Digital contact tracing support tools: A framework for evaluating the added value of citizen support to effective and efficient contact tracing when making use of these tools (Preprint)

UNSTRUCTURED Contact tracing (CT) is considered one of the most essential strategies for containing the transmission of infectious diseases. The COVID-19 pandemic has revealed that with high infection rates, health services conducting CT can become overburdened, leading to limited or incomplete CT. Existing and future digital CT technologies may help to alleviate the burden on public health professionals (PHPs) and to mitigate the spread of the virus. Various digital contact tracing support tools (DCTS-tools) have been and are being designed to mimic the traditional CT process by facilitating the ability of index cases to collect contact details and notify their contacts themselves. Little is known about the potential effects of these types of tools on CT. Besides saving time for health services, transferring the tasks of CT into the hands of citizens may lead to the recollection of more contacts, more contact details, and speed up the contact notification process. The aim of this paper is to provide a framework that contributes to the comprehensive assessment of DCTS-tools. This framework can provide guidance for other researchers and policymakers in designing their own evaluation studies and in determining the extent to which DCTS-tools should be implemented as part of the CT strategy to contain future infectious disease outbreaks. This framework, based on expert opinions and scientific literature, contains research questions and study designs covering the evaluation of various important aspects of CT, including its speed, comprehensiveness, effectiveness with regard to contact notification, positive case detection, potential workload reduction of PHPs, its demographic adoption and reach, and the user experiences of PHPs, index cases and contacts.