期刊
MATHEMATICAL BIOSCIENCES AND ENGINEERING
卷 11, 期 6, 页码 1337-1356出版社
AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/mbe.2014.11.1337
关键词
Mathematical model; epidemiology; stability; Hopf bifurcation; influenza; social media; twitter; data fitting
资金
- Office of the Vice President for Research at the University of South Carolina
- University of South Carolina Magellan Scholar Program
- SC EPSCoR/IDeA Scientific Advocate Network
- NSF [DMS-1122290]
- Oakland University Research Excellence Fund
- Division Of Mathematical Sciences
- Direct For Mathematical & Physical Scien [1122290, 1349939] Funding Source: National Science Foundation
Influenza remains a serious public-health problem worldwide. The rising popularity and scale of social networking sites such as Twitter may play an important role in detecting, affecting, and predicting influenza epidemics. In this paper, we develop a simple mathematical model including the dynamics of tweets - short, 140-character Twitter messages that may enhance the awareness of disease, change individual's behavior, and reduce the transmission of disease among a population during an influenza season. We analyze the model by deriving the basic reproductive number and proving the stability of the steady states. A Hopf bifurcation occurs when a threshold curve is crossed, which suggests the possibility of multiple outbreaks of influenza. We also perform numerical simulations, conduct sensitivity test on a few parameters related to tweets, and compare modeling predictions with surveillance data of influenza-like illness reported cases and the percentage of tweets self-reporting flu during the 2009 H1N1 flu outbreak in England and Wales. These results show that social media programs like Twitter may serve as a good indicator of seasonal influenza epidemics and influence the emergence and spread of the disease.
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