Diverse changes in shipping emissions around the Western Pacific ports under the coeffect of the epidemic and fuel oil policy.

The Western Pacific Ocean (the WPO), as one of the busiest shipping areas in the world, holds a complex water traffic network. In 2020, the International Maritime Organization (IMO) low-sulfur fuel regulations were implemented globally, while the COVID-19 outbreak influenced shipping activities together. This study aimed to assess the combined impact of epidemics and low-sulfur fuel policies on ship emissions, as well as their environmental effects on the WPO. The ship emission model based on the Automatic Identification System (AIS) data was applied to analyze the monthly emission variations during 2018-2020. It was found that the epidemic had obvious diverse influences on the coastal ports in the WPO. Overall, shipping emissions declined by 15 %-30 % in the first half of 2020 compared with those in 2019 due to the COVID-19 lockdown, whereas they rebounded in the second half as a result of trade recovery. The pollutants discharged per unit of cargo by ships rose after the large-range lockdown. China's multiphase domestic emission control areas (DECAs) and the IMO global low-sulfur fuel regulation have greatly reduced SO2 emissions from ships and caused them to "bypass and come back" to save fuel costs around emission control areas from 2018 to 2020. Based on satellite data and land-based measurements, it was found that the air quality over sea water and coastal cities has shown a positive response to changes in ship-emitted NOx and SO2. Our results reveal that changes in shipping emissions during typical periods, depending on their niches in the complex port traffic network, call for further efforts for cleaner fuel oils, optimized ECA and ship lane coordination in the future. Shipping related air pollutions during the later economic recovery also needs to be addressed after international scale standing-by events.

Machine learning based regional epidemic transmission risks precaution in digital society.

The contact and interaction of human is considered to be one of the important factors affecting the epidemic transmission, and it is critical to model the heterogeneity of individual activities in epidemiological risk assessment. In digital society, massive data makes it possible to implement this idea on large scale. Here, we use the mobile phone signaling to track the users' trajectories and construct contact network to describe the topology of daily contact between individuals dynamically. We show the spatiotemporal contact features of about 7.5 million mobile phone users during the outbreak of COVID-19 in Shanghai, China. Furthermore, the individual feature matrix extracted from contact network enables us to carry out the extreme event learning and predict the regional transmission risk, which can be further decomposed into the risk due to the inflow of people from epidemic hot zones and the risk due to people close contacts within the observing area. This method is much more flexible and adaptive, and can be taken as one of the epidemic precautions before the large-scale outbreak with high efficiency and low cost.

Hyperamylasemia Caused by the Hantaan Virus: A Retrospective Study of 101 Patients with Hemorrhagic Fever with Renal Syndrome in West China.

Background: Hyperamylasemia (HA) is an inconspicuous manifestation of hemorrhagic fever with renal syndrome (HFRS) in Baoji city, West China. Hantaan virus (HTNV) is the only pathogen-caused HFRS in this region, but the knowledge about HA in the local HFRS patients has been limited. The aim of this study was to investigate the characteristics of HA and its predictive risk factors for doctors to engage in timely monitoring and dealing with the possible serious changes prewarned by HA in the early stages of the disease to improve the final outcome. Methods: All HFRS patients with and without HA (HA and nHA groups, respectively) were treated in Baoji People's Hospital. The clinical characteristics between the two groups were compared by Student's t-test or Chi-square test. The risk factors for prognosis were measured by the logistic regression analysis. The predictive effects of prognosis in clinical and laboratory parameters were analyzed by the receiver operating characteristic curves. Results: 46.53% of the patients demonstrated HA, among which 71.7% were severe and critical types of HFRS, greater than that in the nHA group (19.57%, P < 0.001). The hospitalization day and the general incidence of acute pancreatitis (AP) were longer or greater in the HA group than in the nHA group (P < 0.01). Age and the time from the onset of the first symptom to the patient being admitted to hospital (T OA) were the predictive risk factors for HA. The best cut-off values were the age of 54 years and T OA of 5.5 days. Conclusion: HTNV-induced HA is a common clinical presentation of HFRS patients in West China. It can increase the severity, the hospitalization days of patients, and the incidence of AP in HFRS. Age and T OA constituted independent risk factors for HA caused by HTNV.