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1.
Chemosphere ; 275: 129968, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1085576

ABSTRACT

A novel coronavirus (2019-nCoV) is an acute life-threatening disease, emerged in China, which imposed a potentially immense toll in terms of public health emergency due to high infection rate and has a devastating economic impact that attracts the world's attention. After that, on January 30, 2020, it was officially declared as a global pandemic by World Health Organization (WHO). The International Committee on Taxonomy of Viruses (ICTV) recognized it as a Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) and the disease named Coronavirus Disease-19 (COVID-19). Several studies have been ameliorated the active role of COVID-19 transmission, etiology, pathogenicity, and mortality rate as serious impact on human life. The symptoms of this disease may include fever, fatigue, cough and some peoples are severely prone to gastrointestinal infection. The elderly and seriously affected peoples are likely concerned with serious outcomes. In this review, we mainly aimed to provide a benchmark summary of the silent characteristics and findings of some candidates for antiviral drugs and immunotherapies such as plasma therapy, cytokine therapy, antibodies, intravenous immunoglobulin, and pharmaceutical health concerns that are related to this disease.


Subject(s)
COVID-19 , Pharmaceutical Preparations , Aged , China , Humans , Pandemics , SARS-CoV-2
2.
Chemosphere ; 272: 129809, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1056443

ABSTRACT

Several major cities that witnessed heavy air pollution by particulate matter (PM2.5) concentration and nitrogen dioxide (NO2) have contributed to high rate of infection and severity of the coronavirus disease (COVID-19) pandemic. Owing to the negative impact of COVID-19 on health and economy, it is imperative to predict the pandemic trend of the COVID-19 outbreak. Pakistan is one of the mostly affected countries by recent COVID-19 pandemic in terms of COVID-cases and economic crises. Like other several Asian countries to combat the virus impacts, Pakistan implemented non-pharmacological interventions (NPI), such as national lockdowns. The current study investigates the effect of major interventions across three out of four provinces of Pakistan for the period from the start of the COVID-19 in March 22, 2020 until June 30, 2020, when lockdowns were started to be eased. High-resolution data on NO2 was recorded from Sentinel-5's Precursor spacecraft with TROPOspheric Monitoring Instrument (Sentinel-5P TROPOMI). Similarly, PM2.5 data were collected from sampling sties to investigate possible correlation among these pollutants and COVID-19. In addition, growth and susceptible-infected-recovered (SIR) models utilizing time-series data of COVID-19 from February 26 to December 31, 2020, with- and without NPI that encompass the predicted number of infected cases, peak time, impact on the healthcare system and mortality in Pakistan. Maximum mean PM2.5 concentration of 108 µgm-3 was recorded for Lahore with the range from 51 to 215 µgm-3, during strict lockdown (L), condition. This is three times higher than Pak-EPA and US-EPA and four times for WHO guidelines, followed by Peshawar (97.2 and 58 ± 130), Islamabad (83 and 158 ± 58), and Karachi (78 and 50 ± 140). The majority of sampling sites in Lahore showed NO2 levels higher than 8.75E-5 (mol/m2) in 2020 compared to 2019 during "L" period. The susceptible-infected-recovered (SIR) model depicted a strong correlation (r) between the predicted and reported cases for Punjab (r = 0.79), Sindh (r = 0.91), Khyber Pakhtunkhwa (KPK) (r = 94) and Islamabad (r = 0.85). Findings showed that major NPI and lockdowns especially have had a large effect on minimizing transmission. Continued community intervention should be undertaken to keep transmission of SARS-CoV-2 under control in cities where higher incidence of COVID-19 cases until the vaccine is available. This study provides a methodological framework that if adopted can assist epidemiologist and policy makers to be well-prepared in advance in cities where PM2.5 concentration and NO2 levels are already high in order to minimize the potential risk of further spread of COVID-19 cases.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Coronavirus , Air Pollutants/analysis , Air Pollution/analysis , Cities , Communicable Disease Control , Environmental Monitoring , Humans , Pakistan/epidemiology , Pandemics , Particulate Matter/analysis , SARS-CoV-2
3.
Chemosphere ; 271: 129584, 2021 May.
Article in English | MEDLINE | ID: covidwho-1014401

ABSTRACT

Information on the spatiotemporal variability of respirable suspended particulate pollutant matter concentrations, especially of particles having size of 2.5 µm and climate are the important factors in relation to emerging COVID-19 cases around the world. This study aims at examining the association between COVID-19 cases, air pollution, climatic and socioeconomic factors using geospatial techniques in three provincial capital cities and the federal capital city of Pakistan. A series of relevant data was acquired from 3 out of 4 provinces of Pakistan (Punjab, Sindh, Khyber Pakhtunkhwa (KPK) including the daily numbers of COVID-19 cases, PM2.5 concentration (µgm-3), a climatic factors including temperature (°F), wind speed (m/s), humidity (%), dew point (%), and pressure (Hg) from June 1 2020, to July 31 2020. Further, the possible relationships between population density and COVID-19 cases was determined. The generalized linear model (GLM) was employed to quantify the effect of PM2.5, temperature, dew point, humidity, wind speed, and pressure range on the daily COVID-19 cases. The grey relational analysis (GRA) was also implemented to examine the changes in COVID-19 cases with PM2.5 concentrations for the provincial city Lahore. About 1,92, 819 COVID-19 cases were reported in Punjab, Sindh, KPK, and Islamabad during the study period. Results indicated a significant relationship between COVID-19 cases and PM2.5 and climatic factors at p < 0.05 except for Lahore in case of humidity (r = 0.175). However, mixed correlations existed across Lahore, Karachi, Peshawar, and Islamabad. The R2 value indicates a moderate relationship between COVID-19 and population density. Findings of this study, although are preliminary, offers the first line of evidence for epidemiologists and may assist the local community to expedient for the growth of effective COVID-19 infection and health risk management guidelines. This remains to be seen.


Subject(s)
Air Pollutants , Air Pollution , COVID-19 , Air Pollutants/analysis , Air Pollution/analysis , Cities , Humans , Pakistan/epidemiology , Pandemics , Particulate Matter/analysis , SARS-CoV-2 , Socioeconomic Factors
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