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What could re-infection tell us about R(0)? A modeling case-study of syphilis transmission

Many infectious diseases can lead to re-infection. We examined the relationship between the prevalence of repeat infection and the basic reproductive number (R(0)). First we solved a generic, deterministic compartmental model of re-infection to derive an analytic solution for the relationship. We th...

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Detalles Bibliográficos
Autores principales: Feldman, Joshua, Mishra, Sharmistha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806446/
https://www.ncbi.nlm.nih.gov/pubmed/31667445
http://dx.doi.org/10.1016/j.idm.2019.09.002
Descripción
Sumario:Many infectious diseases can lead to re-infection. We examined the relationship between the prevalence of repeat infection and the basic reproductive number (R(0)). First we solved a generic, deterministic compartmental model of re-infection to derive an analytic solution for the relationship. We then numerically solved a disease-specific model of syphilis transmission that explicitly tracked re-infection. We derived a generic expression that reflects a non-linear and monotonically increasing relationship between proportion re-infection and R(0) and which is attenuated by entry/exit rates and recovery (i.e. treatment). Numerical simulations from the syphilis model aligned with the analytic relationship. Re-infection proportions could be used to understand how far regions are from epidemic control, and should be included as a routine indicator in infectious disease surveillance.