Quantifying Poverty as a Driver of Ebola Transmission.
BACKGROUND:Poverty has been implicated as a challenge in the control of the current Ebola outbreak in West Africa. Although disparities between affected countries have been appreciated, disparities within West African countries have not been investigated as drivers of Ebola transmission. To quantify...
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ftdoajarticles:oai:doaj.org/article:a1eb4429bdf844299cc8813907ac905d 2023-05-15T15:15:42+02:00 Quantifying Poverty as a Driver of Ebola Transmission. Mosoka P Fallah Laura A Skrip Shai Gertler Dan Yamin Alison P Galvani 2015-12-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0004260 https://doaj.org/article/a1eb4429bdf844299cc8813907ac905d EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC4697799?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0004260 https://doaj.org/article/a1eb4429bdf844299cc8813907ac905d PLoS Neglected Tropical Diseases, Vol 9, Iss 12, p e0004260 (2015) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2015 ftdoajarticles https://doi.org/10.1371/journal.pntd.0004260 2022-12-30T22:25:04Z BACKGROUND:Poverty has been implicated as a challenge in the control of the current Ebola outbreak in West Africa. Although disparities between affected countries have been appreciated, disparities within West African countries have not been investigated as drivers of Ebola transmission. To quantify the role that poverty plays in the transmission of Ebola, we analyzed heterogeneity of Ebola incidence and transmission factors among over 300 communities, categorized by socioeconomic status (SES), within Montserrado County, Liberia. METHODOLOGY/PRINCIPAL FINDINGS:We evaluated 4,437 Ebola cases reported between February 28, 2014 and December 1, 2014 for Montserrado County to determine SES-stratified temporal trends and drivers of Ebola transmission. A dataset including dates of symptom onset, hospitalization, and death, and specified community of residence was used to stratify cases into high, middle and low SES. Additionally, information about 9,129 contacts was provided for a subset of 1,585 traced individuals. To evaluate transmission within and across socioeconomic subpopulations, as well as over the trajectory of the outbreak, we analyzed these data with a time-dependent stochastic model. Cases in the most impoverished communities reported three more contacts on average than cases in high SES communities (p<0.001). Our transmission model shows that infected individuals from middle and low SES communities were associated with 1.5 (95% CI: 1.4-1.6) and 3.5 (95% CI: 3.1-3.9) times as many secondary cases as those from high SES communities, respectively. Furthermore, most of the spread of Ebola across Montserrado County originated from areas of lower SES. CONCLUSIONS/SIGNIFICANCE:Individuals from areas of poverty were associated with high rates of transmission and spread of Ebola to other regions. Thus, Ebola could most effectively be prevented or contained if disease interventions were targeted to areas of extreme poverty and funding was dedicated to development projects that meet basic needs. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 9 12 e0004260 |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
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English |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Mosoka P Fallah Laura A Skrip Shai Gertler Dan Yamin Alison P Galvani Quantifying Poverty as a Driver of Ebola Transmission. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
BACKGROUND:Poverty has been implicated as a challenge in the control of the current Ebola outbreak in West Africa. Although disparities between affected countries have been appreciated, disparities within West African countries have not been investigated as drivers of Ebola transmission. To quantify the role that poverty plays in the transmission of Ebola, we analyzed heterogeneity of Ebola incidence and transmission factors among over 300 communities, categorized by socioeconomic status (SES), within Montserrado County, Liberia. METHODOLOGY/PRINCIPAL FINDINGS:We evaluated 4,437 Ebola cases reported between February 28, 2014 and December 1, 2014 for Montserrado County to determine SES-stratified temporal trends and drivers of Ebola transmission. A dataset including dates of symptom onset, hospitalization, and death, and specified community of residence was used to stratify cases into high, middle and low SES. Additionally, information about 9,129 contacts was provided for a subset of 1,585 traced individuals. To evaluate transmission within and across socioeconomic subpopulations, as well as over the trajectory of the outbreak, we analyzed these data with a time-dependent stochastic model. Cases in the most impoverished communities reported three more contacts on average than cases in high SES communities (p<0.001). Our transmission model shows that infected individuals from middle and low SES communities were associated with 1.5 (95% CI: 1.4-1.6) and 3.5 (95% CI: 3.1-3.9) times as many secondary cases as those from high SES communities, respectively. Furthermore, most of the spread of Ebola across Montserrado County originated from areas of lower SES. CONCLUSIONS/SIGNIFICANCE:Individuals from areas of poverty were associated with high rates of transmission and spread of Ebola to other regions. Thus, Ebola could most effectively be prevented or contained if disease interventions were targeted to areas of extreme poverty and funding was dedicated to development projects that meet basic needs. |
format |
Article in Journal/Newspaper |
author |
Mosoka P Fallah Laura A Skrip Shai Gertler Dan Yamin Alison P Galvani |
author_facet |
Mosoka P Fallah Laura A Skrip Shai Gertler Dan Yamin Alison P Galvani |
author_sort |
Mosoka P Fallah |
title |
Quantifying Poverty as a Driver of Ebola Transmission. |
title_short |
Quantifying Poverty as a Driver of Ebola Transmission. |
title_full |
Quantifying Poverty as a Driver of Ebola Transmission. |
title_fullStr |
Quantifying Poverty as a Driver of Ebola Transmission. |
title_full_unstemmed |
Quantifying Poverty as a Driver of Ebola Transmission. |
title_sort |
quantifying poverty as a driver of ebola transmission. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2015 |
url |
https://doi.org/10.1371/journal.pntd.0004260 https://doaj.org/article/a1eb4429bdf844299cc8813907ac905d |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 9, Iss 12, p e0004260 (2015) |
op_relation |
http://europepmc.org/articles/PMC4697799?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0004260 https://doaj.org/article/a1eb4429bdf844299cc8813907ac905d |
op_doi |
https://doi.org/10.1371/journal.pntd.0004260 |
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PLOS Neglected Tropical Diseases |
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9 |
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12 |
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e0004260 |
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