ABSTRACT
The objective of this paper is to provide an insight on effect of stringency in Covid-19 spread in India especially in Chennai, a city were more lockdown, and restrictions was imposed to control the infection. Even though the restriction was imposed in the country by the end of March 2020, the growth reduction was seen in the mid of June as the awareness was increased. The average Covid-19 case growth was got reduce from 3.43 to 2.62% by July mid. To analysis the impact of stringency, a detailed analysis was done on Chennai city which was imposed with more repeated lockdowns to flatten the curve. We tried to fit a regression line with three difference scenario of data. The results show a promising R-squared and p value, with a right skewed distribution normal probability plot. The impact of lockdown in people's lives in different sectors were also discussed in this paper.
ABSTRACT
BACKGROUND: The COVID-19 pandemic and associated restrictions have greatly affected the delivery of treatment and access to in-person interventions for dementia, especially in low- and middle-income countries such as India. Technology use could potentially help bring the above-mentioned services to persons with dementia (PwD) and their caregivers in the safety of their homes. The aim of this study is to evaluate the dementia care services delivered by the Dementia Care in SCARF (DEMCARES) team in the densely populated city of Chennai in South India during the COVID-19 pandemic.
ABSTRACT
Coronavirus disease 2019 (COVID-19) is caused by a new virus called SARS-CoV-2. Its impact on public health creates adverse effects. Because it is a brand-new virus, scientists are getting to know more every day. Although the majority who've COVID-19 have slight symptoms, COVID- 19 can also cause intense infection or even demise. a few corporations, together with older adults and those who've certain underlying scientific conditions, are at accelerated risk of extreme contamination So monitoring and Visualization of COVID-19 cases and simply representing the information for a higher understanding of the COVID-19 instances around the world helps humans recognize the present-day state of affairs and to try this a cellular application is a fine way. In this paper, We summarize and illustrate with examples the way to amass and Visualize the statistics of the COVID-19 cases in a cellular application using Flutter. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
BACKGROUND: The impact of COVID-19 on the Global scale is tremendously drastic. There are several types of research going on across the world simultaneously to understand and overcome this dire pandemic outbreak. This paper is purely a statistical study on a distinct set of datasets regarding COVID-19 in India. The motivation of this study is to provide an insight into the rapid growth of confirmed COVID-19 cases in India. METHODS: The rapid growth of COVID-19 cases in India started in March 2020. The main objective of this paper is to provide a solid statistical model for the policymaker to handle this kind of pandemic situation in the near future with nonlinear data. In this paper, the data was got from 1st April to 29th November 2020. To come up with a solid statistical model, various nonlinear data such as confirmed COVID-19 cases, maximum temperature, minimum temperature, the total population (state-wise), the total area in km2 (state-wise), and the total rural and urban population count (state-wise) have been analyzed. In this paper, six different Generalized Additive Models (GAM) was identified after a thorough analysis of other researchers' (Xie and Zhu, 2020; Prata et al., 2020) findings. RESULTS: In all perspectives, the results were identified and analyzed. The GAM model regarding total COVID-19 confirmed cases, total population, and the total rural population provides the best average fit of R2 value of 0.934. As the population value is quite high, the author has concise it using logarithm to provide the best p-value of 0.000542 and 0.001407 for a relation between the total number of COVID-19 cases regarding the total population and total rural population respectively.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , SARS-CoV-2 , Incidence , Data Analysis , PandemicsABSTRACT
In this paper, we are developing a system to constantly monitor people if they are wearing a mask and maintain social distancing. The human detection and mask verification from the live streaming is done using an object detection algorithm mobilenet SSD. The distance between two humans is calculated using the eucleidian distance between two bounding boxes of the humans to verify if they are maintaining social distancing. If two humans are not following social distancing or even if they are not wearing any mask the bounding boxes are marked red alerting them. Thus, helps to effectively monitor social distancing norms among the general public. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
ABSTRACT
Coronavirus disease 2019 (COVID-19) is because of a brand-new coronavirus first identified in Wuhan, China, in December 2019. Because it is a brand-new virus, scientists are getting to know more every day. Although the majority who've COVID-19 have slight symptoms, COVID-19 can also cause intense infection or even demise. A few corporations, together with older adults and those who've certain underlying scientific conditions, are at accelerated risk of extreme contamination So monitoring and Visualization of COVID-19 cases and simply representing the information for a higher understanding of the COVID-19 instances around the world helps humans recognize the present-day state of affairs and to try this a cellular application is a fine way. In this article, we summarize and illustrate with examples the way to amass and visualize the statistics of the COVID-19 cases in a cellular application using Flutter. Our way of visualization will assist the healthcare and public works department to make appropriate decision.