Title of article :
Analysis of correlation between food consumption habits and COVID-19 outbreak
Author/Authors :
Fereidouni, Zahra School of Industrial and Systems Engineering - College of Engineering - University of Tehran, Tehran, Iran , Mehdizadeh Somarin, Zahra School of Industrial and Systems Engineering - College of Engineering - University of Tehran, Tehran, Iran , Mohammadnazari, Zahra Kingston Business School - Kingston University, Kingston Hill, Kingston Upon Thames, London, United Kingdom , Aghsami, Amir School of Industrial Engineering - K. N. Toosi University of Technology (KNTU), Tehran, Iran , Jolai, Fariborz School of Industrial and Systems Engineering - College of Engineering - University of Tehran, Tehran, Iran
Abstract :
The outbreak of COVID-19 sparked a massive movement among the world's
people to control this dangerous and unknown disease. So many nutritionists have
made many medical recommendations to control this disease by using special
nutrients. In this regard, we decided to examine the effect of two nutrients, protein
and fat, which are the main ingredient in many nutrients, on the rate of death and
recovery of patients’ covid-19. Available data from 170 countries worldwide have
been examined to discover this effect. Linear and non-linear relationships and the
correlation coefficient between response variables and different nutrients have
been calculated and analyzed in detail. According to the results, these two elements
cannot be considered influential in predicting the current rate with high reliability.
Protein and fat have a high nutritional value and play an essential role in human
health, but the amount of this need for humans is different, which in turn
contradicts the results obtained from patients. Although correlation coefficients are
not high, the existence of this correlation still requires further studies in this field.
We have also used models such as Decision tree, Rule introduction, and Naive
Bayes in our research to predict future results, which will give us an understanding
of the results obtained.
Keywords :
COVID-19 , data analysis , decision tree , rule introduction , naive Bayes
Journal title :
Journal of Industrial and Systems Engineering (JISE)