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Polyethylene glycol (PEG) precipitation is one of the conventional methods for virus concentration. This technique has been used to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in wastewater. The procedures and seeded surrogate viruses were different among implementers; thus, the reported whole process recovery efficiencies considerably varied among studies. The present study compared five PEG precipitation procedures, with different operational parameters, for the RT-qPCR-based whole process recovery of murine hepatitis virus (MHV), bacteriophage phi6, and pepper mild mottle virus (PMMoV), and molecular process recovery of murine norovirus using 34 raw wastewater samples collected in Japan. The five procedures yielded significantly different whole process recovery of MHV (0.070%–2.6%) and phi6 (0.078%–0.51%). The observed concentration of indigenous PMMoV ranged from 8.9 to 9.7 log (7.9 × 10 8 to 5.5 × 10 9 ) copies/L. Interestingly, PEG precipitation with 2-h incubation outperformed that with overnight incubation partially due to the difference in molecular process recovery efficiency. The recovery load of MHV exhibited a positive correlation ( r = 0.70) with that of PMMoV, suggesting that PMMoV is the potential indicator of the recovery efficiency of SARS-CoV-2. In addition, we reviewed 13 published studies and found considerable variability between different studies in the whole process recovery efficiency of enveloped viruses by PEG precipitation. This was due to the differences in operational parameters and surrogate viruses as well as the differences in wastewater quality and bias in the measurement of the seeded load of surrogate viruses, resulting from the use of different analytes and RNA extraction methods. Overall, the operational parameters (e.g., incubation time and pretreatment) should be optimized for PEG precipitation. Co-quantification of PMMoV may allow for the normalization of SARS-CoV-2 RNA concentration by correcting for the differences in whole process recovery efficiency and fecal load among samples.

Tuberculosis (TB) outbreak occurred in a boarding middle school of China. We explored its probable sources and quantified the transmissibility and pathogenicity of TB. Clinical evaluation, tuberculin skin testing and chest radiography were conducted to identify TB cases. Mycobacterium tuberculosis isolates underwent genotyping analysis to identify the outbreak source. A chain-binomial transmission model was used to evaluate transmissibility and pathogenicity of TB. A total of 46 active cases were ascertained among 258 students and 15 teachers/staff, an attack rate of 16.8%. Genetic analyses revealed two groups of M. tuberculosis cocirculating during the outbreak and possible importation from local communities. Secondary attack rates among students were 4.1% (2.9%, 5.3%) within grade and 7.9% (4.9%, 11%) within class. An active TB case was estimated to infect 8.4 (7.2, 9.6) susceptible people on average. The smear-positive cases were 28 (8, 101) times as infective as smear-negative cases. Previous BCG vaccination could reduce the probability of developing symptoms after infection by 70% (1.4%, 91%). The integration of clinical evaluation, genetic sequencing, and statistical modeling greatly enhanced our understanding of TB transmission dynamics. Timely diagnosis of smear-positive cases, especially in the early phase of the outbreak, is the key to preventing further spread among close contacts.

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Estimating and predicting the epidemic size from wastewater surveillance results remain challenging for the practical implementation of wastewater-based epidemiology (WBE). In this study, by employing a highly sensitive detection method, we documented the time series of SARS-CoV-2 RNA occurrence in wastewater influent from an urban community with a 360,000 population in Japan, from August 2020 to February 2021. The detection frequency of the viral RNA increased during the outbreak events of COVID-19 and the highest viral RNA concentration was recorded at the beginning of January 2021, amid the most serious outbreak event during the study period. We found that: (1) direct back-calculation still suffers from great uncertainty dominated by inconsistent detection and the varying gap between the observed wastewater viral load and the estimated patient viral load, and (2) the detection frequency correlated well with reported cases and the prediction of the latter can be carried out via data-driven modeling methods. Our results indicate that wastewater virus occurrence can contribute to epidemic surveillance in ways more than back-calculation, which may spawn future wastewater surveillance implementations.