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Scientific Collaborations: How Do We Measure the Return on Relationships?
Emerging infectious diseases (EIDs), the majority of which are zoonotic, represent a tremendous challenge for public health and biosurveillance infrastructure across the globe. Due to the complexity of zoonotic pathogens, it is essential that research and response to EIDs be a transdisciplinary effo...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4753292/ https://www.ncbi.nlm.nih.gov/pubmed/26913278 http://dx.doi.org/10.3389/fpubh.2016.00009 |
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author | Fair, Jeanne M. Stokes, Martha Mangum Pennington, Deana Mendenhall, Ian H. |
author_facet | Fair, Jeanne M. Stokes, Martha Mangum Pennington, Deana Mendenhall, Ian H. |
author_sort | Fair, Jeanne M. |
collection | PubMed |
description | Emerging infectious diseases (EIDs), the majority of which are zoonotic, represent a tremendous challenge for public health and biosurveillance infrastructure across the globe. Due to the complexity of zoonotic pathogens, it is essential that research and response to EIDs be a transdisciplinary effort. And while crisis and circumstance may be the initial catalyst for responding to an outbreak, we provide examples of how transdisciplinary scientific collectives, which are organized and solidified in advance of crises, can transform the way the world responds to outbreaks and in some cases could even prevent one from occurring (1). Current methods for assessing whether a cooperative engagement between countries is producing measurable and sustainable value is based on the ideas of return on investment and do not consider the inherent importance of relationships. In this article, we apply the idea of return on relationships (ROR) and propose a method for measuring ROR, using a system dynamics modeling framework commonly used in epidemiology. Tracking the numerous and diverse scientific collaborations that emerged from a training workshop for biosurveillance of bats held in Singapore in 2014, we apply a methodology for visualizing and measuring the relationship networks and outcomes that result. Additionally, the collaborative, multidisciplinary network that coalesced in response to the Hantavirus outbreak in New Mexico is 1993 is discussed as an example of the long-term benefits of ROR. |
format | Online Article Text |
id | pubmed-4753292 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-47532922016-02-24 Scientific Collaborations: How Do We Measure the Return on Relationships? Fair, Jeanne M. Stokes, Martha Mangum Pennington, Deana Mendenhall, Ian H. Front Public Health Public Health Emerging infectious diseases (EIDs), the majority of which are zoonotic, represent a tremendous challenge for public health and biosurveillance infrastructure across the globe. Due to the complexity of zoonotic pathogens, it is essential that research and response to EIDs be a transdisciplinary effort. And while crisis and circumstance may be the initial catalyst for responding to an outbreak, we provide examples of how transdisciplinary scientific collectives, which are organized and solidified in advance of crises, can transform the way the world responds to outbreaks and in some cases could even prevent one from occurring (1). Current methods for assessing whether a cooperative engagement between countries is producing measurable and sustainable value is based on the ideas of return on investment and do not consider the inherent importance of relationships. In this article, we apply the idea of return on relationships (ROR) and propose a method for measuring ROR, using a system dynamics modeling framework commonly used in epidemiology. Tracking the numerous and diverse scientific collaborations that emerged from a training workshop for biosurveillance of bats held in Singapore in 2014, we apply a methodology for visualizing and measuring the relationship networks and outcomes that result. Additionally, the collaborative, multidisciplinary network that coalesced in response to the Hantavirus outbreak in New Mexico is 1993 is discussed as an example of the long-term benefits of ROR. Frontiers Media S.A. 2016-02-15 /pmc/articles/PMC4753292/ /pubmed/26913278 http://dx.doi.org/10.3389/fpubh.2016.00009 Text en Copyright © 2016 Fair, Stokes, Pennington and Mendenhall. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Fair, Jeanne M. Stokes, Martha Mangum Pennington, Deana Mendenhall, Ian H. Scientific Collaborations: How Do We Measure the Return on Relationships? |
title | Scientific Collaborations: How Do We Measure the Return on Relationships? |
title_full | Scientific Collaborations: How Do We Measure the Return on Relationships? |
title_fullStr | Scientific Collaborations: How Do We Measure the Return on Relationships? |
title_full_unstemmed | Scientific Collaborations: How Do We Measure the Return on Relationships? |
title_short | Scientific Collaborations: How Do We Measure the Return on Relationships? |
title_sort | scientific collaborations: how do we measure the return on relationships? |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4753292/ https://www.ncbi.nlm.nih.gov/pubmed/26913278 http://dx.doi.org/10.3389/fpubh.2016.00009 |
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