Analyzing the Current Status of India in Global Scenario with Reference to COVID-19 Pandemic

The crux of the paper is to present a detailed analysis of COVID-19 data which is available on global basis. This analysis is performed using some specific package of R software. It provides various insights from the data and help to understand the current status of this pandemic in India so that effective measures can be formulated by policymakers. These insights include global summary of this disease, growth rate of this pandemic and performance of SIR model for the given global data. The analysis has been presented in different tables and graphs to understand the outputs of the problem in a more detailed point of view.


INTRODUCTION
At present entire human community is facing a very crucial stage by the spread of COVID- 19. WHO has declared it a global pandemic (L.-s. Wang et al., 2020) due to its deadly nature.
This pandemic has its origin in Wuhan province of China during December. 2019 in the form of a pneumonia case was reported (Huang et al., 2020). This case was declared novel coronavirus pneumonia by the health experts. Later on WHO declared its official name as COVID-19 (Huang et al., 2020).
Social distancing, washing hands frequently, avoiding touching the mouth, nose, and face etc are important preventive measures for COVID-19 are suggested (WHO, 2020).
In India the first case of COVID-19 was reported on 30th January 2020 with origin from China (PIB, 2020). Now it has been spread in all the states and UTs of the country. As per our analysis date (16 June 2020) there are 3,43,091 total confirm cases, with 180013 recoveries and 9900 deaths (Covid-19.in, 2020) in the country.
Administration and health officials are facing lot of problem to accommodate patients of COVID-19. So, development of some prediction tools to know expected number of cases in upcoming time is the need of hour for future preparations. ( Tobías, 2020; L. Wang et al., 2020; L.-s. Wang et al., 2020). Such prediction techniques can make future preparation more easy to control this pandemic. We can also learn from the other countries and past experience of our own. So we must focus on developing such prediction tools.
In this paper we have analyzed live data of COVID-19 (2020) as on 16 June 2020 by using covid19.analytics (2020) package of R software. We are using various statistical and epidemic models for future prediction of this pandemic. The insights obtained from such analysis can provide blueprints for effective policy making regarding the prevention and control of this outbreak. The paper has been presented in various sections. Section-2 represents the review of literature of various epidemiological models used for transmission dynamics of infectious diseases. In Section-3, the material and methods have been discussed regarding the present investigation. Under this section, the mathematics of the model, the basic reproductive number and the data used have been described. Section-4 represents the summary of the outputs of the analysis. The overall summary and findings have been discussed in section-5. In Section-6 the concluding remarks have been presented and the paper ends with the references.

REVIEW OF LITERATURE
Mathematical modeling has significant contribution in predicting and cotrolling of any  Kermack and McKendrick (1927) has discussed and analyzed the transmission mechanism of many infectious diseases using various models. In their model they have divided the whole population N into three different groups namely S, I and R which denote the susceptible , infected and recovered groups of respectively. The susceptible group contains those units which at present are healthy but are suspected to be infected by disease in near future, and the size of this sub-population is denoted by S, the infected class is that group of population which is already infected by the disease, denoted by I and R denotes that group of population which is recovered from the disease. Till now many authors have worked on the

MATERIAL AND METHODS
Several statistical methodologies like Regression analysis, time series analysis and epidemiological models have been used for analysing of the data set on Covid-19. As Covid-19 is an infectious disease, epidemiological models are the most suitable tools to predict the problem so that to make better policies to overcome the problem. In this paper, we have used the SIR epidemiological model to analyze the transmission dynamics of Covid-19 pandemic.
Various summary reports will give an idea about the present situation of India on different criteria of COVID-19. Insights obtained from such reports provide blueprints to policy makers and health administrators to formulate effective policy and guideline to control this pandemic.

SIR (Susceptible-Infected-Recovered) Model Description
SIR is an epidemic model that shows the change of infection rate over time.

Figure-1. Illustration of the SIR model
To characterize the dynamics in the mathematical form, let the parameters of the model at time t are as follows: To simplify the analysis, it is assumed that the total population under consideration is fixed as N. The evolving ordinary differential equations of the SIR model with above parameters over time are defined as follows:  is the contact rate between the Susceptible and Infectious groups, and is the transition rate between the Infectious individuals, it will decrease by a quantity , who will transmit into the infectious group. Apart from the increase from the transition of susceptible individuals, the size of the infectious group will also decrease by a factor . In the COVID-19 case, the infection ratio could be scaled with 1 , since the population is not fully mixed and people are quarantined at home. R  that is the disease will be transmitted to more than one host. 0 R depends on the disease and host population and it is different for different infectious diseases for instance 0

Data Description:
For our study we have used live data from covid 19.analytics (2020) package of R studio.
This data is updated and analyzed globally on daily basis by the Johns Hopkins University Center for Systems Science and Engineering (JHU CSSE) data repository (2020). This data set is available in two forms, as a time series sequences and aggregated for the last day with greater spatial resolution.
The analysis has been done on the following criteria:

SUMMARY
Summary regarding covid-19 has been generated worldwide. It has shown the performance of top 10 countries of the world with reference to this pandemic. There are total 5 summary reports are generated based on different criteria. This is based on data available till 16 June 2020. Summary II-The second summary report is based on total number of death cases due to covid -19. Here it is clear that US is at top among the list of top ten countries in terms of total death cases due to this pandemic.

Summary-III
This third report is generated on the basis of total number of recovered cases of this pandemic. Here US has highest number of recovered cases.

Summary IV:
This summary report is generated on the basis of total confirm cases but with some additional columns. Here short listing is done on the basis of total percentage of deaths among confirmed cases.

Summary V:
This summary report is prepared on the basis of total confirm cases, total deaths, total recovered cases, total active cases along with their percentages. Worldwide totals, averages and standard deviations are also given in this report.

OVERALL SUMMARY
The overall summary is given as:  Figure-1 shows the number of changes and the growth rate of Covid-19 in India since the beginning of the pandemic. confirmed, active, recovered and death cases. In the graph given below it is clear that there is an increasing trend in confirmed cases, recovered cases and active cases. But there is almost constant rate in the death cases globally.  The fitting of SIR model for India is shown in the following graph. Here it is clear that all three factors having increasing trend. Since, all population is at risk of possible infection, so first factor is always high. It is also clear that in India number of infected people reaches after 80 days of starting of this pandemic. Recovery rate is also increasing with the time.

Role of Government of India:
From the above analysis till 16 June 2020, it is clear that India is in critical position in comparison to other developed countries of the world. Seeing the population density of our country, all the efforts made by government like Janta Curfew, lockdown, social distancing, isolation and quarantine are feasible and best possible efforts made by policymakers in the present scenario. Although high level urban to rural migration is also a part of this pandemic which cannot be ignored. It is high time for policymakers to provide basic amenities to this migrant section and make necessary arrangement for their livelihood. Further to get control over the pandemic Covid-19, the complete testing looks feasible which is a big task for the country like India. The suppressive strategies are also good to control the pandemic as in between the lockdown we get time for preparation such as to make more specific hospitals, life supporting equipments etc. Thus it is the need of the day to increase testing and make more Covid hospitals with life support system to overcome the problem without much loss.

Role of World Health Organization (WHO):
Although current situation of COVID-19 pandemic The current COVID-19 pandemic is unrivalled, but global has vast experience about lesson obtained from similar disease like SARS etc over several past decades.
As part of WHO's response, the R&D Blueprint was activated to accelerate diagnostics, vaccines and therapeutics for this novel coronavirus. The foremost aim of this blueprint is to establish a relation and coordination among health personals, researchers and scientists all over the world to discuss latest development in diagnosis, training and innovations to overcome COVID-19.
Scientists from all over the world met at WHO's headquarter in the month of February 2020, to review the available knowledge about this new virus. They agreed to work together to share knowledge, research and innovations to overcome this pandemic and future outbreaks in near future also.
The discussion was focussed on two important goals. First was to promote innovation and research for prevention of spread of this pandemic. The second was to support research priorities that contribute to global research platforms in hopes of learning from the current pandemic response to better prepare for the next unforeseen epidemic.
Based on the experiences obtained from previous outbreaks like SARS, Ebola etc, this R&D blueprint group of WHO also agreed for mutual coordination in the direction of developing vaccine, new pharmaceutical developments for COVID-19

RECOMMONDATIONS
Seeing the vulnerability of COVID-19 pandemic, the following recommendations are suggested with special reference to India: i. An expert committee should be constituted which includes health officials, NGOs, disaster management experts to review the effects of such pandemic in the country. ii.
A research organization should be developed which specially look such infectious diseases prevalent all over the world and give suggestions to decision makers for Indian context.
iii. Since such pandemic highly affect the economy of the country. So there should be an economic authority which can suggest remedial measures to overcome the situation.
iv. Such pandemic causes lots of migration & unemployment especially in unorganized sector. So government should initiate special social security schemes to ensure their livelihood.
v. Due to such pandemic, routine health activities like immunization etc suffer a lot, which will affect the future health of the country. So government should take extra efforts to overcome this situation.