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Session S15 - Mathematics of Planet Earth

Wednesday, July 14, 16:30 ~ 16:55 UTC-3

On mobility trends analysis of COVID–19 dissemination in Mexico City

Jhoana P. Romero-Leiton

Centro de estudios interdisciplinarios básicos y aplicados CEIBA/Universidad Cesmag, Colombia   -   This email address is being protected from spambots. You need JavaScript enabled to view it.

This work presents a forecast of the spread of the new coronavirus in Mexico City based on a metapopulation structure mathematical model using Bayesian Statistics inspired in a data-driven approach. The mobility of humans on a daily basis in Mexico City is mathematically represented by a matrix origin-destination using the open mobility data from Google and a Transportation Mexican Survey. This matrix origin-destination was incorporated in a compartmental model. We calibrate the model against borough-level incidence data collected between February 27, 2020 and October 27, 2020 using Bayesian inference to estimate critical epidemiological characteristics associated with the coronavirus dispersion. Since working with metapopulation models lead to rather high computational time consume, we did a clustering analysis based on mobility trends in order to work on these clusters of borough separately instead of taken all the boroughs together at once. This clustering analysis could be implemented in smaller or lager scale in different part of the world. In addition, this clustering analysis is divided in the phases that the government of Mexico City has set up to restrict the individuals movement in the city. Also, the reproductive number in Mexico City is calculated using the next generation operator method and the inferred model parameters. The analysis of mobility trends can be helpful for public health officials for the evaluations of interventions of the largest city of Mexico.

Joint work with Kernel Prieto (Universidad Autónoma de México, México) and and M. Victoria Chávez–Hernández (Universidad Autónoma de Nuevo León, México).

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