Cargando…
Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC
We describe two approaches to modeling data from a small to moderate-sized epidemic outbreak. The first approach is based on a branching process approximation and direct analysis of the transmission network, whereas the second one is based on a survival model derived from the classical SIR equations...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665115/ https://www.ncbi.nlm.nih.gov/pubmed/33192155 http://dx.doi.org/10.11145/j.biomath.2019.10.037 |
_version_ | 1783609955519037440 |
---|---|
author | Choi, Boseung Busch, Sydney Kazadi, Dieudonné Ilunga, Benoit Okitolonda, Emile Dai, Yi Lumpkin, Robert Saucedo, Omar KhudaBukhsh, Wasiur R. Tien, Joseph Yotebieng, Marcel Kenah, Eben Rempala, Grzegorz A. |
author_facet | Choi, Boseung Busch, Sydney Kazadi, Dieudonné Ilunga, Benoit Okitolonda, Emile Dai, Yi Lumpkin, Robert Saucedo, Omar KhudaBukhsh, Wasiur R. Tien, Joseph Yotebieng, Marcel Kenah, Eben Rempala, Grzegorz A. |
author_sort | Choi, Boseung |
collection | PubMed |
description | We describe two approaches to modeling data from a small to moderate-sized epidemic outbreak. The first approach is based on a branching process approximation and direct analysis of the transmission network, whereas the second one is based on a survival model derived from the classical SIR equations with no explicit transmission information. We compare these approaches using data from a 2012 outbreak of Ebola virus disease caused by Bundibugyo ebolavirus in city of Isiro, Democratic Republic of the Congo. The branching process model allows for a direct comparison of disease transmission across different environments, such as the general community or the Ebola treatment unit. However, the survival model appears to yield parameter estimates with more accuracy and better precision in some circumstances. |
format | Online Article Text |
id | pubmed-7665115 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76651152020-11-13 Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC Choi, Boseung Busch, Sydney Kazadi, Dieudonné Ilunga, Benoit Okitolonda, Emile Dai, Yi Lumpkin, Robert Saucedo, Omar KhudaBukhsh, Wasiur R. Tien, Joseph Yotebieng, Marcel Kenah, Eben Rempala, Grzegorz A. Biomath (Sofia) Article We describe two approaches to modeling data from a small to moderate-sized epidemic outbreak. The first approach is based on a branching process approximation and direct analysis of the transmission network, whereas the second one is based on a survival model derived from the classical SIR equations with no explicit transmission information. We compare these approaches using data from a 2012 outbreak of Ebola virus disease caused by Bundibugyo ebolavirus in city of Isiro, Democratic Republic of the Congo. The branching process model allows for a direct comparison of disease transmission across different environments, such as the general community or the Ebola treatment unit. However, the survival model appears to yield parameter estimates with more accuracy and better precision in some circumstances. 2019-10-15 2019 /pmc/articles/PMC7665115/ /pubmed/33192155 http://dx.doi.org/10.11145/j.biomath.2019.10.037 Text en This article is distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (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 | Article Choi, Boseung Busch, Sydney Kazadi, Dieudonné Ilunga, Benoit Okitolonda, Emile Dai, Yi Lumpkin, Robert Saucedo, Omar KhudaBukhsh, Wasiur R. Tien, Joseph Yotebieng, Marcel Kenah, Eben Rempala, Grzegorz A. Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC |
title | Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC |
title_full | Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC |
title_fullStr | Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC |
title_full_unstemmed | Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC |
title_short | Modeling outbreak data: Analysis of a 2012 Ebola virus disease epidemic in DRC |
title_sort | modeling outbreak data: analysis of a 2012 ebola virus disease epidemic in drc |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7665115/ https://www.ncbi.nlm.nih.gov/pubmed/33192155 http://dx.doi.org/10.11145/j.biomath.2019.10.037 |
work_keys_str_mv | AT choiboseung modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT buschsydney modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT kazadidieudonne modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT ilungabenoit modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT okitolondaemile modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT daiyi modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT lumpkinrobert modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT saucedoomar modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT khudabukhshwasiurr modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT tienjoseph modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT yotebiengmarcel modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT kenaheben modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc AT rempalagrzegorza modelingoutbreakdataanalysisofa2012ebolavirusdiseaseepidemicindrc |