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A Note on the Risk of Infections Invading Unaffected Regions

We present two probabilistic models to estimate the risk of introducing infectious diseases into previously unaffected countries/regions by infective travellers. We analyse two distinct situations, one dealing with a directly transmitted infection (measles in Italy in 2017) and one dealing with a ve...

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Detalles Bibliográficos
Autores principales: Amaku, Marcos, Coutinho, Francisco Antonio Bezerra, Armstrong, Margaret, Massad, Eduardo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6057402/
https://www.ncbi.nlm.nih.gov/pubmed/30073032
http://dx.doi.org/10.1155/2018/6289681
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author Amaku, Marcos
Coutinho, Francisco Antonio Bezerra
Armstrong, Margaret
Massad, Eduardo
author_facet Amaku, Marcos
Coutinho, Francisco Antonio Bezerra
Armstrong, Margaret
Massad, Eduardo
author_sort Amaku, Marcos
collection PubMed
description We present two probabilistic models to estimate the risk of introducing infectious diseases into previously unaffected countries/regions by infective travellers. We analyse two distinct situations, one dealing with a directly transmitted infection (measles in Italy in 2017) and one dealing with a vector-borne infection (Zika virus in Rio de Janeiro, which may happen in the future). To calculate the risk in the first scenario, we used a simple, nonhomogeneous birth process. The second model proposed in this paper provides a way to calculate the probability that local mosquitoes become infected by the arrival of a single infective traveller during his/her infectiousness period. The result of the risk of measles invasion of Italy was of 93% and the result of the risk of Zika virus invasion of Rio de Janeiro was of 22%.
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spelling pubmed-60574022018-08-02 A Note on the Risk of Infections Invading Unaffected Regions Amaku, Marcos Coutinho, Francisco Antonio Bezerra Armstrong, Margaret Massad, Eduardo Comput Math Methods Med Research Article We present two probabilistic models to estimate the risk of introducing infectious diseases into previously unaffected countries/regions by infective travellers. We analyse two distinct situations, one dealing with a directly transmitted infection (measles in Italy in 2017) and one dealing with a vector-borne infection (Zika virus in Rio de Janeiro, which may happen in the future). To calculate the risk in the first scenario, we used a simple, nonhomogeneous birth process. The second model proposed in this paper provides a way to calculate the probability that local mosquitoes become infected by the arrival of a single infective traveller during his/her infectiousness period. The result of the risk of measles invasion of Italy was of 93% and the result of the risk of Zika virus invasion of Rio de Janeiro was of 22%. Hindawi 2018-07-04 /pmc/articles/PMC6057402/ /pubmed/30073032 http://dx.doi.org/10.1155/2018/6289681 Text en Copyright © 2018 Marcos Amaku et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Amaku, Marcos
Coutinho, Francisco Antonio Bezerra
Armstrong, Margaret
Massad, Eduardo
A Note on the Risk of Infections Invading Unaffected Regions
title A Note on the Risk of Infections Invading Unaffected Regions
title_full A Note on the Risk of Infections Invading Unaffected Regions
title_fullStr A Note on the Risk of Infections Invading Unaffected Regions
title_full_unstemmed A Note on the Risk of Infections Invading Unaffected Regions
title_short A Note on the Risk of Infections Invading Unaffected Regions
title_sort note on the risk of infections invading unaffected regions
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6057402/
https://www.ncbi.nlm.nih.gov/pubmed/30073032
http://dx.doi.org/10.1155/2018/6289681
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