Statistical Study of Relationship and Comparison of Average Monthly Temperature and nCoV-SARS-2: A Case Study of India.

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Statistical Study of Relationship and Comparison of Average Monthly Temperature and nCoV-SARS-2: A Case Study of India.

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Ibrahim Abubakar Sadiq1 Shafiu Ibrahim Musa2

1 Department of Mathematics and Statistics, Mewar University Chittorgarh, Rajasthan India.

2 Department of Physics, Mewar University Chittorgarh, Rajasthan India.

Abstract – In this study we employed statistical methods to relate and make comparison between monthly average temperature and number of confirmed cases for COVID-19 disease. R-studio were used to achieve the results. We extracted our data for the analysis from the Ministry of Health and Family Welfare Government of India for the cumulative confirmed cases of nCoV-SARS-2, the average monthly temperature from 1st March to 31st May 2020 were also extracted via internet from Current Results weather and science facts for Indian Weather. The descriptive analysis of the generated data was presented graphically. Our findings show that, the average temperature so far has no effect on the number of nCoV-SARS-2 in all the four regions of India, in fact number of cases are still in the rise with daily increase.

Keywords: Temperature, COVID-19, T-test, Correlation, R- programming.


As a result of high rate of spread of COVID-19, serious attention has been given to study on rate of the pandemic, transmission ways, methods of prevention and how the virus will survive when exposed to certain amount of temperature. The activities of the virus in association with environmental features is critical. (1) The CoV-SARS-2 infection 2019 or COVID-19 pandemic has turn out to be a very serious health issue of concern by government and general public. The newness of the syndrome encourages an investigation for thoughtful of how natural dynamics influence the spread and existence of the disease. Many researchers have tried vigorously in finding a connection between temperature and COVID-19 number of confirmed cases. But, there is no exact study for the four regions of India. Cascella et al. (2020) performed a study on the novel nCoV-SARS-2 structure. Their examination revealed that the disease fits to the family of single-stranded RNA viruses (+ ssRNA), which has a length of about 30 kb and an envelope with spear structures and they verified the sensitivity of the virus to UV light and temperature. (2) Pirouz et al. (2020) studied the

relationship between environmental features and the number of confirmed cases of Coronavirus using the artificial intelligence techniques. The findings of this investigation placed indication on the role of weather conditions on the pandemic rate.(3) Chen et al. (2020) established a time dependent mathematical model for the estimation of the total number of confirmed cases.(4)

Examination of the prior studies shows that a further investigation about the consequences of ecological factors on the nCoV-SARS-2 is required. Since some of the earlier studies have indicate the influence of weather situations, particularly temperature, on COVID-19. The Coronavirus Disease 2019 (COVID-19) is steady in faeces at room temperature for a minimum of one to two (1-2) days and it can be steady also in an infected person for up to four days. Thermal heat at 56 0C destroys the COVID-19 at about ten thousand (10000) units per 0.25hrs. Thus, temperature is a vital feature in existence of COVID-19 disease. (5)

The objective of this study is to determine if there exist a significant relationship between temperature and COVID-19 confirmed cases from March to May 2020 as well as their comparison for the 4 regions of India. In this study we employed statistical methods to relate and make comparison between temperature and number of confirmed case for COVID-19 disease. T-test was used for comparison and correlation analysis have been used to find if significant relationship exists.


The scope of this study covers only the four region of India, Western, Northern, Southern and Eastern regions. Below are the maps of India showing the location of each region.(6) We consider their average monthly temperature and the cumulative confirmed cases of nCoV-SARS-2 from the early month of March to the end of May, 2020.


2.1 Techniques of T-test Statistic:

The t-test statistic is among the type of inferential statistical techniques used in determining if significant differences exist among the means of two sets of variables, which may be associated in certain structures. A t-test is applied as a hypothesis testing instrument, which permits analysis of a guess suitable to a population. A t-test (t-t) gazes at the test statistic, the t-distribution outcomes, and the degrees of

freedom (DF) to ascertain the statistical significance adequacy. (7)

The statistical procedure for testing hypothesis on two differences means ( 1 2 ) for normality of two





distributions such that variance one ( 2 ) and variance two ( 2 ) are not known. A t-test statistics is appropriate to test

our claim and assumption. We follow the following steps with an assumption that the two variances of the given dual normal distribution are equal and unknown.

1. Statement of Hypothesis (S.T)

H0 : 1 2 0

H1 : 1 2 0


2. Level of significance (L.S) Alpha = 0.05

3. Decision Criteria (D.C)

Reject H0 if tcal t 2,n1 n2 2 or P value 0.05

4. Test Statistic (T.S)


X1 X 2 (1 2 )

1 1Eastern IndiaEastern IndiaNorthern India

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