Using mobile phone data to predict the spatial spread of cholera

Abstract

Effective response to infectious disease epidemics requires focused control measures in areas predicted to be at high risk of new outbreaks. We aimed to test whether mobile operator data could predict the early spatial evolution of the 2010 Haiti cholera epidemic. Daily case data were analysed for 78 study areas from October 16 to December 16, 2010. Movements of 2.9 million anonymous mobile phone SIM cards were used to create a national mobility network. Two gravity models of population mobility were implemented for comparison. Both were optimized based on the complete retrospective epidemic data, available only after the end of the epidemic spread. Risk of an area experiencing an outbreak within seven days showed strong dose-response relationship with the mobile phone-based infectious pressure estimates. The mobile phone-based model performed better (AUC 0.79) than the retrospectively optimized gravity models (AUC 0.66 and 0.74, respectively). Infectious pressure at outbreak onset was significantly correlated with reported cholera cases during the first ten days of the epidemic (p < 0.05). Mobile operator data is a highly promising data source for improving preparedness and response efforts during cholera outbreaks. Findings may be particularly important for containment efforts of emerging infectious diseases, including high-mortality influenza strains.

Figure 1. Mobile phone mobility network.

The average absolute number of mobile phones moving between the study areas (October 15 to December 19, 2010). Thicker, bluer lines indicate larger number of travelers. The original outbreak location (Mirebelais), the Artibonite River (dark blue) and Port-au-Prince (PAP) are depicted (visualisation using Gephi and ArcGIS).

Figure 2

(a) Relationship between infectious pressure, calculated from the mobile phone data (P^phone), and the risk of areas experiencing a new outbreak within seven days. Ninety-five percent confidence intervals based on a binomial distribution are included. (b) ROC curve (sensitivity and specificity) for predicting outbreak occurrence within seven days at increasing thresholds of infectious pressure (red: P^phone, green: P^grav1, black: P^grav2). Random guesses would yield values along the diagonal line.

Figure 3. Correlation (r) between infectious pressure at outbreak onset and average daily number of reported cases during the first D days of the outbreak (one to ten days from onset).

Red: P^phone, solid green: P^grav1, black: P^grav2.