Vulnerability analysis of the global liner shipping network: from static structure to cascading failure dynamics

Robust maritime transportation networks are essential to the development of world economy. But vulnerability of the global liner shipping network (GLSN) to unexpected interruptions has become apparent since the COVID-19 pandemic began, in that a single port interruption could be sufficient to trigger a cascading failure (i.e., port congestion propagation). To understand the vulnerability of the GLSN under such cascading failures, we propose a novel cascading model, which incorporates the realistic factor of liner shipping service routes’ behavior of port rotation adjustments under port failures. We apply the model to an empirical GLSN, showing that the GLSN under cascading failures is significantly more vulnerable than its static structure. Regarding two common adjustments of service routes’ port rotations (i.e., skipping failed ports and choosing alternative ports), we find that choosing alternative ports increases the GLSN vulnerability to cascading failures. Within the proposed model, we also introduce a metric termed port dynamic criticality to characterize the contribution of each port to the overall network robustness against cascading failures, finding it significantly and positively associated with port’s topological centrality in the initial GLSN. These findings provide managerial insights into preventing or mitigating port congestion propagation in the GLSN.

COVID-19 case prediction via wastewater surveillance in a low-prevalence urban community: a modeling approach.

Estimating and predicting the epidemic size from wastewater surveillance results remains 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 the 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.

Comparison of five polyethylene glycol precipitation procedures for the RT-qPCR based recovery of murine hepatitis virus, bacteriophage phi6, and pepper mild mottle virus as a surrogate for SARS-CoV-2 from wastewater.

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 efficiency of murine hepatitis virus (MHV), bacteriophage phi6, and pepper mild mottle virus (PMMoV), and molecular process recovery efficiency of murine norovirus using 34 raw wastewater samples collected in Japan. The five procedures yielded significantly different whole process recovery efficiency of MHV (0.070%-2.6%) and phi6 (0.071%-0.51%). The observed concentration of indigenous PMMoV ranged from 8.9 to 9.7 log (8.2 × 108 to 5.6 × 109) 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.

SCOPE enables type III CRISPR-Cas diagnostics using flexible targeting and stringent CARF ribonuclease activation.

Characteristic properties of type III CRISPR-Cas systems include recognition of target RNA and the subsequent induction of a multifaceted immune response. This involves sequence-specific cleavage of the target RNA and production of cyclic oligoadenylate (cOA) molecules. Here we report that an exposed seed region at the 3' end of the crRNA is essential for target RNA binding and cleavage, whereas cOA production requires base pairing at the 5' end of the crRNA. Moreover, we uncover that the variation in the size and composition of type III complexes within a single host results in variable seed regions. This may prevent escape by invading genetic elements, while controlling cOA production tightly to prevent unnecessary damage to the host. Lastly, we use these findings to develop a new diagnostic tool, SCOPE, for the specific detection of SARS-CoV-2 from human nasal swab samples, revealing sensitivities in the atto-molar range.

Early warning of COVID-19 via wastewater-based epidemiology: potential and bottlenecks.

An effective early warning tool is of great administrative and social significance to the containment and control of an epidemic. Facing the unprecedented global public health crisis caused by COVID-19, wastewater-based epidemiology (WBE) has been given high expectations as a promising surveillance complement to clinical testing which had been plagued by limited capacity and turnaround time. In particular, recent studies have highlighted the role WBE may play in being a part of the early warning system. In this study, we briefly discussed the basics of the concept, the benefits and critical points of such an application, the challenges faced by the scientific community, the progress made so far, and what awaits to be addressed by future studies to make the concept work. We identified that the shedding dynamics of infected individuals, especially in the form of a mathematical shedding model, and the back-calculation of the number of active shedders from observed viral load are the major bottlenecks of WBE application in the COVID-19 pandemic that deserve more attention, and the sampling strategy (location, timing, and interval) needs to be optimized to fit the purpose and scope of the WBE project.

Mortality in chronic kidney disease patients with COVID-19: a systematic review and meta-analysis.

At the beginning of 2020, the outbreak of coronavirus disease 2019 (COVID-19) led to a worldwide pandemic and mass panic. The number of infected people has been increasing exponentially since, and the mortality rate has also been concomitantly increasing. At present, no study has summarized the mortality risk of COVID-19 in patients with chronic kidney disease (CKD). Therefore, the aim of the present study was to conduct a literature review and meta-analysis to understand the frequency of mortality among CKD patients infected with COVID-19. A comprehensive systematic search was conducted on the PubMed, Embase, and Cochrane databases to find articles published until May 15, 2020. Study quality was assessed using a modified version of the Newcastle-Ottawa Scale. After careful screening based on the inclusion and exclusion criteria, 3,867,367 patients from 12 studies were included. The mortality rate was significantly higher among CKD patients with COVID-19 infection than among CKD patients without COVID-19 infection, as indicated by a pooled OR of 5.81 (95% CI 3.78-8.94, P < 0.00001, I2 = 30%). The patients were then stratified into ≥ 70 and < 70 years, and subgroup analysis revealed that among CKD patients with COVID-19 infection, the mortality rate was higher in the < 70 years group (OR 8.69, 95% CI 7.56-9.97, P < 0.0001) than in the ≥ 70 years group (OR 2.44, 95% CI 0.75-6.63, P = 0.15). Thus, COVID-19 patients with CKD have a high mortality risk and require a comprehensive multidisciplinary management strategy.

On a Statistical Transmission Model in Analysis of the Early Phase of COVID-19 Outbreak

Since December 2019, a disease caused by a novel strain of coronavirus (COVID-19) had infected many people and the cumulative confirmed cases have reached almost 180,000 as of 17, March 2020. The COVID-19 outbreak was believed to have emerged from a seafood market in Wuhan, a metropolis city of more than 11 million population in Hubei province, China. We introduced a statistical disease transmission model using case symptom onset data to estimate the transmissibility of the early-phase outbreak in China, and provided sensitivity analyses with various assumptions of disease natural history of the COVID-19. We fitted the transmission model to several publicly available sources of the outbreak data until 11, February 2020, and estimated lock down intervention efficacy of Wuhan city. The estimated $$R_0$$ was between 2.7 and 4.2 from plausible distribution assumptions of the incubation period and relative infectivity over the infectious period. 95% confidence interval of $$R_0$$ were also reported. Potential issues such as data quality concerns and comparison of different modelling approaches were discussed.