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What could re-infection tell us about R0? A modeling case-study of syphilis transmission.


ABSTRACT: Many infectious diseases can lead to re-infection. We examined the relationship between the prevalence of repeat infection and the basic reproductive number (R0). 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 R0 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.

SUBMITTER: Feldman J 

PROVIDER: S-EPMC6806446 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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What could re-infection tell us about R<sub>0</sub>? A modeling case-study of syphilis transmission.

Feldman Joshua J   Mishra Sharmistha S  

Infectious Disease Modelling 20190917


Many infectious diseases can lead to re-infection. We examined the relationship between the prevalence of repeat infection and the basic reproductive number (R<sub>0</sub>). 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 incr  ...[more]

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