Information technological innovations seem to have played quite an important role in detecting early warnings of the current “new flu”, “swine flu” or H1N1. This topic is elaborated in today’s issue of New York Times. Apparently, WHO received the first warning already on April 10th through its web-crawler based monitoring system. This again proves the usefulness of mining unofficial data for monitoring.
One point missing in the debate however, is the fact that other emerging and re-emerging infectious diseases (EIDs) – such as avian influenza (H5N1), Ebola hemorrhagic fever, and West Nile viral encephalitis – emerge not only as the result of changes in host dynamics or in the pathogen. On the contrary, a range of underlying social- ecological changes such as land use change, deforestation and biodiversity loss seem to contribute to the rise of EIDs globally. Durell Kapan and colleagues article on the social-ecological dimensions of avian influenza is a nice synthesis of how land-use change contributes to increases in H5N1.
So, even if ICT innovations such as Google Flu or GPHIN provide the first signals of pending epidemic outbreaks, they are really not designed to capture changes in underlying social-ecological interactions that induce EIDs. For example, if you want to predict novel outbreaks of Hantavirus pulmonary syndrome (HPS) in Brazil, you might want to keep an eye on deforestation patterns and increases in sugarcane production. Or if you want to stay ahead of increasing risks of Ebola hemorrhagic fever outbreaks in Central West Africa, you might want to track coastal fish stock decrease in the region. These are known to increase “bush-meat” hunting and hence the risk of Ebola outbreaks.
The question is what to call such a system. If field epidemiologist Nathan Wolfe is doing early warning, maybe this approach should be called ecological “early-early warning”?