Improving Contact Tracing by Prioritizing Influential Spreaders Identified Through Socio-Demographic Characteristics

Abstract

To mitigate the spread of contagious diseases, there is an ongoing discussion surrounding interventions that strategically target individuals who, due to their social network position, are responsible for more infections than others. However, the practical identification of these individuals using conventional network metrics is considerably challenging due to the lack of required data. A potential remedy to this quandary is the development of easily observable proxy metrics for measuring influential spreading. This study aims to assess the viability of such an approach using the example of contact tracing. Utilizing an empirically calibrated agent-based model, the study investigates the extent to which the efficacy of contact tracing can be enhanced by prioritizing influential spreaders, identified using age and household size as proxy measures. The results reveal that the effectiveness of contact tracing is significantly influenced by whose contacts are traced. When the contacts of those causing the most infections are traced, it can substantially enhance the efficacy of contact tracing, even when they are identified solely based on proxy metrics such as age and household size. For the examined case of the German state of Baden-Württemberg, it appears that middle-aged individuals residing in larger households are responsible for most infections. Therefore, prioritizing contact tracing for this specific demographic group seems to be a robust strategy to improve contact tracing. Overall, the results support the potential of the proposed approach to reduce the overall societal costs of non-pharmaceutical interventions while increasing their impact. Further empirical testing of the approach appears worthwhile.