Kimia Ameria and Kathryn D. Cooper from the College of Information Science and Technology at the University of Nebraska at Omaha proposed a Network-Based SEIR (NB-SEIR) model of pertussis transmission. They used Project Tycho pertussis data to show that the NB-SEIR model estimated the number of infected individuals in Nebraska more accurately than the standard SEIR model.
Related Project Tycho Datasets
Outbreaks of pertussis have increased over the past few years, drawing the attention of health care providers. Un- derstanding the transmission mechanisms of contagious disease is critically important, but depends on many intricate factors including pathogen and host environment, exposed population, and their activities. In this work, we try to improve upon the prediction model for the exposed population. The number of whooping cough reported cases in Nebraska between 2000-2017 was gathered. The standard Susceptible-Exposed-Infected-Recovered (SEIR) model is used to predict the infected numbers. The results show that the SEIR model prediction for the number of infected indi- viduals is much higher than the actual number. To overcome this problem, the Network Based-SEIR model is proposed, and is able to estimate the number of infected more accurately than the classic SEIR model.
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