Abstract: More than 300,000 mammalian virus species are estimated to cause infectious disease in humans. They inhabit a wide range of human tissues, including the lungs, blood, and brain, and often remain undetected. Efficient and accurate detection of viral infection is vital to understand its impact on human health, and to make accurate predictions to limit negative effects, including the prevention of future pandemics. The increasing use of high-throughput sequencing methods in research, agriculture, and healthcare provides an opportunity for the cost-effective surveillance of viral diversity and investigation of virus-disease correlation. However, there are no existing workflows for accurate real-time detection of viral infection from sequencing data at single-cell resolution. We introduce a method that accurately and rapidly detects viral sequences in bulk and single-cell transcriptomics data, enabling the detection of ongoing infection by RNA viruses covering up to 10^(12) virus species.