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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/24875

Title: Real-time parameter estimation of Zika outbreaks using model averaging
Authors: Sebrango-Rodriguez, C. R.
Martinez-Bello, D. A.
Sanchez-Valdes, L.
Thilakarathne, P. J.
Del Fava, E.
Van Der Stuyft, P.
Lopez-Quilez, A.
Shkedy, Ziv
Issue Date: 2017
Citation: EPIDEMIOLOGY AND INFECTION, 145(11), p. 2313-2323
Abstract: Early prediction of the final size of any epidemic and in particular for Zika disease outbreaks can be useful for health authorities in order to plan the response to the outbreak. The Richards model is often been used to estimate epidemiological parameters for arboviral diseases based on the reported cumulative cases in single-and multi-wave outbreaks. However, other non-linear models can also fit the data as well. Typically, one follows the so called post selection estimation procedure, i.e., selects the best fitting model out of the set of candidate models and ignores the model uncertainty in both estimation and inference since these procedures are based on a single model. In this paper we focus on the estimation of the final size and the turning point of the epidemic and conduct a real-time prediction for the final size of the outbreak using several nonlinear models in which these parameters are estimated via model averaging. The proposed method is applied to Zika outbreak data in four cities from Colombia, during the outbreak ocurred in 2015-2016.
Notes: [Sebrango-Rodriguez, C. R.; Sanchez-Valdes, L.] Univ Sancti Spiritus Jose Marti Perez, Ave Martires 360, Sancti Spiritus, Cuba. [Sebrango-Rodriguez, C. R.; Shkedy, Z.] Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat I BioSt, Agoralaan,Bldg D, B-3590 Diepenbeek, Belgium. [Martinez-Bello, D. A.; Lopez-Quilez, A.] Univ Valencia, Fac Math, Dept Stat & Operat Res, C Dr Moliner 50, E-46100 Valencia, Spain. [Sanchez-Valdes, L.] Ctr Inmunol Mol, Calle 16 Esq 15 Atabey, Havana, Cuba. [Thilakarathne, P. J.] Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat, Kapucijnenvoer 35,Blok D,Box 7001, B-3000 Leuven, Belgium. [Del Fava, E.] Bocconi Univ, Carlo F Dondena Ctr Res Social Dynam, Via Guglielmo Rontgen 1, I-20136 Milan, Italy. [Van Der Stuyft, P.] Inst Trop Med, Unit Gen Epidemiol & Dis Control, Antwerp, Belgium. [Van Der Stuyft, P.] Univ Ghent, Dept Publ Hlth, Ghent, Belgium.
URI: http://hdl.handle.net/1942/24875
DOI: 10.1017/S0950268817001078
ISI #: 000409124100016
ISSN: 0950-2688
Category: A1
Type: Journal Contribution
Validation: ecoom, 2018
Appears in Collections: Research publications

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