While recent work in disease forecasting has made significant
strides in accuracy, forecasting the future of an outbreak is still a
complex affair that is sharply limited in contexts with insufficient
data or insufficient understanding of the biological processes and
parameters underpinning the outbreak. In these contexts, a
simpler statistical approach based on leading indicators in internet
data streams may improve forecast availability, quality, and time
horizon. Prior evaluations of such approaches have yielded
conflicting results and to our knowledge have not been performed
at time granularity finer than one week