Résumé
This work is motivated by the disease caused by the novel corona virus Covid-19, rapid spread in India. An encyclopaedic search from India and worldwide social networking sites was performed between 1 March 2020 and 20 Jun 2020. Nowadays social network platform plays a vital role to track spreading behaviour of many diseases earlier then government agencies. Here we introduced the approach to predict and future forecast the disease outcome spread through corona virus in society to give earlier warning to save from life threats. We compiled daily data of Covid-19 incidence from all state regions in India. Five states (Maharashtra, Delhi, Gujarat, Rajasthan and Madhya-Pradesh) with higher incidence and other states considered for time series analysis to construct a predictive model based on daily incidence training data. In this study we have applied the predictive model building approaches like k-nearest neighbour technique, Random-Forest technique and stochastic gradient boosting technique in COVID-19 dataset and the simulated outcome compared with the observed outcome to validate model and measure the performance of model by accuracy (ACC) and Kappa measures. Further forecast the future trends in number of cases of corona virus deceased patients using the Holt Winters Method. Time series analysis is effective tool for predict the outcome of corona virus disease. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022.
Résumé
Every individual wishes and desire to be in good health. In the existence environment it has become exceedingly unusual to maintain a good health. The era of CORONA virus compiled every country of the world to give healthcare highest ion all respect. An ideal response to such an epidemic is an IoT-based health score indicator. Real-time health score indicators built by using Internet of Things (IoT) is intended to relieve the stress and movement of ill and fatigued patients. The patients can quickly perform many necessary or obligatory medical tests on-site. In today's hectic society, the vast majority of people as well as patients prefer medical testing to be done at home. In this study, various tools were combined including the thermometer, blood pressure, glucometer, pulse oximeter, heartbeat, and ECG on a single unit. The sensors along with Arduino and LCD were merged to create a single gadget. Moreover, a server-based Android app will be developed to upload information about all the testing results which can makes the patient life easier. © 2023 IEEE.
Résumé
The outbreak of SARS-CoV-2 (Covid-19) is one of the most unprecedented and devastating events that the world has witnessed so far. It was manifested in Wuhan, China in December 2019 and has spread worldwide. The rapidity at which Covid-19 is transmitted has become one of the major concerns regarding the safety of mankind. The similarity of symptoms between Covid-19 and normal flu, like cough, body ache and headache, makes it difficult to ascertain a case to be of normal flu or of Covid. Consequently, many Covid cases are unreported which further increases the risk of spread of infection. In the present chapter, by using three mathematical models, we aim to give an outline of the spread of Covid-19 in West Bengal and how lockdown has helped to reduce the number of Covid cases. The first model is an exponential model;the second model is based on Geometric Progression which shows spread of coronavirus using a tree chart. The third model, named as Model for Stay at Home, shows that due to lockdown, the number of cases is gradually attaining a constant level instead of growing exponentially;thus urging each citizen to stay at home during lockdown unless an unavoidable situation arises. © 2022 Scrivener Publishing LLC.
Résumé
Covid illness (COVID-19) happened in December 2019 first in Wuhan city of Hubei region of China. World Health Organization (WHO) proclaimed the spread or transmission of this infection as a pandemic. The infection named as severe intense respiratory disorder Covid 2 (SARS-CoV-2) by the International Committee on Taxonomy of Viruses on February 11, 2020. Disease due to this novel-coronavirus is infectious. Therefore, modeling such disease is required to understand methods of transmission, spread, epidemic. Several researchers have found that the transfer of the virus occurs through human contact via their pathogens, such as coughing, sneezing, and breathing. With all sorts of preventive measures (social distancing, wearing mask and lockdown), there is a need to develop a dynamic model of epidemiology for infectious disease. In this article, we have developed a new epidemiological dynamical model-design towards simulating spread and awareness towards this genomic-virus. This model studies the complexity analysis including time series and phase dynamics for the development of the virus in Iraq. Examination helps the comprehension of episode of this infection towards different pieces of the mainland and the world. Accuracy in addition to, validity for the assessment would prove to be superior if models fit less of the data on basis of the features: population-mobility with natural-history, epidemiological-characteristics, & transmission-contrivances for virus-gene. It is concluded that for Iraq the spread is following the log normal behavior with long tail. © 2022 American Institute of Physics Inc.. All rights reserved.
Résumé
Aim: To evaluate the impact of telemedicine on the diagnosis of colorectal cancer during and after the COVID 19 pandemic. Method(s): 120 -200 patients/year are diagnosed with colorectal cancer at Darent Valley Hospital. Our database of colorectal cancer patients from 2018 to 2022 was reviewed and patients stratified according to staging and diagnostic pathway (e.g. screening, rapid access referral or emergency admission). These data were compared pre-, during and post-Covid 19 pandemic. Where possible, local data were compared with available national statistics. Result(s): Our analysis suggests that there has been an increase in patients presenting with advanced (T3/T4) colorectal cancer during and after the pandemic. Several had experienced telemedicine consultations and triage both in primary and secondary care and had never been physically examined by a healthcare professional. A comprehensive analysis of these cases will be presented. Conclusion(s): Data from the UK suggests that the Covid-19 pandemic led to a significant reduction in the diagnosis and treatment of colorectal cancer. This implies that there are a large number of people in the community with undiagnosed colorectal cancer, who may subsequently present with advanced disease. As the early detection of cancer improves outcomes, delays to diagnosis could negatively impact survival from colorectal cancer. The COVID-19 pandemic has led to a rise in tele-medicine and the NHS has recommended that >25% of outpatient appointments should take place remotely. However, the suitability of this mode of communication in surgery has been questioned, especially in the assessment of new patients. It is our concern that an over-reliance on telemedicine is causing delays in the physical examination of patients and may be associated with the apparent increase in patients presenting with advanced colorectal cancer. New pathways should be developed for a post-pandemic NHS to ensure that potential cancer patients are physically seen in a timely manner.
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A face mask is essential personal protective equipment to mitigate the spread of COVID-19. While a cloth mask has the least ability to prevent the passage of infectious respiratory droplets through it compared to surgical and N95 masks, the surgical mask does not fit snugly and causes significant air leakage. The synthetic fibers in the latter reduce comfortability and are an allergen for facial eczema. Moreover, the N95 mask causes CO2 inhalation and reduces heat transfer in the nose. Therefore, the objective of the present work is to improve the effectiveness of a two-layer cloth mask by introducing an intermediate, high-efficiency particulate air (HEPA) filter layer. A significant volume of impacted droplets penetrates through a single-layer cloth mask, ejecting secondary droplets from the rear side. However, a two-layer cloth mask prevents this ejection. Despite slowing down the liquid penetration, capillary imbibition through cloth due to its hydrophilicity causes the transport of the liquid into the second layer, resulting in a thin-liquid layer at the mask's rear-side surface and contaminating it. Conversely, the HEPA filter inserted in the cloth mask prevents the imbibition, making the second cloth layer free of contamination. We attribute the impedance to the imbibition by the intermediate HEPA filter layer to its hydrophobic characteristics. We experimentally and analytically assess the role of wettability on capillary imbibition. The breathability measurements of masks show that the HEPA inserted in the cloth mask does not reduce its breathability compared to that of the surgical mask. © 2022 Author(s).
Résumé
Coronavirus disease (Covid-19) occurred first in Wuhan city of Hubei province of China in December 2019. The World Health Organization (WHO) declared the spread or the transmission of this virus as a global pandemic. The virus was named as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the International Committee on Taxonomy of Viruses on February 11, 2020. Disease due to this novel-coronavirus is infectious. Therefore, modeling such an infectious disease is essential to understand the method of its transmission, spread, and epidemic. Several researchers have found that the transfer of the virus occurs through human contact via their pathogens, such as coughing, sneezing, and breathing. With all sorts of preventive measures (social distancing, wearing mask and lockdown), there is a need to develop a dynamic model of epidemiology for infectious disease. In this article, we have developed a new epidemiological dynamical model named RD_Covid-19 (version 1.0) model. The traditional epidemiological model of an infectious disease known as susceptible-exposed-infected-recovered-dead (SEIRD) is modified to develop this new model. RD_Covid-19 is a networked epidemiological model in which a data-driven logistic model, traditional epidemiological models such as SIR (Susceptible, Infected, Recovered), SEIR and SEIQRDP are interlinked. The model forecasts the spread of the Covid-19. Nonlinear least-squares optimization technique is applied for fitting the model to estimate its parameters. The realistic data is taken from John Hopkins University and WHO dashboard. The outcome of the numerical simulation of the model generates the temporal profile of infected, recovered, and death cases. The severity of the model is measured by computing the basic reproduction number (R0). The model executed to explore the corona outbreak in China, India, Brazil, and Russia. The estimated value of basic reproduction number, R0 is well in agreement with that obtained from the outcome of traditional models SIR and SEIR. The verification and validation (V & V) process of our model is carried out by comparing its results with an analogical logistic model. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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At the present scenario, all people are always in a hurry because no one has sufficient time in this fast life. Therefore, people does not waste their time and also not compromise with their safety in many places like, banking, restaurant, cinema, etc. Where all of them are always facing the queue system or change sequence and also nowadays there are many diseases that spread during the public attachment and while holding and touching or by gathering Like covid-19, swine flu, etc. So to encountered this inconvenience and maintain social distancing at the public places, there are many solutions to enhance the speed and safety of human society. So by this paper, it is trying to express a microcontroller-dependent efficient and intelligent token number display system to reduce the problem as mentioned above. The system which we have used is displaying two-digit numbers from 0 to 99 which used to display 1 set and one set at customers and display. Hence by applying this system, the consumers don't worry about their chance and no wastage of time by waiting in a queue. They have to appear when the token number is displayed on the large screen at the store. The whole process contains two portions display unit and the Processing Unit. Every set of the display unit contains seven segment based two display units which get fed from the push button. The kit on which the software designed and applied is 8051 microcontroller. © 2020. All Rights Reserved.