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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
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author Feldman, Joshua
Mishra, Sharmistha
author_facet Feldman, Joshua
Mishra, Sharmistha
author_sort Feldman, Joshua
collection PubMed
description 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.
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spelling pubmed-68064462019-10-30 What could re-infection tell us about R(0)? A modeling case-study of syphilis transmission Feldman, Joshua Mishra, Sharmistha Infect Dis Model Original Research Article 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. KeAi Publishing 2019-09-17 /pmc/articles/PMC6806446/ /pubmed/31667445 http://dx.doi.org/10.1016/j.idm.2019.09.002 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Original Research Article
Feldman, Joshua
Mishra, Sharmistha
What could re-infection tell us about R(0)? A modeling case-study of syphilis transmission
title What could re-infection tell us about R(0)? A modeling case-study of syphilis transmission
title_full What could re-infection tell us about R(0)? A modeling case-study of syphilis transmission
title_fullStr What could re-infection tell us about R(0)? A modeling case-study of syphilis transmission
title_full_unstemmed What could re-infection tell us about R(0)? A modeling case-study of syphilis transmission
title_short What could re-infection tell us about R(0)? A modeling case-study of syphilis transmission
title_sort what could re-infection tell us about r(0)? a modeling case-study of syphilis transmission
topic Original Research Article
url 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
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