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Modular Reactivation of Mexico City After COVID-19 Lockdown
GUILLERMO DE ANDA JAUREGUI
ENRIQUE HERNANDEZ LEMUS
Acceso Abierto
Atribución-NoComercial-CompartirIgual
arXiv:2008.12688
https://arxiv.org/abs/2008.12688
During the COVID-19 pandemic, the slope of the epidemic curve in Mexico City has been quite unstable. We have predicted that in the case that a fraction of the population above a certain threshold returns to the public space, the negative tendency of the epidemic curve will revert. Such predictions were based on modeling the reactivation of economic activity after lockdown by means of an epidemiological model on a contact network of Mexico City derived from mobile device co-localization. We evaluated the epidemic dynamics considering the tally of active and recovered cases documented in the mexican government's open database. Scenarios were modeled in which different percentages of the population are reintegrated to the public space by scanning values ranging from 5% up to 50%. Null models were built by using data from the Jornada Nacional de Sana Distancia (the Mexican model of elective lockdown) in which there was a mobility reduction of 75% and no mandatory mobility restrictions. We found that a new peak of cases in the epidemic curve was very likely for scenarios in which more than 5% of the population rejoined the public space; The return of more than 50% of the population synchronously will unleash a peak of a magnitude similar to the one that was predicted with no mitigation strategies. By evaluating the tendencies of the epidemic dynamics, the number of new cases registered, new cases hospitalized, and new deaths, we consider that under this scenario, reactivation following only elective measures may not be optimal. Given the need to reactivate economic activities, we suggest to consider alternative measures that allow to diminish the contacts among people returning to the public space. We evaluated that by "encapsulating" reactivated workers may allow a reactivation of a larger fraction of the population without compromising the desired tendency in the epidemic curve.
Cornell University
28-08-2020
Preimpreso
arxiv
Inglés
Epidemia COVID-19
Investigadores
Público en general
OTRAS
Versión publicada
publishedVersion - Versión publicada
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