Ricarda Duerst

Ricarda Duerst is an Affiliate Researcher at the Max Planck Institute for Demographic Research (MPIDR) in Rostock, Germany, affiliated with the Laboratory of Population Health within the Population Health Research Group. Her work focuses on statistical demography, particularly advancing methodological rigor in demographic forecasting through probabilistic modeling and validation frameworks.

Her research spans Demography, Population Health, and Statistical Demography with specialized expertise in Mortality Forecasting and Fertility Forecasting. She develops innovative statistical approaches for short-term demographic projections, including empirical prediction intervals for mortality trends, calibration techniques for fertility rate forecasts, and systematic validation workflows. Her work addresses critical challenges in quantifying uncertainty and improving reliability of demographic predictions used in public health and policy planning.

Recent publications reveal a concentrated research trajectory on forecast validation methodologies, with emphasis on mortality and fertility projections. Her 2023-2024 work establishes practical frameworks for assessing forecast accuracy, calibrating probabilistic paths using historical errors, and quantifying excess deaths through empirical prediction intervals. These contributions advance computational demography by bridging theoretical statistics with real-world demographic applications, particularly in European contexts like Finland.

No scientific awards were mentioned in the provided information.

Information regarding academic advising responsibilities and research grants was not provided in the source text.

Duerst operates within the Laboratory of Population Health at MPIDR, a specialized unit under the Population Health Research Group focusing on labor demography and demographic determinants of health. This laboratory contributes to MPIDR's broader mission through interdisciplinary research connecting demographic methods with population health outcomes, leveraging the institute's expertise in computational demography and sustainable well-being metrics.