Occupational exposure of health care personnel to SARS-CoV-2 particles in the intensive care unit of Tehran hospital

The impact of plastic during the COVID-19 pandemic: The point of view of the environmental science literature

COVID-19 is the official name of the disease provoked by a coronavirus called SARS-CoV-2. Since the advent of the first cases of the new coronavirus, our society has been completely changed. Due to the changes, new environmental challenges were imposed, principally due to the considerable growth in using plastic materials in packages and personal protective equipment such as face masks. The impact of plastic during the COVID-19 pandemic was discussed in the present work from the point of view of the environmental science area. Bibliometric analysis and mapping were performed based on Scopus database search results. Emphasis was placed on analyzing the authors' keywords of the publications. The main concern of the research area concerning the use of plastic during the COVID-19 pandemic is the pollution of water bodies by plastic.

Climate change adaption strategies in urban communities: new evidence from Islamabad, Pakistan

Pakistan is urbanizing at the fastest pace in South Asia, and if left unplanned, it will not only reduce adaptive capacity of its residents rather it will be a chaos for its residents. The aim of this study is to answer the question on how urbanites of Pakistan are coping with climate change and which part of the society required support to cope with changing climate? To answer this questions, this study conducted survey through a structured questionnaire, from the urban residents of Islamabad, to explore their coping mechanisms towards climate change. Survey collected information on demographic, social, economic, and physical aspects, using Hackman's Treatment effect model. The sample selection equation is conditional on the adaptations to climate change in the outcome equation. Main independent variables are income, age, education, and occupation. Selection equation is based on perceptions of individuals about climate change which contains dependent variables of changes in temperature of summers and winters, changes in rain fall pattern, fog, hailstorm, and information received from social media and peer groups. With the result of 57.55, the Wald test shows that overall, there exists goodness of fit at the 99 percent confidence level. The value of rho in the Heckman model is 0.40 which implies the Heckman model provides more consistent and more efficient estimates. The results are suggesting that increasing age enhances the likelihood of adaptations as the positive and significant coefficient of age implies that age has probability to adapt to climate change. The positive and significant coefficient of income, education, and occupation implies that urbanites have higher probability to adapt to climate change. Perception is the essential foundation of adaptation, and differences in perception can be transferred to the adapted strategies. Households that experience a greater variation in annual mean temperature are more likely to adopt any adaptation strategy to cope with climate change. Essentially, poverty encompasses the majority of the characteristics that reduce respondents' adaptation capacity and increase their susceptibility to climate change. The major contextual disparities were discovered across union councils in the form of financial, personal, social, physical, and natural capitals of families. Therefore, obligation is on government to offer greater support for individuals who are less affluent in terms of these assets. For this city, officials must offer subsidy schemes to less privileged and marginalized people of urban dwellers to enhance their adaptive capacity.

Inactivation of airborne SARS-Co-V2 using NTP-UVGI hybrid process

Indoor environments such as healthcare centers are known as one of the key centers in the outbreak of viral infectious diseases. In the present study, the pathogenic agents' treatment system (PATS) was designed by the combination of non-thermal plasma (NTP) with the ultraviolet germicidal irradiation (UVGI) processes. Then, the treatment efficiency of PATS was measured for the "SARS-Co-V2." The exhaled air of the confirmed case of "COVID-19" was considered as the viral source of "SARS-Co-V2" and directed to the upstream of PATS. The treatment process was done by passing directed air through two steps of treatment (NTP and UVGI). The treatment efficiency of PATS was measured by sampling at the sampling points (before and after the treatment process). According to the energy emission pattern (corona discharge, UV rays) in the designed system, during two steps, the high efficiency of treatment for the collected pathogens was achieved. Based on the real-time polymerase chain reaction (RT-PCR) results, the CT value was lower than 29 (CTs < 29), and after the treatment using PATS was upper than 40 (CTs > 40) confirming the highest removal efficiency of "SARS-Co-V2." Also, the treatment efficiency of each reactor in individual operation was at the optimum level. The findings suggested, the present PATS may eliminate the viral pathogens with hospital sources and also, be applicable in the other intensive care unit (ICU) wards with the same risk thus, significantly reducing the possible exposure risk of healthcare and sick companions, and preventing the outbreak of infectious diseases.

SARS-CoV-2 and other airborne respiratory viruses in outdoor aerosols in three Swiss cities before and during the first wave of the COVID-19 pandemic

Caused by the SARS-CoV-2 virus, Coronavirus disease 2019 (COVID-19) has been affecting the world since the end of 2019. While virus-laden particles have been commonly detected and studied in the aerosol samples from indoor healthcare settings, studies are scarce on air surveillance of the virus in outdoor non-healthcare environments, including the correlations between SARS-CoV-2 and other respiratory viruses, between viruses and environmental factors, and between viruses and human behavior changes due to the public health measures against COVID-19. Therefore, in this study, we collected airborne particulate matter (PM) samples from November 2019 to April 2020 in Bern, Lugano, and Zurich. Among 14 detected viruses, influenza A, HCoV-NL63, HCoV-HKU1, and HCoV-229E were abundant in air. SARS-CoV-2 and enterovirus were moderately common, while the remaining viruses occurred only in low concentrations. SARS-CoV-2 was detected in PM₁₀ (PM below 10 µm) samples of Bern and Zurich, and PM_2.5 (PM below 2.5 µm) samples of Bern which exhibited a concentration positively correlated with the local COVID-19 case number. The concentration was also correlated with the concentration of enterovirus which raised the concern of coinfection. The estimated COVID-19 infection risks of an hour exposure at these two sites were generally low but still cannot be neglected. Our study demonstrated the potential functionality of outdoor air surveillance of airborne respiratory viruses, especially at transportation hubs and traffic arteries.

COVID-19 mortality and exposure to airborne PM2.5: A lag time correlation

COVID-19 has escalated into one of the most serious crises in the 21st Century. Given the rapid spread of SARS-CoV-2 and its high mortality rate, here we investigate the impact and relationship of airborne PM_2.5 to COVID-19 mortality. Previous studies have indicated that PM_2.5 has a positive relationship with the spread of COVID-19. To gain insights into the delayed effect of PM_2.5 concentration (μgm^-3) on mortality, we focused on the role of PM_2.5 in Wuhan City in China and COVID-19 during the period December 27, 2019 to April 7, 2020. We also considered the possible impact of various meteorological factors such as temperature, precipitation, wind speed, atmospheric pressure and precipitation on pollutant levels. The results from the Pearson's correlation coefficient analyses reveal that the population exposed to higher levels of PM_2.5 pollution are susceptible to COVID-19 mortality with a lag time of >18 days. By establishing a generalized additive model, the delayed effect of PM_2.5 on the death toll of COVID-19 was verified. A negative correction was identified between temperature and number of COVID-19 deaths, whereas atmospheric pressure exhibits a positive correlation with deaths, both with a significant lag effect. The results from our study suggest that these epidemiological relationships may contribute to the understanding of the COVID-19 pandemic and provide insights for public health strategies.