Skip to content
DraconiticResearch
Search Sources API
186,125 studies31 sourcesUpdated 14 min ago
Peer-reviewedCC BY 4.0PLOS One

Complexity of hospital demand during the COVID-19 pandemic in Mexico City

  • Guillermo de Anda-Jáuregui1
  • José Sifuentes-Osornio2
  • Ofelia Angulo-Guerrero3
  • Juan L. Díaz-De-León-Santiago4
  • Héctor Benítez-Pérez5
  • Luis A. Herrera6
  • Oliva López-Arellano7
  • Arturo Revuelta-Herrera8
  • Ana R. Rosales-Tapia9
  • Manuel Suárez-Lastra10
  • David Kershenobich11
  • Rosaura Ruiz-Gutiérrez
1 more authors
  • Enrique Hernández-Lemus
11 affiliations
  1. 1Population genomics, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
  2. 2Investigadores e Investigadoras por México, Secretaría de Ciencia, Humanidades, Tecnología e Innovación, Mexico City, Mexico
  3. 3Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
  4. 4Secretaría de Ciencia, Humanidades, Tecnología e Innovación, Mexico City, Mexico
  5. 5Secretaría de Educación, Ciencia, Tecnología e Innovación, Gobierno de la Ciudad de México, Mexico City, Mexico
  6. 6Dirección General de Cómputo y de Tecnologías de Información y Comunicación, Instituto de Investigaciones en Matemáticas Aplicadas y en Sistemas, Universidad Nacional Autónoma de México, Mexico City, Mexico
  7. 7Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City, Mexico
  8. 8Instituto Tecnológico de Estudios Superiores de Monterrey, Monterrey, Mexico
  9. 9Secretaría de Salud de la Ciudad de México, Mexico City, Mexico
  10. 10Instituto de Geografía, Universidad Nacional Autónoma de México, Mexico City, Mexico
  11. 11Secretaría de Salud, Mexico City, Mexico
Open at sourcePDFDOICite

Abstract

The COVID-19 pandemic posed unprecedented challenges to healthcare systems worldwide. In densely populated urban areas such as Mexico City, hospital strain was amplified by high case volumes and limited resources. This study aims to characterize the spatial and temporal organization of hospital demand and its relationship to patient outcomes. We conducted a retrospective analysis of COVID-19 hospitalization data in Mexico City using line-list data from the SISVER surveillance system. Spatial dynamics were examined using the weighted centroid of hospitalizations, and patient–hospital interactions were modeled as a time-resolved bipartite network. The emergence of giant components was used as a proxy for system strain and evaluated in relation to patient outcomes. Hospital demand exhibited marked spatial shifts, including a northward displacement of the hospitalization centroid over time. A small group of 17 hospitals consistently managed the majority of cases. During periods of high demand, the network underwent structural transitions characterized by the emergence of large connected components spanning diverse neighborhoods. These periods of increased system-wide connectivity were associated with higher case fatality rates, particularly among patients over 40. Hospital demand reorganizes at the system level under stress, leading to loss of spatial structure and increased strain. The emergence of large connected components may serve as an early indicator of systemic overload. These findings provide a network-based perspective on healthcare system stress and may inform strategies for resource allocation and emergency response.

Related

  1. Morphology, molecular phylogeny and azaspiracid profile of Azadinium poporum (Dinophyceae) from the Gulf of Mexico
    Zhaohe Luo, Bernd Krock, Kenneth Neil Mertens +4
    Harmful AlgaePeer-reviewedLicence not stated28 citedGeneral biochemistryGeneral biologyHAL
  2. Demand for de novo serine biosynthesis in C. elegans embryos is buffered by the glycine cleavage system and maternal diet
    Joanna Zaino, Amanda Anderson, Omar Rachidi Alaoui +1
    Journal of Biological ChemistryPeer-reviewedCC BY 4.0Enzymology & metabolismCrossref
  3. Mapping the technology–demand interface: how brain organoid evolution is reshaping the translational landscape of stroke
    Caohang Qiu, Ning Sun, Jun Yang +6
    Frontiers in cell and developmental biologyPeer-reviewedCC BYFull textGeneral biochemistryEurope PMC
  4. Pyrrolysine supply and demand shapes the translational landscape in Methanosarcina acetivorans.
    Grace D Britt, Daniel R Utter, Yeonsoo Park +2
    Proceedings of the National Academy of Sciences of the United States of AmericaPeer-reviewedCC BYFull textMolecular biology & gene regulationEurope PMC
  5. dubTAGs enable on-demand stabilization for tunable and reversible control of endogenous protein levels
    S. Guharajan, X. Song, Q. Wu +5
    bioRxivPreprintCC BYFull textMolecular biology & gene regulationbioRxiv

Cite

BibTeXRIS
BibTeX
@article{andajauregui2026complexity,
  title = {{Complexity of hospital demand during the COVID-19 pandemic in Mexico City}},
  author = {Guillermo de Anda-Jáuregui and José Sifuentes-Osornio and Ofelia Angulo-Guerrero and Juan L. Díaz-De-León-Santiago and Héctor Benítez-Pérez and Luis A. Herrera and Oliva López-Arellano and Arturo Revuelta-Herrera and Ana R. Rosales-Tapia and Manuel Suárez-Lastra and David Kershenobich and Rosaura Ruiz-Gutiérrez and Enrique Hernández-Lemus},
  journal = {PLOS One},
  year = {2026},
  month = sep,
  doi = {10.1371/journal.pone.0358798},
  url = {https://doi.org/10.1371/journal.pone.0358798},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Complexity of hospital demand during the COVID-19 pandemic in Mexico City
AU  - Guillermo de Anda-Jáuregui
AU  - José Sifuentes-Osornio
AU  - Ofelia Angulo-Guerrero
AU  - Juan L. Díaz-De-León-Santiago
AU  - Héctor Benítez-Pérez
AU  - Luis A. Herrera
AU  - Oliva López-Arellano
AU  - Arturo Revuelta-Herrera
AU  - Ana R. Rosales-Tapia
AU  - Manuel Suárez-Lastra
AU  - David Kershenobich
AU  - Rosaura Ruiz-Gutiérrez
AU  - Enrique Hernández-Lemus
PY  - 2026
DA  - 2026/09/30
JO  - PLOS One
DO  - 10.1371/journal.pone.0358798
UR  - https://doi.org/10.1371/journal.pone.0358798
AB  - The COVID-19 pandemic posed unprecedented challenges to healthcare systems worldwide. In densely populated urban areas such as Mexico City, hospital strain was amplified by high case volumes and limited resources. This study aims to characterize the spatial and temporal organization of hospital demand and its relationship to patient outcomes. We conducted a retrospective analysis of COVID-19 hospitalization data in Mexico City using line-list data from the SISVER surveillance system. Spatial dynamics were examined using the weighted centroid of hospitalizations, and patient–hospital interactions were modeled as a time-resolved bipartite network. The emergence of giant components was used as a proxy for system strain and evaluated in relation to patient outcomes. Hospital demand exhibited marked spatial shifts, including a northward displacement of the hospitalization centroid over time. A small group of 17 hospitals consistently managed the majority of cases. During periods of high demand, the network underwent structural transitions characterized by the emergence of large connected components spanning diverse neighborhoods. These periods of increased system-wide connectivity were associated with higher case fatality rates, particularly among patients over 40. Hospital demand reorganizes at the system level under stress, leading to loss of spatial structure and increased strain. The emergence of large connected components may serve as an early indicator of systemic overload. These findings provide a network-based perspective on healthcare system stress and may inform strategies for resource allocation and emergency response.
SN  - 1932-6203
ER  -