Complexity of Government response to Covid-19 pandemic: A perspective of coupled dynamics on information heterogeneity and epidemic outbreak (preprint)

This study aims at modeling the universal failure in preventing the outbreak of COVID-19 via real-world data from the perspective of complexity and network science. Through formalizing information heterogeneity and government intervention in the coupled dynamics of epidemic and infodemic spreading; first, we find that information heterogeneity and its induced variation in human responses significantly increase the complexity of the government intervention decision. The complexity results in a dilemma between the socially optimal intervention that is risky for the government and the privately optimal intervention that is safer for the government but harmful to the social welfare. Second, via counterfactual analysis against the COVID-19 crisis in Wuhan, 2020, we find that the intervention dilemma becomes even worse if the initial decision time and the decision horizon vary. In the short horizon, both socially and privately optimal interventions agree with each other and require blocking the spread of all COVID-19-related information, leading to a negligible infection ratio 30 days after the initial reporting time. However, if the time horizon is prolonged to 180 days, only the privately optimal intervention requires information blocking, which would induce a catastrophically higher infection ratio than that in the counter-factual world where the socially optimal intervention encourages early-stage information spread. These findings contribute to the literature by revealing the complexity incurred by the coupled infodemic-epidemic dynamics and information heterogeneity to the governmental intervention decision, which also sheds insight into the design of an effective early warning system against the epidemic crisis in the future.

Dynamic characteristics of a COVID-19 outbreak in Nanjing, Jiangsu province, China

Objectives Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage B.1.617.2 (also named the Delta variant) was declared as a variant of concern by the World Health Organization (WHO). This study aimed to describe the outbreak that occurred in Nanjing city triggered by the Delta variant through the epidemiological parameters and to understand the evolving epidemiology of the Delta variant. Methods We collected the data of all COVID-19 cases during the outbreak from 20 July 2021 to 24 August 2021 and estimated the distribution of serial interval, basic and time-dependent reproduction numbers (R0 and Rt), and household secondary attack rate (SAR). We also analyzed the cycle threshold (Ct) values of infections. Results A total of 235 cases have been confirmed. The mean value of serial interval was estimated to be 4.79 days with the Weibull distribution. The R0 was 3.73 [95% confidence interval (CI), 2.66–5.15] as estimated by the exponential growth (EG) method. The Rt decreased from 4.36 on 20 July 2021 to below 1 on 1 August 2021 as estimated by the Bayesian approach. We estimated the household SAR as 27.35% (95% CI, 22.04–33.39%), and the median Ct value of open reading frame 1ab (ORF1ab) genes and nucleocapsid protein (N) genes as 25.25 [interquartile range (IQR), 20.53–29.50] and 23.85 (IQR, 18.70–28.70), respectively. Conclusions The Delta variant is more aggressive and transmissible than the original virus types, so continuous non-pharmaceutical interventions are still needed.

MAP3K19 regulatory variation in populations with African ancestry is associated with severe COVID-19 (preprint)

Ancestry impacts the likelihood of hospitalization due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV2). To identify ancestry-linked genetic risk variants associated with COVID-19 hospitalization, we performed an integrative analysis of two genome-wide association studies (GWASs) evaluating genetic variation among ancestrally diverse cohorts. We resolved four single nucleotide polymorphisms (SNPs) that are more frequent in COVID-19 hospitalized patients with non-European ancestry than the general population. Among them, the COVID-19 risk SNP rs16831827 shows the largest difference in allele frequency between African and European populations. The minor allele frequency of rs16831827*T was significantly higher in hospitalized COVID-19 patients with African ancestry. SNP rs16831827 also associates with COVID-19 hospitalization in an independent GWAS from the UK Biobank wherein both the hospitalized and control patients are entirely of African ancestry. rs16831827 is an expression quantitative trait locus (eQTL) of MAP3K19. Apart from rs16831827, two rare SNPs of MAP3K19, rs186150828 and rs192473276, were also significantly associated with COVID-19 hospitalization among African populations in the Regeneron COVID-19 hospitalization GWAS (p < 5x10-7). MAP3K19 expression is induced during ciliogenesis and most abundant in ciliated tissues including the lung and testis. Multiple COVID-19 related single-cell RNA sequencing data revealed that MAP3K19 is highly expressed in nasal multiciliated epithelial cells, nasopharyngeal ciliated cells, and airway ciliated cells. The COVID-19 hospitalization risk allele rs16831827*T is associated with reduced MAP3K19 expression. Hence, rs16831827 may increase the risk of severe COVID-19 by reducing baseline MAP3K19 expression.

Resilience Development in Multiple Shocks: Lessons in Mental Health and Well-Being Deterioration during COVID-19

Resilience describes individuals' and organizations' recovery from crises and adaptation to disturbances and adversities. Emerging research shows the deterioration of the population's mental health and well-being during the multiple waves of the COVID-19 pandemic, suggesting that the resilience developed is insufficient to address the system's persistent shocks. Drawing on the findings on mental health and well-being during the COVID-19 pandemic and the psychological and organizational resilience theories, we developed a system dynamics theory model exploring how the presence of multiple shocks to the system challenges the population's health and well-being. We initiated the model with three shocks with the same intensities and durations, and then experimented with scenarios in which the strength of multiple shocks (duration and intensity) was attenuated and amplified. The model showed that temporary environmental adjustments with limited long-term stabilized solutions and a lack of health service provision can increase the accumulative risks of health and well-being deterioration. We highlight the role of essential health service sectors' resilience and individuals' and organizations' tolerance of adversities and disturbances in providing sustainable resilience. We conclude by discussing critical factors in organizational and psychological resilience development in crises with multiple shocks to the system.

Genetic screening for hypertension and COVID-19 reveals functional variant of SPEG associated with severe COVID-19 in female (preprint)

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused more than 6.4 million deaths worldwide and is still spreading among global populations. The prevalent comorbidity between hypertension and severe COVID-19 suggests common genetic factors may affect the outcome of both diseases. As both hypertension and severe COVID-19 demonstrate sex-specific prevalence, common genetic factors among the two diseases may display gender-based differential associations. By evaluating COVID-19 association signals of 172-candidate hypertension single nucleotide polymorphisms derived from more than one million European individuals in two severe COVID-19 genome-wide association studies from UK BioBank with European ancestry, we revealed one functional cis expression quantitative trait locus of SPEG (rs12474050) associating with both hypertension and severe COVID-19 in female. The risk allele of rs12474050*T is correlated with lower SPEG expression in muscle-skeletal, heart-atrial appendage, and heart-left ventricle; among these tissues the SPEG expression is higher in female than in male COVID-19 patients. Further analysis revealed SPEG is mainly expressed in cardiomyocytes in heart and is upregulated upon SARS-CoV-2 infection, with significantly higher folder change of SPEG expression observed in female compared to male COVID-19 patients. Taken together, our analyses strongly suggest the involvement of SPEG in both hypertension and severe COVID-19 in female, which provides new insights for sex-specific effect of severe COVID-19 in female.

An Overview of System Strength Challenges in Australia’s National Electricity Market Grid

The national electricity market (NEM) of Australia is reforming via the rapid uptake of variable renewable energy (VRE) integration concurrent with the retirement of conventional synchronous generation. System strength has emerged as a prominent challenge and constraint to power system stability and ongoing grid connection of VRE such as solar and wind. In order to facilitate decarbonization pathways, Australia is the first country to evolve system strength and inertia frameworks and assessment methods to accommodate energy transition barriers, and other parts of the world are now beginning to follow the same approach. With the evolvement of the system strength framework as a new trending strategy to break the transition barriers raised by renewable energy project development and grid connection studies, this paper provides a high-level overview of system strength, covering such fundamental principles as its definition, attributes, and manifestations, as well as industry commentary, cutting-edge technologies and works currently underway for the delivery of a secure and reliable electricity system with the rapid integration of inverter-based resources (IBRs) in the NEM grid. The intent of this study is to provide a comprehensive reference on the engineering practices of the system strength challenge along with complementary technical, regulatory, and industry perspectives.

Changes of small non-coding RNAs by severe acute respiratory syndrome coronavirus 2 infection (preprint)

The ongoing pandemic of coronavirus disease 2019 (COVID-19), which results from the rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a significant global public health threat, with molecular mechanisms underlying its pathogenesis largely unknown. Small non-coding RNAs (sncRNAs) are known to play important roles in almost all biological processes. In the context of viral infections, sncRNAs have been shown to regulate the host responses, viral replication, and host-virus interaction. Compared with other subfamilies of sncRNAs, including microRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs), tRNA-derived RNA fragments (tRFs) are relatively new and emerge as a significant regulator of host-virus interactions. Using T4 PNK-RNA-seq, a modified next-generation sequencing (NGS), we recently found that nasopharyngeal swabs (NPS) samples from SARS-CoV-2 positive and negative subjects show a significant difference in sncRNA profiles. There are about 166 SARS-CoV-2-impacted sncRNAs. Among them, tRFs are the most significantly affected and almost all impacted tRFs are derived from the 5'-end of tRNAs (tRF5). Using a modified qRT-PCR, which was recently developed to specifically quantify tRF5s by isolating the tRF signals from its corresponding parent tRNA signals, we validated that tRF5s derived from tRNA GluCTC (tRF5-GluCTC), LysCTT (tRF5-LysCTT), ValCAC (tRF5-ValCAC), CysGCA (tRF5-CysGCA) and GlnCTG (tRF5-GlnCTG) are enhanced in NPS samples of SARS-CoV2 patients and SARS41 CoV2-infected airway epithelial cells. In addition to host-derived ncRNAs, we also identified several sncRNAs derived from the virus (svRNAs), among which a svRNA derived from CoV2 genomic site 346 to 382 (sv-CoV2-346) has the highest expression. The induction of both tRFs and sv-CoV2-346 has not been reported previously, as the lack of the 3'-OH ends of these sncRNAs prevents them to be detected by routine NGS. In summary, our studies demonstrated the involvement of tRFs in COVID-19 and revealed new CoV2 svRNAs.

Optimization of Multi-Blade Centrifugal Fan Blade Design for Ventilation and Air-Conditioning System Based on Disturbance CST Function

The multi-blade centrifugal fan is commonly used in modern building ventilation and air-conditioning system. However, it does not readily satisfy the increasing demand for energy saving, high efficiency or noise reduction. Its performance is inherently limited by the geometrical structure of single circular arc blades. Q35-type multi-blade centrifugal fan studied as an example by combining the disturbance CST function to parameterize the blades. The optimization parameter change range is confirmed, and test samples are extracted before establishing an RBF proxy model. The NSGA-II algorithm is incorporated, and multi-objective optimization is performed with flow rate and total pressure efficiency as optimization goals. The results show that the fan performance is effectively improved. At the design working point, the air volume of the multi-blade centrifugal fan increases by 1.4 m3/min;at the same time, the total pressure efficiency increases by 3.1%, and the noise is reduced by 1.12 dB, applying the proposed design. The obtained higher fan efficiency can effectively improve performance of the whole ventilation and air-conditioning system. This novel optimization method also has relatively few parameters, which makes it potentially valuable for designing multi-wing centrifugal and other types of fans, providing a new idea for energy saving and emission reduction design of fan.

The efficient use of radiation, water, and nitrogen uptake by low-nitrogen-tolerant broomcorn millet (Panicum miliaceum L.) increased grain yield in the Loess Plateau, China

• Low N input decreased broomcorn millet grain yield by poor resource use efficiency. • Low-N-tolerant cultivars performed better than low-N-sensitive cultivars at low N. • Low-N-tolerant cultivars had increased photosynthesis and dry matter transport. • Low-N-tolerant cultivars had high productivity under field conditions. The development of highly productive, low-N-tolerant cultivars is important to facilitate green and sustainable agriculture. However, it is unclear how low-N-tolerant cultivars achieve high grain yields under field conditions. In this study, the physiology facilitating the strong growth and efficient resource use of four low-N-tolerant Panicum miliaceum L. cultivars was compared with two low-N-sensitive cultivars using low and typical N fertilization applications (0, 75, and 150 kg N ha−1) on the semiarid Loess Plateau, China in 2019 and 2020. Compared to normal N fertilization, low N fertilization treatments significantly decreased plant photosynthetic capacity by regulating leaf stomatal closing, resulting in reduced dry matter accumulation and transportation, growth inhibition, weakened resource utilization, and consequently, a 28.9% decrease in grain yield. Compared to the low-N-sensitive cultivars, the low-N-tolerant cultivars had improved growth, leaf photosynthetic capacity, and dry matter transportation. These improved physiological characteristics resulted in more effective resource capture in the low-N-tolerant cultivars. This included higher and more efficient radiation use (24.4% and 26.9%), water use (63.5% and 48.2%), and N uptake (37.0% and 33.7%) in 2019 and 2020, respectively. Furthermore, the low-N-tolerant cultivars had increased productivity, with higher grain yields (38.6-41.6%) and harvest index values (16.7-28.2%) under low N conditions in the two years of the study. Overall, the results of this study determined the effect of low N input on broomcorn millet productivity and illustrated the strategies by which low-N-tolerant cultivars increased grain yield in semiarid field conditions. [Display omitted] [ABSTRACT FROM AUTHOR] Copyright of Agricultural & Forest Meteorology is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Exploring the effect of social media and spatial characteristics during the COVID-19 pandemic in China (preprint)

The declaration of COVID-19 as a pandemic has largely amplified the spread of related information on social media, such as Twitter, Facebook, and WeChat.Unlike the previous studies which focused on how to detect the misinformation or fake news related toCOVID-19, we investigate how the disease and information co-evolve in the population. We focus onCOVID-19and its information during the period when the disease was widely spread in China, i.e., from January 25th to March 24th, 2020. We first explore how the disease and information co-evolve via the spatial analysis of the two spreading processes. We visualize the geo-location of both disease and information at the province level and find that disease is more geo-localized compared to information. We find a high correlation between the disease and information data, and also people care about the spread only when it comes to their neighborhood. Regard to the content of the information, we find that positive messages are more negatively correlated with the disease compared to negative and neutral messages. Additionally, we introduce machine learning algorithms, i.e., linear regression and random forest, to further predict the number of infected using different disease spatial related and information-related characteristics. We obtain that the disease spatial related characteristics of nearby cities can help to improve the prediction accuracy. Meanwhile, information-related characteristics can also help to improve the prediction performance, but with a delay, i.e., the improvement comes from using, for instance, the number of messages 10 days ago, for disease prediction. The methodology proposed in this paper may shed light on new clues of emerging infections

SARS-CoV-2 envelope protein causes acute respiratory distress syndrome (ARDS)-like pathological damage and constitutes an antiviral target (preprint)

Cytokine storm and multi-organ failure are the main causes of SARS-CoV-2-related death. However, the origin of the virus excessively damaging abilities remains unknown. Here we show that the SARS-CoV-2 envelope (2-E) protein alone is sufficient to cause acute respiratory distress syndrome (ARDS)-like damage in vitro and in vivo. Overexpression of 2-E protein induced rapid pyroptosis-like cell death in various susceptible cells and robust secretion of cytokines and chemokines in macrophages. Intravenous administration of purified 2-E protein into mice caused ARDS-like pathological damage in lung and spleen. Overexpressed 2-E protein formed cation channels in host cell membranes, eventually leading to membrane rupture. Newly identified channel inhibitors exhibited potent anti-SARS-CoV-2 activity and excellent protective effects against the 2-E-induced damage both in vitro and in vivo. Importantly, their channel inhibition, cell protection and antiviral activities were positively correlated with each other, supporting 2-E is a promising drug target against SARS-CoV-2.

Characteristics of Recurrent Positive RT-PCR Findings of Recovered Patients From COVID-19 in Wuhan, China: A Retrospective study (preprint)

After two month of the outbreak of corona virus disease 2019 (COVID-19) in Wuhan China, tens of thousands hospitalized patients, being recovered, little was known about the follow-up of the recovered patients. 758 recovered patients, hospitalized in 17 hospitals previously and quarantined in 32 rehabilitation post stations in Wuhan, China, were retrospectively reviewed for clinical characters, reverse transcriptase- polymerase chain reaction (RT-PCR) from throat swab specimens and serological COVID-19 rapid diagnostic test (RDT) for SARS-Cov-2. Among them, 59 patients (7.78%) had recurrent positive findings for COVID-19 on RT-PCR from throat swabs. Among the 50 patients which was effective samples for antibody detection, 45/50 (90.00%) and 4/50 (8.00%) patients had positive of IgG or dual positive of IgG/IgM RDT for COVID-19, respectively. A certain number of quarantined patients with COVID-19 had recurrent RT-PCR results of SARS-Cov-2, the possibility of transmission in the patients needs further investigation.

Potential Factors for Prediction of Disease Severity of COVID-19 Patients (preprint)

ObjectiveCoronavirus disease 2019 (COVID-19) is an escalating global epidemic caused by SARS-CoV-2, with a high mortality in critical patients. Effective indicators for predicting disease severity in SARS-CoV-2 infected patients are urgently needed. MethodsIn this study, 43 COVID-19 patients admitted in Chongqing Public Health Medical Center were involved. Demographic data, clinical features, and laboratory examinations were obtained through electronic medical records. Peripheral blood specimens were collected from COVID-19 patients and examined for lymphocyte subsets and cytokine profiles by flow cytometry. Potential contributing factors for prediction of disease severity were further analyzed. ResultsA total of 43 COVID-19 patients were included in this study, including 29 mild patients and 14 sever patients. Severe patients were significantly older (61.9{+/-}9.4 vs 44.4{+/-}15.9) and had higher incidence in co-infection with bacteria compared to mild group (85.7%vs27.6%). Significantly more severe patients had the clinical symptoms of anhelation (78.6%) and asthma (71.4%). For laboratory examination, 57.1% severe cases showed significant reduction in lymphocyte count. The levels of Interluekin-6 (IL6), IL10, erythrocyte sedimentation rate (ESR) and D-Dimer (D-D) were significantly higher in severe patients than mild patients, while the level of albumin (ALB) was remarkably lower in severe patients. Further analysis demonstrated that ESR, D-D, age, ALB and IL6 were the major contributing factors for distinguishing severe patients from mild patients. Moreover, ESR was identified as the most powerful factor to predict disease progression of COVID-19 patients. ConclusionAge and the levels of ESR, D-D, ALB and IL6 are closely related to the disease severity of COVID-19 patients. ESR can be used as a valuable indicator for distinguishing severe COVID-19 patients in early stage, so as to increase the survival of severe patients.

COVID-19 Propagation Prediction and Assessment Method with Imported Cases and Infection Generations: Shanxi Province as a Case (preprint)

When everyone focuses on 2019 coronavirus disease (COVID-19) in Hubei province, the epidemic in other province cannot be ignored, which also has an impact on the epidemic in the whole country. The most distinctive epidemic characteristic in all regions except Wuhan is that the most of confirmed cases are imported cases from Wuhan, and the propagation chain is relatively clear. Based on detailed contact tracing information of confirmed cases, combined with first-order outbreak response measures, we establish a disease transmission dynamical model to describe the infection propagation chain among the human population. Using Shanxi province as a case, modeling results indicate that the epidemic peak in Shanxi province occurred in February 2. In addition, our model suggests that according to the current development trend, COVID-19 will disappear in February with the final epidemic number of approximately 175 cases. It is verified that the most effective outbreak control measures in Shanxi include home isolation of people, surveillance and isolation of second-generation cases, contact tracing and management of contacts. With the end of the holiday, if the average number of contacts per person per day is less than 6 , it has little impact on the incidence of COVID-19, and even if third- and fourth-generation cases occur, the epidemic will be under control, no later than late March with a finial outbreak size of 220 cases. However, if the average number of contacts per person per day is greater than 6, the number of COVID-19 cases will continue to be reported resulting in another epidemic peak. Through the forecast and evaluation of COVID-19 in Shanxi, it is verified that the model with infection generations is more accurate to describe the spread mode and can be extended to regions with imported cases.