Forecasting the impact of environmental stresses on the frequent waves of COVID19

Abstract

A novel approach to link the environmental stresses with the COVID-19 cases is adopted during this research. The time-dependent data are extracted from the online repositories that are freely available for knowledge and research. Since the time series data analysis is desired for the COVID-19 time-dependent frequent waves, here in this manuscript, we have developed a time series model with the aid of "nonlinear autoregressive network with exogenous inputs (NARX)" approach. The distribution of infectious agent-containing droplets from an infected person to an uninfected person is a common form of respiratory disease transmission. SARS-CoV-2 has mainly spread via short-range respiratory droplet transmission. Airborne transmission of SARS-CoV-2 seems to have occurred over long distances or times in unusual conditions; SARS-CoV-2 RNA was found in PM10 collected in Italy. This research shows that SARS-CoV-2 particles adsorbed to outdoor PM remained viable for a long time, given the epidemiology of outdoor

COVID-19 Variants and Transfer Learning for the Emerging Stringency Indices

“…The researchers [ 14 , 18 ] assessed the impact of the environmental stressors such as the impact of ozone, impact of nitrogen present in the environment, and other factors, on the spread of this enveloped virus. Another group of researchers [ 5 ] discussed the impact of pollution as well as the temperature, on the spread of this virus.…”

“…To be more explicit, different variants of coronavirus exist in the world with different properties and characteristics since 1962 [ 1 , 6 , 14 , 16 , 17 , 19 – 23 ]. According to the recent studies, the major variants that are extensively reported are: the Alpha Variant (formerly called the UK Variant and officially known as B.1.1.7) , Variant (South Africa Variant/ B.1.351), Variant (Brazil Variant, officially known as P.1), and the Variant (India Variant and officially known as B.1.617.2).…”

Improvement on PDP Evaluation Performance Based on Neural Networks and SGDK-means Algorithm

“…We believe that the training of neural networks will be easier when the capability of computation is improved. The proposed method can be employed to study big data access control in social networks (Yu et al 2021a ; Yang et al 2020 ) and CoVID-19 (Yu et al 2021b , c , d ).…”

The impact of vaccination on the spread of COVID-19: Studying by a mathematical model

“…Mathematical models are important tools for predicting and simulating the spread of epidemics, and can provide a theoretical basis for decision-makers to formulate various epidemic prevention measures. There are many mathematical models related to the spread of COVID-19, such as those in [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] . There are also some studies on the impact of vaccination on the spread of COVID-19.…”