Editorial Board

A Refereed Monthly International Journal of Management

Analyse Impact and Prediction of Trend of Covid-19 in India

Dr. Asha Sharma

Assistant Professor

Department of Accountancy and Statistics

University College of Commerce & Management Studies

Mohanlal Sukhadia University, Udaipur

E-mail: drashasharma.sharma07@gmail.com

ABSTRACT

The coronavirus COVID-19 is affecting 212 countries and territories around the world. COVID-19 is a strange but dangerous virus. It has spread like an epidemic overall at the global level. For this purpose, it is tried to find out whether COVID-19 has equally effected all the countries. The facts of Top 10 highly affected countries by epidemic coronavirus and facts of India is considered for study purposes. To test the hypothesis the statistical techniques correlation is used to measure it. For result verification purposes and finding model fitness, an artificial neural network technique is used.

It is also tried to know the trend of growing cases and to understand the similarity in the increasing trend of cases and deaths in the countries. So that the reason and some techniques can be found out to control it.  Growth of cases and other factors included for the study are found similar and highly positive in Germany and Turkey to India while the low level of correlation is found with the USA and Spain. In the last, some recommendation has been made to reduce the growth rate of cases by a coronavirus.

Keywords:  COVID-19, Artificial Neural Network, Increasing trend, India, Death percentage

1. INTRODUCTION

Coronaviruses are a large family of viruses that may cause illness in animals or humans.  In humans, several coronaviruses are known to cause respiratory infections ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). The most recently discovered coronavirus causes coronavirus disease COVID-19.^[i]

COVID-19 is a disease that can cause what doctors call a respiratory tract infection. It can affect your upper respiratory tract (sinuses, nose, and throat) or lower respiratory tract (windpipe and lungs). It's caused by a coronavirus named SARS-CoV-2.^[ii]

It spread by human to human transmission. It is the most worrisome part of COVID-19. The number of cases infected by the epidemic is increasing so rapidly. Novel Coronavirus disease is very dangerous. There are three parameters to understand in order to assess the magnitude of the risk posed by this coronavirus:

• Transmission Rate (Ro) - number of newly infected people from a single case
• Case Fatality Rate (CFR) - percent of cases that result in death
• Determine whether the asymptomatic transmission is possible^[iii]

2. REVIEW OF LITERATURE

1. S. Malik Peiris, S. Y. Lam, L. L. M. Poon, K. Y. Yuen, and W. H. Set (2011) analyzed and found that a nebulizer under a controlled condition was used to generate a high and relatively low humidity environment. All the experiments conducted in duplicate and the residual viral infectivity was titrated.

Casanova LM, Jeon S, Rutala WA, Weber DJ, Sobsey MD (2010) explored in the paper that the rate of risks arises by the severe acute respiratory syndrome (SARS) coronavirus (SARS-CoV) on surfaces requires data on the survival of this virus on environmental surfaces is very high.

Grant WB, Lahore H, McDonnell SL, Baggerly CA, French CB, Aliano JL^,  Bhattoa HP (2020) discussed in the paper that the world is in the grip of the COVID-19 pandemic can reduce the risk of infection and death can be reduced to quarantines and it is desperately required.

3. MATERIAL AND METHODS

The research methodology comprises the research design, sample design, sources of data, selection of data, various designs, and techniques used for analyzing the data. The methodology is explained using the following points:

3.1 Research Design: The research the design used for the research problem is causal research based on the relationship between the dependent and independent variables as the objective is to determine which variable might be causing certain factors, i.e. whether there are cause and effect relationships or not.

Table 1 Status of Highly effected counties by COVID -19 as on 18th April2020

Source- https://www.worldometers.info/coronavirus/

Table 1 shows the status of countries of highly infected cases by COVID-19 and death percentages by corona virus-infected till 18 April 2020.

3.2 Methods of data collection

For the study in hand, the secondary data was collected through the reports from the World Health Organization, government official websites,

4. RESULT AND DISCUSSIONS

Following statistical tests and tools will be used to meet with the above-mentioned objectives and for proving the hypothesis:

• Correlation
• Artificial Neural Network

For applying this statistical tool software SPSS 19 is used.

4.1 OBJECTIVE

• To understand the trend of Coronavirus in India
• To find the association between the trend of infected cases in India and any other country.
• To know the impact of COVID-19 on all the countries equally
• To study the country in which trend is equal to India

All the countries are not equally effected by COVID-19

4.2 LIST OF DEPENDENT AND INDEPENDENT VARIABLE

Table 2 Description of variables

Table 2 shows how variable are segregated in dependent & independent variables as shown

4.3 HYPOTHESIS

In terms of hypothesis, it can be written as

H01 All the countries are not equally affected by COVID-19

H11 All the countries are equally affected by COVID-19

4.4 TESTING OF HYPOTHESIS BY CORRELATION

H01 All the countries are not equally affected by COVID-19

The result shows that trend of No. of the case and the number of deaths are equal to Turkey, Germany, France, Italy, UK, and. There is no association found in case history and status of the USA, Belgium, and China.

4.5 1 TEST FOR MODEL ADEQUACY (ARTIFICIAL NEURAL NETWORK)

The neural network technique is used to predict the demand for higher education and to prove the hypothesis.

Fg-1 Input, hidden and output layer

Figure 1 gives the network information. It describes the process of working. It works into three-layer: the input layer, hidden layer, and output layer. These layers describing out of the entire factor which components have more weight or more important.

Fig 2 Normalised Importance

Table 4 and figure 2 shows the importance of how the network classifies the prospective applicants. So, statistical models will help in this situation. Result says that performance mainly depends on the economic factor and social factor has less affected the performance of a country.

The result of this model is almost equal to Correlation. Indian trend of the increasing status of dependent and independent variables is found equal to Germany, Belgium. Less associated countries with India are Turkey, China, Italy, France, the UK, Iran, the USA, and Spain.

PROJECTION AND ESTIMATION OF CORONAVIRUS CASES

As the result shows that India's growth history of the case is close to Germany and Turkey and the opposite of the USA and Spain. It identifies out of selected eleven countries that are highly affected by a coronavirus in the world.

Chart 1 shows the estimated and projected growth rate by 27 July 2020

It is predicted June 15, 2020, the growth the rate will be reduced to less than 1% and it will totally be recovered by 27 July, 2020.

RECOMMENDATIONS

The factors are taken for study which are proved much influencing. So on the basis the result, it is recommended:

• Need to more aware, protected in urban area
• Take it seriously where the high-density populated area.
• Follow the rules decided by the government of the concerned countries.

CONCLUSION

It can be concluded that all the approaches applied to prove the hypothesis and measure the result i.e. correlation and artificial the neural network used for measuring results say almost the same result that the Indian the trend of the increasing status of dependent and independent variable is found equal to Germany, Belgium. Less associated countries with India are Turkey, China, Italy, France, the UK, Iran, the USA, and Spain.

Finally, we can say that the attack of coronavirus disease is a big challenge. The study will help out to come over and to control the dragon coronavirus. It is clear the area which is highly concentrated on the infected patient of the virus can be evaluated, monitored, and controlled.

It will recommend that it is required to be more aware, more precaution in the urban areas. It should be taken very seriously where the high-density populated area. It is predicted on June 15, 2020, the growth rate will be reduced to less than 1% and it will totally be recovered by 27 July 2020.

REFERENCES

^[i]https://www.who.int/

^[ii]https://www.webmd.com/lung/coronavirus

^[iii]https://www.worldometers.info/coronavirus/

Alice Zwerling, Marcel A. Behr, Aman Verma, Timothy F. Brewer, Dick Menzies, Madhukar Pai PLoS Med. 2011 Mar; 8(3): e1001012. Published online 2011 Mar 22. doi: 10.1371/journal.pmed.1001012PMCID: PMC3062527

Cortegiani, A., Ingoglia, G., Ippolito, M., Giarratano, A., & Einav, S. (2020). A systematic review on the efficacy and safety of chloroquine for the treatment of COVID-19. J Crit Care. doi:10.1016/j.jcrc.2020.03.005

Grant, W. B., Lahore, H., McDonnell, S. L., Baggerly, C. A., French, C. B., Aliano, J. L., & Bhattoa, H. P. (2020). Evidence that Vitamin D Supplementation Could Reduce Risk of Influenza and COVID-19 Infections and Deaths. Nutrients, 12(4). doi:10.3390/nu12040988

Asha Sharma (2020) Exploring Economic and Social Sustainable Indicator in Relation to Performance at Global Region Level," International Journal of Scientific Research in Multidisciplinary Studies , Vol.6, Issue.3, pp.6-13, 2020

1. S. Malik Peiris,¹S. Y. Lam,¹ L. L. M. Poon,¹ K. Y. Yuen,¹ and W. H. Set.(2011) The Effects of Temperature and Relative Humidity on the Viability of the SARS Coronavirus. Hindawi, journal of virology. Volume 2011 |Article ID 734690

Casanova LM, Jeon S, Rutala WA, Weber DJ, Sobsey MD (2010). Effects of air temperature and relative humidity on coronavirus survival on surfaces. Applied and Environmental Microbiology, 12 Mar 2010, 76(9):2712-2717.DOI: 10.1128/AEM.02291-09 PMID: 20228108 PMCID: PMC2863430

Grant WB¹, Lahore H², McDonnell SL³, Baggerly CA³, French CB³, Aliano JL³, Bhattoa HP⁴.Evidence that Vitamin D Supplementation Could Reduce Risk of Influenza and COVID-. 19 Infections and Deaths. Nutrients. 2020 Apr 2;12(4). pii: E988. doi: 10.3390/nu12040988.

Websites

https://worldpopulationreview.com/countries/countries-by-density/

https://data.worldbank.org/indicator/EN.POP.DNST?locations=IN

https://ourworldindata.org/gender-ratio

https://www.cdc.gov/coronavirus/2019-ncov

https://ourworldindata.org/coronavirus

https://www.statista.com

https://ourworldindata.org/tourism

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