The World Health Organization declared the outbreak of the novel coronavirus (COVID-19) as a pandemic on March 11, 2020. Due to the global threat, many countries impose immediate lockdown. The impact of lockdown on the environmental pollutants and climate indicators gained considerable attention in the literature. This study aims to describe the variations in the environmental pollutants (CO, NO 2 , SO 2 , PM 2.5 and PM 10) with and without the lockdown period in the majorly hit states and provinces of the USA and China, respectively. Data during the first quarter year of 2019 and 2020 (lockdown period) was used in this study. Moreover, the effect of these pollutants on the pandemic spread was also studied. The results illustrated that the overall concentrations of CO, NO 2 and PM 2.5 were decreased by 19.28%, 36.7% and 1.10%, respectively, while PM 10 and SO 2 were increased by 27.81% and 3.81% respectively in five selected states of the USA during the lockdown period. However, in the case of chosen provinces of China, overall, the concentrations of all selected pollutants, i.e., CO, NO 2 , SO 2 , PM 2.5 and PM 10 , were reduced by 26.53%, 38.98%, 18.36%, 17.78% and 37.85%, respectively. The COVID-19 reported cases and deaths were significantly correlated with NO 2 , PM 2.5 and PM 10 in both China and the USA. The findings of this study concluded that the limited anthropogenic activities in the lockdown situation due to this novel pandemic disease result in a significant improvement of air quality by reducing the concentrations of environmental pollutants. As the trend goes on, the reduction of most pollutant concentrations is expected as long as partial or complete lockdown goes on.

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ImportanceThe COVID-19 pandemic has been associated with an increase in mental health diagnoses among adolescents, though the extent of the increase, particularly for severe cases requiring hospitalization, has not been well characterized. Large-scale federated informatics approaches provide the ability to efficiently and securely query health care data sets to assess and monitor hospitalization patterns for mental health conditions among adolescents.ObjectiveTo estimate changes in the proportion of hospitalizations associated with mental health conditions among adolescents following onset of the COVID-19 pandemic.Design, Setting, and ParticipantsThis retrospective, multisite cohort study of adolescents 11 to 17 years of age who were hospitalized with at least 1 mental health condition diagnosis between February 1, 2019, and April 30, 2021, used patient-level data from electronic health records of 8 children’s hospitals in the US and France.Main Outcomes and MeasuresChange in the monthly proportion of mental health condition–associated hospitalizations between the prepandemic (February 1, 2019, to March 31, 2020) and pandemic (April 1, 2020, to April 30, 2021) periods using interrupted time series analysis.ResultsThere were 9696 adolescents hospitalized with a mental health condition during the prepandemic period (5966 [61.5%] female) and 11 101 during the pandemic period (7603 [68.5%] female). The mean (SD) age in the prepandemic cohort was 14.6 (1.9) years and in the pandemic cohort, 14.7 (1.8) years. The most prevalent diagnoses during the pandemic were anxiety (6066 [57.4%]), depression (5065 [48.0%]), and suicidality or self-injury (4673 [44.2%]). There was an increase in the proportions of monthly hospitalizations during the pandemic for anxiety (0.55%; 95% CI, 0.26%-0.84%), depression (0.50%; 95% CI, 0.19%-0.79%), and suicidality or self-injury (0.38%; 95% CI, 0.08%-0.68%). There was an estimated 0.60% increase (95% CI, 0.31%-0.89%) overall in the monthly proportion of mental health–associated hospitalizations following onset of the pandemic compared with the prepandemic period.Conclusions and RelevanceIn this cohort study, onset of the COVID-19 pandemic was associated with increased hospitalizations with mental health diagnoses among adolescents. These findings support the need for greater resources within children’s hospitals to care for adolescents with mental health conditions during the pandemic and beyond.

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The study aimed to investigate the correlation between meteorological parameters and the spread of the COVID-19 pandemic in Islamabad, Pakistan. The meteorological parameters include temperature minimum (°C), temperature maximum (°C), temperature average (°C), humidity minimum (%), humidity maximum (%), humidity average (%), and rainfall (mm). The data of COVID-19, such as the number of new confirmed cases and deaths was obtained from the Ministry of Health, Pakistan. The correlations of various types, i.e., Pearson, Spearman, and Kendall correlations between meteorological parameters and COVID-19, were employed for data analyses. The results exhibited a highly significant relationship between COVID-19 and temperature minimum and temperature average among all meteorological parameters. The study findings may help competitive authorities to combat this disease in Pakistan.