Modeling the impact of twitter on influenza epidemics
Influenza remains a serious public-health problem worldwide. Therising popularity and scale of social networking sites such asTwitter may play an important role in detecting, affecting, andpredicting influenza epidemics. In this paper, we develop a simplemathematical model including the dynamics of...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2014-08-01
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| Series: | Mathematical Biosciences and Engineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2014.11.1337 |
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| Summary: | Influenza remains a serious public-health problem worldwide. Therising popularity and scale of social networking sites such asTwitter may play an important role in detecting, affecting, andpredicting influenza epidemics. In this paper, we develop a simplemathematical model including the dynamics of ``tweets'' --- short,140-character Twitter messages that may enhance the awareness ofdisease, change individual's behavior, and reduce the transmissionof disease among a population during an influenza season. We analyzethe model by deriving the basic reproductive number and proving thestability of the steady states. A Hopf bifurcation occurs when athreshold curve is crossed, which suggests the possibility ofmultiple outbreaks of influenza. We also perform numericalsimulations, conduct sensitivity test on a few parameters related totweets, and compare modeling predictions with surveillance data ofinfluenza-like illness reported cases and the percentage of tweetsself-reporting flu during the 2009 H1N1 flu outbreak in England andWales. These results show that social media programs like Twittermay serve as a good indicator of seasonal influenza epidemics andinfluence the emergence and spread of the disease. |
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| ISSN: | 1551-0018 |