| Summary: | Evidence from Sierra Leone reveals the significant limitations of big data in disease detection and containment efforts. Early in the 2014-2016 Ebola epidemic in West Africa, media heralded HealthMap's ability to detect the outbreak from newsfeeds. Later, big data-specifically, call detail record data collected from millions of cell phones-was hyped as useful for stopping the disease by tracking contagious people. It did not work. In this article, I trace the causes of big data's containment failures. During epidemics, big data experiments can have opportunity costs: namely, forestalling urgent response. Finally, what counts as data during epidemics must include that coming from anthropological technologies because they are so useful for detection and containment.
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