Predicting Unobserved Exposures from Seasonal Epidemic Data

@article{Forgoston2013PredictingUE,
  title={Predicting Unobserved Exposures from Seasonal Epidemic Data},
  author={Eric Forgoston and Ira B. Schwartz},
  journal={Bulletin of Mathematical Biology},
  year={2013},
  volume={75},
  pages={1450-1471}
}
We consider a stochastic Susceptible-Exposed-Infected-Recovered (SEIR) epidemiological model with a contact rate that fluctuates seasonally. Through the use of a nonlinear, stochastic projection, we are able to analytically determine the lower dimensional manifold on which the deterministic and stochastic dynamics correctly interact. Our method produces a low dimensional stochastic model that captures the same timing of disease outbreak and the same amplitude and phase of recurrent behavior… 
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