Real-time estimation of disease activity in emerging outbreaks using internet search information.

ABSTRACT: Understanding the behavior of emerging disease outbreaks in, or ahead of, real-time could help healthcare officials better design interventions to mitigate impacts on affected populations. Most healthcare-based disease surveillance systems, however, have significant inherent reporting delays due to data collection, aggregation, and distribution processes. Recent work has shown that machine learning methods leveraging a combination of traditionally collected epidemiological information and novel Internet-based data sources, such as disease-related Internet search activity, can produce meaningful "nowcasts" of disease incidence ahead of healthcare-based estimates, with most successful case studies focusing on endemic and seasonal diseases such as influenza and dengue. Here, we apply similar

SUBMITTER: Aiken EL 

PROVIDER: S-EPMC7451983 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature