Journal
JOURNAL OF THE ROYAL SOCIETY INTERFACE
Volume 12, Issue 104, Pages -Publisher
ROYAL SOC
DOI: 10.1098/rsif.2014.0840
Keywords
multilayer network model; spatially explicit model; ecohydrology; epidemic forecast; model calibration; model validation
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Funding
- European Research Council (ERC) advanced grant program through the project 'River networks as ecological corridors for species, populations and waterborne disease' [RINEC 227612]
- Swiss National Science Foundation (SNF/FNS) project 'Dynamics and controls of large-scale cholera outbreaks' [DYCHO CR23I2_138104]
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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.
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