Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020
Armin Spreco
, Anna Jöud, Olle Eriksson, Kristian Soltesz, Reidar Källström, Örjan Dahlström, Henrik Eriksson, Joakim Ekberg, Carl-Oscar Jonson, Carl-Johan Fraenkel, Torbjörn Lundh, Philip Gerlee, Fredrik Gustafsson, and Toomas Timpka
Author affiliations: Linköping University, Linköping, Sweden (A. Spreco, O. Eriksson, R. Källström, Ö. Dahlström, H. Eriksson J. Ekberg, C.-O. Jonson, F. Gustafsson, T. Timpka); Region Östergötland, Linköping (A. Spreco, R. Källström, J. Ekberg, C.-O. Jonson, T. Timpka); Lund University, Lund, Sweden (A. Jöud, K. Soltesz); Skåne University Hospital, Lund (A. Jöud. C.-J. Fraenkel); Chalmers University of Technology, Gothenburg, Sweden (T. Lundh, P. Gerlee); Gothenburg University, Gothenburg (T. Lundh, P. Gerlee)
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Video
Video. Nowcasting performance using the telenursing chief complaints cough by adult and fever by adult separately during the first wave of the COVID-19 pandemic in Östergötland County, Sweden. The time series have been smoothed with a 7-day moving average to eliminate weekday effects. Black line indicates the actual number of hospitalizations per day that have already occurred when the nowcasts are calculated. Grey line indicates the actual number of hospitalizations per day that will be observed as time goes by but was not yet observed when the nowcasts were calculated. Blue line indicates the nowcasted number of hospitalizations per day based on cough by adult the following x days (where x is based on the best time lag of 14–21 days) from the day when the nowcasts are calculated. Red line indicates the nowcasted number of hospitalizations per day based on fever by adult for the following t days (where t is based on the best time lag of 14–21 days). COVID-19, coronavirus disease.
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