Correlation Between Temperature and COVID-19 (Suspected, Confirmed and Death) Cases based on Machine Learning Analysis

Correlation Between Temperature and COVID-19 (Suspected, Confirmed and Death) Cases based on Machine Learning Analysis

Ruben Morales-Menendez, Hafiz M. N. Iqbal, Pradeep Kumar Gupta, Fida Hussain, Sultan Ahmad, Mohammad Khubeb Siddiqui, Khudeja Khatoon

Currently, the whole world is struggling with the biggest health problem COVID-19 name coined bythe World Health Organization (WHO). This was raised from China in December 2019. This pandemicis going to change the world. Due to its communicable nature, it is contagious to both medically andeconomically. Though different contributing factors are not known yet. Herein, an effort has beenmade to find the correlation between temperature and different cases situation (suspected, confirmed,and death cases). For a said purpose, k-means clustering-based machine learning method has beenemployed on the data set from different regions of China, which has been obtained from the WHO.The novelty of this work is that we have included the temperature field in the original WHO data setand further explore the trends. The trends show the effect of temperature on each region in threedifferent perspectives of COVID-19 – suspected, confirmed and death.

2020

machine learning, coronavirus, K-Means Clustering, COVID-19

DOI: 10.22207/JPAM.14.SPL1.40

Journal of Pure and Applied Microbiology

Journal of Pure and Applied Microbiology

Microbiology