Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/77581
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dc.contributorDepartment of Applied Mathematics-
dc.creatorZhao, S-
dc.creatorStone, L-
dc.creatorGao, D-
dc.creatorHe, D-
dc.date.accessioned2018-08-28T01:33:22Z-
dc.date.available2018-08-28T01:33:22Z-
dc.identifier.issn1935-2727en_US
dc.identifier.urihttp://hdl.handle.net/10397/77581-
dc.language.isoenen_US
dc.publisherPublic Library of Scienceen_US
dc.rights© 2018 Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en_US
dc.rightsThe following publication: Zhao S, Stone L, Gao D, He D (2018) Modelling the large-scale yellow fever outbreak in Luanda, Angola, and the impact of vaccination. PLoS Negl Trop Dis 12(1): e0006158 is available at https://doi.org/10.1371/journal.pntd.0006158en_US
dc.titleModelling the large-scale yellow fever outbreak in Luanda, Angola, and the impact of vaccinationen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume12en_US
dc.identifier.issue1en_US
dc.identifier.doi10.1371/journal.pntd.0006158en_US
dcterms.abstractBackground: Yellow fever (YF), transmitted via bites of infected mosquitoes, is a life-threatening viral disease endemic to tropical and subtropical regions of Africa and South America. YF has largely been controlled by widespread national vaccination campaigns. Nevertheless, between December 2015 and August 2016, YF resurged in Angola, quickly spread and becoming the largest YF outbreak for the last 30 years. Recently, YF resurged again in Brazil (December 2016). Thus, there is an urgent need to gain better understanding of the transmission pattern of YF.-
dcterms.abstractModel: The present study provides a refined mathematical model, combined with modern likelihood-based statistical inference techniques, to assess and reconstruct important epidemiological processes underlying Angola’s YF outbreak. This includes the outbreak’s attack rate, the reproduction number (R0), the role of the mosquito vector, the influence of climatic factors and the unusual but noticeable appearance of two-waves in the YF outbreak. The model explores actual and hypothetical vaccination strategies, and the impacts of possible human reactive behaviors (e.g., response to media precautions).-
dcterms.abstractFindings: While there were 73 deaths reported over the study period, the model indicates that the vaccination campaign saved 5.1-fold more people from death and saved from illness 5.6-fold of the observed 941 cases. Delaying the availability of the vaccines further would have greatly worsened the epidemic in terms of increased case numbers and mortality. The analysis estimated a mean R0 ͌ 2:6-3:4 and an estimated YF attack rate of 0.09-0.15% (proportion of population infected by YFV) over the whole period from December 2015 to August 2016. Our estimated lower and upper bounds of R0 are in line with previous studies. Unusually, R0 oscillated in a manner that was “delayed” with the reported deaths. High recent number of deaths were associated (followed) with periods of relatively low disease transmission and low R0, and vice-versa. The time-series of Luanda’s YF cases suggest the outbreak occurred in two waves, a feature that would have become far more prominent had there been no mass vaccination. The waves could possibly be due to protective reactive behavioral changes of the population affecting the mosquito population. The second wave could well be an outcome of the March-April rainfall patterns in the 2016 El Niño year by creating ideal conditions for the breeding of the mosquito vectors. The modelling framework is a powerful tool for studying future YF epidemic outbreaks, and provides a basis for future vaccination campaign evaluations.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationPLoS neglected tropical diseases, 2018, v. 12, no. 1, e0006158-
dcterms.isPartOfPLoS neglected tropical diseases-
dcterms.issued2018-
dc.identifier.isiWOS:000424022700029-
dc.identifier.scopus2-s2.0-85041561747-
dc.identifier.eissn1935-2735en_US
dc.identifier.artne0006158en_US
dc.identifier.rosgroupid2017002175-
dc.description.ros2017-2018 > Academic research: refereed > Publication in refereed journal-
dc.description.validate201808 bcrcen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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