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Assessing the relationship between epidemic growth scaling and epidemic size: The 2014–16 Ebola epidemic in West Africa
We assess the relationship between epidemic size and the scaling of epidemic growth of Ebola epidemics at the level of administrative areas during the 2014–16 Ebola epidemic in West Africa. For this purpose, we quantify growth scaling parameters from the ascending phase of Ebola outbreaks comprising...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518536/ https://www.ncbi.nlm.nih.gov/pubmed/30318028 http://dx.doi.org/10.1017/S0950268818002819 |
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author | Ganyani, Tapiwa Roosa, Kimberlyn Faes, Christel Hens, Niel Chowell, Gerardo |
author_facet | Ganyani, Tapiwa Roosa, Kimberlyn Faes, Christel Hens, Niel Chowell, Gerardo |
author_sort | Ganyani, Tapiwa |
collection | PubMed |
description | We assess the relationship between epidemic size and the scaling of epidemic growth of Ebola epidemics at the level of administrative areas during the 2014–16 Ebola epidemic in West Africa. For this purpose, we quantify growth scaling parameters from the ascending phase of Ebola outbreaks comprising at least 7 weeks of epidemic growth. We then study how these parameters are associated with observed epidemic sizes. For validation purposes, we also analyse two historic Ebola outbreaks. We find a high monotonic association between the scaling of epidemic growth parameter and the observed epidemic size. For example, scaling of growth parameters around 0.3–0.4, 0.4–0.6 and 0.6 are associated with epidemic sizes on the order of 350–460, 460–840 and 840–2500 cases, respectively. These results are not explained by differences in epidemic onset across affected areas. We also find the relationship between the scaling of epidemic growth parameter and the observed epidemic size to be consistent for two past Ebola outbreaks in Congo (1976) and Uganda (2000). Signature features of epidemic growth could become useful to assess the risk of observing a major epidemic outbreak, generate improved diseases forecasts and enhance the predictive power of epidemic models. Our results indicate that the epidemic growth scaling parameter is a useful indicator of epidemic size, which may have significant implications to guide control of Ebola outbreaks and possibly other infectious diseases. |
format | Online Article Text |
id | pubmed-6518536 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-65185362019-06-04 Assessing the relationship between epidemic growth scaling and epidemic size: The 2014–16 Ebola epidemic in West Africa Ganyani, Tapiwa Roosa, Kimberlyn Faes, Christel Hens, Niel Chowell, Gerardo Epidemiol Infect Original Paper We assess the relationship between epidemic size and the scaling of epidemic growth of Ebola epidemics at the level of administrative areas during the 2014–16 Ebola epidemic in West Africa. For this purpose, we quantify growth scaling parameters from the ascending phase of Ebola outbreaks comprising at least 7 weeks of epidemic growth. We then study how these parameters are associated with observed epidemic sizes. For validation purposes, we also analyse two historic Ebola outbreaks. We find a high monotonic association between the scaling of epidemic growth parameter and the observed epidemic size. For example, scaling of growth parameters around 0.3–0.4, 0.4–0.6 and 0.6 are associated with epidemic sizes on the order of 350–460, 460–840 and 840–2500 cases, respectively. These results are not explained by differences in epidemic onset across affected areas. We also find the relationship between the scaling of epidemic growth parameter and the observed epidemic size to be consistent for two past Ebola outbreaks in Congo (1976) and Uganda (2000). Signature features of epidemic growth could become useful to assess the risk of observing a major epidemic outbreak, generate improved diseases forecasts and enhance the predictive power of epidemic models. Our results indicate that the epidemic growth scaling parameter is a useful indicator of epidemic size, which may have significant implications to guide control of Ebola outbreaks and possibly other infectious diseases. Cambridge University Press 2018-10-15 /pmc/articles/PMC6518536/ /pubmed/30318028 http://dx.doi.org/10.1017/S0950268818002819 Text en © The Author(s) 2018 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Paper Ganyani, Tapiwa Roosa, Kimberlyn Faes, Christel Hens, Niel Chowell, Gerardo Assessing the relationship between epidemic growth scaling and epidemic size: The 2014–16 Ebola epidemic in West Africa |
title | Assessing the relationship between epidemic growth scaling and epidemic size: The 2014–16 Ebola epidemic in West Africa |
title_full | Assessing the relationship between epidemic growth scaling and epidemic size: The 2014–16 Ebola epidemic in West Africa |
title_fullStr | Assessing the relationship between epidemic growth scaling and epidemic size: The 2014–16 Ebola epidemic in West Africa |
title_full_unstemmed | Assessing the relationship between epidemic growth scaling and epidemic size: The 2014–16 Ebola epidemic in West Africa |
title_short | Assessing the relationship between epidemic growth scaling and epidemic size: The 2014–16 Ebola epidemic in West Africa |
title_sort | assessing the relationship between epidemic growth scaling and epidemic size: the 2014–16 ebola epidemic in west africa |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6518536/ https://www.ncbi.nlm.nih.gov/pubmed/30318028 http://dx.doi.org/10.1017/S0950268818002819 |
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