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BACKGROUND: Children with SARS-CoV-2 infection typically have mild symptoms that do not require medical attention, leaving a gap in our understanding of the spectrum of illnesses that the virus causes in children. METHODS: We conducted a prospective cohort study of children and adolescents (<21 years of age) with a SARS-CoV-2-infected close contact. We collected nasopharyngeal or nasal swabs at enrollment and tested for SARS-CoV-2 using a real-time PCR assay. RESULTS: Of 382 children, 293 (77%) were SARS-CoV-2-infected. SARS-CoV-2-infected children were more likely to be Hispanic (p<0.0001), less likely to have asthma (p=0.005), and more likely to have an infected sibling contact (p=0.001) than uninfected children. Children ages 6-13 years were frequently asymptomatic (39%) and had respiratory symptoms less often than younger children (29% vs. 48%; p=0.01) or adolescents (29% vs. 60%; p<0.0001). Compared to children ages 6-13 years, adolescents more frequently reported influenza-like (61% vs. 39%; p<0.0001), gastrointestinal (27% vs. 9%; p=0.002), and sensory symptoms (42% vs. 9%; p<0.0001), and had more prolonged illnesses [median (IQR) duration: 7 (4, 12) vs. 4 (3, 8) days; p=0.01]. Despite the age-related variability in symptoms, we found no differences in nasopharyngeal viral load by age or between symptomatic and asymptomatic children. CONCLUSIONS: Hispanic ethnicity and an infected sibling close contact are associated with increased SARS-CoV-2 infection risk among children, while asthma is associated with decreased risk. Age-related differences in the clinical manifestations of SARS-CoV-2 infection must be considered when evaluating children for COVID-19 and in developing screening strategies for schools and childcare settings.

Organoids are self-organizing, expanding 3D cultures derived from stem cells. Using tissue derived from patients, these miniaturized models recapitulate various aspects of patient physiology and disease phenotypes, including genetic profiles and drug sensitivities. As such, patient-derived organoid (PDO) platforms provide an unprecedented opportunity for improving preclinical drug discovery, clinical trial validation, and, ultimately, patient care. Here, we review the evolution and scope of organoid technology, highlight recent encouraging results using PDOs as potential patient ''avatars'' to predict drug response and outcomes, and discuss critical parameters for widespread clinical adoption. These include improvements in assay speed, reproducibility, standardization, and automation, which are necessary to realize the translational potential of PDOs as clinical tools. The multiple entry points where PDOs may contribute valuable insights in drug discovery and lessen the risks associated with clinical trials are also discussed.