ABSTRACT
Epidemiological data is the data obtained based on disease, injury or environmental hazard occurrence using the previous data on the epidemic situation. We can use it for analysis and find the trends and patterns. We can use different machine learning models to create a platform that can be used for different time series data. We can rely on the properties of time series data like trends and seasonality and use this for future prediction. Acquiring the dataset is the first step in data preprocessing in machine learning. We have collected the dataset from ourWorldIndia website which is a real-life dataset of covid-19. This paper presents the idea of a dedicated machine learning model to forecast the future using epidemiological data. We have taken a data-set of covid-19 for the prediction of the number of daily cases infected by the coronavirus. Our machine learning model can be applied on the dataset of any country in the world. We have applied it on the dataset of India in the experimentation. Our goal behind this research paper is to give the ML model which can be easily used on any epidemiological data for prediction by analysing the seasonality.
ABSTRACT
Machine learning (ML) and artificial intelligence (AI) approaches are prominent and well established in the field of health-care informatics. Because they have a more productive ability to predict, they are successfully applied in several health-care applications. ML approaches are needed thanks to the unsatisfactory experience of the novel virus, considerable ambiguity, complicated social circumstances, and inadequate accessible data. Several approaches have been applied as a tool to combat and protect against the new diseases. The COVID-19 outbreak has rapid growth, so it is not easy to predict the patients and resources within a specified time. ML is a strong approach in the fighting against the pandemic such as COVID-19. It is found significant to predict the susceptible, infected, recovered, or exposed persons and can assist the control strategies to block the spread of infections. This study critically examines the appropriateness and contribution of AI/ML methods on COVID-19 datasets, enhancing the understanding to apply these methods for quick analysis and verification of pandemic databases. © 2022 Elsevier Inc. All rights reserved.
ABSTRACT
News at the times of Covid-19 poses the threat to the health industry. This paper finds the study to understand the features and social sites that propagates fake news without any restriction. The analysis of this fake news has came to the conclusion that it has broadly effected the health, political, entertainment and religious themes. The health related fake news during pandemic tops the chart. The problem of 'fake news' has become the topic of concern and it plays with the sentiments of the people. This problem has spread rapidly during the pandemic due the easy accessibility of social sites. In this paper we are discussing the overview of fake news and using block chain technology and its framework which has served as an efficient tool to combat the spread of fake news and how the various features of fake news have design issues and how it is tackled. © 2021 IEEE.
ABSTRACT
This study analyzes the factors affecting psychological wellbeing and personal coping strategies adopted by individuals, "during the lockdown of the COVID-19 pandemic". Ox CAP-MH and Brief COPE was used to develop an online survey. Using the data collected from 351 respondents of the Indian general population, it was found that psychological well-being was affected by activity levels & social involvement;endogenous & exogenous sense of influence;leisure, bias & self worth;adaptability & mindfulness;and mental stress & sleep. Factors associated with personal coping strategies included positive reframing & active coping;defence mechanisms & self-doubt;use of emotional support & planning for the recovery of the pandemic covid-19 by personal coping;substance use & humour;spirituality;persistence threshold;using social support system. Finally result obtained is "the attitude of females and males varies", towards the majority of the factors. The implications theoretically and in practice have been discussed.
ABSTRACT
The epidemic of acute respiratory infection of coronavirus as COVID-19 has shaken up the world. At the time of writing on 15th September 2020 213 nations all around the globe have reported a total of 32,755,000confirmed cases of coronavirus COVID-19 that originated from Wuhan, China, with a death toll of 4.7 million deaths? The corona epidemic has posed a serious threat to the existence of mankind with global pressure on healthcare sectors. None of the aspects of the existence of societies is unaffected by COVID-19, be it jobs, industries, economy, education, societal, research sector, with rapidly mounting death tolls being a wake-up call for global health. It is very much necessary for the mankind that whole of the scientific world come together with new methods, technologies, medicines and vaccines to curb the spread of this deadly disease. Currently, there is no precise and accurate treatment method available for COVID-19, but a wide range of studies are going on exploring all the possible antiviral solutions. Meanwhile among various fields of science and technology nanotechnology has great potential and can play an important role by providing effective solutions for diagnosis, detection, sensing, treatment and protection against COVID-19. The nanoscale and large surface area of nanoparticles can be very effective in various stages of coronavirus treatment. The article aims to highlight the major prospective contributions and solutions that nanotechnology can fetch to alleviate the chronic COVID-19 pandemic. © 2021, Rasayan Journal of Chemistry, c/o Dr. Pratima Sharma. All rights reserved.