Best paper award of the Swedish Society of Medical Statistics (FMS) 2023

Winner of Swedish Society for Medical Statistics best student paper 2023 is Fanny Bergström, PhD-student at the Department of Mathematics at Stockholm university for her paper Bayesian nowcasting with leading indicators applied to COVID-19 fatalities in Sweden ¹. During the COVID pandemic we could all experience in Swedish media a delay in the live death reporting. In some instances, the decrease in fatal nowcasting could have been interpreted as a decrease of disease activity in the general population, whereas in reality it was just a result of delayed reporting. This could have important implications of the overall pandemic strategy and hence it is important to improve nowcasting methods. Fanny and her co-authors propose a novel Bayesian nowcasting method for real-time estimation of infectious disease surveillance with reporting delay. The authors extend existing methods by incorporating additional correlated data (e.g. ICU hospitalizations) to improve fatality predictions in the presence of delayed reporting. They apply the method to data of COVID-19 fatalities in Sweden and show that it improves the performance compared to established methods. The method’s application is made accessible in a weekly-updated website².

The suggested method can be applied to a variety of infectious diseases and has the potential to be important from a society perspective in pandemic situation.

¹Bergström, F., Günther, F., Höhle, M., & Britton, T. (2022). Bayesian nowcasting with leading indicators applied to COVID-19 fatalities in Sweden. PLOS Computational Biology, 18(12).

²https://staff.math.su.se/fanny.bergstrom/covid19-nowcasting/