From: Public health impact of strain specific immunity to *Borrelia burgdorferi*

Model |
Key assumptions^{a}
| Benefits | Limitations |
---|---|---|---|

Deterministic probability | Lyme disease patients’ probability of exposure to infectious bite similar to general population. |
Extremely simple and flexible. Allows a separate analysis focusing on infections caused by invasive strains of B. burgdorferi.
| May over estimate the impact of immunity on averted cases. |

Immunity is permanent. | |||

Provides the upper limit of averted cases. | |||

Equilibrium dynamic | Lyme disease patients’ probability of exposure to infectious bite similar to general population. | Simple. | May under estimate the impact of immunity on averted cases. |

Provides the lower limit of averted cases. | |||

Immunity lasts 5 to 30 years. | |||

Lyme disease patients are at risk for tick bites for 30 years. | |||

Individual-based stochastic | Lyme disease patients’ probability of exposure to infectious bite higher than in general population. | Most complex, allows manipulation of many parameters. | Simulations are time-demanding. |

May provide the most realistic estimate of the number of averted cases. | |||

Immunity lasts 5 to 30 years. | |||

Patients are at risk for tick bites for 30 years. |