Faecal shedding of rotavirus vaccine in Chinese children after vaccination with Lanzhou lamb rotavirus vaccine li2018faecal
Prospective post-marketing study of faecal shedding after oral Lanzhou lamb rotavirus vaccine (LLR) in children in China (September–November 2011/2012). 114 children provided 1,184 stool samples collected for 15 days post-vaccination. Shedding was assessed by enzyme immunoassay (EIA, Oxoid Prospect ELISA kit, EIA positive threshold OD=0.21) and by real-time RT-PCR targeting the NSP3 gene (quantified by plasmid standard curve). Viral loads in PCR-positive samples ranged from <1.0×10^3 to 1.9×10^8 copies/g stool. Reference time for all measurements is days post-vaccination.
Analytes
stool_lanzhou_lamb_rotavirus_vaccine_EIA
Enzyme immunoassay (Oxoid Prospect ELISA Kit) detection of rotavirus antigen in stool. Positive threshold defined as OD >= 0.21 (positive control OD 2.5, negative control OD 0.1). Results reported qualitatively/semiquantitatively in table (e.g., + (weak positive), ++ (positive), +++ (strongpositive), ++++ (strong positive), N).
Measurements only — no shedding model is fitted to this analyte, usually because it is sampled once per participant, leaving no trajectory to fit, or because nothing was ever detected. Open triangles are non-detects, drawn at the assay's censoring limit. See the modelling methods for what these estimates do and do not support.
stool_lanzhou_lamb_rotavirus_vaccine_pcr
Real-time RT-PCR quantification of rotavirus (vaccine strain) in stool targeting the NSP3 gene. Quantified using serial dilutions of plasmid-derived NSP3 RNA standards and reported as copies per gram of stool.
Fitted by censored maximum likelihood. The red line is the median individual; the shaded region is the full range of a simulated cohort drawn from the fitted population, so it shows what simulating from this dataset would produce rather than a confidence interval, with dashed lines at the central 95%. Open triangles are non-detects, drawn at the censoring limit and entering the fit as "below this value" rather than being dropped. See the modelling methods for what these estimates do and do not support.