Modeling hospital logistics capacity through system dynamics during the COVID-19 pandemic: Case of Pasco Healthcare Network in Peru

Rosario Lock, Yennis Benavente, Gustavo Gatica, Paulo Olivares, Johana Ramirez, Alvaro Gonzalez-Holgado

Research output: Contribution to journalConference articlepeer-review

Abstract

The present investigation, whose main objective is based on modeling the hospital logistics capacity in the Pasco Healthcare Network (Peru) through Systems Dynamics during the first and second wave of the appearance of the SARS-COVid-2 virus, oriented towards a study in the capacity to respond to the most intense health emergency in recent decades. In the first instance, the reality of the studied system was made known, which was possible thanks to the information provided by the actors that make up the hospital logistics capacity, sources uploaded to the WHO worldwide. Afterwards, we proceeded to characterize the variables that make up the system, prioritizing each of these through the application of a structural analysis that measured the levels of influence between one variable and another. Because of this, we proceeded to create the causal diagram, and likewise facilitate the inclusion of the network model through the Stella software. Once the model has been simulated, the results obtained are reported.

Original languageEnglish
Pages (from-to)1042-1047
Number of pages6
JournalProcedia Computer Science
Volume238
DOIs
Publication statusPublished - 2024
Event15th International Conference on Ambient Systems, Networks and Technologies Networks, ANT 2024 / The 7th International Conference on Emerging Data and Industry 4.0, EDI40 2024 - Hasselt, Belgium
Duration: 23 Apr 202425 Apr 2024

Keywords

  • Causal diagram
  • Logistic capacity
  • Structural analysis
  • System dynamics

ASJC Scopus subject areas

  • General Computer Science

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