Transactions of the International Conference on Health Information Technology Advancement

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The re-emergence of infectious diseases such as measles and polio is creating logistics challenges for the state authorities to curb their spread and contain them. (CL, 2015) Real-time surveillance of infectious diseases is important to detect possible epidemics in advance to prevent shortages of medications (FDA, 2018). The outbreak of an infectious disease creates panic in the community and is accompanied by a sudden increase in the online interest in knowing more about the disease and its symptoms. Prior studies have found a strong relationship between web-based information and disease outbreak but the influence of dynamics of web-based information in real-time is often not considered (Zhang, 2017). The dynamics or rate of change of the online interest in a disease can inform or misinform about perspective cases of the disease in a region. Oftentimes, especially in this connected world individuals overreact to the situation which may send spurious online signals regarding the disease progression. Hence, we study the relationship between the dynamics of online information and the infectious disease outbreak. We also investigate if this relationship could be influenced by regional demographic factors. We analyze weekly online interest dynamics for five infectious diseases over a period of three years across 50 states of the United States. We control for several factors (including weather, demographics, and travelers) and utilize hierarchical functional data models to incorporate real-time dynamics and clustering at the regional level. Preliminary findings suggest that online interest dynamics have a significant relationship with disease outbreak and the effect is segregated at the regional level. These findings are important to develop a system for real-time surveillance and account for the influence of heterogonous online interest during an endemic outbreak.