Social networks, spread of COVID-19, and demographics in New York state
In this paper, the effectiveness of social distancing measures and the impact of socio-demographic characteristics on the infection rate of COVID-19 at a zip code level was investigated. The Susceptible-Infected-Recovered (SIR) model and Barab\'{a}si-Albert model were used to model the spread o...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2021
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| Online Access: | https://hdl.handle.net/10356/148488 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In this paper, the effectiveness of social distancing measures and the impact of socio-demographic characteristics on the infection rate of COVID-19 at a zip code level was investigated. The Susceptible-Infected-Recovered (SIR) model and Barab\'{a}si-Albert model were used to model the spread of COVID-19 over social contact networks and to find optimal infection and recovery rates so as to produce simulations that are most consistent with real-world data of the COVID-19 spread. Following this, regression analysis was carried out and the results showed that while there were significantly correlated variables, no independent variable had a significant relationship with the optimal infection rate in our fitted regression model. This paper recommends that future work must be done to address the limitations of this study and improve on this study. |
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