Online respondent-driven detection for enhanced contact tracing of COVID-19

Abstract Background Contact tracing (CT) is a core intervention in the global COVID-19 response, but it laborious task for public health professionals (PHPs) who execute CT. In many countries, workload associated with CT of exceeded available resources Online respondent-driven detection (RDD) an innovative method case finding that can enhance efficiency, through active involvement index cases and contacts execution This accelerate decrease PHPs' workload. However, unclear if why (not) PHPs want to apply RDD what they need this purpose. Methods mixed methods study undertaken Netherlands Germany. We developed interview guide based on ‘reasoned action approach' elicit factors influence intention their needs. conducted 17 semi-structured interviews Dutch - will conduct 6-10 German involved COVID-19. Based interviews, online questionnaire validate qualitative findings larger population PHPs. Preliminary results believe facilitates autonomous participation and, conversely, less control anticipated could impact quality efficiency CT, delivery compliance measures. Several factors, e.g. CT-capacity skills willingness participate RDD, influenced expressed retain opportunities support maintain oversight over CT-process. Conclusions during ongoing pandemic future large scale outbreaks infectious diseases. order be properly applied, needs should addressed.