong Kong youth population. Methods: HKYES is an on-going territory-wide epidemiological study collecting youth mental health data with randomly stratified sampling. Participants aged 15-24 years were to complete a physical symptom checklist, Depression, Anxiety and Stress Scale (DASS-21), Insomnia Severity Index (ISI), Patient Health Questionnaire-15 (PHQ-15), and Short Health Anxiety Inventory (SHAI). Results: A total of 594 participants have completed the survey since April 2020. The three most common physical symptoms were headache (n=106, 17.8%), fever (n=94, 15.8%) and fatigue (n=78, 13.1%). The mean scores of DASS depression, anxiety and stress subscales were 7.98 (SD 8.14), 5.81 (SD 6.32), and 8.83 (SD 7.93) respectively. Among all, 135 (22.8%) participants reported moderate to severe levels of depressive symptoms, 133 (22.4%) reported moderate to severe levels of anxiety symptoms, and 71 (12%) reported moderate to severe levels of stress. There were 40 (6.7%) and 60 (10.1%) participants showing significant levels of insomnia and somatic symptoms, while around one-third of the participants reported a high level of health anxiety. Conclusions: Youth is at risk of severe psychological impact during the coronavirus. Monitoring the mental health trajectory for youth should become routine practice during times of crisis. [ABSTRACT FROM AUTHOR]

The Corona Virus Disease 2019 (COVID-19) appeared in Wuhan, China, at the end of 2019, spreading from there across China and within weeks across the whole world. In order to control the rapid spread of the virus, the Chinese government implemented a national lockdown policy. It restricted human mobility and non-essential economic activities, which, as a side effect, resulted in the reduction of the emission of pollutants and thus the improvement of the air quality in many cities in China. In this paper, we report on a study on the changes in air quality in the Guanzhong Basin during the COVID-19 lockdown period. We compared the concentrations of PM2.5, PM10, SO2, NO2, CO and O3 obtained from ground-based monitoring stations before and after the COVID-19 outbreak. The analysis confirmed that the air quality in the Guanzhong Basin was significantly improved after the COVID-19 outbreak. During the emergency response period with the strictest restrictions (Level-1), the concentrations of PM2.5, PM10, SO2, NO2 and CO were lower by 37%, 30%, 29%, 52% and 33%, respectively, compared with those before the COVID-19 outbreak. In contrast, O3 concentrations increased substantially. The changes in the pollutant concentrations varied between cities during the period of the COVID-19 pandemic. The highest O3 concentration changes were observed in Xi'an, Weinan and Xianyang city; the SO2 concentration decreased substantially in Tongchuan city; the air quality had improved the most in Baoji City. Next, to complement the sparsely distributed air quality ground-based monitoring stations, the geographic and temporally weighted regression (GTWR) model, combined with satellite observations of the aerosol optical depth (AOD) and meteorological factors was used to estimate the spatial and temporal distributions of PM2.5 and PM10 concentrations with a resolution of 6 km × 6 km before and after the COVID-19 outbreak. The model was validated by a comparison with ground-based observations from the air quality monitoring network in five cities in the Guanzhong Basin with excellent statistical metrics. For PM2.5 and PM10 the correlation coefficients R2 were 0.86 and 0.80, the root mean squared errors (RMSE) were 11.03 µg/m3 and 14.87 µg/m3 and the biases were 0.19 µg/m3 and −0.27 µg/m3, which led to the conclusion that the GTWR model could be used to estimate the PM concentrations in locations where monitoring data were not available. Overall, the PM concentrations in the Guanzhong Basin decreased substantially during the lockdown period, with a strong initial decrease and a slower one thereafter, although the spatial distributions remained similar. [ABSTRACT FROM AUTHOR]

• A Maximum-Entropy Ecological Niche Model is used to estimate a global-scale probability distribution of COVID-19 high infection rate. • Environmental parameters (surface air temperature, precipitation, and elevation) and humanrelated parameters (CO 2 emission and population density) are used in the model. • The model is trained only with data of Italian provinces with high infection rate, but predicts known actual infection focuses, e.g. the Hubei province in China. • A risk index is proposed, which correctly classifies most World countries, which have reported high COVID-19 spread rate, as zones with high-risk of infection rate increase. • The methodology follows an Open-science approach where the model is published as a standardized Web service that maximises re-usability on new data and new diseases, and guarantees the transparency of the approach and the results. COVID-19 pandemic is a global threat to human health and economy that requires urgent prevention and monitoring strategies. Several models are under study to control the disease spread and infection rate and to detect possible factors that might favour them, with a focus on understanding the correlation between the disease and specific geophysical parameters. However, the pandemic does not present evident environmental hindrances in the infected countries. Nevertheless, a lower rate of infections has been observed in some countries, which might be related to particular population and climatic conditions. In this paper, infection rate of COVID-19 is modelled globally at a 0.5∘ resolution, using a Maximum Entropy-based Ecological Niche Model that identifies geographical areas potentially subject to a high infection rate. The model identifies locations that could favour infection rate due to their particular geophysical (surface air temperature, precipitation, and elevation) and human-related characteristics (CO 2 and population density). It was trained by facilitating data from Italian provinces that have reported a high infection rate and subsequently tested using datasets from World countries' reports. Based on this model, a risk index was calculated to identify the potential World countries and regions that have a high risk of disease increment. The distribution outputs foresee a high infection rate in many locations where real-world disease outbreaks have occurred, e.g. the Hubei province in China, and reports a high risk of disease increment in most World countries which have reported significant outbreaks (e.g. Western U.S.A.). Overall, the results suggest that a complex combination of the selected parameters might be of integral importance to understand the propagation of COVID-19 among human populations, particularly in Europe. The model and the data were distributed through Open-science Web services to maximise opportunities for re-usability regarding new data and new diseases, and also to enhance the transparency of the approach and results. [ABSTRACT FROM AUTHOR]

The present outbreak of the novel coronavirus SARS‐CoV‐2, epicentered in China in December 2019, has spread to many other countries. The entire humanity has a vital responsibility to tackle this pandemic and the technologies are being helpful to them to a greater extent. The purpose of the work is to precisely bring scientific and general awareness to the people all around the world who are currently fighting the war against COVID-19. It's visible that the number of people infected is increasing day by day and the medical community is tirelessly working to maintain the situation under control. Other than the negative effects caused by COVID-19, it is also equally important for the public to understand some of the positive impacts it has directly or indirectly given to society. This work emphasizes the various impacts that are created on society as well as the environment. As a special additive, some important key areas are highlighted namely, how the modernized technologies are aiding the people during the period of social distancing. Some effective technological implications carried out by both information technology and educational institutions are highlighted. There are also several steps taken by the state government and central government in each country in adopting the complete lockdown rule. These steps are taken primarily to prevent the people from COVID-19 impact. Moreover, the teachings we need to learn from the quarantine situation created to prevent further spread of this global pandemic is discussed in brief and the importance of carrying them to the future. Finally, the paper also elucidates the general preventive measures that have to be taken to prevent this deadly coronavirus, and the role of technology in this pandemic situation has also been discussed. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 is a kind of systemic virus, and lungs are not the only target organ. SARS-CoV-2 attacks digestive system, urogenital system, nervous system and circulatory system. Some new mechanisms about SARS-CoV-2 invading human cell. SARS-CoV-2 plays an important role in "Inflammatory Cascade". Since early December 2019, a number of pneumonia cases associated with unknown coronavirus infection were identified in Wuhan, China, and many additional cases were identified in other regions of China and in other countries within 3 months. Currently, more than 80,000 cases have been diagnosed in China, including more than 3000 deaths. The epidemic is spreading to the rest of the world, posing a grave challenge to prevention and control. On February 12, 2020, the International Committee on Taxonomy of Viruses and the World Health Organization officially named the novel coronavirus and associated pneumonia as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease 2019 (COVID-19), respectively. According to the recent research on SARS-CoV-2, the virus mainly infects the respiratory system but may cause damage to other systems. In this paper, we will systematically review the pathogenic features, transmission routes, and infection mechanisms of SARS-CoV-2, as well as any adverse effects on the digestive system, urogenital system, central nervous system, and circulatory system, in order to provide a theoretical and clinical basis for the diagnosis, classification, treatment, and prognosis assessment of SARS-CoV-2 infection. [ABSTRACT FROM AUTHOR]

The sudden outbreak of the COVID-19 pandemic has brought drastic changes to people's daily lives, work, and the surrounding environment. Investigations into these changes are very important for decision makers to implement policies on economic loss assessments and stimulation packages, city reopening, resilience of the environment, and arrangement of medical resources. In order to analyze the impact of COVID-19 on people's lives, activities, and the natural environment, this paper investigates the spatial and temporal characteristics of Nighttime Light (NTL) radiance and Air Quality Index (AQI) before and during the pandemic in mainland China. The monthly mean NTL radiance, and daily and monthly mean AQI are calculated over mainland China and compared before and during the pandemic. Our results show that the monthly average NTL brightness is much lower during the quarantine period than before. This study categorizes NTL into three classes: residential area, transportation, and public facilities and commercial centers, with NTL radiance ranges of 5–20, 20–40 and greater than 40 (nW· cm − 2 · sr − 1 ), respectively. We found that the Number of Pixels (NOP) with NTL detection increased in the residential area and decreased in the commercial centers for most of the provinces after the shutdown, while transportation and public facilities generally stayed the same. More specifically, we examined these factors in Wuhan, where the first confirmed cases were reported, and where the earliest quarantine measures were taken. Observations and analysis of pixels associated with commercial centers were observed to have lower NTL radiance values, indicating a dimming behavior, while residential area pixels recorded increased levels of brightness after the beginning of the lockdown. The study also discovered a significant decreasing trend in the daily average AQI for mainland China from January to March 2020, with cleaner air in most provinces during February and March, compared to January 2020. In conclusion, the outbreak and spread of COVID-19 has had a crucial impact on people's daily lives and activity ranges through the increased implementation of lockdown and quarantine policies. On the other hand, the air quality of mainland China has improved with the reduction in non-essential industries and motor vehicle usage. This evidence demonstrates that the Chinese government has executed very stringent quarantine policies to deal with the pandemic. The decisive response to control the spread of COVID-19 provides a reference for other parts of the world. [ABSTRACT FROM AUTHOR]

Background: The current outbreak of COVID-19 infection, which started in Wuhan, Hubei province, China, in December 2019, is an ongoing challenge and a significant threat to public health requiring surveillance, prompt diagnosis, and research efforts to understand a new, emergent, and unknown pathogen and to develop effective therapies. Despite the increasing number of published studies on COVID-19, in all the examined studies the lack of a well-defined pathophysiology of death among patients who died following COVID-19 infection is evident. Autopsy should be considered mandatory to define the exact cause of death, thus providing useful clinical and epidemiologic information as well as pathophysiological insights to further provide therapeutic tools. Methods: A literature review was performed on PubMed database, using the key terms: "COVID-19", "nCov 19", and "Sars Cov 2". 9709 articles were retrieved; by excluding all duplicated articles, additional criteria were then applied: articles or abstracts in English and articles containing one of the following words: "death", "died", "comorbidity", "cause of death", "biopsy", "autopsy", or "pathological". Results: A total of 50 articles met the inclusion criteria. However, only 7 of these studies reported autopsy-based data. Discussion: The analysis of the main data from the selected studies concerns the complete analysis of 12,954 patients, of whom 2269 died (with a mortality rate of 17.52%). Laboratory confirmation of COVID-19 infection was obtained in all cases and comorbidities were fully reported in 46 studies. The most common comorbidities were: cardiovascular diseases (hypertension and coronary artery disease), metabolic disorders (diabetes, overweight, or obesity), respiratory disorders (chronic obstructive pulmonary disease), and cancer. The most common reported complications were: acute respiratory distress syndrome (ARDS), acute kidney injury, cardiac injury, liver insufficiency, and septic shock. Only 7 papers reported histological investigations. Nevertheless, only two complete autopsies are described and the cause of death was listed as COVID-19 in only one of them. The lack of postmortem investigation did not allow a definition of the exact cause of death to determine the pathways of this infection. Based on the few histopathological findings reported in the analyzed studies, it seems to be a clear alteration of the coagulation system: frequently prothrombotic activity with consequent thromboembolism was described in COVID-19 patients. As a scientific community, we are called on to face this global threat, and to defeat it with all the available tools necessary. Despite the improvement and reinforcement of any method of study in every field of medicine and science, encouraging the autopsy practice as a tool of investigation could also therefore, help physicians to define an effective treatment to reduce mortality. [ABSTRACT FROM AUTHOR]

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began in December 2019 and rapidly spread to other provinces in China as well as other countries. In this study, 262 patients diagnosed with moderate to severe SARS-CoV-2 pneumonia in Wuhan, China, were analyzed. Data were compared between survivors and nonsurvivors. Of all the 262 patients, 23 (8.8%) patients died and 239 (91.2%) were discharged. The median age was 63.5 years and 46.9% of patients were male. The main complaints were fever (83.6%), cough (63.4%), and fatigue (49.2%) in the surviving group, while there were more complaints of dyspnea (39.1%) and shortness of breath (56.5%) in the nonsurviving group. The main comorbidities were hypertension (35.5%), diabetes mellitus (16.4%), and coronary artery disease (9.9%). Morbidity is higher in elderly patients with more comorbidities. Patients were mainly treated with nasal cannula (93.9%), while the nonsurviving group received more invasive mechanical ventilation (39.1%). Arbidol (80.9%), ribavirin (36.6%), oseltamivir (38.9%), interferon (16.4%), and ganciclovir (14.5%) were used for the antiviral treatment. In the nonsurviving group, the number of white blood cells (WBC) was significantly increased and lymphocytes were decreased, and lymphopenia was more common. The levels of aspartate transaminase (AST), brain natriuretic peptide (BNP), creatine kinase isoenzyme MB (CK-MB), lactate dehydrogenase (LDH), and C-reactive protein (CRP) were also significantly increased in the nonsurviving group. The adjusted hazard ratios (HRs) for association of known variables for all-cause mortality due to the coronavirus disease 2019 were 2.467 (95% confidence interval [CI], 1.007–6.044; p = 0.048) for shortness of breath and 1.025 (95% CI, 1.001–1.049; p = 0.042) for AST. Elderly patients with more comorbidities and complaints of dyspnea and shortness of breath had increased risk of death. Patients with lymphopenia and high levels of WBC, AST, BNP, CK-MB, LDH, and CRP may be more likely to deteriorate. [ABSTRACT FROM AUTHOR]