Hans Nesse - Global Health - SEIR Model

**Overview:**

The SEIR models the flows of people between four states: susceptible (S), exposed (E), infected (I), and resistant (R). Each of those variables represents the number of people in those groups. The parameters alpha and beta partially control how fast people move from being susceptible to exposed (beta), from exposed to infected (sigma), and from infected to resistant (gamma). This model has two additional parameters; one is the background mortality (mu) which is unaffected by disease-state, while the other is vaccination (nu). The vaccination moves people from the susceptible to resistant directly, without becoming exposed or infected.

The SEIR differs from the SIR model in the addition of a latency period. Individuals who are exposed (E) have had contact with an infected person, but are not themselves infectious.

**Instructions:**

The boxes on the right side of the page control the parameters of the model. The page should load with some parameters already in the box. Click "submit" to run the model. The parameters can all be modified and the model re-run. The parameters are

Beta | The parameter controlling how often a susceptible-infected contact results in a new exposure. |

Gamma | The rate an infected recovers and moves into the resistant phase. |

Sigma | The rate at which an exposed person becomes infective. |

Mu | The natural mortality rate (this is unrelated to disease). This models a population of a constant size, |

Initial susceptible | The number of susceptible individuals at the beginning of the model run. |

Initial exposed | The number of exposed individuals at the beginning of the model run. |

Initial infected | The number of infected individuals at the beginning of the model run. |

Initial recovered | The number of recovered individuals at the beginning of the model run. |

Days | Controls how long the model will run. |

**Details:**

This is an ordinary differential equation model, described by the following equation: