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In the new paradigm of health-centric governance, policymakers are in constant need of appropriate metrics to determine suitable policies in a non-arbitrary fashion. To this end, in this paper, a compartmentalized model for the transmission of COVID-19 is developed, with a socially distanced compartment added to the model. The modification allows for administrators to quantify the extent to which voluntary social distancing norms are followed, and address restrictions accordingly. Modifications are also made to incorporate inter-region migration, and suitable metrics are proposed to quantify the impact of migration on the rise of cases. The healthcare capacity is modeled and a method is developed to study the consequences of the saturation of the healthcare system. The model and related measures are used to study the nature of the transmission and spread of COVID-19 in India, and appropriate insights are drawn. [ABSTRACT FROM AUTHOR]

This study aims to analyse the effectiveness of the lockdown measure taken to control the transmission of COVID‐19 in India by examining the peak of the epidemic pre and post the adoption of stringent lockdown from 25 March 2020. Susceptible‐exposed‐infectious‐recovered (SEIR) model has been developed to trace the peak of the outbreak. The study suggests that with the implementation of lockdown the peak of epidemic in India has delayed by two and a half month. Before lockdown peak was examined in end of May 2020 but post lockdown, it is expected to arrive in mid‐August 2020. Thus lockdown measures has delayed the arrival of peak of epidemic which would be helpful in preparing the healthcare system in advance, to tackle worst situation if arises in future. [ABSTRACT FROM AUTHOR]

Objective: There has been much discussion and debate around the underreporting of COVID-19 infections and deaths in India. In this short report we first estimate the underreporting factor for infections from publicly available data released by the Indian Council of Medical Research on reported number of cases and national seroprevalence surveys. We then use a compartmental epidemiologic model to estimate the undetected number of infections and deaths, yielding estimates of the corresponding underreporting factors. We compare the serosurvey based ad hoc estimate of the infection fatality rate (IFR) with the model-based estimate. Since the first and second waves in India are intrinsically different in nature, we carry out this exercise in two periods: the first wave (April 1, 2020–January 31, 2021) and part of the second wave (February 1, 2021–May 15, 2021). The latest national seroprevalence estimate is from January 2021, and thus only relevant to our wave 1 calculations. Results: Both wave 1 and wave 2 estimates qualitatively show that there is a large degree of "covert infections" in India, with model-based estimated underreporting factor for infections as 11.11 (95% credible interval (CrI) 10.71–11.47) and for deaths as 3.56 (95% CrI 3.48–3.64) for wave 1. For wave 2, underreporting factor for infections escalate to 26.77 (95% CrI 24.26–28.81) and to 5.77 (95% CrI 5.34–6.15) for deaths. If we rely on only reported deaths, the IFR estimate is 0.13% for wave 1 and 0.03% for part of wave 2. Taking underreporting of deaths into account, the IFR estimate is 0.46% for wave 1 and 0.18% for wave 2 (till May 15). Combining waves 1 and 2, as of May 15, while India reported a total of nearly 25 million cases and 270 thousand deaths, the estimated number of infections and deaths stand at 491 million (36% of the population) and 1.21 million respectively, yielding an estimated (combined) infection fatality rate of 0.25%. There is considerable variation in these estimates across Indian states. Up to date seroprevalence studies and mortality data are needed to validate these model-based estimates. [ABSTRACT FROM AUTHOR]

COVID -19 (Corona Virus Disease of 2019) what is known to be first incidence from Wuhan, China has now discovered its spread & threat to every other country. Protective measurements and better addressing policies seem to be the only way of fighting against COVID-19 progression till the vaccination to be invented. Study aims at finding the estimated progression of COVID -19 spread in India at different rates of transmission (R0) by using Susceptible, Exposed, Infected, Recovered (SEIR) model using online data COVID -19 registered cases in India collected from 30th January 2020 to 28th April 2020 for earlier phase of the research & then till June 30th 2020 for later part of the study. Also the data of around 206 countries for BCG vaccine coverage & 155 countries for temperature effect were assessed for finding correlation with COVID-19 morbidity. Reproduction number for COVID -19 for India was found at R0 =2.51 with transmission rate (β) = 0.24560 per day, latent period α = 0.19231 & recovery rate γ = 0.09785 for earlier date 28 th April 2020, then found to be decreased at R0 = 2.03 & β = 0.19865 per day later for June 30 th 2020 while recovery and latency time assumed to be constant. Weak negative correlation found for BCG & temperature rise with COVID -19 morbidity. [ABSTRACT FROM AUTHOR]

Throughout the globe, mankind is in vastly infected situations due to a cruel and destructive virus called coronavirus (COVID‐19). The pivotal aim of the present investigation is to analyze and examine the evolution of COVID‐19 in India with the available data in two cases first from the beginning to 31st March and beginning to 23rd April in order to show its exponential growth in the crucial period. The present situation in India with respect to confirmed, active, recovered and deaths cases have been illustrated with the aid of available data. The species of novel virus and its stages of growth with respect some essential points are presented. The exponential growth of projected virus by the day‐to‐day base is captured in two‐dimensional plots to predict its developments and identify the needs to control its spread on mankind. Moreover, the SEIR model is considered to present some interesting consequences about COVID‐19 within the frame of fractional calculus. A newly proposed technique called q‐Homotopy analysis transform method (q‐HATM) is hired to find the solution for the nonlinear system portraying projected model and also presented the existence and uniqueness of the obtained results with help of fixed point theory. The behavior has been captured with respect to fractional order and time. The present study exemplifies the importance of fractional operator and efficiency of the projected algorithm. [ABSTRACT FROM AUTHOR]