Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/27301
Title: Assessing the relationship between epidemic growth scaling and epidemic size: The 2014–16 Ebola epidemic in West Africa
Authors: GANYANI, Tapiwa 
Roosa, Kimberlyn
FAES, Christel 
HENS, Niel 
Chowell, Gerardo
Issue Date: 2018
Publisher: CAMBRIDGE UNIV PRESS
Source: EPIDEMIOLOGY AND INFECTION, 147, Art N° E27
Abstract: We assess the relationship between epidemic size and the scaling of epidemic growth of Ebola epidemics at the level of administrative areas during the 2014–16 Ebola epidemic in West Africa. For this purpose, we quantify growth scaling parameters from the ascending phase of Ebola outbreaks comprising at least 7 weeks of epidemic growth. We then study how these parameters are associated with observed epidemic sizes. For validation purposes, we also analyse two historic Ebola outbreaks. We find a high monotonic association between the scaling of epidemic growth parameter and the observed epidemic size. For example, scaling of growth parameters around 0.3–0.4, 0.4–0.6 and 0.6 are associated with epidemic sizes on the order of 350–460, 460–840 and 840–2500 cases, respectively. These results are not explained by differences in epidemic onset across affected areas. We also find the relationship between the scaling of epidemic growth parameter and the observed epidemic size to be consistent for two past Ebola outbreaks in Congo (1976) and Uganda (2000). Signature features of epidemic growth could become useful to assess the risk of observing a major epidemic outbreak, generate improved diseases forecasts and enhance the predictive power of epidemic models. Our results indicate that the epidemic growth scaling parameter is a useful indicator of epidemic size, which may have significant implications to guide control of Ebola outbreaks and possibly other infectious diseases.
Notes: Ganyani, T (reprint author), UHasselt Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, Diepenbeek, Belgium. tapiwa.ganyani@uhasselt.he
Keywords: Ebola epidemic; epidemic modeling; epidemic size; generalised growth model; sub-exponential growth
Document URI: http://hdl.handle.net/1942/27301
ISSN: 0950-2688
e-ISSN: 1469-4409
DOI: 10.1017/S0950268818002819
ISI #: 000455339100026
Category: A1
Type: Journal Contribution
Validations: ecoom 2020
Appears in Collections:Research publications

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