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Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors
Zoonotic diseases spread through pathogens-infected animal carriers. In the case of Ebola Virus Disease (EVD), evidence supports that the main carriers are fruit bats and non-human primates. Further, EVD spread is a multi-factorial problem that depends on sociodemographic and economic (SDE) factors....
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9436100/ https://www.ncbi.nlm.nih.gov/pubmed/36048780 http://dx.doi.org/10.1371/journal.pone.0271886 |
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author | Mursel, Sena Alter, Nathaniel Slavit, Lindsay Smith, Anna Bocchini, Paolo Buceta, Javier |
author_facet | Mursel, Sena Alter, Nathaniel Slavit, Lindsay Smith, Anna Bocchini, Paolo Buceta, Javier |
author_sort | Mursel, Sena |
collection | PubMed |
description | Zoonotic diseases spread through pathogens-infected animal carriers. In the case of Ebola Virus Disease (EVD), evidence supports that the main carriers are fruit bats and non-human primates. Further, EVD spread is a multi-factorial problem that depends on sociodemographic and economic (SDE) factors. Here we inquire into this phenomenon and aim at determining, quantitatively, the Ebola spillover infection exposure map and try to link it to SDE factors. To that end, we designed and conducted a survey in Sierra Leone and implement a pipeline to analyze data using regression and machine learning techniques. Our methodology is able (1) to identify the features that are best predictors of an individual’s tendency to partake in behaviors that can expose them to Ebola infection, (2) to develop a predictive model about the spillover risk statistics that can be calibrated for different regions and future times, and (3) to compute a spillover exposure map for Sierra Leone. Our results and conclusions are relevant to identify the regions in Sierra Leone at risk of EVD spillover and, consequently, to design and implement policies for an effective deployment of resources (e.g., drug supplies) and other preventative measures (e.g., educational campaigns). |
format | Online Article Text |
id | pubmed-9436100 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-94361002022-09-02 Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors Mursel, Sena Alter, Nathaniel Slavit, Lindsay Smith, Anna Bocchini, Paolo Buceta, Javier PLoS One Research Article Zoonotic diseases spread through pathogens-infected animal carriers. In the case of Ebola Virus Disease (EVD), evidence supports that the main carriers are fruit bats and non-human primates. Further, EVD spread is a multi-factorial problem that depends on sociodemographic and economic (SDE) factors. Here we inquire into this phenomenon and aim at determining, quantitatively, the Ebola spillover infection exposure map and try to link it to SDE factors. To that end, we designed and conducted a survey in Sierra Leone and implement a pipeline to analyze data using regression and machine learning techniques. Our methodology is able (1) to identify the features that are best predictors of an individual’s tendency to partake in behaviors that can expose them to Ebola infection, (2) to develop a predictive model about the spillover risk statistics that can be calibrated for different regions and future times, and (3) to compute a spillover exposure map for Sierra Leone. Our results and conclusions are relevant to identify the regions in Sierra Leone at risk of EVD spillover and, consequently, to design and implement policies for an effective deployment of resources (e.g., drug supplies) and other preventative measures (e.g., educational campaigns). Public Library of Science 2022-09-01 /pmc/articles/PMC9436100/ /pubmed/36048780 http://dx.doi.org/10.1371/journal.pone.0271886 Text en © 2022 Mursel et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://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 Mursel, Sena Alter, Nathaniel Slavit, Lindsay Smith, Anna Bocchini, Paolo Buceta, Javier Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors |
title | Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors |
title_full | Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors |
title_fullStr | Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors |
title_full_unstemmed | Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors |
title_short | Estimation of Ebola’s spillover infection exposure in Sierra Leone based on sociodemographic and economic factors |
title_sort | estimation of ebola’s spillover infection exposure in sierra leone based on sociodemographic and economic factors |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9436100/ https://www.ncbi.nlm.nih.gov/pubmed/36048780 http://dx.doi.org/10.1371/journal.pone.0271886 |
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