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| | Authors | Casualty classification | Healthcare resource variables | Optimizing the results |
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| DEs | Lowery [155] | Classification of severely ill wounded | Procedures for the presentation of critically ill patients, particularly surgery and ICU | Optimizing the timing of visits for casualty patients in different types of intensive care units |
| Swisher et al. [156] | All the wounded | Number of caregivers | The average length of time for a casualty visit with a different number of nursing staff |
| Yi et al. [157] | Patients are divided according to the type of disease | The time of treatment of the wounded in each department | The process of visits for patients with different diseases has been improved to reduce the waiting time for the casualty |
| Cimellaro et al. [61] | The severity of the wounded is divided into white, yellow, green, and white from low to high | Medical resources occupied by casualty patients with different injuries (emergency rooms, ICU) | The model simulates the waiting time of casualty patients with different hospital attendance rates under different seismic intensity and analyzes the difference in waiting time of casualty patients with different emergency plans |
| Basaglia et al. [158] | All the wounded | Emergency, hospitalization, and doctor | The two models are defined by balancing the need to represent a complex system with sufficient accuracy, the limitations posed by data availability, and the multiplicity of outcomes of patient treatment |
| Shahverdi et al. [159] | All the wounded | — | Discrete modeling from patient arrival patterns, impacts on resources, and effects on unit capacities/capabilities to assess hospital system resilience to disaster events involving physical damage and demand surge |
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| ABMs | Kaushal et al. [160] | Emergency casualty | Healthcare workers and hospital beds | The efficiency of emergency fast-track reception has been improved, and the waiting time for the injured has been optimized |
| Taboada et al. [161] | Emergency casualty | Healthcare workers and medical equipment | The model optimizes the waiting time, treatment time, and number of patients treated for the injured in the emergency department |
| Cimellaro et al. [60] | All the wounded | Ambulances, hospital networks, and road networks | Optimized the casualty transport process |
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| SD | Diaz et al. [162] | All the wounded | Healthcare workers | Combined with the relationship between medical supply and demand, the situation of different workloads is studied, and the doctor’s work efficiency method is optimized |
| Cassettari et al. [163] | All the wounded | Sickbed | Effect of treatment time on bed resources |
| Hirsch [164] | All the wounded | Treatment process and infrastructure | The impact of infrastructure failures on the treatment process |
| Arboleda et al. [165] | All the wounded | Hospital beds, doctors, medicines, and infrastructure | The impact of different casualty attendance rates or different infrastructure failures on the number of wounded waiting for treatment in each department |
| Khanmohammadi et al. [62] | All the wounded | Healthcare buildings and infrastructure | The impact of hospital building and infrastructure repair on the proportion of wounded |
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