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Título del libro: Mathematical Modeling, Simulations, And Ai For Emergent Pandemic Diseases: Lessons Learned From Covid-19
Título del capítulo: After COVID-19: Mathematical models, epidemic preparedness, and external factors in epidemic management

Autores UNAM:
JORGE XICOTENCATL VELASCO HERNANDEZ;
Autores externos:

Idioma:

Año de publicación:
2023
Palabras clave:

COVID population dynamics; COVID-19; Mathematical epidemiology; Mathematical models


Resumen:

We look at some of the important topics of relevance by late 2021, for the mitigation and control of the SARS-CoV-2 pandemic. Overall, mathematical models have been a very useful tool for the efficient management of the epidemic. We review some of the main conclusions derived from their use in some of the important factors related to the evolution of the epidemic such as nonpharmaceutical interventions, vaccination rates and coverage, evolution of SARS-CoV-2 variants, and their impact on the control of the epidemic. We also provide some recent results on the analysis of the epidemic in Mexico, as an example of its evolution in a country with high mortality, low testing, low contact tracing, and weak enforcing of NPI. © 2023 Elsevier B.V. All rights reserved.


Entidades citadas de la UNAM: