SynthesisDisaster medicine and public health preparedness2022
COVID-19 Models for Hospital Surge Capacity Planning: A Systematic Review.
Synthesis in Disaster medicine and public health preparedness, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
40 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A systematic literature review on public health and healthcare resources for pandemic preparedness planning.BMC public health · 2024Pooled it
- A systematic review of health sector responses to the coincidence of disasters and COVID-19.BMC public health · 2021Pooled it
- Aggregated 50-State, Regional, and State-Level Trends in State and Local Government Health Employees in the U.S. From 2000 Through 2023.AJPM focus · 2026Article
- Dynamic demand forecasting and capacity assessment for emergency care system: a hybrid time series and machine learning approach with evidence from Beijing.BMC health services research · 2026Article
- Article
- A Strategy for Surge Management: Senior Residents on the Admitting Frontlines.Journal of community hospital internal medicine perspectives · 2026Article
- Frequency of Minor and Major Surgeries in Patients with COVID19.Medical journal of the Islamic Republic of Iran · 2026Article
- Optimizing Emergency Response in Hospitals: A Systematic Review of Surge Capacity Planning and Crisis Resource Management.Healthcare (Basel, Switzerland) · 2025Review
- Review
- Examining Burnout Among Intern Physicians During the COVID-19 Pandemic: Insights and Solutions from Qualitative Research.Healthcare (Basel, Switzerland) · 2025Article
- The Rise of FLiRT Variants in the COVID-19 Pandemic: What we Know so Far.Current pharmaceutical design · 2025Article
- Early Mortality Prediction in Intensive Care Unit Patients Based on Serum Metabolomic Fingerprint.International journal of molecular sciences · 2024Article
- Repurposing surgical wards in pandemics - An appraisal of outcomes of COVID-19 patients treated in Orthopaedic wards.Journal of family medicine and primary care · 2024Article
- An AI-based multiphase framework for improving the mechanical ventilation availability in emergency departments during respiratory disease seasons: a case study.International journal of emergency medicine · 2024Article
- Relationship between on-demand telehealth visits and emergency department and hospital surge during the COVID-19 pandemic.Journal of the American College of Emergency Physicians open · 2024Article
- Healthcare transition readiness of families of youth with cystic fibrosis during COVID-19: A correlational multicenter analysis.Health care transitions · 2024Article
- Article
- A simulation model for predicting hospital occupancy for Covid-19 using archetype analysis.Healthcare analytics (New York, N.Y.) · 2023Article
- One health system supporting surveillance during COVID-19 epidemic in Abruzzo region, southern Italy.One health (Amsterdam, Netherlands) · 2023Article
- Strategies, challenges and opportunities in the implementation of COVID-19 field hospitals: a scoping review.BMJ open · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveHealth system preparedness for coronavirus disease (COVID-19) includes projecting the number and timing of cases requiring various types of treatment. Several tools were developed to assist in this planning process. This review highlights models that project both caseload and hospital capacity requirements over time.
methodsWe systematically reviewed the medical and engineering literature according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We completed searches using PubMed, EMBASE, ISI Web of Science, Google Scholar, and the Google search engine.
resultsThe search strategy identified 690 articles. For a detailed review, we selected 6 models that met our predefined criteria. Half of the models did not include age-stratified parameters, and only 1 included the option to represent a second wave. Hospital patient flow was simplified in all models; however, some considered more complex patient pathways. One model included fatality ratios with length of stay (LOS) adjustments for survivors versus those who die, and accommodated different LOS for critical care patients with or without a ventilator.
conclusionThe results of our study provide information to physicians, hospital administrators, emergency response personnel, and governmental agencies on available models for preparing scenario-based plans for responding to the COVID-19 or similar type of outbreak.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.