Keeping a step ahead of disease

Predictive models of disease propagation could help speed up and optimize emergency response operations to combat epidemic outbreaks. But in such delicate situations, the stakes are high, as misallocating resources can cost lives. To investigate the validity and the limits of different types of predictive models, researchers from ENAC and Politecnico di Milano (Italy) simulated the Haitian cholera epidemic that followed the devastating 2010 earthquake using variants of a predictive model developed specifically for that case. They published their results in the Journal of the Royal Society Interface.

The researchers studied six variants of a numerical model developed at ENAC’s Laboratory of Ecohydrology. The variants differed in their spatial resolution, in whether the disease could spread geographically from one region to another, and in the number of parameters that were used to model the dynamics of the disease within each region. The objective of their study was to evaluate which type of setup is best adapted to act as a decision-making tool to guide the response in the event of an epidemic.

While they found that with enough calibration data, five out of the six variants were able to reproduce the rough spatial and temporal dynamics of the outbreak, the results did differ in important details. Specifically, models that allowed the disease to spread from region to region did the best job at modeling the initial dynamics of the outbreak, while spatially disconnected models were more reliable at describing long-term dynamics. However, when the goal was to predict (rather than simply describe) the behavior of the epidemic following its initial propagation, spatially connected models were again found to be more reliable than the spatially disconnected models traditionally used in mathematical epidemiology.

The researchers concluded that predictive models do have a role to play in informing decision-makers. By further augmenting the models with real-time hydrological and ecological information and weather predictions, today’s primarily descriptive models could evolve into full-fledged decision-support systems and become an essential tool for the optimization of sanitary and humanitarian efforts.

Reference: 
Mari L, Bertuzzo E, Finger F, Casagrandi R, Gatto M, Rinaldo A. 2015 On the predictive ability of mechanistic models for the Haitian cholera epidemic. J. R. Soc. Interface 12: 20140840. http://dx.doi.org/10.1098/rsif.2014.0840

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