A global pandemic of the 2019 coronavirus disease (COVID-19), caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is responsible for over 150,000 deaths worldwide, including >12,000 deaths in New York City (NYC) alone. Given the rapid emergence of this pathogen, little is known about its genetic variation, immune system interactions, population prevalence, and environmental distribution. As a result, there is a pressing clinical and public health need for scalable molecular technologies that can rapidly detect SARS-CoV-2 infection and robustly interrogate strain evolution and host response in patients. To address these challenges, we designed a loop-mediated isothermal amplification (LAMP) assay to identify SARS-CoV-2 infection within 30 minutes of application, including directly from lysed cells. Simultaneously, we developed a large-scale host and viral transcriptomic profiling platform that employs total RNA sequencing (RNA-seq) of nasopharyngeal swab specimens. Applying both technologies to 442 samples, spanning 338 clinical samples tested for SARS-CoV-2, 86 environmental samples from the NYC subway, and 14 controls, we assembled a broad molecular picture of the COVID-19 epidemic in NYC. We found close concordance between viral titers measured with our rapid LAMP assay, RNA-seq, and the state-of-the-art RT-PCR. Full transcriptomic analyses revealed a distinct subset of the Western European clade A2a as the predominant genomic subtype in NYC cases, which was defined by two single nucleotide variants in nsp2 and ORF 3a and a clade-specific, 9-bp in-frame deletion in the virulence factor nsp1. High SARS-CoV2 viral titers were associated with distinct host transcriptional responses, including activation of the ACE2 gene and interferon response genes (e.g., IFIT1). Since ACE inhibitors (ACEIs) can also increase ACE2 expression, outcomes for patients taking ACEIs were examined, and showed a significantly increased risk of intubation and death. Our results demonstrate the utility of two molecular diagnostic platforms in defining the genetic features of an evolving global pandemic and provide insights that can aid future COVID-19 diagnostics, public health monitoring, and therapeutic options.