id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-268816-nth3o6ot	Roy, Satyaki	Factors affecting COVID-19 infected and death rates inform lockdown-related policymaking	2020-10-23		.txt	text/plain	5733	363	56	The features in the order shown under "Feature name" are: GDP, inter-state distance based on lat-long coordinates, gender, ethnicity, quality of health care facility, number of homeless people, total infected and death, population density, airport passenger traffic, age group, days for infection and death to peak, number of people tested for COVID-19, days elapsed between first reported infection and the imposition of lockdown measures at a given state. Unless otherwise stated, the feature set comprises GDP, gender, ethnicity, health care, homeless, lockdown type, population density, airport activity, and age groups, whereas the output labels consist of infected and death scores on a scale of 0-6. Although proposing a machine learning algorithm that works best on COVID-19 data is not the purpose of this study, it is worth reporting that decision tree classifier (DT) slightly outperforms the other algorithms for both cases of infected and death scores.	./cache/cord-268816-nth3o6ot.txt	./txt/cord-268816-nth3o6ot.txt