Airborne fungal communities are more susceptible to anthropogenic activities than bacteria.

Airborne microorganisms (AM) have significant environmental and health implications. Extensive studies have been conducted to investigate the factors influencing the composition and diversity of AM. However, the knowledge of AM with anthropogenic activities has not reach a consensus. In this study, we took advantage of the dramatic decline of outdoor anthropogenic activities resulting from COVID-19 lockdown to reveal their associations. We collected airborne particulate matter before and during the lockdown period in two cities. The results showed that it was fungal diversity and communities but not bacteria obviously different between pre-lockdown and lockdown samples, suggesting that airborne fungi were more susceptible to anthropogenic activities than bacteria. However, after the implementation of lockdown, the co-occurrence networks of both bacterial and fungal community became more complex, which might be due to the variation of microbial sources. Furthermore, Mantel test and correlation analysis showed that air pollutants also partly contributed to microbial alterations. Airborne fungal community was more affected by air pollutants than bacterial community. Notably, some human pathogens like Nigrospora and Arthrinium were negatively correlated with air pollutants. Overall, our study highlighted the more impacts of anthropogenic activities on airborne fungal community than bacterial community and advanced the understanding of associations between anthropogenic activities and AM.

Post-traumatic Reactions and Social-Emotional Competence Among Chinese High School Students Experiencing COVID-19 Lockdown: A Network Analysis.

In the post-pandemic era, psychological traumas have emerged as major mental health issues. However, the post-traumatic reactions and their connections with social-emotional competence among high school students experiencing COVID-19 lockdown have not been adequately explored. This study aimed to reveal the characteristics of their positive and negative post-traumatic reactions, and their connections with social-emotional competence. Network analysis was used on data from 1096 Chinese high school students who experienced COVID-19 lockdown. Measures included the DSECS-S, the PTGI and the PC-PTSD-5. The results revealed that "Valuing life" and "Recalling unwillingly" were identified as core factors of post-traumatic reactions, while "Having close friendships", "Getting along well with others" and "Respecting others' emotions" played a bridging role in connecting the communities of social-emotional competence and post-traumatic reactions. This study enriches research on post-traumatic reactions, emphasizing the importance of implementing social-emotional competence programs to tackle mental health crises.

White privilege, ethnic disadvantage, and stigmatized linguistic capital: COVID-19 infection rates and lockdown law enforcement in Hong Kong.

The COVID-19 pandemic has exposed and exacerbated existing disparities in various societies. This study investigates disparities among racial, ethnic, and linguistic groups in Hong Kong's society in COVID-19 infection rates and lockdown enforcement practices that was imposed 545 times from January 2021 to September 2022 and affected 9% of the population. It is found that neighborhoods with more white individuals had lower infection rates than the overall population, while those with more ethnically minoritized groups had higher infection rates. Furthermore, hit rate tests reveal that the government targeted more neighborhoods with a higher share of individuals from linguistically minoritized groups. This novel finding suggests that not only race, but linguistic difference of the same ethnicity can cause bias. The study highlights the positive impact of providing ethnic support services on health outcomes in neighborhoods with a higher share of individuals from ethnically minoritized groups.

Impact of COVID-19 Lockdown on NO2 Pollution and the Associated Health Burden in China: A Comparison of Different Approaches.

So far, a large number of studies have quantified the effect of COVID-19 lockdown measures on air quality in different countries worldwide. However, few studies have compared the influence of different approaches on the estimation results. The present study aimed to utilize a random forest machine learning approach as well as a difference-to-difference approach to explore the effect of lockdown policy on nitrogen dioxide (NO2) concentration during COVID-19 outbreak period in mainland China. Datasets from 2017 to 2019 were adopted to establish the random forest models, which were then applied to predict the NO2 concentrations in 2020, representing a scenario without the lockdown effect. The results showed that random forest models achieved remarkable predictive accuracy for predicting NO2 concentrations, with index of agreement values ranging between 0.34 and 0.76. Compared with the modelled NO2 concentrations, on average, the observed NO2 concentrations decreased by approximately 16 µg/m3 in the lockdown period in 2020. The difference-to-difference approach tended to underestimate the influence of COVID-19 lockdown measures. Due to the improvement of NO2 pollution, around 3722 non-accidental premature deaths were avoided in the studied population. The presented machine learning modelling framework has a great potential to be transferred to other short-term events with abrupt pollutant emission changes.

The Contribution of Legionella anisa to Legionella Contamination of Water in the Built Environment.

Legionella bacteria can proliferate in poorly maintained water systems, posing risks to users. All Legionella species are potentially pathogenic, but Legionella pneumophila (L. pneumophila) is usually the primary focus of testing. However, Legionella anisa (L. anisa) also colonizes water distribution systems, is frequently found with L. pneumophila, and could be a good indicator for increased risk of nosocomial infection. Anonymized data from three commercial Legionella testing laboratories afforded an analysis of 565,750 water samples. The data covered July 2019 to August 2021, including the COVID-19 pandemic. The results confirmed that L. anisa commonly colonizes water distribution systems, being the most frequently identified non-L. pneumophila species. The proportions of L. anisa and L. pneumophila generally remained similar, but increases in L. pneumophila during COVID-19 lockdown suggest static water supplies might favor its growth. Disinfection of hospital water systems was effective, but re-colonization did occur, appearing to favor L. pneumophila; however, L. anisa colony numbers also increased as a proportion of the total. While L. pneumophila remains the main species of concern as a risk to human health, L. anisa's role should not be underestimated, either as a potential infection risk or as an indicator of the need to intervene to control Legionella's colonization of water supplies.

Source apportionment of particle-bound polycyclic aromatic hydrocarbons (PAHs), oxygenated PAHs (OPAHs), and their associated long-term health risks in a major European city.

Many studies have drawn attention to the associations of oxygenated polycyclic aromatic hydrocarbons (OPAHs) with harmful health effects, advocating for their systematic monitoring alongside simple PAHs to better understand the aerosol carcinogenic potential in urban areas. To address this need, this study conducted an extensive PM2.5 sampling campaign in Athens, Greece, at the Thissio Supersite of the National Observatory of Athens, from December 2018 to July 2021, aiming to characterize the levels and variability of polycyclic aromatic compounds (PACs), perform source apportionment, and assess health risk. Cumulative OPAH concentrations (Σ-OPAHs) were in the same range as Σ-PAHs (annual average 4.2 and 5.6 ng m-3, respectively). They exhibited a common seasonal profile with enhanced levels during the heating seasons, primarily attributed to residential wood burning (RWB). The episodic impact of biomass burning was also observed during a peri-urban wildfire event in May 2021, when PAH and OPAH concentrations increased by a factor of three compared to the monthly average. The study period also included the winter 2020-2021 COVID-19 lockdown, during which PAH and OPAH levels decreased by >50 % compared to past winters. Positive matrix factorization (PMF) source apportionment, based on a carbonaceous aerosol speciation dataset, identified PAC sources related to RWB, local traffic (gasoline vehicles) and urban traffic (including diesel emissions), as well as an impact of regional organic aerosol. Despite its seasonal character, RWB accounted for nearly half of Σ-PAH and over two-thirds of Σ-OPAH concentrations. Using the estimated source profiles and contributions, the source-specific carcinogenic potency of the studied PACs was calculated, revealing that almost 50 % was related to RWB. These findings underscore the urgent need to regulate domestic biomass burning at a European level, which can provide concrete benefits for improving urban air quality, towards the new stricter EU standards, and reducing long-term health effects.

Intensification mechanisms and moisture dynamics of super cyclonic storm 'Amphan' over the Bay of Bengal: Implications for aerosol re-distribution.

The present research investigates the dynamics and underlying causes contributing to the exceptional intensity of Super Cyclonic Storm (SuCS) Amphan (16th to 21st May 2020) over the Bay of Bengal (BoB), as well as its impact on aerosol redistribution along the four cities of eastern coast and north-eastern India. Notably, the SuCS was formed during the first phase of the COVID-19 lockdown in India, giving it a unique aspect of study and analysis. Our analysis based on 30 years of climatology data from Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) reanalysis reveals 'positive' monthly anomalous winds (0.8 to 1.6 m/s) prevailed over the central BoB for May 2020. The present study further found the evolution of 'barrier layer thickness'(BLT) leading up to landfall, noting a thickening trend from 8 to 3 days before landfall, contributing to maintaining warmer sea surface temperatures near the coast. Additionally, utilizing European Centre for Medium-Range Weather Forecasts (ECMWF), reanalysis version-5 (ERA-5) data, a mean positive sea surface temperature (SST) anomaly of 0.8 to 1 °C was observed 'before' cyclone period (10-15 May 2020) near the cyclogenesis point. A detailed examination of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) vertical cross-section plots during the cyclone's intensification stage reveals the presence of high-altitude clouds composed primarily of ice crystals. Further, analysis also indicates that the cyclone transported Sea-salt PM2.5 aerosols from the ocean, dispersing them in the landfall region.The aerosol optical Depth (AOD) data obtained from the National Aeronautics and Space Administration's (NASA) 'Clouds and the Earth's Radiant Energy System (CERES)' mission and MERRA-2 were also analysed, revealing that the cyclone redistributed aerosols over the Bengal basin region (mainly over 'Kolkata') and three other nearby cities along the track of the cyclone (i.e., Bhubaneswar (Odisha) Agartala (Tripura) and Shillong (Meghalaya) respectively).

Frequency of Non-strabismic Binocular Vision Anomalies among Optometrists in a Tertiary Eye Care Center in Southern India.

Purpose: Lifestyle in the modern era has drastically changed across the globe, and the healthcare profession was no exception. The increased time spent in the virtual space for various purposes, including online classes and webinars, is hypothesized to increase the risk of vision-related disorders such as asthenopia, dry eyes, and visual fatigue. The purpose of this study was to evaluate fusional vergence and ocular accommodation among optometry professionals in a tertiary eye care center during the immediate post-coronavirus disease 2019 (post-COVID-19) lockdown period. Methods: Optometrists posted in the general out-patient department, specialty clinics, and the ocular diagnostics department were included in the study. A total of 65 optometrists were included in the study. All optometrists underwent a comprehensive binocular vision assessment. Convergence Insufficiency Symptom Survey questionnaires were administered to all optometrists at the beginning of the assessment. Results: Out of 65 optometrists, 48 (73.8%) were women. The mean (standard deviation) age of the participants was 24 (3) years. Eleven (16.9%) optometrists had normal binocular vision parameters, and the rest 54 (83.1%) had non-strabismic binocular vision anomalies. Reduced accommodative facility and convergence insufficiency were seen among 43 (66.2%) optometrists, whereas 30 (46.2%) had reduced accommodative facility alone. Twelve (18.5%) participants were symptomatic as per the convergence insufficiency symptom survey. Conclusion: This study highlights the fact that a large proportion of optometrists have undetected non-strabismic binocular vision anomalies in a tertiary eye care center. It is important for eye care professionals to undergo regular binocular vision assessments in association with ophthalmic examinations and relevant management. This will ensure that these dysfunctions do not impede work productivity and overall quality of life.

Response of PM2.5 chemical composition to the emission reduction and meteorological variation during the COVID-19 lockdown.

PM2.5 is a main atmospheric pollutant with various sources and complex chemical compositions, which are influenced by various factors, such as anthropogenic emissions (AE) and meteorological conditions (MC). MC have a significant impacts on variations in atmospheric pollutant; therefore, emission reduction policies and ambient air quality are non-linearly correlated, which hinders the accurate assessment of the effectiveness of control measures. In this study, we conducted online observations of PM2.5 and its chemical composition in Hohhot, China, from December 1, 2019, to February 29, 2020, to investigate how the chemical compositions of PM2.5 respond to the variations in AE and MC. Moreover, the random forest (RF) model was used to quantify the contributions of AE and MC to PM2.5 and its chemical composition during severe hazes and the COVID-19 pandemic lockdown period. During the clean period, MC reduced PM2.5 concentrations by 124%, while MC incresed PM2.5 concentrations by 49% during severe pollution episode. Inorganic aerosols (SO42-, NO3-, and NH4+) showed the strongest response to MC. MC significantly contributed to PM2.5 (36%), SO42- (32%), NO3- (29%), NH4+ (28%), OC (22%), and SOC (17%) levels during pollution episodes. From the pre-lockdown to lockdown period, AE (MC) contributed 52% (48%), 81% (19%), 48% (52%), 68% (32%), 59% (41%), and 288% (-188%) to the PM2.5, SO42-, NO3-, NH4+, OC, and SOC reductions, respectively. The variations in MC (especially the increase in relative humidity) rapidly generated meteorologically sensitive species (SO42-, NO3-, and NH4+), which led to severe winter pollution. This study provides a reference for assessing the net benefits of emission reduction measures for PM2.5 and its chemical compositions.

Associations of insulin sensitivity and immune inflammatory responses with child blood lead (Pb) and PM2.5 exposure at an e-waste recycling area during the COVID-19 lockdown.

Fine particular matter (PM2.5) and lead (Pb) exposure can induce insulin resistance, elevating the likelihood of diabetes onset. Nonetheless, the underlying mechanism remains ambiguous. Consequently, we assessed the association of PM2.5 and Pb exposure with insulin resistance and inflammation biomarkers in children. A total of 235 children aged 3-7 years in a kindergarten in e-waste recycling areas were enrolled before and during the Corona Virus Disease 2019 (COVID-19) lockdown. Daily PM2.5 data was collected and used to calculate the individual PM2.5 daily exposure dose (DED-PM2.5). Concentrations of whole blood Pb, fasting blood glucose, serum insulin, and high mobility group box 1 (HMGB1) in serum were measured. Compared with that before COVID-19, the COVID-19 lockdown group had lower DED-PM2.5 and blood Pb, higher serum HMGB1, and lower blood glucose and homeostasis model assessment of insulin resistance (HOMA-IR) index. Decreased DED-PM2.5 and blood Pb levels were linked to decreased levels of fasting blood glucose and increased serum HMGB1 in all children. Increased serum HMGB1 levels were linked to reduced levels of blood glucose and HOMA-IR. Due to the implementation of COVID-19 prevention and control measures, e-waste dismantling activities and exposure levels of PM2.5 and Pb declined, which probably reduced the association of PM2.5 and Pb on insulin sensitivity and diabetes risk, but a high level of risk of chronic low-grade inflammation remained. Our findings add new evidence for the associations among PM2.5 and Pb exposure, systemic inflammation and insulin resistance, which could be a possible explanation for diabetes related to environmental exposure.

A longitudinal study of child adjustment during the COVID-19 pandemic: the protective role of the parent-child relationship in middle childhood.

This longitudinal study assessed how parent-child relationship quality during the first COVID-19 lockdown was related to changes in internalizing, externalizing, and sleep problems during the first months of the pandemic: during lockdown, partial deconfinement, and total deconfinement. Participants included 167 children (9-12 year) and their parents recruited in the province of Quebec, Canada. Child behavior problems decreased between lockdown and the two deconfinement assessments, but more sleep and behavior problems were associated with lower levels of relationship quality (more conflict, less closeness, and more insecure attachment). Significant interaction effects showed that changes in externalizing and sleep problems varied as a function of parent-child relationship. Results support the critical importance of the parent-child relationship with regard to child adjustment in middle childhood in times of crisis such as a pandemic. They also highlight resilience in children aged 9 to 12, with a decrease in problems over time.

Intestinal Parasitic Infection in Children and Adolescents With Ocular Diseases: The Prevalence, Spectrum, and Effect of Lockdown During the COVID-19 Pandemic.

INTRODUCTION: People with visual impairments and blindness face challenges in performing regular tasks such as maintaining proper sanitation, which makes them vulnerable to intestinal parasitic infections. AIMS AND OBJECTIVES: This study aims to examine the prevalence and distribution of intestinal parasitic infections in children and adolescents with ocular diseases and to assess if the lockdown during the COVID-19 pandemic affected these rates. METHODS: This retrospective, hospital record-based study was conducted among children and adolescents attending the Regional Institute of Ophthalmology in Kolkata, India. It involved routine stool examinations as part of their treatment during 2019-2020. Early morning stool specimens were collected and brought to the institute laboratory in containers. Stools were examined under a microscope for cysts, ova, parasites, and adult worms. Findings were recorded in the laboratory record book. These data were then extracted into a spreadsheet and analyzed using IBM SPSS Statistics for Windows, Version 26 (Released 2019; IBM Corp., Armonk, New York). RESULTS: The prevalence of intestinal parasitic infections was 8.59% (59 out of 687 patients). Among those 59 positive cases, Ascaris lumbricoides, Giardia lamblia, Entamoeba histolytica, Trichuris trichiura, Taenia spp., Enterobius vermicularis, and Isospora belli were detected in 27 (45.8%), 15 (25.4%), 8 (13.6%), 6 (10.2%), 3 (5.1%), 2 (3.4%), and 1 (1.7%) patients, respectively. The positivity rate of stool samples was higher from September and thereafter from January to March. The sample positivity rate was higher post-pandemic and lockdown, but not statistically significant (11.5% vs. 5.3%; χ²=4.044, df=1, p=0.44). CONCLUSION: Ascaris lumbricoides was the most commonly observed intestinal parasite in children and adolescents with ocular disease in our setting. Seasonal variation was noted with higher case positivity at the end of the rainy season and thereafter in winter. Therefore, we propose to strengthen the routine deworming program during this period in Eastern India. Higher sample positivity after the pandemic may be attributed to school closures during the lockdown period, which might have caused some children to miss their routine deworming medication.

Prevalence and Predictors of Internet Addiction Among Adolescents Before the First Wave of COVID-19 Lockdown in India.

Background Internet dependency behavior was found to be prevalent among adolescents even before the first wave of COVID-19 lockdowns across the world including India. Adolescent users develop Internet addiction due to various risk factors. Aim The aim is to measure the prevalence and psychosocial predictors of internet addiction among adolescents before the first wave of the COVID-19 lockdown in India. Methods A cross-sectional, descriptive study before the first wave of the COVID-19 lockdown, included 1199 adolescents of both genders, aged 11 to 19 years, at selected educational settings from a city in south India, by using Young's Internet addiction test (IAT)-20 and structured questioner. Results The study found almost all the participants (100%) were using the internet in a day and the highest number of subjects started using the internet during their 6th standard of education (13%). Before the first wave of COVID-19 lockdown, the prevalence of a total of mild, moderate, and severe forms of internet addiction among adolescents was 65%. Individual, family, and community-related risk factors were found significant association with Internet addiction. The age of 14-16 years (OR 2.050, p= 0.000), duration of internet use in a day (OR 0.740, p= 0.064), financial matters (OR 0.981, p=0.016), total internet addiction score (OR 1.03, p=0.035) and timings of internet use (OR 1.161, p=0.004), were significant predictors of Internet addiction. Conclusion Internet addiction was prevalent and a notable behavior addiction among adolescents during the margin time of pre-pandemic and the first wave of the COVID-19 lockdown in India. The study highlighted many significant psychosocial risk factors and predictors of Internet Addiction in adolescents, thus the need for a panoramic approach to identify internet addiction in adolescents, to bring the modest behavior of healthy use of the internet in adolescents.

Provision of Telepsychological Care Via Email during COVID-19 Confinement: An Exploratory Study.

Within teletherapy, email interventions have been studied scarcely. For this reason, this exploratory study aims to characterize the assistance provided by email in a university telepsychology service and to compare the data with the assistance provided by telephone in the same service and period. For this purpose, the records of 81 users assisted via email during the COVID-19 pandemic lockdown in Spain were analyzed. The data were compared with those of the 338 users assisted by telephone in the same period. Despite its many limitations, results indicate high satisfaction with the email modality. Users express that they prefer a preference for using email when they do not feel safe in other ways. We found a lot of variation between the number of emails exchanged and the days that each case was active. Additionally, differences were found with telephone users in aspects such as age (email users being younger) and in a depression screening (email users scoring more positively). This study concludes on the high potential of this channel for the application of certain techniques (e.g., psychoeducation) or for people with certain characteristics.

Changes in Sleep Duration and Sleep Timing in the General Population from before to during the First COVID-19 Lockdown: A Systematic Review and Meta-Analysis.

BACKGROUND: The COVID-19 lockdown had a profound effect on everyday life, including sleep health. This systematic review and meta-analysis evaluated changes in quantitative sleep parameters during the first lockdown compared with pre-lockdown in the general population. METHODS: A search in scientific databases was performed to identify eligible observational studies from inception to 8 February 2023. We performed a random effects meta-analysis of those studies reporting (a) means of sleep duration, time in bed (TIB), and sleep timing (bedtime and wake-up time); (b) the percentages of atypical sleep duration before and during the lockdown; (c) the percentages of change in sleep duration and sleep timing. RESULTS: A total of 154 studies were included. A small increase in sleep duration (0.25 standardized mean difference, 95% CI 0.180-0.315) was found, with 55.0% of the individuals reporting changes, predominantly an increase (35.2%). The pooled relative risk for sleeping more than 8/9 h per night was 3.31 (95% IC 2.60-4.21). There was a moderately significant delay in sleep timing and a surge in napping. CONCLUSION: An increase in sleep duration and napping, and delayed sleep timing were observed. High-quality studies should evaluate whether these parameters have now become chronic or have returned to pre-lockdown values.

Atmospheric Oxidation Capacity Elevated during 2020 Spring Lockdown in Chengdu, China: Lessons for Future Secondary Pollution Control.

This study presents the measurement of photochemical precursors during the lockdown period from January 23, 2020, to March 14, 2020, in Chengdu in response to the coronavirus (COVID-19) pandemic. To derive the lockdown impact on air quality, the observations are compared to the equivalent periods in the last 2 years. An observation-based model is used to investigate the atmospheric oxidation capacity change during lockdown. OH, HO2, and RO2 concentrations are simulated, which are elevated by 42, 220, and 277%, respectively, during the lockdown period, mainly due to the reduction in nitrogen oxides (NOx). However, the radical turnover rates, i.e., OH oxidation rate L(OH) and local ozone production rate P(O3), which determine the secondary intermediates formation and O3 formation, only increase by 24 and 48%, respectively. Therefore, the oxidation capacity increases slightly during lockdown, which is partly attributed to unchanged alkene concentrations. During the lockdown, alkene ozonolysis seems to be a significant radical primary source due to the elevated O3 concentrations. This unique data set during the lockdown period highlights the importance of controlling alkene emission to mitigate secondary pollution formation in Chengdu and may also be applicable in other regions of China given an expected NOx reduction due to the rapid transformation to electrified fleets in the future.

Quantifying the impact of urban road traffic on air quality: activity pre-pandemic and during partial and full lockdowns.

The impact of partial and full COVID lockdowns in 2020 on vehicle miles traveled (VMT) in Kuwait was estimated using data extracted from the Directions API of Google Maps and a Python script running as a cronjob. This approach was validated by comparing the predictions based on the app to measuring traffic flows for 1 week across four road segments considered in this study. VMT during lockdown periods were compared to VMT for the same calendar weeks before the pandemic. NOx emissions were estimated based on VMT and were used to simulate the spatial patterns of NOx concentrations using an air quality model (AERMOD). Compared to pre-pandemic periods, VMT was reduced by up to 25.5% and 42.6% during the 2-week partial and full lockdown episodes, respectively. The largest reduction in the traffic flow rate occurred during the middle of these 2-week periods, when the traffic flow rate decreased by 35% and 49% during the partial and full lockdown periods, respectively. The AERMOD simulation results predicted a reduction in the average maximum concentration of emissions directly related to VMT across the region by up to 38%, with the maximum concentration shifting to less populous residential areas as a result of the lockdown.

Machine learning insights into PM2.5 changes during COVID-19 lockdown: LSTM and RF analysis in Mashhad.

This study seeks to investigate the impact of COVID-19 lockdown measures on air quality in the city of Mashhad employing two strategies. We initiated our research using basic statistical methods such as paired sample t-tests to compare hourly PM2.5 data in two scenarios: before and during quarantine, and pre- and post-lockdown. This initial analysis provided a broad understanding of potential changes in air quality. Notably, a low reduction of 2.40% in PM2.5 was recorded when compared to air quality prior to the lockdown period. This finding highlights the wide range of factors that impact the levels of particulate matter in urban settings, with the transportation sector often being widely recognized as one of the principal causes of this issue. Nevertheless, throughout the period after the quarantine, a remarkable decrease in air quality was observed characterized by distinct seasonal patterns, in contrast to previous years. This finding demonstrates a significant correlation between changes in human mobility patterns and their influence on the air quality of urban areas. It also emphasizes the need to use air pollution modeling as a fundamental tool to evaluate and understand these linkages to support long-term plans for reducing air pollution. To obtain a more quantitative understanding, we then employed cutting-edge machine learning methods, such as random forest and long short-term memory algorithms, to accurately determine the effect of the lockdown on PM2.5 levels. Our models' results demonstrated remarkable efficacy in assessing the pollutant concentration in Mashhad during lockdown measures. The test set yielded an R-squared value of 0.82 for the long short-term memory network model, whereas the random forest model showed a calculated cross-validation R-squared of 0.78. The required computational cost for training the LSTM and the RF models across all data was 25 min and 3 s, respectively. In summary, through the integration of statistical methods and machine learning, this research attempts to provide a comprehensive understanding of the impact of human interventions on air quality dynamics.

Assessment and mapping of noise pollution in recreation spaces using geostatistic method after COVID-19 lockdown in Turkey.

Increased use of recreational areas after the lifting of COVID-19 pandemic restrictions has led to increased noise levels. This study aims to determine the level of noise pollution experienced in recreational areas with the increasing domestic and international tourism activities after the lifting of pandemic lockdowns, to produce spatial distribution maps of noise pollution, and to develop strategic planning suggestions for reducing noise pollution in line with the results obtained. Antalya-Konyaalti Beach Recreation Area, the most important international tourism destination of Turkey, is determined as the study area. To determine the existing noise pollution, 31 measurement points were marked at 100 m intervals within the study area. Noise measurements were taken during the daytime (07:00-19:00), evening (19:00-23:00), and nighttime (23:00-07:00) on weekdays (Monday, Wednesday, Friday) and weekends (Sunday) over 2 months in the summer when the lockdown was lifted. In addition, the sound level at each measurement point was recorded for 15 min, while the number of vehicles passing through the area during the same period was determined. The database created as a result of measurements and observations was analyzed using statistical and geostatistical methods. After the analysis of the data, it was found that the co-kriging-stable model showed superior performance in noise mapping. Additionally, it was revealed that there is a high correlation between traffic density and noise intensity, with the highest equivalent noise level (Leq) on weekdays and weekend evenings due to traffic and user density. In conclusion, regions exposed to intense noise pollution were identified and strategic planning recommendations were developed to prevent/reduce noise sources in these identified regions.

Patterns and outcomes of acute toxicological cases before, during, and after COVID-19 lockdown in Sohag University hospitals, Egypt.

Background: Toxicologists manage poisoning by preventing, detecting, and treating it, which requires continuous data collection and analysis of toxicological hazards. Aim of the work: The study aims to report and compare the pattern and outcome of acute toxicological cases admitted to Sohag University Hospitals during the COVID-19 lockdown (2020-2021) with the year before (2019) and the year after (2022). Methods: This comparative study reviewed the sociodemographic and clinical data in the medical records. The study showed that Sohag University Hospitals received 670 toxicological cases between 2019 and 2022; 105 cases in 2019, 347 cases in 2020-2021, and 218 cases in 2022. Results: Most of patients were below seven years with no sex differences. Accidental poisoning was the most frequent toxicity. The oral route was the most common in the three studied periods. During the lockdown, metal phosphide was the most frequent (19.0%), while therapeutic agents were the most reported after the lockdown (23.9%). The delay time showed a significant difference between the studied periods (p-value < 0.001). In the three studied periods, complete recovery was achieved in more than 70% of cases; however, the mortality rate and the rate of complications during the lockdown period (10.4% and 9.5%, respectively) were almost twice those of the year before and the year after the pandemic with significant odds ratio of mortality during pandemic (OR) 0.07 CI 95% (0.02, 0.11). Conclusion: The pandemic had a bad impact on outcomes as showed the highest percentage of mortality compared to before and after COVID-19 periods.