id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-351430-bpv7p7zo	Pequeno, Pedro	Air transportation, population density and temperature predict the spread of COVID-19 in Brazil	2020-06-03		.txt	text/plain	4780	222	47	Further, we considered the following predictors: (1) time in days, to account for the exponential growth in case numbers during this period (Fig. 2) ; (2) number of arriving flights in the city's metropolitan area in 2020, as airline connections can facilitate the spread of the virus (Ribeiro et al., 2020) ; (3) city population density, to account for facilitation of transmission under higher densities (Poole, 2020) ; (4) proportion of elderly people (≥60 years old) in the population, assuming that the elderly may be more likely to show severe symptoms of SARS-CoV-2 and, thus, to be diagnosed with COVID-19; (5) citizen mean income, which may affect the likelihood of people being infected by the virus, for example, due to limited access to basic sanitation or limited social isolation capabilities; (6) and the following meteorological variables: mean daily temperature ( C), mean daily solar radiation (kJ/m 2 ), mean daily relative humidity (%) and mean daily precipitation (mm).	./cache/cord-351430-bpv7p7zo.txt	./txt/cord-351430-bpv7p7zo.txt