2019/05/03 by Semra Gündüç, Semra Gunduc
Computer Science · Decision Sciences · Physics and Astronomy · #Action (physics) #Complex Network Analysis Techniques #Contagious disease #Diffusion #Epidemic model #Information transmission #Innovation Diffusion and Forecasting #Opinion Dynamics and Social Influence #Population #Simple (philosophy) #Social contact #Susceptible individual #cs.SI #physics.soc-ph
paper · pdf · doi:10.1142/s1793962319500156
published as INTERNATIONAL JOURNAL OF MODELING SIMULATION AND SCIENTIFIC COMPUTING, Volume: 10 Issue: 3 Article Number: 1950015, JUN 2019. Volume: 10 Issue: 3 Article Number: 1950015 · 20 pages
openalex publication_date 2019/05/03 · openalex created_date 2019/05/09 · arxiv created 2021/03/13 · arxiv updated 2021/03/16 · openalex updated_date 2026/08/05
In this work, the spread of a contagious disease on a society where the individuals may take precautions is modeled. The primary assumption is that the infected individuals transmit the infection to the susceptible members of the community through direct contact interactions. In the meantime, the susceptibles gather information from the adjacent sites which may lead to taking precautions. The SIR model is used for the diffusion of infection while the Bass equation models the information diffusion. The sociological classification of the individuals indicates that a small percentage of the population takes action immediately after being informed, while the majority expects to see some real advantage of taking action. The individuals are assumed to take two different precautions. The precursory measures are getting vaccinated or trying to avoid direct contact with the neighbors. A weighted average of states of the neighbors leads to the choice of action. The fully connected and scale-free Networks are employed as the underlying network of interactions. The comparison between the simple contagion diffusion and the diffusion of infection in a responsive society showed that a very limited precaution makes a considerable difference in the speed and the size of the spread of illness. Particularly, highly connected hub nodes play an essential role in the reduction of the spread of disease.