Libro de resúmenes del Encuentro Científico Internacional 2021 - Estudios de epidemias mediante simulaciones de Monte Carlo cinético: Aplicaciones a Covid-19

Congress

Authorship

Pedro Morelo, Diego ; CENTRES, PAULO MARCELO ; Guzman Arellano, Robert Mikhail ; GIMENEZ, MARIA CECILIA

Date

2021

Publishing House and Editing Place

Modesto Montoya

Summary Information provided by the agent in SIGEVA

Since December 2019, the acute respiratory disease Covid-19 due to the new coronavirus SARS-CoV-2, which emerged in the city of Wuhan, has spread rapidly throughout China. During 2020, this disease spread throughout the world, becoming a pandemic and causing great loss of life and socioeconomic impact. There are several models that explain the evolution of an epidemic, generally based on the initial proposal of Kermack and McKendrick, with improvements and variations over the years. Among the m... Since December 2019, the acute respiratory disease Covid-19 due to the new coronavirus SARS-CoV-2, which emerged in the city of Wuhan, has spread rapidly throughout China. During 2020, this disease spread throughout the world, becoming a pandemic and causing great loss of life and socioeconomic impact. There are several models that explain the evolution of an epidemic, generally based on the initial proposal of Kermack and McKendrick, with improvements and variations over the years. Among the most used models are those of the SIR type. These models consist of studying the evolution of the different populations of individuals, divided into the aforementioned categories, according to certain rules of contagion and recovery or death [1,2]. In most cases, the approach of the models consists of the evolution of the populations, which can be solved by deterministic numerical methods such as Runge Kutta or alternatively with stochastic simulation models, such as kinetic Monte Carlo (KMC). In the present work, the problem of the evolution of epidemics is approached through different simulation methods. Firstly, homogeneous populations are considered and the dependence of the number of infected with the different parameters (Basic Reproductive Number R0, duration of infection, population size, etc.) is studied. Second, two-dimensional mobile agent models are proposed. These models have the advantage of being able to introduce other variables, such as social distancing, varying the density and speed with which the agents move [2,3]. Finally, the evolution of the Covid-19 epidemic in some countries that overcame the epidemic was studied, by adjusting for the different evolution of populations.