id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-258742-li71b9e0	Dolgikh, S.	Covid-19 Epidemiological Factor Analysis: Identifying Principal Factors with Machine Learning	2020-06-05		.txt	text/plain	2031	120	56	Based on a subset of Covid-19 Wave 1 cases at a time point near TZ+3m (April, 2020), we perform an analysis of the influencing factors for the epidemics impacts with several different statistical methods. The intent of the work is to repeat similar analysis at several different points in the time series of cases that would allow to make a confident conclusion about the epidemiological and social factors with strong influence on the course of the epidemics. The purpose of the analysis is to develop and verify the methods that would allow to identify the main factors, different and in addition to the known ones, that have significant influence on the course and the impact of the epidemics based on the available data. As can be see seen, the combination of three factors: policy, BCG immunization and smoking has the highest correlation and the lowest linear regression error for the resulting effect.	./cache/cord-258742-li71b9e0.txt	./txt/cord-258742-li71b9e0.txt