Assessing eco-geographic influences on COVID-19 transmission: a global analysis.

COVID-19 has been massively transmitted for almost 3 years, and its multiple variants have caused serious health problems and an economic crisis. Our goal was to identify the influencing factors that reduce the threshold of disease transmission and to analyze the epidemiological patterns of COVID-19. This study served as an early assessment of the epidemiological characteristics of COVID-19 using the MaxEnt species distribution algorithm using the maximum entropy model. The transmission of COVID-19 was evaluated based on human factors and environmental variables, including climate, terrain and vegetation, along with COVID-19 daily confirmed case location data. The results of the SDM model indicate that population density was the major factor influencing the spread of COVID-19. Altitude, land cover and climatic factor showed low impact. We identified a set of practical, high-resolution, multi-factor-based maximum entropy ecological niche risk prediction systems to assess the transmission risk of the COVID-19 epidemic globally. This study provided a comprehensive analysis of various factors influencing the transmission of COVID-19, incorporating both human and environmental variables. These findings emphasize the role of different types of influencing variables in disease transmission, which could have implications for global health regulations and preparedness strategies for future outbreaks.

Analysis the molecular similarity of least common amino acid sites in ACE2 receptor to predict the potential susceptible species for SARS-CoV-2.

SARS-CoV-2 infections in animals have been reported globally. However, the understanding of the complete spectrum of animals susceptible to SARS-CoV-2 remains limited. The virus's dynamic nature and its potential to infect a wide range of animals are crucial considerations for a One Health approach that integrates both human and animal health. This study introduces a bioinformatic approach to predict potential susceptibility to SARS-CoV-2 in both domestic and wild animals. By examining genomic sequencing, we establish phylogenetic relationships between the virus and its potential hosts. We focus on the interaction between the SARS-CoV-2 genome sequence and specific regions of the host species' ACE2 receptor. We analyzed and compared ACE2 receptor sequences from 29 species known to be infected, selecting 10 least common amino acid sites (LCAS) from key binding domains based on similarity patterns. Our analysis included 49 species across primates, carnivores, rodents, and artiodactyls, revealing complete consistency in the LCAS and identifying them as potentially susceptible. We employed the LCAS similarity pattern to predict the likelihood of SARS-CoV-2 infection in unexamined species. This method serves as a valuable screening tool for assessing infection risks in domestic and wild animals, aiding in the prevention of disease outbreaks.

An innovative approach to minimize excess sludge production in sewage treatment using integrated bioreactors.

The present investigation deals with an application of integrated sequential oxic and anoxic bioreactor (SOABR) and fluidized immobilized cell carbon oxidation (FICCO) reactor for the treatment of domestic wastewater with minimum sludge generation. The performance of integrated SOABR-FICCO system was evaluated on treating the domestic wastewater at hydraulic retention time (HRT) of 3hr and 6hr for 120days at organic loading rate (OLR) of 191±31mg/(L·hr). The influent wastewater was characterized by chemical oxygen demand (COD) 573±93mg/L; biochemical oxygen demand (BOD5) 197±35mg/L and total suspended solids (TSS) 450±136mg/L. The integrated SOABR-FICCO reactors have established a significant removal of COD by 94%±1%, BOD5 by 95%±0.6% and TSS by 95%±4% with treated domestic wastewater characteristics COD 33±5mg/L; BOD5 9±0.8mg/L and TSS 17±9mg/L under continuous mode of operation for 120days. The mass of dry sludge generated from SOABR-FICCO system was 22.9g/m3. The sludge volume index of sludge formed in the SOABR reactor was 32mL/g and in FICCO reactor it was 46mL/g. The sludge formed in SOABR and FICCO reactor was characterized by TGA, DSC and SEM analysis. Overall, the results demonstrated that the integrated SOABR-FICCO reactors substantially removed the pollution parameters from domestic wastewater with minimum sludge production.