Inferring human behavior through online social networks may provide accurate behavioral estimates for outbreak forecasting of arboviruses.
Human behavior is known to be a fundamental, yet often neglected, component of infectious disease epidemiology, especially during outbreaks. To quantify its role and fluctuations, analyzing message contents on popular online social networks - part of so-called digital epidemiology - is a promising a...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
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| Series: | PLOS Global Public Health |
| Online Access: | https://doi.org/10.1371/journal.pgph.0004889 |
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