Corpus ID: 13751063

Urban contact structures for epidemic simulations: Correcting biases in data-driven approaches

@article{Du2018UrbanCS,
  title={Urban contact structures for epidemic simulations: Correcting biases in data-driven approaches},
  author={Z. Du and C. Gao and Y. Bai and Yongjian Yang and Petter Holme},
  journal={ArXiv},
  year={2018},
  volume={abs/1804.10644}
}
  • Z. Du, C. Gao, +2 authors Petter Holme
  • Published 2018
  • Computer Science, Physics
  • ArXiv
  • Epidemics are emergent phenomena depending on the epidemiological characteristics of pathogens and the interaction and movement of people. Public transit systems have provided much important information about the movement of people, but there are also other means of transportation (e.g., bicycle and private car), that are invisible to public transit data. This discrepancy can induce a bias in disease models that leads to mispredictions of epidemic growth (e.g., peak prevalence and time). In our… CONTINUE READING

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