Predicting the next pandemic Data Science Stories

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Humanity’s data-driven line of defense against global pandemic threats

The world is connected on an unprecedented scale, and as a result the threat of global pandemics has increased exponentially. Traditionally, disease control efforts have reacted to outbreaks. These delayed response times are too slow for a global population that is always on the move. Pandemics such as HIV/AIDS and H1N1 spread from one region to the next at a speed inconceivable a century ago. Escalating the threat, viruses are becoming increasingly resistant to antibiotics, rendering traditional preventative measures ineffective. It’s a new world in need of a new approach to disease control.

Instead of reacting, Global Viral Forecasting (GVF) harnesses big data to prevent global pandemics before they start. In GVF’s view, “dramatic failures in such pandemic control, such as the ongoing lack of success in HIV vaccine development twenty-five years into the pandemic, have shown that the wait-and-respond approach is not sufficient.” Founded by world-renowned virologist Dr. Nathan Wolfe, GVF gathers its data from multiple sources, including viral discovery in the field, anthropological research in disease hotspots to identify how viruses cross from wildlife to humans, and tracking social media trends to predict and prevent outbreaks. The source of nearly 75% of all diseases are passed between animals and humans, cross-species transmission is believed to have caused HIV. Using a network of viral listening posts located in Cameroon, the Democratic Republic of Congo, Madagascar, China, Malaysia, Sierra Leone and Gabon, GVF aims to stop viruses before they pass from animal to human.

For GVF, both the physical and the digital worlds are the lab, creating large sets of data that enable real preventative measures. But there is always a need for more data to help predict and prevent the next global pandemic. In “Crunching Digital Data Can Help The World”, an opinion piece Wolfe wrote with Lucky Gunasekara and Zachary Bogue for CNN.com, they characterize big data as “a source and multiplier of social good. Big data can help us change our world for the better.”

Leveraging large sets of data from multiple sources – field work, research and trends on the open web – Wolfe and his team are able to make accurate and actionable predictions using engineering and software techniques that were nascent a decade ago, when Wolfe founded GVF. To improve the effectiveness of their predictions, GVF are constantly looking for new sources of relevant data. Moving forward, GVF aims to track purchases of over-the-counter medications and creating social interaction models from anonymous mobile phone data. As Wolfe notes, “the GVF team incessantly talks about needing more – they need big data. Data has power, but it is difficult to predict precise benefits without actually crunching the data.”

GVF’s efforts have borne real results. On the strength of its field work, GVF has tracked how viruses spread from bushmeat to human. They have identified a fifth form of human malaria, and studied how the disease originated. They have identified how disease control efforts failed in containing swine flu, and propose more proactive approaches to preventing and treating future outbreaks.

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