[Clinical characteristics of 16 neonates infected with SARS-CoV-2 during Omicron variant outbreak].

Objective: To analyze the clinical characteristics of the neonates infected with SARS-CoV-2 during the Omicron outbreak in Shanghai 2022. Methods: In this retrospective case series study, all the 16 neonates with SARS-CoV-2 Omicron infection who were admitted to the neonatal unit in Shanghai Public Health Clinical Center from March 1st to May 31st, 2022 were enrolled. Their epidemiological history, clinical manifestations, nucleic acid cycle threshold (Ct) value and outcomes were analyzed. Based on maternal vaccination, they were divided into vaccinated group and unvaccinated group. Rank sum test and Chi-square test were used for the comparison between the groups. Results: Among the 16 neonates, 10 were male, and 6 were female. All the infants were full-term. The infection was confirmed at the age of 12.5 (8.0, 20.5) days. All the neonates had a history of exposure to infected family members, and thus horizontal transmission was the primary mode. Four infants were asymptomatic, 12 were symptomatic, and there were no severe or critical cases. The most common clinical manifestation was fever (11 cases), with the highest temperature of 38.1 (37.9, 38.3) ℃ and a course of 1-5 days. Other clinical manifestations included nasal obstruction (3 cases), runny nose (2 cases), cough (2 cases), poor feeding (2 cases), vomiting (1 case), and mild tachypnea (1 case). The complete blood counts of all neonates were within the normal range, and the C-reactive protein increased slightly in 1 infant. Chest imaging was performed in 2 infants, showing mild focal exudative changes. Nucleic acid turned negative (Ct value ≥35) within 7-15 days after diagnosis. All neonates fully recovered after supportive treatment, and the length of hospitalization was 13 (10, 14) days. In the telephone follow-up 2 weeks after discharge for all 16 cases, no infant showed reoccurrence of clinical manifestations or nucleic acid reactivation. Maternal vaccination was not significantly correlated with symptomatic infection or the persistence of positive nucleic acid result in neonates (all P>0.05). Conclusions: Horizontal transmission is the primary mode for neonatal SARS-CoV-2 Omicron infection. Neonatal infections are usually mild or asymptomatic, with good short-term outcomes. And their clinical manifestations and laboratory examinations are nonspecific.

[Characteristics of SARS-CoV-2 Omicron infection in children imported from Hong Kong].

Objective: To understand the clinical characteristics of children with SARS-CoV-2 Omicron infection imported from Hong Kong Special Administrative Region. Methods: This retrospective study was conducted to collect the data including clinical manifestations, outcomes and vaccination of 107 children with SARS-CoV-2 Omicron infection imported from Hong Kong Special Administrative Region to be admitted to the designated referral hospital in Shanghai from February to March 2022. According to the occurrence of clinical symptoms, the cases were divided into asymptomatic group and symptomatic group. According to the age of diagnosis, the cases were divided into <3 years group, 3-<6 years group and 6-<18 years group, and the clinical manifestations in different age group were analyzed with t-test and Mann-Whitney rank-sum test. Besides, to analyze the effectiveness of vaccination against SARS-CoV-2 Omicron infection in different age group, the cases aged 3-<18 years were also subdivided into unvaccinated group, 1-dose group and 2-dose group, and the relative risk (RR) was used to demonstrate the effectiveness. Results: Among the 107 cases, 66 were male and 41 were female, with infection age of 10 (5, 14) years. There were 29 cases in the asymptomatic group, and 78 cases in the symptomatic group, and no significant difference in the age of infection was observed between the 2 groups (11 (6, 14) vs. 10 (5, 14) years, Z=0.49, P>0.05). And there were no severe cases in symptomatic group. The length of hospitalization was (18±6) days, and was longer in symptomatic group than that in asymptomatic group ((19±6) vs. (16±7) d, t=0.17, P=0.030). Eight-two cases (76.6%) had a history of epidemiological exposure and, among whom, 81 cases (75.7%) were associated with household transmission. Among symptomatic group, 57 cases (73.1%) had fever and 20 cases (25.6%) had cough. Of the 74 cases undergoing chest CT examination, 17 cases (23.0%) showed mild abnormalities. Of the 83 cases who received the lab tests, 23 cases (27.7%) had white blood cell counts<4×109/L, 3 cases (3.6%) had C-reaction protein >8.0 mg/L, and 6 cases (7.2%) had slightly elevated aspartate transaminase and alanine aminotransferase. Among the 92 children aged 3-<18 years, 31 cases were unvaccinated, 34 cases received 1 dose, and 27 cases received 2 doses. The interval between the last vaccination and infection was 2.2 (0.6, 6.0) months; the interval between the last vaccination and infection in the 2-dose group was longer than that in 1-dose group (6.0 (4.5, 7.3) vs. 0.7 (0.3,2.0) months, Z=3.59, P<0.001).The risk of symptomatic infection was reduced by 45% (RR=0.55, 95% CI 0.35-0.87) with two-dose vaccination compared to non-vaccination in cases aged 3-<18 years. All these cases recovered completely. Conclusions: Children infected with SARS-CoV-2 Omicron are usually mild or asymptomatic. Household transmission is the main pattern of infection with SARS-CoV-2 Omicron in children. Two-dose SARS-CoV-2 vaccination in children aged 3-<18 years can provide partial protection against disease caused by SARS-CoV-2 Omicron.

The effects of regularisation on RNN models for Covid-19 time series forecasting

Many time series forecasting models applied to the COVID-19 pandemic data have been limited to the amount of locations that they operate on. To improve the efficiency of a model it is desirable to have one model produce outputs for as many different locations as possible. Another drawback of previous models is that most operate on large amounts of data. However, during the initial states of the spread of the disease, before the epidemic became a pandemic, there was not enough data for the models therefore the proposed model not only has to produce forecasts for multiple locations at once, but they must also be accurate based on small amounts of data. This work proposes a multi-output recurrent neural network capable of producing forecasts for 187 different locations even when trained on only 28 days of time series data for each location. Regularisation methods were used to reduce the noise in the model during training. Applying regularisers helped the model better generalise its predictions for the multiple locations the results show that the model using the Long-Short Term Memory network combined with 20% Dropout performed, on average, 3% better than its baseline without the regularisers the improvement was measured using the Root Mean Squared Error. Previously proposed models were not capable of producing forecasts on a global scale without training multiple versions of the same model. This work proposes one model capable of making predictions on a global scale after only the first four weeks of the epidemic. © 2021 IEEE.

Uncertainty, GVC participation and the export of Chinese firms

Increasing uncertainty has hindered the development of international trade in recent years. Participating in the global value chain (GVC) has become one way for Chinese export firms to deal with uncertainty and reduce external risks. Based on trade theory with heterogeneous firms, this study constructs a theoretical framework encompassing uncertainty and GVC participation. We find that uncertainty inhibits the export of firms, but GVC participation can alleviate the negative impact of uncertainty, which is verified through empirical analysis. Additionally, mechanism analysis reveals that GVC participation plays a moderating role through product diversity, market diversity, cost-saving effects, and quality-improving effects. This study demonstrates that in the absence of serious adverse events, GVC is highly efficient. Accordingly, China should actively participate in the governance of the COVID-19 pandemic, reduce the external uncertainty faced by Chinese export firms, promote the return of an efficient GVC, and further ameliorate the negative impact of uncertainty.

A risk assessment model of WSMC projects under emergencies

As a novel market-based water-saving mechanism, the Water Saving Management Contract (WSMC) project faces interruption risk caused by emergencies like the coronavirus disease-2019 (COVID-19) pandemic. An interruption risk assessment model of WSMC projects is established through a quantitative evaluation of the impact of emergencies on water users based on input-output theory. First, the concept of the interruption risk index (IRI) is defined as a function of the duration of enterprise shutdown (DES). Second, the DES is divided into two parts: the duration caused by COVID-19 and the that under other types of emergencies. Third, the risk tolerance threshold is given to estimate the interruption result, and its different consequences are discussed. Finally, a WSMC project in China is taken as a case study, and its interruption risks are analysed. The results show that the IRIs of this WSMC in both 2020 and 2021 are theoretically greater than the risk tolerance thresholds, and the high pandemic prevention standards and conservative pandemic estimates are the main reasons for the above results. The model established in this study provides a reference for WSMC participants to deal with emergencies and provides the theoretical support for the extension of the WSMC.

Robotics and Artificial Intelligence Applications in Manage and Control of COVID-19 Pandemic

Robotics and Artificial Intelligence (A.I.), applications have played an essential role in managing and controlling COVID-19 pandemic specifically in hospitals, hotels, restaurants, airports, transportation systems, schools, and others community levels. Artificial intelligence technologies, autonomous vehicles, drones, mobile robots, humanoid robots, manipulator robots and other intelligent robots are used potentially during the outbreak to control the transmission network from person to person. Due to the highly uses, we consider A.I. and robotics in health will likely continue after the COVID-19 pandemic and development of these technologies is needed for fighting against infectious diseases. Furthermore, the uses of these systems in different fields like industry, sports, ergonomics, distribution of goods, and social life will keep going in the coming years. In this article, the artificial intelligent devices and robots helped in fighting, and managing covid19 are explored, including the new trends. These new trends are led by artificial intelligence, autonomous driving, network communication, cooperative work, nanorobotics, friendly human-robot interfaces, safe human-robot interaction, and emotion expression and perception. Furthermore, these news trends are applied to different fields such as medicine, health care, sports, ergonomics, industry, distribution of goods, and service robot. These tendencies will keep going their evolution in the coming years.

[Clinical analysis of liver chemistries in children and adolescent with 2019-nCoV infection].

Objective: To describe the clinical features of liver involvement in children and adolescent with 2019-nCoV infection. Methods: The clinical data of 77 hospitalized cases admitted to the Children's Hospital of Fudan University were collected from January 19 to November 28, 2020. The characteristics and risk factors of abnormal liver chemistries in children with laboratory-confirmed 2019-nCoV infection were analyzed. Results: Of the 77 cases, 44 were male (57.1%) and 33 were female (42.9%), with a median age of 10 years. 27(35.1%) were asymptomatic, 28(36.4%) had mild illness, 22(28.6%)had non-severe pneumonia. Hydroxychloroquine was used in 7 cases. Of the 75 children without underlying diseases, alanine aminotransferase was elevated in 1 case (1.5%, during hydroxychloroquine therapy), aspartate aminotransferase was elevated in 7 cases (10.3%), alkaline phosphatase was elevated in 7 cases (28%), and total bilirubin, direct bilirubin, albumin, international normalized ratio were in normal range. There was no statistical difference between the pneumonia group and the non-pneumonia group in term of liver chemistries (P > 0.05), same as between the elevated erythrocyte sedimentation rate group and the normal group. There was no aggravation of liver injury in the child with biliary atresia. The child with epilepsy showed no abnormal liver chemistries after infection. Conclusion: Children with 2019-nCoV infection had mild clinical symptoms with few cases of liver injury. The abnormal liver chemistries in children with COVID-19 infection may be related to the underlying disease and the use of antiviral drugs.