Web-Based Apps for Responding to Acute Infectious Disease Outbreaks in the Community: Systematic Review (Preprint)

Abstract

BACKGROUND Background: Web-based technology has dramatically improved our ability to detect communicable disease outbreaks, with the potential to reduce morbidity and mortality due to swift public health action. Applications accessible through the internet and on mobile devices create an opportunity to enhance our traditional indicator-based surveillance systems, which have high specificity but issues with timeliness. OBJECTIVE Objective: We sought to describe the literature on web-based apps for indicator-based surveillance and response to acute communicable disease outbreaks in the community, in regards to their design, implementation and evaluation. METHODS We conducted a systematic search of the published literature across four databases (Medline via OVID, via OVID, Web of Science Core Collection, ProQuest Science and Google Scholar) for peer-reviewed journal articles from January 1998 to October 2019 using a keyword search. Articles with full text available were extracted for review, and exclusion criteria applied to identify eligible articles. RESULTS From 6649 retrieved articles, a total of 23 remained, describing 15 web-apps. Apps were primarily designed to improve the early detection of disease outbreaks, targeted government settings, and comprised complex algorithmic and/or statistical outbreak detection mechanisms. We identified a need for these apps to have more features to support secure information exchange and outbreak response actions, with a focus on outbreak verification processes and staff and resources to support app operations. Evaluation studies (6/15 apps) were mostly cross-sectional with some evidence of reduction to time to notification of outbreak, but studies were lacking user-based needs assessments and evaluation of implementation. CONCLUSIONS Public health officials designing new or improving existing disease outbreak web apps should ensure that outbreak detection is automatic and signals are verified by users, the app is easy to use, and that staff and resources are available to support the operations of the app, as well as conduct rigorous and holistic evaluations. CLINICALTRIAL N/A