Article

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

2026-03-02

Abstract excerpt

<h4>Purpose</h4> We introduce PRE-CISE, a pre-calibration workflow that integrates coverage analysis, local sensitivity, and collinearity diagnostics to streamline model calibration and transparently address nonidentifiability. We demonstrate the benefits of PRE-CISE using a four-state Sick-Sicker Markov testbed and a COVID-19 case study. <h4>Methods</h4> PRE-CISE begins with a coverage analysis to verify that m...

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Literature Corpus work: 946d5549-ae98-5aeb-9063-4d4378a31ef5
DOI: 10.64898/2026.02.27.26346591

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