ArticleCentral European journal of operations research2022
Hospital preparedness during epidemics using simulation: the case of COVID-19.
Article in Central European journal of operations research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Trial
- Discrete event simulation and agent-based modelling of distributed situation awareness in patient flow management.Scientific reports · 2025Article
- A modular approach to forecasting COVID-19 hospital bed occupancy.Communications medicine · 2025Article
- Evaluation of a pragmatic approach to predicting COVID-19-positive hospital bed occupancy.BMJ health & care informatics · 2025Observational
- Strengthening Public Health Systems to Combat the Rising Threat of Nipah Virus: A Call for Global Preparedness and Response.Advances in experimental medicine and biology · 2025Review
- Article
- Article
- A simulation model for predicting hospital occupancy for Covid-19 using archetype analysis.Healthcare analytics (New York, N.Y.) · 2023Article
- Forecasting ward-level bed requirements to aid pandemic resource planning: Lessons learned and future directions.Health care management science · 2023Article
- A queuing model for ventilator capacity management during the COVID-19 pandemic.Health care management science · 2023Article
- Artificial intelligence and discrete-event simulation for capacity management of intensive care units during the Covid-19 pandemic: A case study.Journal of business research · 2023Article
- A multistate model and its standalone tool to predict hospital and ICU occupancy by patients with COVID-19.Heliyon · 2023Article
- Unraveling the COVID-19 hospitalization dynamics in Spain using Bayesian inference.BMC medical research methodology · 2023Article
- A goal programming model for two-stage COVID19 test sampling centers location-allocation problem.Central European journal of operations research · 2023Article
- Estimation of patient flow in hospitals using up-to-date data. Application to bed demand prediction during pandemic waves.PloS one · 2023Article
- Mathematical optimization models for reallocating and sharing health equipment in pandemic situations.Top (Berlin, Germany) · 2023Article
- Using simulation modelling and systems science to help contain COVID-19: A systematic review.Systems research and behavioral science · 2022Article
- Simulation Study of the Impact of COVID-19 Policies on the Efficiency of a Smart Clinic MRI Service.Healthcare (Basel, Switzerland) · 2022Article
- Central European journal of operations research (CJOR) "operations research applied to health services (ORAHS) in Europe: general trends and ORAHS 2020 conference in Vienna, Austria".Central European journal of operations research · 2022Article
- How Can Hybrid Simulation Support Organizations in Assessing COVID-19 Containment Measures?Healthcare (Basel, Switzerland) · 2021Article
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3 authors.
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Abstract
This paper presents a discrete event simulation model to support decision-making for the short-term planning of hospital resource needs, especially Intensive Care Unit (ICU) beds, to cope with outbreaks, such as the COVID-19 pandemic. Given its purpose as a short-term forecasting tool, the simulation model requires an accurate representation of the current system state and high fidelity in mimicking the system dynamics from that state. The two main components of the simulation model are the stochastic modeling of patient admission and patient flow processes. The patient arrival process is modelled using a Gompertz growth model, which enables the representation of the exponential growth caused by the initial spread of the virus, followed by a period of maximum arrival rate and then a decreasing phase until the wave subsides. We conducted an empirical study concluding that the Gompertz model provides a better fit to pandemic-related data (positive cases and hospitalization numbers) and has superior prediction capacity than other sigmoid models based on Richards, Logistic, and Stannard functions. Patient flow modelling considers different pathways and dynamic length of stay estimation in several healthcare stages using patient-level data. We report on the application of the simulation model in two Autonomous Regions of Spain (Navarre and La Rioja) during the two COVID-19 waves experienced in 2020. The simulation model was employed on a daily basis to inform the regional logistic health care planning team, who programmed the ward and ICU beds based on the resulting predictions.
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