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Dynamics of Ebola epidemics in West Africa 2014
This paper investigates the dynamics of Ebola virus transmission in West Africa during 2014. The reproduction numbers for the total period of epidemic and for different consequent time intervals are estimated based on a simple linear model. It contains one major parameter - the average infectious pe...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000Research
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4722695/ https://www.ncbi.nlm.nih.gov/pubmed/26834975 http://dx.doi.org/10.12688/f1000research.5941.2 |
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author | Evans, Robin J. Mammadov, Musa |
author_facet | Evans, Robin J. Mammadov, Musa |
author_sort | Evans, Robin J. |
collection | PubMed |
description | This paper investigates the dynamics of Ebola virus transmission in West Africa during 2014. The reproduction numbers for the total period of epidemic and for different consequent time intervals are estimated based on a simple linear model. It contains one major parameter - the average infectious period that defines the dynamics of epidemics. Numerical implementations are carried out on data collected from three countries Guinea, Sierra Leone and Liberia as well as the total data collected worldwide. Predictions are provided by considering different scenarios involving the average times of infectiousness for the next few months and the end of the current epidemic is estimated according to each scenario. |
format | Online Article Text |
id | pubmed-4722695 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | F1000Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-47226952016-01-29 Dynamics of Ebola epidemics in West Africa 2014 Evans, Robin J. Mammadov, Musa F1000Res Research Note This paper investigates the dynamics of Ebola virus transmission in West Africa during 2014. The reproduction numbers for the total period of epidemic and for different consequent time intervals are estimated based on a simple linear model. It contains one major parameter - the average infectious period that defines the dynamics of epidemics. Numerical implementations are carried out on data collected from three countries Guinea, Sierra Leone and Liberia as well as the total data collected worldwide. Predictions are provided by considering different scenarios involving the average times of infectiousness for the next few months and the end of the current epidemic is estimated according to each scenario. F1000Research 2015-05-26 /pmc/articles/PMC4722695/ /pubmed/26834975 http://dx.doi.org/10.12688/f1000research.5941.2 Text en Copyright: © 2015 Evans RJ and Mammadov M http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Note Evans, Robin J. Mammadov, Musa Dynamics of Ebola epidemics in West Africa 2014 |
title | Dynamics of Ebola epidemics in West Africa 2014 |
title_full | Dynamics of Ebola epidemics in West Africa 2014 |
title_fullStr | Dynamics of Ebola epidemics in West Africa 2014 |
title_full_unstemmed | Dynamics of Ebola epidemics in West Africa 2014 |
title_short | Dynamics of Ebola epidemics in West Africa 2014 |
title_sort | dynamics of ebola epidemics in west africa 2014 |
topic | Research Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4722695/ https://www.ncbi.nlm.nih.gov/pubmed/26834975 http://dx.doi.org/10.12688/f1000research.5941.2 |
work_keys_str_mv | AT evansrobinj dynamicsofebolaepidemicsinwestafrica2014 AT mammadovmusa dynamicsofebolaepidemicsinwestafrica2014 |