id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-292699-855am0mv	Engbert, Ralf	Sequential data assimilation of the stochastic SEIR epidemic model for regional COVID-19 dynamics	2020-04-17		.txt	text/plain	5369	363	54	The key motivation of the current study was to apply sequential data assimilation of the stochastic SEIR model to estimate the contact parameter. An approximative instantaneous negative log-likelihood L(t k , β) of the contact parameter β at observation time t k is obtained from the ensemble Kalman filter (see Model inference based on sequential data assimilation). Forward iteration with the estimated time-varying contact parameter show that the slope of the epidemic curve is approximately reproduced by the model (Fig. 3a ,c; grey lines indicate the ensemble of simulated trajectories; blue points are observed data). In scenario I, we started with the adapted ensemble of internal model states after data assimilation (April 4th) and iterated the model forward with the mean contact parameter estimated in the week March 29th to April 4th after implementation of interventions (Fig. 4 , green area).	./cache/cord-292699-855am0mv.txt	./txt/cord-292699-855am0mv.txt