Multiscale Modeling of Hospital Length of Stay for Successive SARS-CoV-2 Variants: A Multi-State Forecasting Framework
Minchan Choi, Jungeun Kim, Heesung Kim, Ruarai J. Tobin, Sunmi Lee

TL;DR
This study models hospital stays for different SARS-CoV-2 variants and age groups to improve pandemic resource planning.
Contribution
A multi-state forecasting framework that integrates variant-specific and age-based hospital length of stay dynamics.
Findings
Omicron-phase hospital stays were 5–8 days, shorter than the 10–14 days in earlier phases.
Older patients (65+) had longer stays (8–12 days) and more prolonged admissions (over 30 days).
The model can support real-time bed-availability systems and variant-specific resource planning.
Abstract
Understanding how hospital length of stay (LoS) evolves with successive SARS-CoV-2 variants is central to the multiscale modeling and forecasting of COVID-19 and other respiratory virus dynamics. Using records from 1249 COVID-19 patients admitted to Chungbuk National University Hospital (2021–2023), we quantified LoS across three distinct variant phases (Pre-Delta, Delta, and Omicron) and three age groups (0–39, 40–64, and 65+ years). A gamma-distributed multi-state model—capturing transitions between semi-critical and critical wards—incorporated variant phase and age as log-linear covariates. Parameters were estimated via maximum likelihood with 95% confidence intervals derived from bootstrap resampling, and Monte Carlo iterations yielded detailed LoS distributions. Omicron-phase stays were 5–8 days, shorter than the 10–14 days observed in earlier phases, reflecting improved treatment…
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Taxonomy
TopicsHealthcare Operations and Scheduling Optimization · COVID-19 epidemiological studies · COVID-19 and healthcare impacts
