Data and code to run earthquake simulations and design effective plans for hospital system response to earthquake emergencies.
Abstract/Contents
- Abstract
- Data and code to optimize the response of the hospital system in Lima by strategically treating and transferring patients after an M 8.0 earthquake. The emergency plans in the analysis minimize patient waiting times in the city and use ambulance capacities effectively. Additionally, these files contain the data and code to model the post-earthquake functionality of the operating rooms and beds in the public hospital system of Lima, Peru. The data includes vulnerability information of hundreds of buildings belonging to 41 healthcare campuses. The files also have the data and code to model earthquake multiseverity casualties in the city of Lima. The data includes information on the distribution of buildings, their vulnerabilities, their occupants, and soil conditions. Finally, these files also have the data and code to generate mean ground motions for Lima as a result of a M 8.0 earthquake. The data includes the soil conditions in the whole region. All the results are for a M 8.0 earthquake, but the code can be easily adapted for other earthquake scenarios.
Description
Type of resource | software, multimedia |
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Date created | March 2020 |
Creators/Contributors
Author | Ceferino, Luis |
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Subjects
Subject | earthquakes |
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Subject | hospitals |
Subject | casualties |
Subject | resilience |
Subject | Peru |
Genre | Dataset |
Bibliographic information
Related Publication | L. Ceferino, J. Mitrani-Reiser, A. Kiremidjian. "Effective Plans for Hospital System Response to Earthquake Emergencies." Nat. Commun. 11, 4325, 2020. https://doi.org/10.1038/s41467-020-18072-w |
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Related Publication | L. Ceferino, A. Kiremidjian, and G. Deierlein, “Computing Hospital System Resilience : a Supply-Demand Perspective,” in 11th National Conference on Earthquake Engineering (NCEE), 2018. |
Related Publication | L. Ceferino, A. Kiremidjian, and G. Deierlein, “Regional Multi-severity Casualty Estimation Due to Building Damage Following a Mw 8.8 Earthquake Scenario in Lima, Peru,” Earthq. Spectra, vol. 4, no. 3, 2018. |
Related Publication | L. Ceferino, A. S. Kiremidjian, and G. G. Deierlein, “Probabilistic Model for Regional Multiseverity Casualty Estimation due to Building Damage Following an Earthquake,” Spec. Collect. ASCE-ASME J. Risk Uncertain. Eng. Syst. Part A Civ. Eng., vol. 4, no. 3, 2018. |
Location | https://purl.stanford.edu/dp530wq8437 |
Access conditions
- Use and reproduction
- User agrees that, where applicable, content will not be used to identify or to otherwise infringe the privacy or confidentiality rights of individuals. Content distributed via the Stanford Digital Repository may be subject to additional license and use restrictions applied by the depositor.
- License
- This work is licensed under a Creative Commons Attribution 3.0 Unported license (CC BY).
Preferred citation
- Preferred Citation
- Ceferino, Luis. (2019). Data and code to run earthquake simulations and design effective plans for hospital system response to earthquake emergencies. Stanford Digital Repository. Available at: https://purl.stanford.edu/dp530wq8437
Collection
Stanford Research Data
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- Contact
- lceferinor@gmail.com
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