The Impact of COVID-19 Lockdown on Ambient Air Quality in Shanghai, 2022

The COVID-19 lockdown contributes to the improvement of air quality. Most previous studies have attributed this to the reduction of human activity while ignoring the meteorological changes, this may lead to an overestimation or underestimation of the impact of COVID-19 lockdown measures on air pollution levels. To investigate this issue, we propose an XGBoost-based model to predict the concentrations of PM2.5 and PM10 during the COVID-19 lockdown period in 2022, Shanghai, and thus explore the limits of anthropogenic emission on air pollution levels by comprehensively employing the meteorological factors and the concentrations of other air pollutants. Results demonstrate that actual observations of PM2.5 and PM10 during the COVID-19 lockdown period were reduced by 60.81% and 43.12% compared with the predicted values (regarded as the period without the lockdown measures). In addition, by comparing with the time series prediction results without considering meteorological factors, the actual observations of PM2.5 and PM10 during the lockdown period were reduced by 50.20% and 19.06%, respectively, against the predicted values during the non-lockdown period. The analysis results indicate that ignoring meteorological factors will underestimate the positive impact of COVID-19 lockdown measures on air quality. © 2023 by the authors.

Face Mask Detector for Raspberry Pi Based on Computer Vision and Edge Computing

The pandemic of the coronavirus disease 2019 has shown weakness and threats in various fields of human activity. In turn, the World Health Organization has recommended different preventive measures to decrease the spreading of coronavirus. Nonetheless, the world community ought to be ready for worldwide pandemics in the closest future. One of the most productive approaches to prevent spreading the virus is still using a face mask. This case has required staff who would verify visitors in public areas to wear masks. The aim of this paper was to identify persons remotely who wore masks or not, and also inform the personnel about the status through the message queuing telemetry transport as soon as possible using the edge computing paradigm. To solve this problem, we proposed to use the Raspberry Pi with a camera as an edge device, as well as the TensorFlow framework for pre-processing data at the edge. The offered system is developed as a system that could be introduced into the entrance of public areas. Experimental results have shown that the proposed approach was able to optimize network traffic and detect persons without masks. This study can be applied to various closed and public areas for monitoring situations. © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

The effects of city morphology on airborne transmission of COVID-19. Case study: Port Said City, Egypt.

Looking beyond COVID-19 outbreak, Scholars continue to develop innovative approaches to bring the city on to health and safety. Recent studies have indicated that urban spaces could produce or propagate pathogens, which is an urgent topic at the city level. However, there is a dearth of studies investigating the interrelationship between urban morphology and pandemics outbreak at the neighborhood level. Accordingly, this research will trace the effect of cities morphologies on the rate of spread of COVID-19 through a simulation study held on five areas that form the urban morphology of Port Said City, using Envi-met software. Results are explored based on the degree of concentration and rate of diffusion of coronavirus particles. It was observed on a regular basis that wind speed has a directly proportional relationship with the diffusion of the particles and an inversely proportional relationship with the concentration of the particles. However, certain urban characteristics led to inconsistent and opposing results like wind tunnels, shaded arcades, height variance, and spacious in-between spaces. Moreover, it is obvious that the city morphology is being transformed over time toward safer conditions; urban areas constructed recently have low vulnerability to respiratory pandemics outbreak compared to older areas.

Effect of Covid-19 on Audit Evidence Collection and Its Relationship with Fraud Detection

During the COVID-19, mostly human activities were hampered. In the heat of the Pandemic, human activities are encouraged to follow the Work from Home (WFH) policy. This creates obstacles to the process of collecting company data by the accountants for audit purposes by the auditors. The Auditors also have to make sure of the sufficiency and relevancy of the audit process that has been determined. In addition to collecting data for auditing, the auditor must also have to be able to detect potential fraud that occurs, With the Work from Home (WFH) policy which indirectly affects the movement of the auditors due to the existence of these limitations become it becomes a new challenge for auditors to continue to be able to detect potential fraud and it is hoped that later the results of the audit will meet with the financial statements users expectation. © 2022 ACM.

Changes of Air Pollutants in Urban Cities during the COVID-19 Lockdown-Sri Lanka

In response to the COVID-19 pandemic in early 2020, Sri Lanka underwent a nationwide lockdown that limited motor vehicle movement, industrial operations, and human activities. This study analyzes the impact of COVID-19 lockdown on carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), and particulate matter (PM10, PM2.5) concentrations in two urban cities (Colombo and Kandy) in Sri Lanka, by comparison of data from the lockdown period (March to May 2020) with its analogous period of 2019 and 2021. The results showed that the percentage change of daytime PM10, PM2.5, CO, and NO2 concentration during the lockdown in Colombo (Kandy) is –42.3% (–39.5%), –46% (–54.2%), –14.7% (–8.8%) and –82.2% (–80.9%), respectively. In both cities, the response of NO2 to the lockdown was the most sensitive. In contrast, daytime O3 concentration in Colombo (Kandy) has increased by 6.7% (27.2%), suggesting that the increase in O3 concentration was mainly due to a reduction in NOx emissions leading to lower O3 titration by NO. In addition, daytime SO2 concentration in Colombo has increased by 22.9%, while daytime SO2 concentration in Kandy has decreased by –40%. During the lockdown period, human activities were significantly reduced, causing significant reductions in industrial operations and transportation activities, further reducing emissions and improving air quality in two cities. The results of this study offer potential for local authorities to better understand the emission sources, assess the effectiveness of current air pollution control strategies, and form a basis for formulating better environmental policies to improve air quality and human health. © The Author(s).

CYBER SECURITY IN THE HEALTHCARE SECTOR - CURRENT THREATS

Information technology is a common part of human activities today. In most countries of the world, the security, health, and industrial sectors can be established here. The dependence of these sectors on information technology has been significantly strengthened by the global covid-19 pandemic and the current war in Ukraine. Data digitization has brought positives such as availability, fast transmission, and processing of necessary information. As well as negatives as constant attempts to steal, destroy or abuse them. Health care is one of the sectors where it is the target of not only enrichment attacks, but also terrorist motives - the attack causes chaos and panic among the population. The number of such attacks increased dramatically during the covid - 19 pandemic and the military conflict in Ukraine. The article is therefore intended to point out the need for constant evaluation of changing environmental influences and motivations for attacks with regard to the topicality of security. The introduction of the article contains a theoretical framework of the issue with a description of the motivation and behavior of the offender. It goes on to list the most common ways of conducting cyber-attacks. Significant attacks on hospitals in the Czech Republic and around the world are also mentioned. It focuses on their motivation, success and damage caused. Finally, the common characteristic strengths and weaknesses of the SWOT method are evaluated, followed by opportunities and threats. In the end, the current extended recommendations follow the current routine operation of security procedures with an emphasis on changes and new threats in the global environment. © 2022 International Multidisciplinary Scientific Geoconference. All rights reserved.

Capturing Secchi disk depth by using Sentinel-2 MSI imagery in Jiaozhou Bay, China from 2017 to 2021

Water clarity is a key parameter for assessing changes of aquatic environment. Coastal waters are complex and variable, remote sensing of water clarity for it is often limited by low spatial resolution. The Sentinel-2 Multi-Spectral Instrument (MSI) imagery with a resolution of up to 10 m are employed to solve the problem from 2017 to 2021. Distribution and characteristics of Secchi disk depth (SDD) in Jiaozhou Bay (JZB) are analyzed. Subtle changes in localized small areas are discovered, and main factors affecting the changes are explored. Among natural factors, precipitation and wind play dominant roles in variation in SDD. Human activities have a significant influence on transparency, among which fishery farming has the greatest impact. This is clearly evidenced by the significant improvement of SDD in JZB due to the sharp decrease in human activities caused by coronavirus disease 2019 (COVID-19).Copyright © 2022 The Authors

Surface Subsidence Characteristics and Causes in Beijing (China) before and after COVID-19 by Sentinel-1A TS-InSAR

Surface subsidence is a serious threat to human life, buildings and traffic in Beijing. Surface subsidence is closely related to human activities, and human activities in Beijing area showed a decreasing trend during the Corona Virus Disease 2019 (COVID-19). To study surface subsidence in Beijing before and after the COVID-19 outbreak and its causes, a total of 51 Sentinel-1A SAR images covering Beijing from January 2018 to April 2022 were selected to derive subsidence information by Time Series Interferometry Synthetic Aperture Radar (TS-InSAR). The results of surface subsidence in Beijing demonstrate that Changping, Chaoyang, Tongzhou and Daxing Districts exhibited the most serious subsidence phenomenon before the COVID-19 outbreak. The four main subsidence areas form an anti-Beijing Bay that surrounds other important urban areas. The maximum subsidence rate reached −57.0 mm/year. After the COVID-19 outbreak, the main subsidence area was separated into three giant subsidence funnels and several small subsidence funnels. During this period, the maximum subsidence rate was reduced to −43.0 mm/year. Human activity decrease with the COVID-19 outbreak. This study effectively analysed the influence of natural factors on surface subsidence after excluding most of the human factors. The following conclusions are obtained from the analysis: (1) Groundwater level changes, Beijing's geological structure and infrastructure construction are the main reasons for surface subsidence in Beijing. (2) Seasonal changes in rainfall and temperature indirectly affect groundwater level changes, thereby affecting surface subsidence in the area. (3) The COVID-19 outbreak in early 2020 reduced the payload of Beijing's transportation facilities. It also slowed down the progress of various infrastructure construction projects in Beijing. These scenarios affected the pressure on the soft land base in Beijing and reduced the surface subsidence trend to some extent. © 2023 by the authors.

Effectiveness analysis of multiple epidemic prevention measures in the context of COVID-19 using the SVIRD model and ensemble Kalman filter.

The ability to accurately forecast the spread of coronavirus disease 2019 (COVID-19) is of great importance to the resumption of societal normality. Existing methods of epidemic forecasting often ignore the comprehensive analysis of multiple epidemic prevention measures. This paper aims to analyze various epidemic prevention measures through a compound framework. Here, a susceptible-vaccinated-infected-recovered-deceased (SVIRD) model is constructed to consider the effects of population mobility among origin and destination, vaccination, and positive retest populations. And we further use real-time observations to correct the model trajectory with the help of data assimilation. Seven prevention measures are used to analyze the short-term trend of active cases. The results of the synthetic scene recommended that four measures-improving the vaccination protection rate (IVPR), reducing the number of contacts per person per day (RNCP), selecting the region with less infected people as origin A (SES-O) and limiting population flow entering from A to B per day (LAIP-OD)-are the most effective in the short-term, with maximum reductions of 75%, 53%, 35% and 31%, respectively, in active cases after 150 days. The results of the real-world experiment with Hong Kong as the origin and Shenzhen as the destination indicate that when the daily vaccination rate increased from 5% to 9.5%, the number of active cases decreased by only 7.35%. The results demonstrate that reducing the number of contacts per person per day after productive life resumes is more effective than increasing vaccination rates.

Activities Carried Out during the First COVID-19 Lockdown by Italian Citizens.

The SARS-CoV-2 pandemic has altered how citizens engage in activities. This study describes the new activities citizens engaged in during the first lockdown, factors that helped them cope with the confinement, the supports they used the most, and which supports they would have liked to receive. This cross-sectional study consists of an online survey made of 49 questions that was completed by the citizens of the province of Reggio Emilia (Italy) from 4 May until 15 June 2020. The outcomes of this study were explored by focusing on four of the survey questions. Of the 1826 citizens who responded, 84.2% had started new leisure activities. Males, participants who lived in the plain or foothills, and those who experienced nervousness engaged less in new activities, while those whose employment status changed, whose lifestyle worsened, or whose use of alcohol increased engaged in more activities. The support of family and friends, leisure activities, continuing to work, and an optimistic attitude were perceived to be of help. Grocery delivery and hotlines providing any type of information and mental health support were used frequently; a lack of health and social care services and of support in reconciling work with childcare was perceived. Findings may help institutions and policy makers to better support citizens in any future circumstances requiring prolonged confinement.

Analyzing the Trends of COVID-19 and Human Activity Intensity in Malaysia.

COVID-19 has struck the world with multiple waves. Each wave was caused by a variant and presented different peaks and baselines. This made the identification of waves with the time series of the cases a difficult task. Human activity intensities may affect the occurrence of an outbreak. We demonstrated a metric of time series, namely log-moving-average-ratio (LMAR), to identify the waves and directions of the changes in the disease cases and check-ins (MySejahtera). Based on the detected waves and changes, we explore the relationship between the two. Using the stimulus-organism-response model with our results, we presented a four-stage model: (1) government-imposed movement restrictions, (2) revenge travel, (3) self-imposed movement reduction, and (4) the new normal. The inverse patterns between check-ins and pandemic waves suggested that the self-imposed movement reduction would naturally happen and would be sufficient for a smaller epidemic wave. People may spontaneously be aware of the severity of epidemic situations and take appropriate disease prevention measures to reduce the risks of exposure and infection. In summary, LMAR is more sensitive to the waves and could be adopted to characterize the association between travel willingness and confirmed disease cases.

Detecting Door Operations Using Wearable Devices

Recording indoor human activities such as room occupancy is important to control the COVID-19 pandemic. Logs of human activities can be recorded using wearable devices, provided that the action of entering or exiting a room can be recognized based on the operation of doors. However, relatively few studies on human activity recognition have considered the detection of door operations using wearable devices. In this study, we propose a new deep learning-based technique to detect door operations. We developed a smartwatch application to collect and label multiple forms of data. To evaluate the proposed approach, we conducted an experiment in which we collected data during 4 door operations (2 types of doors with 2 activities, including entering and exiting) using the application. The collected data were then used to train deep learning models. The experimental results show that the average F1 scores ranged from 0.787 to 0.909 when acceleration and angular velocity data were used, which suggests that the proposed technique can detect door operations sufficiently well. © 2022 IEEE.

The Bad And Good Regencies According To The Covid-19 Pandemic In Papua Province In Indonesia

Covid-19 pandemic has quickly spread over the world between 2019 and 2020, reaching Indonesia and Papua Province. Furthermore, public health services are affected by this pandemic. Therefore, this study differentiates between the infected, treated, recovering, and dying of Covid-19 patients in bad and good regencies in Papua Province. During the epidemic, a cross-sectional approach was employed to compare and contrast the health care services in bad and good regencies. This study's secondary and primary data were analyzed using a paired samples t-test. According to the results, the several factors that differentiate between bad and good regencies, include the confirmation of Covid-19, being treated, healed, died, the Covid-19 pandemic, integrated health service posts, community health service centers, hospital health services, and doctors/midwives practice. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Webinar - Is the World Experiencing Dual Pandemics: COVID and Mental Health? Let's talk Positive

Background: In partnership with the Poornima University, the Jodhpur School of Public Health conducted a participatory and live webinar on "Is the world experiencing dual pandemics-COVID and Mental Health? Let's talk positive." On 15th May 2021. Dr. Naresh Nebhinani Additional Professor, Department of Psychiatry AIIMS Jodhpur was the distinguished speaker, who along with Poornima University co-founder Mr. Rahul Singhi and other panellists from Jodhpur School of Public health addressed the topic. Finding(s): The COVID-19 pandemic and the shattering economy have resulted in a detrimental impact on many people's mental health around the globe. It has created new barriers among children, health workers, and elderly along with those who already suffer from mental illness. Every third person who was infected by COVID has shown some signs of mental health issues in one form or the other and prevalence of such disorders have increased by 35% in COVID. The role of behavioural changes towards mental health issues, along with positive attitude, better coping mechanisms, positive lifestyle changes including healthy living, sobriety, healthy eating, regular physical exercise, relaxation, spiritual practice, connectedness with family and close associates, balanced use of gadgets, proper sleep etc result in better outcomes and indicators of mental health resulting due to COVID 19 impacts could be controlled. Conclusion(s): While the health-care system fights to rescue millions of lives on a daily basis, there is a significant risk of a looming pandemic of hidden mental health conditions that might devastate the present mental-health infrastructure. We need inter-disciplinary support of various sectors to execute the plan for people's participation to talk about mental health issues. With specialized psychological interventions and multi-stakeholder collaboration, we can easily curb mental health issues and have a positive outlook in life thereby establishing a balance despite external situations. Copyright © 2023, Institute of Medico-legal Publication. All rights reserved.

Effects of COVID-19 lockdown on the observed density of coral reef fish along coastal habitats of Moorea, French Polynesia.

During the first COVID-19 lockdown in 2020, levels of coastal activities such as subsistence fishing and marine tourism declined rapidly throughout French Polynesia. Here, we examined whether the reduction in coastal use led to changes in fish density around the island of Moorea. Two natural coastal marine habitats (bare sand and mangrove) and one type of man-made coastal structure (embankment) were monitored on the west coast of the island before and after the first COVID-19 lockdown. At the end of the lockdown (May 2020), significantly higher apparent densities of juvenile and adult fish, including many harvested species, were recorded compared to levels documented in 2019 at the same period (April 2019). Fish densities subsequently declined as coastal activities recovered; however, 2 months after the end of the lockdown (July 2020), densities were still higher than they were in July 2019 with significant family-specific variation across habitats. This study highlights that short-term reductions in human activity can have a positive impact on coastal fish communities and may encourage future management policy that minimizes human impacts on coastline habitats. Supplementary Information: The online version contains supplementary material available at 10.1007/s10113-022-02011-0.

Planetary defense: The communication challenge-Lessons from the COVID-19 pandemic

As impact events are known to have had severe effects on the geological and biological evolution of the Earth, the need to detect potentially hazardous objects that might collide with the Earth, and to possibly protect our planet from asteroid impacts, has been recognized in recent years. Planetary defense covers human activities to address potential impacts of Near-Earth Objects on Earth. Once the immediate threat of such an impact is obvious, this fact, along with the intended countermeasures, will have to be communicated to the public. There is a parallel to the recent coronavirus (COVID-19) situation: an imminent threat and the required response are being communicated. Reactions between acceptance and cooperation all the way to denial, conspiracy theories, fake news, and active opposition can be observed. It is evident that these factors will have to be considered in the strategy for communicating the asteroid threat. © 2022 The Geological Society of America.

The Effect of the COVID-19 Pandemic on Nitrogen Dioxide (NO2) Gas Concentration in Yogyakarta Special Province

COVID-19 has plagued the world, one of which is Indonesia. During the COVID-19 pandemic, all anthropogenic activities are limited, including activities that cause air pollution, such as transportation and industrial activities. Nitrogen Dioxide (NO2) is one of the parameters of air pollution which has the main source of human activity. Therefore, this study aims to analyze the effect of the COVID-19 pandemic on changes in NO2 gas concentrations in the Yogyakarta Special Province. This study uses Sentinel 5-P satellite imagery data obtained through cloud computing on Google Earth Engine (GEE) to obtain NO2 gas concentration values. The results showed that there was a 3.7% decrease in the concentration of NO2 gas before and after the COVID-19 pandemic. The correlation result between the number of COVID-19 cases and the concentration of NO2 gas is 0.39, which means it has a weak correlation. © 2022 IEEE.

Texture-Based Covid-19 Images Detection System using Haar Wavelet Transformation Algorithm

Covid-19 remains the worldwide highlight because it is still growing rapidly and has greatly impacted human activities. Preventing its transmission by detecting to allow other actions to be taken continues to be carried out. Various research efforts have been performed to detect Covid-19. Along with developing its detection, technology can be conducted by image processing or machine learning. The detection in this study was carried out using X-ray images of Covid-19 positive people, totaling 101 images, propagated through pre-processing to 404 images. Then, these images were compared with the X-ray images of normal people amounting to 202 and the X-ray images of pneumonia-positive people totaling 390. The extraction process was performed using the Haar wavelet transformation by classifying the data using Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) methods. The Fine KNN model obtained the best accuracy with an average of 94.66%. © 2022 IEEE.

Technological Innovations in the Production of Peruvian Television Newscasts During the Emergence of Covid-19

The outbreak of Covid-19 imposed radical changes in all human activities and television journalism was no exception. This study aims to analyze the innovations that were applied by television journalists in Peru in order to continue practicing their work in one of the countries hardest hit by the pandemic. The applied methodology was qualitative, semi-structured interviews were carried out which allowed knowing the innovations that were applied to overcome the dangers and sanitary restrictions. As a result, it was obtained that the journalists hybridized their teams and production methods with non-television technologies such as video calls, mobile phones, or the implementation of telework to continue producing television news in a context for which they were never prepared. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

The Impacts of the COVID-19 Pandemic on an Educational Institution's Administrative Process, a Process Mining Approach

The COVID-19 pandemic has affected virtually every human activity over the past 2 years. This paper examines how the COVID-19 pandemic interfered with the business processes in Brazil's public vocational and higher education institution. Throughout the pandemic, the Organization forced the enactment of the paper-recorded processes in a virtual implementation. To unveil how the referred paper-recorded processes subset got executed during the pandemic, we conduct a process mining on the company's information system. The process mining data shows various indications of task merging, precluding, and duration modifications. The analysis of 4231 instances of administrative processes between 2019 and 2021 showed a reduction in duration times and the number of tasks. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.