Governments, institutions, and citizens of nearly every nation have been compelled to respond to COVID-19. Many measures have been adopted, including contact tracing and risk assessment, whereby citizen whereabouts are constantly monitored to trace contact with other infectious individuals and isolate contagious parties via algorithmic evaluation of their risk status. This paper investigates how citizens make sense of Health Code (jiankangma), the contact tracing and risk assessment algorithm in China. We probe how people accept or resist the algorithm by examining their ongoing, dynamic, and relational interactions with it over time. By seeking a deeper, iterative understanding of how individuals accept or resist the algorithm, our data unearths three key sites of concern. First, how understandings of algorithmic surveillance shape and are shaped by notions of privacy, including fatalism towards the possibility of true privacy in China and a trade-off narrative between privacy and twin imperatives of public and economic health. Second, how trust in the algorithm is mediated by the perceived competency of the technology, the veracity of input data, and well-publicized failures in both data collection and analysis. Third, how the implementation of Health Code in social life alters beliefs about the algorithm, such as its further role after COVID-19 passes, or contradictory and disorganized enforcement measures upon risk assessment. Chinese citizens make sense of Health Code in a relational fashion, whereby users respond very differently to the same sociotechnical assemblage based upon social and individual factors.