PRE-CISE: A PRE-calibration Coverage, Identifiability, and SEnsitivity analysis workflow to streamline model calibration

20260 citationsJournal Articlegreen Open Access

Authors

J. Goldhaber-Fiebert · Center for Policy Analysis

Fernando Alarid-Escudero · Center for Policy Analysis

Abstract

PRE-CISE provides a practical, transparent pathway that helps modelers refine prior distribution bounds and calibration targets before intensive calibration, improving uncertainty reporting and strengthening the reliability of model-based health policy analyses.

Topics & Keywords

COVID-19 epidemiological studies Sepsis Diagnosis and Treatment Gaussian Processes and Bayesian Inference

Publication Details

Published in: medRxiv

DOI: 10.64898/2026.02.27.26346591

Field-Weighted Citation Impact: 0.00

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PRE-CISE: A PRE-calibration Coverage, Identifiability, and SEnsitivity analysis workflow to streamline model calibration

Authors

Abstract

Topics & Keywords

Publication Details