A Statistical Analysis: “Impact of Weather in Homogeneity of Covid-19 Variations In India”

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A Statistical Analysis: “Impact of Weather in Homogeneity of Covid-19 Variations In India”

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Ibrahim Abubakar Sadiq1, Jyoti S. Raghav2, Rabilu Ado3

1Department of Statistics, Ahmadu Bello University, Zaria, Nigeria.

1,2,3Department of Mathematics and Statistics, Mewar University, Grangrar Chittorgarh, Rajasthan, India.

Abstract:- Corona virus recently has become a unique universal severe problem required much attention of researcher to come out with optimum solution. The specific intention of this research is to make comparison and test the homogeneity of various averages. Analyses of Variance (ANOVA) by using the R-Studio and tests concern to the effects of weather in corona spread were observed. Over the rapid increased in daily and widespread active reported positive cases of covid-19 in the set of three neighboring state of India were observed. Objective of this paper is to find indication and homogeneity of COVID-19 variations under the specific weather effects with the conclusion at 5% and 1% level of significance.

Key Words: Statistics, P-value, Covid-19, Weather, R-Studio, ANOVA


Corona virus disease 2019 is described as severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), 2019-nCoV previously. When a new virus comes in existence, for the cope-up, we have to much more familiar about it consequences. As we already informed by media and medical staff that most respiratory viruses are spread by large droplets that come out when people cough and sneeze and stay in the open sky air usually for about six feet in front of them. They land on metal surfaces and transmitted between one human to another human by touching those metals, instance door latch or any other surfaces. Rest viruses can wide spread in the atmosphere and remain up for a longer duration in the form of tiny droplet nuclei.

The whole world has put glances on the second most populated entity, India, which is having about 17.7% of the global population. Till 22th June, recorded total of 4, 26197 confirmed cases and 13707 reported deceased all over Country. This deplorable situation informs about future outbreaks.

Present published studies have acknowledged that the widespread of COVID-19 is supposed to be more in the cold climate then the warm and hot climate, regular with seasonal flu (Bloom-Feshbach et al., 2013). Many viruses from the Corona group, with the SARS CoV-1 along with MERS CoV, also illustrate seasonality and inclination for minimum temperature as well as humidity (Casanova et al., 2010). The SARS CoV-2, which is known as COVID-19, has been examined to be like that of SARS CoV-1 on many types of metal surfaces in particular weather (van Doremalen et al., 2020). Sajadi et al. (2020) have examined the average temperature and concern humidity in many parts of the global from November, 2019 to Feb, 2020 and examined the widespread particularly in the entities lying in among latitudes 3050° North, and having concern similar weather functioning. In another observation, Oliveiros et al. (2020) recorded the impact of similar temperature, humidity and wind velocity on the rate of COVID- 19 infection in China during Jan 23 to Mar 1, 2020. The rate of augment and doubling duration of corona patient cases were examined and classified with the weather inputs using linear regression study. The consequences have indicated that the doubling duration of the corona patient cases were positively correlated along with temperature as well as negatively correlated with humidity. Though, these concern correlations numerical were less (R2 < 0.18) to describe any positive conclusion. Precipitation and wind velocity were established to exhibit no correlation with the doubling duration of the corona patient cases. Bukhari and Jameel (2020) observed the impact of humidity as well as temperature on the rising COVID-19 worldwide cases during January 2020 to March 19, 2020. The observations have indicated absolute humidity as best metric compare to relative humidity as well as temperature or weather for study purpose of this spread. It was also examined that 90% of the new infected cases up to 21 March 2020 had arisen within a definite range of AH (4 to 9 g/m3) as well as T (3 to 17 °C). Further many other observations may help us to enhance our perception on the realistic impact of weather and temperature on the wide spreading.


The specific objectives of this observation is to measure and make precise comparison under the effects of covid-19 reported cases at non-similar weather in the two set of three neighboring states in India

The objectives may be accomplished through the following objectives.

i. To make comparison in COVID-19 cases due to weather at Gujarat, Maharashtra and Tamil Nadu.

ii. To make comparison in COVID-19 cases due to weather at Delhi, Rajasthan and Madhya Pradesh.

3.1 Hypotheses 13.2 Hypothesis 23.3 Hypothesis 32.7 Data Analysis for Maharashtra, Gujarat and Tamil Nadu

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