Influenza pandemics are responsible for many deaths in the past one hundred years. The most recent influenza pandemic originated in Mexico in April of 2009 and spread world-wide causing great socio-economical damage. In this report we created a stochastic cellular automaton model to simulate the spread of the 2009 influenza. The cellular automaton was based on the Reed-Frost mathematical model. Using data for daily hospitalizations with influenza like symptoms from New York City, different disease variables were calculated. We calculated the disease growth rate, λ, to be 1.24 for the period between the 8th of May until the 25th of May and used it to calculate a contact rate (p value) which was equal to 0.00038. The contact rate was input into the cellular automaton and an arbitrary diffusion of 10% was chosen. The p value was subsequently adjusted for the increase in virulence from diffusion by using empirical methods to 0.00029. The results showed that each cell on its own acted much like the mathematical model, and system-wide disease progression was analysed.
Many variables have the potential to influence the outcome of a pandemic. Immunity, medications, antigenic shift, human social behaviour and economy are a few examples that have been discussed and examined.
Cellular automata are shown to be useful modelling tools for simulating influenza pandemics, with many options for introducing new parameters and adjusting existing ones.
|Uddannelser||Basis - International Naturvidenskabelig Bacheloruddannelse, (Bachelor uddannelse) Bachelor|
|Udgivelsesdato||28 maj 2018|
|Vejledere||John Patrick Gallagher|