Estimation of COVID-19 Dynamics in the Different States of the United States during the First Months of the Pandemic †
Metadatos
Mostrar el registro completo del ítemAutor
Rojas Valenzuela, Ignacio; Valenzuela Cansino, Olga; Delgado-Marquez, Elvira; Rojas Ruiz, Fernando JoséEditorial
MDPI
Materia
COVID-19 pandemic in the united states time series
Fecha
2021-07-13Referencia bibliográfica
Rojas Valenzuela, I. et. al. Eng. Proc. 2021, 5, 53. [https://doi.org/10.3390/engproc2021005053]
Patrocinador
projects with reference RTI2018-101674-B-I00 and CV20-64934Resumen
Estimation of COVID-19 dynamics and its evolution is a multidisciplinary effort, which
requires the unification of heterogeneous disciplines (scientific, mathematics, epidemiological,
biological/bio-chemical, virologists and health disciplines to mention the most relevant) to work
together towards a better understanding of this pandemic. Time series analysis is of great importance
to determine both the similarity in the behavior of COVID-19 in certain countries/states and the
establishment of models that can analyze and predict the transmission process of this infectious
disease. In this contribution, an analysis of the different states of the United States will be carried out
to measure the similarity of COVID-19 time series, using dynamic time warping distance (DTW) as a
distance metric. A parametric methodology is proposed to jointly analyze infected and deceased
persons. This metric allows comparison of time series that have a different time length, making it
very appropriate for studying the United States, since the virus did not spread simultaneously in
all the states/provinces. After a measure of the similarity between the time series of the states of
United States was determined, a hierarchical cluster was created, which makes it possible to analyze
the behavioral relationships of the pandemic between different states and to discover interesting
patterns and correlations in the underlying data of COVID-19 in the United States. With the proposed
methodology, nine different clusters were obtained, showing a different behavior in the eastern zone
and western zone of the United States. Finally, to make a prediction of the evolution of COVID-19 in
the states, Logistic, Gompertz and SIR models were computed. With these mathematical models, it is
possible to have a more precise knowledge of the evolution and forecast of the pandemic.