Prediction of Coronavirus Outbreak Based on Cuisines and Temperature Using Machine Learning Algorithms

Abstract

In the current pandemic scenario, every possibility to find the cure is a contribution towards welfare of mankind. As of 15th May 2020, there are 4,543,060 confirmed cases and 1,712,895 patients have been recovered. The first COVID-19 case was reported in Wuhan, China. Till March the highest number of cases as well as deaths were reported by Italy. The type of food people eats, and its nutritional value decides the health or immunity of people whereas temperature plays an important role for the activity of corona. With the help of machine learning tools such as decision tree and heatmap we have shown the correlation of temperature, number of cases and Kcal per capita per day consumption in India and Italy. This correlation forms the basis of our research and it was found to be one of the important factors for the spread of this disease. Through our study we have found that temperature and calory intake of people play an important role in deciding the rise of number of cases in any country.

Note: Funding: This paper is self-funding.

Declaration of Interest: The authors declare “No conflict of interest” for this paper.

Keywords: SARS-CoV 2, Beta coronavirus, heatmap, incubation, carbohydrate intake, decision tree, India, Italy, heatmap, average temperature, death rate, analysis