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4.
Environ Res ; 191: 110148, 2020 12.
Article in English | MEDLINE | ID: covidwho-733860

ABSTRACT

This research aims to explore the correlation between meteorological parameters and COVID-19 pandemic in New Jersey, United States. The authors employ extensive correlation analysis including Pearson correlation, Spearman correlation, Kendall's rank correlation and auto regressive distributed lag (ARDL) to check the effects of meteorological parameters on the COVID new cases of New Jersey. In doing so, PM 2.5, air quality index, temperature (°C), humidity (%), health security index, human development index, and population density are considered as crucial meteorological and non-meteorological factors. This research work used the maximum available data of all variables from 1st March to 7th July 2020. Among the weather indicators, temperature (°C) was found to have a negative correlation, while humidity and air quality highlighted a positive correlation with daily new cases of COVID-19 in New Jersey. The empirical findings illustrated that there is a strong positive association of lagged humidity, air quality, PM 2.5, and previous infections with daily new cases. Similarly, the ARDL findings suggest that air quality, humidity and infections have lagged effects with the COVID-19 spread across New Jersey. The empirical conclusions of this research might serve as a key input to mitigate the rapid spread of COVID-19 across the United States.


Subject(s)
Betacoronavirus , Coronavirus Infections , Pandemics , Pneumonia, Viral , COVID-19 , Humans , Meteorological Concepts , New Jersey/epidemiology , SARS-CoV-2 , Temperature
5.
Air Qual Atmos Health ; 13(11): 1335-1342, 2020.
Article in English | MEDLINE | ID: covidwho-714213

ABSTRACT

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, NO2, SO2, PM2.5 and PM10) 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, NO2 and PM2.5 were decreased by 19.28%, 36.7% and 1.10%, respectively, while PM10 and SO2 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, NO2, SO2, PM2.5 and PM10, 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 NO2, PM2.5 and PM10 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.Graphical abstract.

6.
Environ Res ; 187: 109652, 2020 08.
Article in English | MEDLINE | ID: covidwho-260502

ABSTRACT

In December 2019, the novel coronavirus COVID-19 outbreak was first detected in Wuhan Hubei province, China. The April 24, 2020, the Centers for Disease Control and Preventions (CDC) has confirmed more than 39,000 cases, including >1800 deaths. California's Governor Gavin Newsom ordered mandatory stay at home after World Health Organization (WHO) declared COVID-19 as a global pandemic in early March. We have evaluated the correlation between environmental pollution determinants and the COVID-19 outbreak in California by using the secondary published data from the Centers for Disease Control and the Environmental Pollution Agency (EPA). We employed Spearman and Kendall correlation tests to analyze the association of PM 2.5, PM 10, SO2, NO2, Pb, VOC, and CO with COVID-19 cases in California. Our findings indicate that environmental pollutants such as PM10, PM2.5, SO2, NO2, and CO have a significant correlation with the COVID-19 epidemic in California. Overall, our study is a useful supplement to encourage regulatory bodies to promote changes in environmental policies as pollution source control can reduce the harmful effects of environmental pollutants.


Subject(s)
Air Pollution/adverse effects , Coronavirus Infections/epidemiology , Pneumonia, Viral/epidemiology , Betacoronavirus , COVID-19 , California/epidemiology , Humans , Pandemics , Particulate Matter/adverse effects , SARS-CoV-2
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