From chaos to coherence: Managing pandemics with data

For most of human history, when the world’s population was small and sparsely distributed, infectious diseases were lethal but local. Since then, rising populations and globalisation have turned viruses and bacteria into mass killers.

A century ago, the Spanish flu pandemic killed approximately 50m, recording more deaths than World War I. Although improved medicine and living conditions have cut infectious diseases more recently, the specter haunts us still; severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), Ebola, and lethal influenza like avian and swine flu have taken thousands of lives and caused billions of dollars of economic damage over the past two decades.

Quick and accurate data analytics that can pinpoint outbreaks and predict progression is key to fighting infectious diseases. Historical approaches, like investigator reports and hospital records, are reliable but slow and poor at prediction. There is, however, growing optimism that newer approaches, including mobile-phone tracking and data mining of search engines and social media, can help deliver a faster, more refined picture of where diseases are unfolding and might head to next.

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