ABSTRACT
The epidemiological aspects of the viral dynamic of the SARS-CoV-2 have become increasingly crucial due to major questions and uncertainties around the unaddressed issues of how corpse burial or the disposal of contaminated waste impacts nearby soil and groundwater. Here, a theoretical framework base on a meshless algorithm using the moving least squares (MLS) shape functions is adopted for solving the time-fractional model of the viral diffusion in and across three different environments including water, tissue, and soil. Our computations predict that by considering the α (order of fractional derivative) best fit to experimental data, the virus has a traveling distance of 1 m m in water after 22, regardless of the source of contamination (e.g., from tissue or soil). The outcomes and extrapolations of our study are fundamental for providing valuable benchmarks for future experimentation on this topic and ultimately for the accurate description of viral spread across different environments. In addition to COVID-19 relief efforts, our methodology can be adapted for a wide range of applications such as studying virus ecology and genomic reservoirs in freshwater and marine environments.
ABSTRACT
The COVID-19 pandemic lockdown has led to the significant reductions in the pollutant levels across the globe. Several studies have been carried out for examining and quantifying the improvement in the air quality due to the reduction of the pollution at the surface. Unlike most of the studies carried out earlier on COVID-19 lockdown, this study investigates the role of the dynamics on the vertical distribution of the trace gases (Carbonmonoxide (CO), Water Vapor (WV) and Ozone (O3)) over India in the Boundary Layer (BL), Middle Troposphere (MT) and Upper Troposphere (UT) during COVID-19 lockdown using satellite observations and re-analysis data products obtained during 2010-2020. Substantial differences in the time series and variability have been observed over different zones of India in different atmospheric layers. The changes observed in these species are large over Central India compared to South India and Indo-Gangetic plain regions. An enhancement in CO (~25-40%) and WV (50-60%) has been noticed over Central India in the UT at 147 hPa and 215 hPa, respectively, during lockdown. The strong updrafts before the lockdown and the extended weak zonal wind aloft over this region are found responsible for the observed enhancement in these trace gases in the UT. In spite of the non-availability of the anthropogenic pollution during the lockdown, this study highlights the transport of pollutants through long-range transport (always present even before lockdown) dominance over the Indian region not only near the surface but also aloft due to associated atmospheric dynamics.
ABSTRACT
Parkinson's disease (PD) patients who contracted Coronavirus disease 2019 (Covid-19) had a decline in motor functions; nevertheless, there is limited evidence on whether PD patients have a higher risk for contracting Covid-19 or have worse outcomes. This is the first systematic review and meta-analysis to review the impact of PD on the prognosis of Covid-19 patients. We performed a systematic search through seven electronic databases under the recommendations of the Preferred Reporting Items for Systematic Review and Meta-analyses statement (PRISMA) guidelines. The R software version 4.0.2 was used to calculate pooled sample sizes and their associated confidence intervals (95%CI). Finally, we included 13 papers in this study. The pooled prevalence rate of Covid-19 was 2.12% (95%CI: 0.75-5.98). Fever, cough, fatigue and anorexia were the most common symptoms with a rate of 72.72% (95% CI: 57.3 - 92.29), 66.99% (95% CI: 49.08-91.42), 61.58% (95% CI: 46.69-81.21) and 52.55% (95% CI: 35.09-78.68), respectively. The pooled rates were 39.89% (95% CI: 27.09-58.73) for hospitalisation, 4.7% (95% CI: 1.56-14.16) for ICU admission and 25.1% (95%CI: 16.37-38.49) for mortality. On further comparison of hospitalisation and mortality rates among Covid-19 patients with and without PD, there were no significant differences. In conclusion, the prevalence and prognosis of Covid-19 patients seem comparable in patients with PD and those without it. The increased hospitalisation and mortality may be attributed to old age and co-morbidities.