Multi-population stochastic modeling of Ebola in Sierra Leone: Investigation of spatial heterogeneity.
A major outbreak of the Ebola virus occurred in 2014 in Sierra Leone. We investigate the spatial heterogeneity of the outbreak among districts in Sierra Leone. The stochastic discrete-time susceptible-exposed-infectious-removed (SEIR) model is used, allowing for probabilistic movements from one comp...
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doaj-3275a668d438409eaa2bb59245b39fe22021-05-29T04:31:59ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01165e025076510.1371/journal.pone.0250765Multi-population stochastic modeling of Ebola in Sierra Leone: Investigation of spatial heterogeneity.Rachid MuleiaMarc AertsChristel FaesA major outbreak of the Ebola virus occurred in 2014 in Sierra Leone. We investigate the spatial heterogeneity of the outbreak among districts in Sierra Leone. The stochastic discrete-time susceptible-exposed-infectious-removed (SEIR) model is used, allowing for probabilistic movements from one compartment to another. Our model accounts for heterogeneity among districts by making use of a hierarchical approach. The transmission rates are considered time-varying. It is investigated whether or not incubation period, infectious period and transmission rates are different among districts. Estimation is done using the Bayesian formalism. The posterior estimates of the effective reproductive number were substantially different across the districts, with pronounced variability in districts with few cases of Ebola. The posterior estimates of the reproductive number at the district level varied between below 1.0 and 4.5, whereas at nationwide level it varied between below 1.0 and 2.5. The posterior estimate of the effective reproductive number reached a value below 1.0 around December. In some districts, the effective reproductive number pointed out for the persistence of the outbreak or for a likely resurgence of new cases of Ebola virus disease (EVD). The posterior estimates have shown to be highly sensitive to prior elicitation, mainly the incubation period and infectious period.https://doi.org/10.1371/journal.pone.0250765 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rachid Muleia Marc Aerts Christel Faes |
spellingShingle |
Rachid Muleia Marc Aerts Christel Faes Multi-population stochastic modeling of Ebola in Sierra Leone: Investigation of spatial heterogeneity. PLoS ONE |
author_facet |
Rachid Muleia Marc Aerts Christel Faes |
author_sort |
Rachid Muleia |
title |
Multi-population stochastic modeling of Ebola in Sierra Leone: Investigation of spatial heterogeneity. |
title_short |
Multi-population stochastic modeling of Ebola in Sierra Leone: Investigation of spatial heterogeneity. |
title_full |
Multi-population stochastic modeling of Ebola in Sierra Leone: Investigation of spatial heterogeneity. |
title_fullStr |
Multi-population stochastic modeling of Ebola in Sierra Leone: Investigation of spatial heterogeneity. |
title_full_unstemmed |
Multi-population stochastic modeling of Ebola in Sierra Leone: Investigation of spatial heterogeneity. |
title_sort |
multi-population stochastic modeling of ebola in sierra leone: investigation of spatial heterogeneity. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2021-01-01 |
description |
A major outbreak of the Ebola virus occurred in 2014 in Sierra Leone. We investigate the spatial heterogeneity of the outbreak among districts in Sierra Leone. The stochastic discrete-time susceptible-exposed-infectious-removed (SEIR) model is used, allowing for probabilistic movements from one compartment to another. Our model accounts for heterogeneity among districts by making use of a hierarchical approach. The transmission rates are considered time-varying. It is investigated whether or not incubation period, infectious period and transmission rates are different among districts. Estimation is done using the Bayesian formalism. The posterior estimates of the effective reproductive number were substantially different across the districts, with pronounced variability in districts with few cases of Ebola. The posterior estimates of the reproductive number at the district level varied between below 1.0 and 4.5, whereas at nationwide level it varied between below 1.0 and 2.5. The posterior estimate of the effective reproductive number reached a value below 1.0 around December. In some districts, the effective reproductive number pointed out for the persistence of the outbreak or for a likely resurgence of new cases of Ebola virus disease (EVD). The posterior estimates have shown to be highly sensitive to prior elicitation, mainly the incubation period and infectious period. |
url |
https://doi.org/10.1371/journal.pone.0250765 |
work_keys_str_mv |
AT rachidmuleia multipopulationstochasticmodelingofebolainsierraleoneinvestigationofspatialheterogeneity AT marcaerts multipopulationstochasticmodelingofebolainsierraleoneinvestigationofspatialheterogeneity AT christelfaes multipopulationstochasticmodelingofebolainsierraleoneinvestigationofspatialheterogeneity |
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