Nucleic acid-based assays, such as polymerase chain reaction (PCR), that amplify and detect organism-specific genome sequences are a standard method for infectious disease surveillance. However, challenges arise for virus surveillance because of their genetic diversity. Here, we calculated the variability of nucleotides within the genomes of 10 human viral species in silico and found that endemic viruses exhibit a high percentage of variable nucleotides (e.g., 51.4% for norovirus genogroup II). This genetic diversity led to the variable probability of detection of PCR assays (the proportion of viral sequences that contain the assay\'s target sequences divided by the total number of viral sequences). We then experimentally confirmed that the probability of the target sequence detection is indicative of the number of mismatches between PCR assays and norovirus genomes. Next, we developed a degenerate PCR assay that detects 97% of known norovirus genogroup II genome sequences and recognized norovirus in eight clinical samples. By contrast, previously developed assays with 31% and 16% probability of detection had 1.1 and 2.5 mismatches on average, respectively, which negatively impacted RNA quantification. In addition, the two PCR assays with a lower probability of detection also resulted in false negatives for wastewater-based epidemiology. Our findings suggest that the probability of detection serves as a simple metric for evaluating nucleic acid-based assays for genetically diverse virus surveillance.IMPORTANCENucleic acid-based assays, such as polymerase chain reaction (PCR), that amplify and detect organism-specific genome sequences are employed widely as a standard method for infectious disease surveillance. However, challenges arise for virus surveillance because of the rapid evolution and genetic variation of viruses. The study analyzed clinical and wastewater samples using multiple PCR assays and found significant performance variation among the PCR assays for genetically diverse norovirus surveillance. This finding suggests that some PCR assays may miss detecting certain virus strains, leading to a compromise in detection sensitivity. To address this issue, we propose a metric called the probability of detection, which can be simply calculated in silico using a code developed in this study, to evaluate nucleic acid-based assays for genetically diverse virus surveillance. This new approach can help improve the sensitivity and accuracy of virus detection, which is crucial for effective infectious disease surveillance and control.

A 59-year-old male with follicular lymphoma treated by anti-CD20-mediated B-cell depletion and ablative chemotherapy was hospitalized with a COVID-19 infection. Although the patient did not develop specific humoral immunity, he had a mild clinical course overall. The failure of all therapeutic options allowed infection to persist nearly 300 days with active accumulation of SARS-CoV-2 virus mutations. As a rescue therapy, an infusion of REGEN-COV (10933 and 10987) anti-spike monoclonal antibodies was performed 270 days from initial diagnosis. Due to partial clearance after the first dose (2.4 g), a consolidation dose (8 g) was infused six weeks later. Complete virus clearance could then be observed over the following month, after he was vaccinated with the Pfizer-BioNTech anti-COVID-19 vaccination. The successful management of this patient required prolonged enhanced quarantine, monitoring of virus mutations, pioneering clinical decisions based upon close consultation, and the coordination of multidisciplinary experts in virology, immunology, pharmacology, input from REGN, the FDA, the IRB, the health care team, the patient, and the patient\'s family. Current decisions to take revolve around patient\'s follicular lymphoma management, and monitoring for virus clearance persistence beyond disappearance of REGEN-COV monoclonal antibodies after anti-SARS-CoV-2 vaccination. Overall, specific guidelines for similar cases should be established.

One of the serious threats facing the administration of antiretroviral therapy to human immunodeficiency virus (HIV-1) infected patients is the reported increasing prevalence of transmitted drug resistance. However, given that HIV-1 drug-resistant strains are often less fit than the wild-type strains, it is expected that drug-resistant strains that are present during the primary phase of the HIV-1 infection are replaced by the fitter wild-type strains. This replacement of HIV-1 resistant mutations involves the emergence of wild-type strains by a process of backward mutation. How quickly the replacement happens is dependent on the class of HIV-1 mutation group. We estimate the backward mutation rates and relative fitness of various mutational groups known to confer HIV-1 drug resistance. We do this by fitting a stochastic model to data for individuals who were originally infected by an HIV-1 strain carrying any one of the known drug resistance-conferring mutations and observed over a period of time to see whether the resistant strain is replaced. To do this, we seek a distribution, generated from simulations of the stochastic model, that best describes the observed (clinical data) replacement times of a given mutation. We found that Lamivudine/Emtricitabine-associated mutations have a distinctly higher, backward mutation rate and low relative fitness compared to the other classes (as has been reported before) while protease inhibitors-associated mutations have a slower backward mutation rate and high relative fitness. For the other mutation classes, we found more uncertainty in their estimates.