AbstractIntroductionTraditional approaches to case-finding, case isolation, and contact tracing methods have so far proved insufficient on their own to prevent the development of local epidemics of COVID-19 in many high-income countries despite relatively advanced public health systems. As a result, many governments have resorted to widespread social distancing measures and mass quarantines (‘lock-downs’) to reduce transmission and to prevent healthcare systems from being overwhelmed. However, such measures impose heavy human and societal costs. Automated or semi-automated digital contact tracing, in conjunction with scaled-up community testing, has been proposed as a key part of exit strategies from lockdowns. However, the effectiveness of these approaches to contact tracing is unclear, and to be effective, trusted, and widely adopted such technology must overcome several challenges.Methods and analysisWe will perform a rapid systematic review to assess the effectiveness of automated and semi-automated digital tools for contact tracing, and identify key considerations for successful implementation, to inform the control of COVID-19. We will search PubMed, EMBASE, EBSCO Medical COVID information portal, OVID Global Health, Cochrane Library, medRxiv, BioRxiv, and arXiv for peer-reviewed and pre-print papers on automated or semi-automated digital tools for contact tracing of COVID-19, another respiratory disease with pandemic potential (limited to SARS, MERS, or pandemic influenza), or Ebola, in human populations. Studies will be eligible if published in English between 1 January 2000 and 14 April 2020. We will synthesise study findings narratively and will consider meta-analysis if ≥ 3 suitable studies with comparable interventions and outcomes are available.Ethics and disseminationEthical approval is not required for this review. We plan to disseminate findings via pre-print, journal publication, through social media and web-based platforms and through direct stakeholder engagement.
Better Normal, A Silver Lining in 2020: JAFES is Accepted for Indexing in PubMed Central