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Logistical constraints lead to an intermediate optimum in outbreak response vaccination

Dynamic models in disease ecology have historically evaluated vaccination strategies under the assumption that they are implemented homogeneously in space and time. However, this approach fails to formally account for operational and logistical constraints inherent in the distribution of vaccination...

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Detalles Bibliográficos
Autores principales: Tao, Yun, Shea, Katriona, Ferrari, Matthew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988332/
https://www.ncbi.nlm.nih.gov/pubmed/29791432
http://dx.doi.org/10.1371/journal.pcbi.1006161
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author Tao, Yun
Shea, Katriona
Ferrari, Matthew
author_facet Tao, Yun
Shea, Katriona
Ferrari, Matthew
author_sort Tao, Yun
collection PubMed
description Dynamic models in disease ecology have historically evaluated vaccination strategies under the assumption that they are implemented homogeneously in space and time. However, this approach fails to formally account for operational and logistical constraints inherent in the distribution of vaccination to the population at risk. Thus, feedback between the dynamic processes of vaccine distribution and transmission might be overlooked. Here, we present a spatially explicit, stochastic Susceptible-Infected-Recovered-Vaccinated model that highlights the density-dependence and spatial constraints of various diffusive strategies of vaccination during an outbreak. The model integrates an agent-based process of disease spread with a partial differential process of vaccination deployment. We characterize the vaccination response in terms of a diffusion rate that describes the distribution of vaccination to the population at risk from a central location. This generates an explicit trade-off between slow diffusion, which concentrates effort near the central location, and fast diffusion, which spreads a fixed vaccination effort thinly over a large area. We use stochastic simulation to identify the optimum vaccination diffusion rate as a function of population density, interaction scale, transmissibility, and vaccine intensity. Our results show that, conditional on a timely response, the optimal strategy for minimizing outbreak size is to distribute vaccination resource at an intermediate rate: fast enough to outpace the epidemic, but slow enough to achieve local herd immunity. If the response is delayed, however, the optimal strategy for minimizing outbreak size changes to a rapidly diffusive distribution of vaccination effort. The latter may also result in significantly larger outbreaks, thus suggesting a benefit of allocating resources to timely outbreak detection and response.
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spelling pubmed-59883322018-06-16 Logistical constraints lead to an intermediate optimum in outbreak response vaccination Tao, Yun Shea, Katriona Ferrari, Matthew PLoS Comput Biol Research Article Dynamic models in disease ecology have historically evaluated vaccination strategies under the assumption that they are implemented homogeneously in space and time. However, this approach fails to formally account for operational and logistical constraints inherent in the distribution of vaccination to the population at risk. Thus, feedback between the dynamic processes of vaccine distribution and transmission might be overlooked. Here, we present a spatially explicit, stochastic Susceptible-Infected-Recovered-Vaccinated model that highlights the density-dependence and spatial constraints of various diffusive strategies of vaccination during an outbreak. The model integrates an agent-based process of disease spread with a partial differential process of vaccination deployment. We characterize the vaccination response in terms of a diffusion rate that describes the distribution of vaccination to the population at risk from a central location. This generates an explicit trade-off between slow diffusion, which concentrates effort near the central location, and fast diffusion, which spreads a fixed vaccination effort thinly over a large area. We use stochastic simulation to identify the optimum vaccination diffusion rate as a function of population density, interaction scale, transmissibility, and vaccine intensity. Our results show that, conditional on a timely response, the optimal strategy for minimizing outbreak size is to distribute vaccination resource at an intermediate rate: fast enough to outpace the epidemic, but slow enough to achieve local herd immunity. If the response is delayed, however, the optimal strategy for minimizing outbreak size changes to a rapidly diffusive distribution of vaccination effort. The latter may also result in significantly larger outbreaks, thus suggesting a benefit of allocating resources to timely outbreak detection and response. Public Library of Science 2018-05-23 /pmc/articles/PMC5988332/ /pubmed/29791432 http://dx.doi.org/10.1371/journal.pcbi.1006161 Text en © 2018 Tao et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Tao, Yun
Shea, Katriona
Ferrari, Matthew
Logistical constraints lead to an intermediate optimum in outbreak response vaccination
title Logistical constraints lead to an intermediate optimum in outbreak response vaccination
title_full Logistical constraints lead to an intermediate optimum in outbreak response vaccination
title_fullStr Logistical constraints lead to an intermediate optimum in outbreak response vaccination
title_full_unstemmed Logistical constraints lead to an intermediate optimum in outbreak response vaccination
title_short Logistical constraints lead to an intermediate optimum in outbreak response vaccination
title_sort logistical constraints lead to an intermediate optimum in outbreak response vaccination
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5988332/
https://www.ncbi.nlm.nih.gov/pubmed/29791432
http://dx.doi.org/10.1371/journal.pcbi.1006161
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