title: On the predictive ability of mechanistic models for the Haitian cholera epidemic.
abstract: Predictive models of epidemic cholera need to resolve at suitable aggregation levels spatial data pertaining to local communities, epidemiological records, hydrologic drivers, waterways, patterns of human mobility and proxies of exposure rates. We address the above issue in a formal model comparison framework and provide a quantitative assessment of the explanatory and predictive abilities of various model settings with different spatial aggregation levels and coupling mechanisms. Reference is made to records of the recent Haiti cholera epidemics. Our intensive computations and objective model comparisons show that spatially explicit models accounting for spatial connections have better explanatory power than spatially disconnected ones for short-to-intermediate calibration windows, while parsimonious, spatially disconnected models perform better with long training sets. On average, spatially connected models show better predictive ability than disconnected ones. We suggest limits and validity of the various approaches and discuss the pathway towards the development of case-specific predictive tools in the context of emergency management.
authors: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy Laboratory of Ecohydrology ECHO/IIE/ENAC, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland lorenzo.mari@polimi.it.
authors: Lorenzo
authors: L
authors: Mari
authors: Laboratory of Ecohydrology ECHO/IIE/ENAC, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
authors: Enrico
authors: E
authors: Bertuzzo
authors: Laboratory of Ecohydrology ECHO/IIE/ENAC, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
authors: Flavio
authors: F
authors: Finger
authors: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy.
authors: Renato
authors: R
authors: Casagrandi
authors: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Milano, Italy.
authors: Marino
authors: M
authors: Gatto
authors: Laboratory of Ecohydrology ECHO/IIE/ENAC, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland Dipartimento di Ingegneria Civile, Edile ed Ambientale, Università di Padova, 35131 Padova, Italy.
authors: Andrea
authors: A
authors: Rinaldo
mesh_terms: D000465:Algorithms; D002138:Calibration; D002771:Cholera / Q000453:epidemiology*; D004189:Disaster Planning; D058872:Epidemics; D005843:Geography; D006205:Haiti; D006801:Humans; D015233:Models, Statistical; D009010:Monte Carlo Method; D016011:Normal Distribution; D011237:Predictive Value of Tests; D011634:Public Health
keywords: ecohydrology; epidemic forecast; model calibration; model validation; multilayer network model; spatially explicit model
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