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Magpantay FMG, Mao J, Ren S, Zhao S, Meadows T. The reinfection threshold, revisited. Math Biosci 2023; 363:109045. [PMID: 37442222 DOI: 10.1016/j.mbs.2023.109045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 06/29/2023] [Accepted: 07/06/2023] [Indexed: 07/15/2023]
Abstract
One mode by which infection-derived immunity fails is when recovery leads to a reduced but nonzero risk of reinfection. This type of partial protection is called leaky immunity with the degree of leakiness quantified by the relative probability a previously infected individual will get infected upon exposure compared to a naively susceptible individual. Previous authors have defined the reinfection threshold, which occurs when the basic reproduction number equals the inverse of the leakiness, however, there has been some debate about whether or not this is a real threshold. Here we show how the reinfection threshold relates to two important occurrences: (1) the point at which the endemic equilibrium changes from being a stable spiral to a stable node, and (2) the point at which the rate of change of the prevalence increases the most relative to leakiness. When the recovery period is short relative to the average lifetime then both occurrences are close to the reinfection threshold. We show how these results are related to the reinfection threshold found in other models of imperfect immunity. To further demonstrate the significance of this threshold in modeling, we conducted a simulation study to evaluate some of the consequences the reinfection threshold might have in parameter estimation and modeling. Using specific parameter values chosen to reflect an acute infection, we found that the basic reproduction number values larger than that of the reinfection threshold value were less identifiable than those below the threshold.
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Affiliation(s)
- F M G Magpantay
- Department of Mathematics and Statistics, Queen's University, 48 University Avenue, Kingston, ON, Canada, K7L 3N6.
| | - J Mao
- Department of Mathematics and Statistics, Queen's University, 48 University Avenue, Kingston, ON, Canada, K7L 3N6; Department of Physics, Engineering Physics and Astronomy, Queen's University, 64 Bader Lane, Kingston, ON, Canada, K7L 3N6
| | - S Ren
- Department of Mathematics and Statistics, Queen's University, 48 University Avenue, Kingston, ON, Canada, K7L 3N6
| | - S Zhao
- Department of Mathematics and Statistics, Queen's University, 48 University Avenue, Kingston, ON, Canada, K7L 3N6
| | - T Meadows
- Department of Mathematics and Statistics, Queen's University, 48 University Avenue, Kingston, ON, Canada, K7L 3N6
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