Global age-structured spatial modeling for emerging infectious diseases like COVID-19.

Modeling the global dynamics of emerging infectious diseases (EIDs) like COVID-19 can provide important guidance in the preparation and mitigation of pandemic threats. While age-structured transmission models are widely used to simulate the evolution of EIDs, most of these studies focus on the analysis of specific countries and fail to characterize the spatial spread of EIDs across the world. Here, we developed a global pandemic simulator that integrates age-structured disease transmission models across 3,157 cities and explored its usage under several scenarios. We found that without mitigations, EIDs like COVID-19 are highly likely to cause profound global impacts. For pandemics seeded in most cities, the impacts are equally severe by the end of the first year. The result highlights the urgent need for strengthening global infectious disease monitoring capacity to provide early warnings of future outbreaks. Additionally, we found that the global mitigation efforts could be easily hampered if developed countries or countries near the seed origin take no control. The result indicates that successful pandemic mitigations require collective efforts across countries. The role of developed countries is vitally important as their passive responses may significantly impact other countries.

McAN: a novel computational algorithm and platform for constructing and visualizing haplotype networks.

Haplotype networks are graphs used to represent evolutionary relationships between a set of taxa and are characterized by intuitiveness in analyzing genealogical relationships of closely related genomes. We here propose a novel algorithm termed McAN that considers mutation spectrum history (mutations in ancestry haplotype should be contained in descendant haplotype), node size (corresponding to sample count for a given node) and sampling time when constructing haplotype network. We show that McAN is two orders of magnitude faster than state-of-the-art algorithms without losing accuracy, making it suitable for analysis of a large number of sequences. Based on our algorithm, we developed an online web server and offline tool for haplotype network construction, community lineage determination, and interactive network visualization. We demonstrate that McAN is highly suitable for analyzing and visualizing massive genomic data and is helpful to enhance the understanding of genome evolution. Availability: Source code is written in C/C++ and available at https://github.com/Theory-Lun/McAN and https://ngdc.cncb.ac.cn/biocode/tools/BT007301 under the MIT license. Web server is available at https://ngdc.cncb.ac.cn/bit/hapnet/. SARS-CoV-2 dataset are available at https://ngdc.cncb.ac.cn/ncov/. Contact: songshh@big.ac.cn (Song S), zhaowm@big.ac.cn (Zhao W), baoym@big.ac.cn (Bao Y), zhangzhang@big.ac.cn (Zhang Z), ybxue@big.ac.cn (Xue Y).

A novel gene signature based on the hub genes of COVID-19 predicts the prognosis of idiopathic pulmonary fibrosis.

Background: Increasing evidence has demonstrated that there was a strong correlation between COVID-19 and idiopathic pulmonary fibrosis (IPF). However, the studies are limited, and the real biological mechanisms behind the IPF progression were still uncleared. Methods: GSE70866 and GSE 157103 datasets were downloaded. The weight gene co-expression network analysis (WGCNA) algorithms were conducted to identify the most correlated gene module with COVID-19. Then the genes were extracted to construct a risk signature in IPF patients by performing Univariate and Lasso Cox Regression analysis. Univariate and Multivariate Cox Regression analyses were used to identify the independent value for predicting the prognosis of IPF patients. What's more, the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and gene set enrichment analysis (GSEA) were conducted to unveil the potential biological pathways. CIBERSORT algorithms were performed to calculate the correlation between the risk score and immune cells infiltrating levels. Results: Two hundred thirty three differentially expressed genes were calculated as the hub genes in COVID-19. Fourteen of these genes were identified as the prognostic differentially expressed genes in IPF. Three (MET, UCHL1, and IGF1) of the fourteen genes were chosen to construct the risk signature. The risk signature can greatly predict the prognosis of high-risk and low-risk groups based on the calculated risk score. The functional pathway enrichment analysis and immune infiltrating analysis showed that the risk signature may regulate the immune-related pathways and immune cells. Conclusion: We identified prognostic differentially expressed hub genes related to COVID-19 in IPF. A risk signature was constructed based on those genes and showed great value for predicting the prognosis in IPF patients. What's more, three genes in the risk signature may be clinically valuable as potential targets for treating IPF patients and IPF patients with COVID-19.

A novel gene signature based on the hub genes of COVID-19 predicts the prognosis of idiopathic pulmonary fibrosis

Background: Increasing evidence has demonstrated that there was a strong correlation between COVID-19 and idiopathic pulmonary fibrosis (IPF). However, the studies are limited, and the real biological mechanisms behind the IPF progression were still uncleared. Methods: GSE70866 and GSE 157103 datasets were downloaded. The weight gene co-expression network analysis (WGCNA) algorithms were conducted to identify the most correlated gene module with COVID-19. Then the genes were extracted to construct a risk signature in IPF patients by performing Univariate and Lasso Cox Regression analysis. Univariate and Multivariate Cox Regression analyses were used to identify the independent value for predicting the prognosis of IPF patients. What’s more, the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and gene set enrichment analysis (GSEA) were conducted to unveil the potential biological pathways. CIBERSORT algorithms were performed to calculate the correlation between the risk score and immune cells infiltrating levels. Results: Two hundred thirty three differentially expressed genes were calculated as the hub genes in COVID-19. Fourteen of these genes were identified as the prognostic differentially expressed genes in IPF. Three (MET, UCHL1, and IGF1) of the fourteen genes were chosen to construct the risk signature. The risk signature can greatly predict the prognosis of high-risk and low-risk groups based on the calculated risk score. The functional pathway enrichment analysis and immune infiltrating analysis showed that the risk signature may regulate the immune-related pathways and immune cells. Conclusion: We identified prognostic differentially expressed hub genes related to COVID-19 in IPF. A risk signature was constructed based on those genes and showed great value for predicting the prognosis in IPF patients. What’s more, three genes in the risk signature may be clinically valuable as potential targets for treating IPF patients and IPF patients with COVID-19.

[Degradation of Chloroquine Phosphate by UV-activated Persulfate].

The degradation of chloroquine phosphate (CQP), an anti-COVID-19 drug, was investigated in a UV-activated persulfate system (UV/PS). The second-order rate constants of CQP with hydroxyl radicals (HO·) and sulfate radicals (SO4-·) were determined using a competition kinetics experiment, and the effects of persulfate concentration, pH, and inorganic anions on the degradation of CQP were also systematically studied. Furthermore, a kinetic model was established to predict the concentration of CQP and major free radicals to explore its mechanism of influence. The results showed that the degradation efficiency of CQP could reach 91.3% after 10 min under UV/PS, which was significantly higher than that under UV, sunlight, or PS alone. At pH=6.9, the second-order rate reaction constants of CQP with HO· and SO4-· were 8.9×109 L·(mol·s)-1and 1.4×1010 L·(mol·s)-1, respectively, and the main active species was SO4-·. The degradation rate of CQP increased with increasing concentrations of PS and decreased with the addition of HCO3- and Cl-. The removal efficiency of CQP was inhibited under stronger alkaline conditions. N-de-ethylation, cleavage of the C-N bond, and hydrogen abstraction were proposed as the principal pathways of CQP degradation based on LC-MS analysis. The mineralization rate of CQP could be improved by increasing PS concentration and pH values. This study could be helpful for the treatment of anti-COVID-19 pharmaceutical wastewater.

The impact of COVID-19 on the doctor-patient relationship in China

A strong doctor-patient relationship (DPR) is crucial to the effectiveness of treatment. It is imperative to maintain a good DPR during treatment. During 2019, Coronavirus Disease 2019 (COVID-19) brought new challenges to already difficult doctor-patient relationships. This paper summarized the current state of the DPR, compared the changes between China and other countries after the outbreak of COVID-19, and listed the solutions proposed by various countries. Finally, the author suggested some solutions in order to improve the DPR according to China's own circumstances.

A network representation approach for COVID-19 drug recommendation.

The coronavirus disease 2019 (COVID-19) has outbreak since early December 2019, and COVID-19 has caused over 100 million cases and 2 million deaths around the world. After one year of the COVID-19 outbreak, there is no certain and approve medicine against it. Drug repositioning has become one line of scientific research that is being pursued to develop an effective drug. However, due to the lack of COVID-19 data, there is still no specific drug repositioning targeting the COVID-19. In this paper, we propose a framework for COVID-19 drug repositioning. This framework has several advantages that can be exploited: one is that a local graph aggregating representation is used across a heterogeneous network to address the data sparsity problem; another is the multi-hop neighbors of the heterogeneous graph are aggregated to recall as many COVID-19 potential drugs as possible. Our experimental results show that our COVDR framework performs significantly better than baseline methods, and the docking simulation verifies that our three potential drugs have the ability to against COVID-19 disease.

Purifying Selection Determines the Short-Term Time Dependency of Evolutionary Rates in SARS-CoV-2 and pH1N1 Influenza.

High-throughput sequencing enables rapid genome sequencing during infectious disease outbreaks and provides an opportunity to quantify the evolutionary dynamics of pathogens in near real-time. One difficulty of undertaking evolutionary analyses over short timescales is the dependency of the inferred evolutionary parameters on the timespan of observation. Crucially, there are an increasing number of molecular clock analyses using external evolutionary rate priors to infer evolutionary parameters. However, it is not clear which rate prior is appropriate for a given time window of observation due to the time-dependent nature of evolutionary rate estimates. Here, we characterize the molecular evolutionary dynamics of SARS-CoV-2 and 2009 pandemic H1N1 (pH1N1) influenza during the first 12 months of their respective pandemics. We use Bayesian phylogenetic methods to estimate the dates of emergence, evolutionary rates, and growth rates of SARS-CoV-2 and pH1N1 over time and investigate how varying sampling window and data set sizes affect the accuracy of parameter estimation. We further use a generalized McDonald-Kreitman test to estimate the number of segregating nonneutral sites over time. We find that the inferred evolutionary parameters for both pandemics are time dependent, and that the inferred rates of SARS-CoV-2 and pH1N1 decline by ∼50% and ∼100%, respectively, over the course of 1 year. After at least 4 months since the start of sequence sampling, inferred growth rates and emergence dates remain relatively stable and can be inferred reliably using a logistic growth coalescent model. We show that the time dependency of the mean substitution rate is due to elevated substitution rates at terminal branches which are 2-4 times higher than those of internal branches for both viruses. The elevated rate at terminal branches is strongly correlated with an increasing number of segregating nonneutral sites, demonstrating the role of purifying selection in generating the time dependency of evolutionary parameters during pandemics.

Experimental and numerical investigation on the lateral force resistance of modular steel sub-frames with laminated double beam

Modular construction was widely applied since higher integrity, faster speed and less emission. Especially for COVID-19, several modular steel hospitals were urgently built for treatment and successfully contributed to epidemic control. It has been known that laminated double beam has the capability of significantly strengthening the cooperation between adjacent floor and ceiling beams in modular steel buildings. However, the effect of the superposition of laminated double beam on the lateral force resistance of modular steel structure has not been fully understood. In present study, a series of full-scale lateral experimental tests and finite element analysis were conducted to comprehensively investigate the lateral response of modular steel sub-frames with laminated double beam. Moreover, a simple validated analytical procedure was developed to support the design and assessment of modular steel buildings in engineering practice. The results show that the application of corner plug-in junction could significantly strengthen the connection of critical components of a modular steel sub-frame. The superimposed bending action of the laminated beam was demonstrated by that the strain neutral axes of the layered beams are relatively close to the interface of the beams resulting from interfacial bolt connections. It shows that the superimposition of adjacent double beams could obviously reinforce the structural integrity and lateral force resistance of a modular steel sub-frame. Furthermore, the developed analytical procedure provides an accurate and efficient method for estimating the initial lateral stiffness of modular steel sub-frames.

Can trade help with fighting the pandemic? Evidence from imports of Chinese medical products: European Journal of Economics and Economic Policies = Europäische Zeitschrift für Ökonomie und Wirtschaftspolitik

To contain the COVID-19 pandemic, medical products play an important role around the world. This paper studies the relationship between trade and pandemic control by testing the impact of importing medical products from China on COVID-19 cases and deaths. Using a fixed-effects model, we find that there is a significant negative correlation between imports of medical products from China and COVID-19 cases;for every 1 percent increase in protection equipment imported from China, new COVID-19 cases per day drop by 0.24 percent, and COVID-19-related deaths decrease by 0.13 percent in two weeks. The evidence suggests that trade can play a vital role in fighting the pandemic.

Coronavirus disease and the cardiovascular system: a narrative review of the mechanisms of injury and management implications.

Coronavirus disease (COVID-19), first identified in Wuhan, China, in December 2019, is now a pandemic, having already spread to 188 countries, with more than 28,280,000 infections worldwide. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is the responsible infectious agent, and similar to other human coronaviruses, uses membrane-bound angiotensin-converting enzyme 2 (membrane-bound ACE2) for entry into the host cells. COVID-19 has important cardiovascular implications, especially for patients with pre-existing cardiovascular co-morbidities, potentially mediated through several mechanisms, including direct myocardial injury, worsening of those pre-existing cardiovascular co-morbidities, and adverse cardiovascular effects of potential therapies for COVID-19. The disease is causing a significant burden on health systems worldwide. Elective surgeries and procedures were postponed for a considerable period of time, and many patients with known cardiovascular disease (CVD) risk factors presented late to hospitals, for fear of contracting COVID-19, with serious adverse consequences. Significant negative impact on a population level is highlighted by prolonged isolation, decreased exercise and physical activity, and higher levels of depression and anxiety, all predisposing to elevated cardiovascular risk. This article provides a timely overview of COVID-19 and its impact on the cardiovascular system, focusing on the pathogenesis, potential adverse cardiovascular events, the potential treatment options, protection for health care providers and patients, and what the cardiovascular community could do to mitigate the impact of COVID-19.

Similarities and differences between multiple inflammatory syndrome in children associated with COVID-19 and Kawasaki disease: clinical presentations, diagnosis, and treatment.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been spreading rapidly around the world, while "multisystem inflammatory syndrome in children" (MIS-C) is a new type of syndrome that has now been reported in many countries. Similar and different characteristics between KD and MIS-C have been reported in a variety of literature. We aimed to focus on reviewing clinical presentations, diagnosis, and treatment of KD and MIS-C. METHODS: We searched articles in the electronic databases, including the Cochrane Library database, EMBASE, and MEDLINE with the keywords "multiple inflammatory syndrome" and/or "COVID-19" and/or "Kawasaki disease" and "children". RESULTS: Main presentations of MIS-C and KD include fever, rashes, mucous membrane involvement, conjunctivitis, hands and feet erythema/edema, and cervical lymphadenopathy. However, compared with the highest incidence of KD among some Asian countries, MIS-C is common among Black and Hispanic children. MIS-C is common in older children and teenagers, whereas classic KD is common in children under five years of age. Gastrointestinal symptoms, shock, and coagulopathy are common in MIS-C patients but are not common in classic KD. Cardiac manifestations are more common than KD, including myocarditis with cardiac dysfunction and coronary artery dilation or aneurysms. Severe cases in MIS-C present with vasodilated or cardiogenic shock that requires fluid resuscitation, muscular support, and even mechanical ventilation and extracorporeal membrane oxygenation (ECMO), whereas KD rarely presents with these manifestations and requires these treatments. Increased serum ferritin, leukopenia, lymphopenia and thrombocytopenia are common in MIS-C. However, thrombocytosis is a characteristic feature of KD. Intravenous immunoglobulin (IVIG) and moderate-high dose aspirin are still a standard recommended treatment for KD. In addition to the above-mentioned medications, steroids and biological drugs are frequently used in patients with MIS-C. Most of the children with KD have a good prognosis; however, the long-term clinical outcomes of MIS-C are not clear. CONCLUSIONS: The overall presentation and treatment of MIS-C appear to overlap with KD. However, there are still great differences between the syndromes, and it is controversial to say whether MIS-C is a new entity or is a "severe type" of KD.

Semen parameters in men recovered from COVID-19.

The novel coronavirus disease (COVID-19) pandemic is emerging as a global health threat and shows a higher risk for men than women. Thus far, the studies on andrological consequences of COVID-19 are limited. To ascertain the consequences of COVID-19 on sperm parameters after recovery, we recruited 41 reproductive-aged male patients who had recovered from COVID-19, and analyzed their semen parameters and serum sex hormones at a median time of 56 days after hospital discharge. For longitudinal analysis, a second sampling was obtained from 22 of the 41 patients after a median time interval of 29 days from first sampling. Compared with controls who had not suffered from COVID-19, the total sperm count, sperm concentration, and percentages of motile and progressively motile spermatozoa in the patients were significantly lower at first sampling, while sperm vitality and morphology were not affected. The total sperm count, sperm concentration, and number of motile spermatozoa per ejaculate were significantly increased and the percentage of morphologically abnormal sperm was reduced at the second sampling compared with those at first in the 22 patients examined. Though there were higher prolactin and lower progesterone levels in patients at first sampling than those in controls, no significant alterations were detected for any sex hormones examined over time following COVID-19 recovery in the 22 patients. Although it should be interpreted carefully, these findings indicate an adverse but potentially reversible consequence of COVID-19 on sperm quality.

Reduction of Human Mobility Matters during Early COVID-19 Outbreaks: Evidence from India, Japan and China.

Mobility restrictions have been a heated topic during the global pandemic of coronavirus disease 2019 (COVID-19). However, multiple recent findings have verified its importance in blocking virus spread. Evidence on the association between mobility, cases imported from abroad and local medical resource supplies is limited. To reveal the association, this study quantified the importance of inter- and intra-country mobility in containing virus spread and avoiding hospitalizations during early stages of COVID-19 outbreaks in India, Japan, and China. We calculated the time-varying reproductive number (Rt) and duration from illness onset to diagnosis confirmation (Doc), to represent conditions of virus spread and hospital bed shortages, respectively. Results showed that inter-country mobility fluctuation could explain 80%, 35%, and 12% of the variance in imported cases and could prevent 20 million, 5 million, and 40 million imported cases in India, Japan and China, respectively. The critical time for screening and monitoring of imported cases is 2 weeks at minimum and 4 weeks at maximum, according to the time when the Pearson's Rs between Rt and imported cases reaches a peak (>0.8). We also found that if local transmission is initiated, a 1% increase in intra-country mobility would result in 1430 (±501), 109 (±181), and 10 (±1) additional bed shortages, as estimated using the Doc in India, Japan, and China, respectively. Our findings provide vital reference for governments to tailor their pre-vaccination policies regarding mobility, especially during future epidemic waves of COVID-19 or similar severe epidemic outbreaks.

A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19).

OBJECTIVE: The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) has caused more than 26 million cases of Corona virus disease (COVID-19) in the world so far. To control the spread of the disease, screening large numbers of suspected cases for appropriate quarantine and treatment are a priority. Pathogenic laboratory testing is typically the gold standard, but it bears the burden of significant false negativity, adding to the urgent need of alternative diagnostic methods to combat the disease. Based on COVID-19 radiographic changes in CT images, this study hypothesized that artificial intelligence methods might be able to extract specific graphical features of COVID-19 and provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control. METHODS: We collected 1065 CT images of pathogen-confirmed COVID-19 cases along with those previously diagnosed with typical viral pneumonia. We modified the inception transfer-learning model to establish the algorithm, followed by internal and external validation. RESULTS: The internal validation achieved a total accuracy of 89.5% with a specificity of 0.88 and sensitivity of 0.87. The external testing dataset showed a total accuracy of 79.3% with a specificity of 0.83 and sensitivity of 0.67. In addition, in 54 COVID-19 images, the first two nucleic acid test results were negative, and 46 were predicted as COVID-19 positive by the algorithm, with an accuracy of 85.2%. CONCLUSION: These results demonstrate the proof-of-principle for using artificial intelligence to extract radiological features for timely and accurate COVID-19 diagnosis. KEY POINTS: • The study evaluated the diagnostic performance of a deep learning algorithm using CT images to screen for COVID-19 during the influenza season. • As a screening method, our model achieved a relatively high sensitivity on internal and external CT image datasets. • The model was used to distinguish between COVID-19 and other typical viral pneumonia, both of which have quite similar radiologic characteristics.

The Adrenal Cortex, an Underestimated Site of SARS-CoV-2 Infection.

Background: The majority of the critically ill patients may have critical illness-related corticosteroid insufficiency (CIRCI). The therapeutic effect of dexamethasone may be related to its ability to improve cortical function. Recent study showed that dexamethasone can reduce COVID-19 deaths by up to one third in critically ill patients. The aim of this article is to investigate whether SARS-CoV-2 can attack the adrenal cortex to aggravate the relative adrenal insufficiency. Methods: We summarized the clinical features of COVID-19 reported in currently available observational studies. ACE2 and TMPRSS2 expression was examined in human adrenal glands by immunohistochemical staining. We retrospectively analyzed serum cortisol levels in critically ill patients with or without COVID-19. Results: High percentage of critically ill patients with SARS-COV-2 infection in the study were treated with vasopressors. ACE2 receptor and TMPRSS2 serine protease were colocalized in adrenocortical cells in zona fasciculata and zona reticularis. We collected plasma cortisol concentrations in nine critically ill patients with COVID-19. The cortisol levels of critically ill patients with COVID-19 were lower than those in non-COVID-19 critically ill group. Six of the nine COVID-19 critically ill patients had random plasma cortisol concentrations below 10 µg/dl, which met the criteria for the diagnosis of CIRCI. Conclusion: We demonstrate that ACE2 and TMPRSS2 are colocalized in adrenocortical cells, and that the cortisol levels are lower in critically ill patients with COVID-19 as compared to those of non-COVID-19 critically ill patients. Based on our findings, we recommend measuring plasma cortisol level to guide hormonal therapy.

Healthy neonate born to a SARS-CoV-2 infected woman: A case report and review of literature.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a newly discovered coronavirus that has generated a worldwide outbreak of infections. Many people with coronavirus disease-2019 (COVID-19) have developed severe illness, and a significant number have died. However, little is known regarding infection by the novel virus in pregnant women. We herein present a case of COVID-19 confirmed in a woman delivering a neonate who was negative for SARS-CoV-2 and related it to a review of the literature on pregnant women and human coronavirus infections. CASE SUMMARY: The patient was a 36-year-old pregnant woman in her third trimester who had developed progressive clinical symptoms when she was confirmed as infected with SARS-CoV-2. Given the potential risks for both the pregnant woman and the fetus, an emergency cesarean section was performed, and the baby and his mother were separately quarantined and cared for. As a result, the baby currently shows no signs of SARS-CoV-2 infection (his lower respiratory tract samples were negative for the virus), while the mother completely recovered from COVID-19. CONCLUSION: Although we presented a single case, the successful result is of great significance for pregnant women with SARS-CoV-2 infection and with respect to fully understanding novel coronavirus pneumonia.

Clinical significance of T-lymphocyte subsets in the treatment of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is widely spread due to its strong infectivity by close contact via droplets or skin touch. With fever or cough as the first symptom, some patients suffering from coronavirus disease 2019 (COVID-19) quickly progressed to serious condition, which severely threatened the health of patients. As immunodeficiency is a significant factor of the poor condition, the relationship between COVID-19 and T-lymphocyte subsets will be summarized. The paper is written to indicate the clinical significance of T-lymphocyte subsets in the monitoring and treatment of COVID-19. It is suggested that the subgroup levels of T-lymphocyte subsets should be dynamically monitored during the course of disease for better understanding the condition and taking positive intervention, which will provide guidance to control immune inflammatory cascade and hold back the development of critical situation.