id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-287949-243xlmep	Onovo, A. A.	Using Supervised Machine Learning and Empirical Bayesian Kriging to reveal Correlates and Patterns of COVID-19 Disease outbreak in sub-Saharan Africa: Exploratory Data Analysis	2020-05-02		.txt	text/plain	4908	233	51	Explanatory or independent variables in the model included total population, GDP per capita, percentage of population with access to electricity, percentage of population with access to basic drinking water, incidence of malaria (per 1,000 population at risk), percentage of men and women aged 15 and over who currently smoke any tobacco product, Diarrhea treatment (percent of children under 5 receiving oral rehydration and continued feeding), percentage of infants who received third-dose of pneumococcal conjugate-based vaccine (PCV), incidence of tuberculosis (per 100,000 people), percent out-of-pocket expenditure, life expectancy at birth, Health Systems Performance Index, estimated incidence rate (new HIV infection per 1,000 uninfected population, children aged 0-14 years), estimated incidence rate (new HIV infection per 1,000 uninfected population, adolescents aged 10-19 years), HIV prevalence among people aged 15-49 years, transmission classification of COVID-19 disease (1=imported, 2=local transmission), income group (1=High Income, 2=Low income, 3=Lower middle income, 4=Upper middle income), Geocoordinates of SSA countries (latitude and longitude), and Time (days) between the first and last reported coronavirus cases.	./cache/cord-287949-243xlmep.txt	./txt/cord-287949-243xlmep.txt