id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-337482-imxkpfrn	Koplan, Jeffrey	Maxims for a Pandemic: Time, Distance, and Data	2020-10-27		.txt	text/plain	1220	75	51	In their article, Alagoz and colleagues explored the effect of COVID-19–related public health mandates in 3 U.S. locations. The editorialists discuss lessons from this analysis and the role of modeling to inform decision making related to the COVID-19 pandemic and future public health crises. I n their article, Alagoz and colleagues explored the effect of coronavirus disease 2019 (COVID-19)-related public health mandates in 3 U.S. locations-Dane County, Wisconsin; the Milwaukee metropolitan area; and New York City-using agent-based simulation models (1) . They modeled variations in adherence to social distancing mandates, time of intervention, and population density. Alagoz and colleagues' study provides an opportunity to pause and assess how modeling can and should inform COVID-19 decision making. With mass vaccination months, if not years, away and few effective therapies, the timely use of nonpharmaceutical public health interventions will reduce morbidity and mortality from COVID-19. Effect of timing of and adherence to social distancing measures on COVID-19 burden in the United States.	./cache/cord-337482-imxkpfrn.txt	./txt/cord-337482-imxkpfrn.txt