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The advent of the internet and digital data sources has transformed our ability to collect and report potential
health events. But still greater changes are in store. When ProMED-mail started in 1994, it required a satellite connection to reach most of the locations in Africa and Asia. Now, many of these same places have internet access, often broadband. Even more strikingly, many once remote locations in developing countries have mobile phone coverage, which continues to expand explosively. The International Telecommunication Union estimates that, while there were 2 billion internet users (more than half in developing countries), there were 5.3 billion mobile cellphone subscriptions in 2010, almost 75% in developing countries, with about 90% of the world now covered.43 Consequently, surveillance data or disease reports can now be sent from almost anywhere in the world, including field locations or centers that were once totally inaccessible, and the astute clinician no longer need be isolated.44,45 A number of pioneering efforts, such as Voxiva, had previously used cellphones to send health alerts.46 So many people now have mobile phones that reporting can be done by almost anyone on the spot. This has led to an interest in developing ‘‘participatory epidemiology.’’45 Communitybased reporting can be done by individuals who are not necessarily medical personnel but are trained to recognize events of interest, and there has been recent interest in selfreporting of disease symptoms either by cellphone or on the web, or through social media.26,45 The rise of social networking systems has the potential to play an increasingly important role in the future. The challenge will be in using these tools effectively. As with digital disease detection, this revolution in communications technology promises to break down many of the barriers to reporting, but at the risk of increasing the noise level and volume of raw data and the difficulty of verifying reports or establishing representativeness (if needed), much of which is best done by humans interpreting the data. However, there are unparalleled opportunities for detecting health events, whether a sick bushmeat hunter or a wildlife die-off seen by a game warden.
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