Research on the Model and Application of Virus Contact and Transmission in Cabin

A cellular automata model is established for the virus in the cabin through contact and transmission. The probability of virus transmission and infection in the cabin is analyzed. The curve of the virus change in the cabin is obtained by using MATLAB to solve the problem. Then, effective intervention measures are proposed to reduce The probability of the virus spreading through contact in the cabin. 1. Background Air travel brings people from different geographical environments together. Due to the different geographical environments in different regions, people's immunity and acceptability are different. The virus in the cabin is mainly transmitted through contact, air, and media. For passengers and crew, contact and transmission are divided into direct contact and indirect contact. Passengers will carry the virus to different places, which will lead to the rapid spread of the virus and cause economic losses to people. 2. Cogitation of the Research The SIR cellular automata model of virus contact and transmission was established. The MATLAB program was used to obtain the change curve of infected persons, susceptible persons, and immune persons after the virus was transmitted through contact in a unit time. Passengers are divided into susceptible persons, infected persons and immunized persons. The state of the cell, the state of the cell neighbor and the evolution rules are determined, and the actual situation is realized through computer simulation. By comparing the results obtained by the two models, analyzing the differences in the data obtained by the two methods, determining an optimal method, and then proposing some improved measures to remind passengers what behaviors may cause them to be infected by the virus in order to reduce Probability of virus transmission. 3. Research Program 3.1 Construction of SIR Cellular Automata Model The SIR model is to classify the population infected by the virus in a certain space. The number of susceptible, infected, and immune populations at time t are ) t ( S 、 ) t ( I 、 ) t ( R , and are defined by cellular automata and are represented by mathematical symbols ) , , , ( f N S L C ∝ = , Among them, the ∝ L means cell is all the people, S is the state set, N is the neighbor of the cell, and f is the evolution rule of the cell. The established cellular automaton model is as follows. (1) Cell space: two-dimensional cell space. 2020 2nd International Symposium on the Frontiers of Biotechnology and Bioengineering (FBB 2020) Published by CSP © 2020 the Authors 265 (2) Neighbor form: Moore type with a neighbour radius of 1, and the eight surrounding neighbours are expressed in order as: ) 1 , 1 ( ) , 1 ( ) 1 , 1 ( ) 1 , ( ) , ( ) 1 , ( ) 1 , 1 ( ) , 1 ( ) 1 , 1 ( + + + − + + − + − − − − j i j i j i j i j i j i j i j i j i (1) (3)Cell evolution rules: The initial state of all cells is S = 0, and the state of the pathogen is set to 1. The sick infected the susceptible at the rate of infection, and exchanged randomly at a probability of. Scan all cells from time 0, and update the cell status according to the following rules. When 0 , i = t j S (susceptible), the cell at (i,j),its Adjacency matrix