IoT based Automatic Temperature Detection for Covid Prevention

Physicians and the government struggled considerably to limit the spread of COVID-19 during the pandemic, as there was no treatment or vaccinations available. The temperature detection system has only been used to monitor the temperature. This research work proposes an automated temperature detection system, if the temperature is lower than the predetermined temperature (35 degree Celsius), the person will be allowedinside any public place;otherwise, the access will be refused, and then the buzzing system has been used to warn the authorities by producing an alarm sound, and then the area will be instantly sterilized. Thus, by sensing through the sensors, the proposed system assists in limiting the direct transmission of COVID-19 and the fast spreading condition during pandemic scenarios. © 2022 IEEE.

Comparison of first and second waves of COVID-19 in metropolitan Chennai City

The study aims to perform a comparative analysis of new cases of COVID-19 reported during the peak time of two waves in Chennai city in 2019-2020. Eight zone-wise variables for 15 zones of Chennai City were studied. They were reduced to fewer factors using a dimension reduction technique called factor analysis, and a standardized index value for each zone and two waves was obtained. The region of hot spots was identified using the Kriging interpolation method using the standardized index value. During wave 1, the average daily number of deaths, new cases, and active cases was 37, 2071, and 21163, respectively, but it was 76, 6663, and 39385 in the second wave. The second wave has a two times higher number of deaths, 3.2 times higher number of new cases, and 1.8 times of active cases. The first wave had a higher percentage of infected people aged 40 years or older, whereas it was more people aged 10-39 years in the second wave. The Krigged estimates showed comparison showed the regions at a higher risk of transmission. Population demographics play COVID-19 a vital role. The zone with a more slum population (Sholiganallur) does not show much intensity of new cases.

Forecasting Vaccination Drive in India for Herd Immunity using SIR and Prophet Model

This paper aims to study the COVID-19 vaccination drive in India to forecast the time, it will take vaccinate the minimum number of population for achieving herd immunity. As per the government data on 25th March, 2021, a total of 5,55,04,440 doses have been administered as first dose and 85,02,968 as the second dose, which is just a mere fraction of the total population of India which stands at 1.3 billion. As the number of cases are rising, considering the situation, it is important to expedite the drive and follow strict restrictions to achieve herd immunity. A simulation of the SIR model has been created to identify the effective reproduction number (Re), and then through time series analysis using Prophet model, the conclusion has been drawn for the number of days it will take to vaccinate enough population to achieve herd immunity. As an initial step, we will be fitting the data available for COVID-19 for India in the SIR model which is a set of three Ordinary Differential Equations (ODE). The results from the ODEs will be used to determining the initial Re which will be matched with the data set. Once confirming the Re value present in data set, the same will be passed to the data-driven forecasting time series model to get insights and draw conclusions which will help authorities to help in planning the drive and implement necessary actions to avoid further growth of COVID-19 cases. © 2021 IEEE.

Role of high dose oral liposomal vitamin -C in reducing mortality in patients with COVID-19

Introduction: Severe cases of COVID-19 are associated with hypoxemic respiratory failure, acute respiratory distress syndrome (ARDS), septic shock, cardiac dysfunction, elevation in multiple inflammatory cytokines, thrombo embolic disease, and/or exacerbation of underlying co morbidities. In addition to pulmonary disease, patients with COVID-19 may also experience cardiac, hepatic, renal, and central nervous system disease. AIM OF THE STUDY;To describe the role and outcome, of high-dose of oral liposomal vitamin C treatment in reducing mortality in Covid-19 patients admitted in Government Medical College & ESI Hospital, Coimbatore, India. Materials and methods: Patients who admitted with the diagnosis of COVID-19 by RTPCR in government medical college and ESI hospital Coimbatore during 1 th march 2021 to may 31,2021 are taken for this retrospective study. Of the 8634 patients admitted 5422(62%) required non oxygen beds. -2989(34%) required oxygen beds on admission -223 patients(2.5%) required beds (with,98 on c pap, 34 ventilators,64 high flow nasal oxygen, 43 non re-breathing mask and 58 non invasive ventilators), all outcomes are compared with same type of patients admitted in similar hospital and similar set of patients, without high dose vitamin c.