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Resource Allocation for Epidemic Control Across Multiple Sub-populations
The number of pathogenic threats to plant, animal and human health is increasing. Controlling the spread of such threats is costly and often resources are limited. A key challenge facing decision makers is how to allocate resources to control the different threats in order to achieve the least amoun...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6491412/ https://www.ncbi.nlm.nih.gov/pubmed/30809774 http://dx.doi.org/10.1007/s11538-019-00584-2 |
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author | Dangerfield, Ciara E. Vyska, Martin Gilligan, Christopher A. |
author_facet | Dangerfield, Ciara E. Vyska, Martin Gilligan, Christopher A. |
author_sort | Dangerfield, Ciara E. |
collection | PubMed |
description | The number of pathogenic threats to plant, animal and human health is increasing. Controlling the spread of such threats is costly and often resources are limited. A key challenge facing decision makers is how to allocate resources to control the different threats in order to achieve the least amount of damage from the collective impact. In this paper we consider the allocation of limited resources across n independent target populations to treat pathogens whose spread is modelled using the susceptible–infected–susceptible model. Using mathematical analysis of the systems dynamics, we show that for effective disease control, with a limited budget, treatment should be focused on a subset of populations, rather than attempting to treat all populations less intensively. The choice of populations to treat can be approximated by a knapsack-type problem. We show that the knapsack closely approximates the exact optimum and greatly outperforms a number of simpler strategies. A key advantage of the knapsack approximation is that it provides insight into the way in which the economic and epidemiological dynamics affect the optimal allocation of resources. In particular using the knapsack approximation to apportion control takes into account two important aspects of the dynamics: the indirect interaction between the populations due to the shared pool of limited resources and the dependence on the initial conditions. |
format | Online Article Text |
id | pubmed-6491412 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-64914122019-05-17 Resource Allocation for Epidemic Control Across Multiple Sub-populations Dangerfield, Ciara E. Vyska, Martin Gilligan, Christopher A. Bull Math Biol Article The number of pathogenic threats to plant, animal and human health is increasing. Controlling the spread of such threats is costly and often resources are limited. A key challenge facing decision makers is how to allocate resources to control the different threats in order to achieve the least amount of damage from the collective impact. In this paper we consider the allocation of limited resources across n independent target populations to treat pathogens whose spread is modelled using the susceptible–infected–susceptible model. Using mathematical analysis of the systems dynamics, we show that for effective disease control, with a limited budget, treatment should be focused on a subset of populations, rather than attempting to treat all populations less intensively. The choice of populations to treat can be approximated by a knapsack-type problem. We show that the knapsack closely approximates the exact optimum and greatly outperforms a number of simpler strategies. A key advantage of the knapsack approximation is that it provides insight into the way in which the economic and epidemiological dynamics affect the optimal allocation of resources. In particular using the knapsack approximation to apportion control takes into account two important aspects of the dynamics: the indirect interaction between the populations due to the shared pool of limited resources and the dependence on the initial conditions. Springer US 2019-02-26 2019 /pmc/articles/PMC6491412/ /pubmed/30809774 http://dx.doi.org/10.1007/s11538-019-00584-2 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Dangerfield, Ciara E. Vyska, Martin Gilligan, Christopher A. Resource Allocation for Epidemic Control Across Multiple Sub-populations |
title | Resource Allocation for Epidemic Control Across Multiple Sub-populations |
title_full | Resource Allocation for Epidemic Control Across Multiple Sub-populations |
title_fullStr | Resource Allocation for Epidemic Control Across Multiple Sub-populations |
title_full_unstemmed | Resource Allocation for Epidemic Control Across Multiple Sub-populations |
title_short | Resource Allocation for Epidemic Control Across Multiple Sub-populations |
title_sort | resource allocation for epidemic control across multiple sub-populations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6491412/ https://www.ncbi.nlm.nih.gov/pubmed/30809774 http://dx.doi.org/10.1007/s11538-019-00584-2 |
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