id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-126012-h7er0prc	Diaz, Victor Hugo Grisales	COVID-19: Forecasting mortality given mobility trend data and non-pharmaceutical interventions	2020-09-25		.txt	text/plain	3165	156	52	We develop a novel hybrid epidemiological model and a specific methodology for its calibration to distinguish and assess the impact of mobility restrictions (given by Apple's mobility trends data) from other complementary non-pharmaceutical interventions (NPIs) used to control the spread of COVID-19. Using the calibrated model, we estimate that mobility restrictions contribute to 47 % (US States) and 47 % (worldwide) of the overall suppression of the disease transmission rate using data up to 13/08/2020. At the same time, we evaluate the effectiveness of restrictions on mobility (i.e., walking, driving and transport) on the reduction of the disease transmission rate and hence the control of the cumulative number of infected and deceased individuals. In this contribution, our previous model [5] is extended to predict mortality and to include a term to estimate the reduction on the contagious rates given reported mobility data.	./cache/cord-126012-h7er0prc.txt	./txt/cord-126012-h7er0prc.txt