Parameters and order identification of fractional-order epidemiological systems by Lévy-PSO and its application for the spread of COVID-19

To identify the knowledge about parameters and order is very important for the modeling of fractional-order epidemiological systems. In this paper, such an identification problem is formulated as a nonlinear optimization problem. For solving this, the Lévy-PSO algorithm, which is obtained by applying Lévy flight to generalize the classical particle swarm optimization (PSO), is used. More precisely, we first utilize Lévy-PSO to identify the constant parameters and the order of fractional-order SIR, SEIR systems with simulated data to show the effectiveness of our proposed identification strategy. Then, we continue employing Lévy-PSO to solve the parameter estimation problem of fractional-order SEAIR model under the real data of COVID-19 in Shanghai from 2/26/2022 to 4/27/2022. Numerical examples and associated comparisons with other existing methods allow us to achieve that our proposed identification strategy can generate a good performance with high accuracy and rapid convergence.

Impacts of Greenhouse Gases and Anthropogenic Aerosols Changes on Surface Air Temperature in East Asia under Different Post-pandemic Period Emission Scenarios

In order to know how surface air temperature (SAT) changes in East Asia under different emission scenarios after the COVID-19 outbreak, in this paper, we investigated the impacts of greenhouse gases (GHGs) and anthropogenic aerosols changes on SAT in East Asia by using the aerosol-climate coupled model BCC-AGCM 2.0_CUACE/Aero, combining with the post-pandemic emission scenarios proposed by Covid multi-Earth system model intercomparison project (CovidMIP scenarios for short, including fossil-fueled recovery, moderate green stimulus, strong green stimulus, hereinafter as FFF, MGG, SGG, respectively). We assessed the impacts of changes in GHGs and anthropogenic aerosols together and separately on SAT in East Asia and its typical subregions during 2020‒2050. The results show that by mid-21st-century, SAT in East Asia will increase by 0.81±0.083°C under Baseline (same as SSP2-4.5 scenario), i.e., SAT difference between 2045‒2050 and 2020‒2025), and there will be more intense warming in all the three scenarios in East Asia, in which the largest SAT difference (SAT-d) compared to Baseline is 0.33±0.11°C under SGG and the smallest SAT-d is 0.07±0.14°C under FFF. To further explore the mechanism of these SAT-d, we analyzed the trend of surface longwave and shortwave net radiation flux driven by GHGs and anthropogenic aerosols there. It is found that in early period (2020‒2035), the role of aerosol changes is bigger than that of GHG changes in dominating SAT-d, particularly sulfate, whose reduction will become the main contributor to SAT-d by affecting the net solar flux at surface. In later period (2036‒2050), because of GHGs’ longer atmospheric lifetime than aerosols, the role of decreasing GHGs concentrations will determine the drop in SAT-d through affecting the net longwave flux at surface.

Do COVID-19 CT features vary between patients from within and outside mainland China? Findings from a meta-analysis

Background Chest computerized tomography (CT) plays an important role in detecting patients with suspected coronavirus disease 2019 (COVID-19), however, there are no systematic summaries on whether the chest CT findings of patients within mainland China are applicable to those found in patients outside. Methods Relevant studies were retrieved comprehensively by searching PubMed, Embase, and Cochrane Library databases before 15 April 2022. Quality assessment of diagnostic accuracy studies (QUADAS) was used to evaluate the quality of the included studies, which were divided into two groups according to whether they were in mainland China or outside. Data on diagnostic performance, unilateral or bilateral lung involvement, and typical chest CT imaging appearances were extracted, and then, meta-analyses were performed with R software to compare the CT features of COVID-19 pneumonia between patients from within and outside mainland China. Results Of the 8,258 studies screened, 19 studies with 3,400 patients in mainland China and 14 studies with 554 outside mainland China were included. Overall, the risk of quality assessment and publication bias was low. The diagnostic value of chest CT is similar between patients from within and outside mainland China (93, 91%). The pooled incidence of unilateral lung involvement (15, 7%), the crazy-paving sign (31, 21%), mixed ground-glass opacities (GGO) and consolidations (51, 35%), air bronchogram (44, 25%), vascular engorgement (59, 33%), bronchial wall thickening (19, 12%), and septal thickening (39, 26%) in patients from mainland China were significantly higher than those from outside;however, the incidence rates of bilateral lung involvement (75, 84%), GGO (78, 87%), consolidations (45, 58%), nodules (12, 17%), and pleural effusion (9, 15%) were significantly lower. Conclusion Considering that the chest CT features of patients in mainland China may not reflect those of the patients abroad, radiologists and clinicians should be familiar with various CT presentations suggestive of COVID-19 in different regions.

Real-Word Effectiveness of Global COVID-19 Vaccines Against SARS-CoV-2 Variants: A Systematic Review and Meta-Analysis.

Background: Currently, promoted vaccinations against SARS-CoV-2 are being given out globally. However, the occurrence of numerous COVID-19 variants has hindered the goal of rapid mitigation of the COVID-19 pandemic by effective mass vaccinations. The real-word effectiveness of the current vaccines against COVID-19 variants has not been assessed by published reviews. Therefore, our study evaluated the overall effectiveness of current vaccines and the differences between the various vaccines and variants. Methods: PubMed, Embase, Cochrane Library, medRxiv, bioRxiv, and arXiv were searched to screen the eligible studies. The Newcastle-Ottawa scale and the Egger test were applied to estimate the quality of the literature and any publication bias, respectively. The pooled incident rates of different variants after vaccination were estimated by single-arm analysis. Meanwhile, the pooled efficacies of various vaccines against variants were evaluated by two-arm analysis using odds ratios (ORs) and vaccine effectiveness (VE). Results: A total of 6,118 studies were identified initially and 44 articles were included. We found that the overall incidence of variants post first/second vaccine were 0.07 and 0.03, respectively. The VE of the incidence of variants post first vaccine between the vaccine and the placebo or unvaccinated population was 40% and post second vaccine was 96%, respectively. The sub-single-arm analysis showed a low prevalence rate of COVID-19 variants after specific vaccination with the pooled incidence below 0.10 in most subgroups. Meanwhile, the sub-two-arm analysis indicated that most current vaccines had a good or moderate preventive effect on certain variants considering that the VE in these subgroups was between 66 and 95%, which was broadly in line with the results of the sub-single-arm analysis. Conclusion: Our meta-analysis shows that the current vaccines that are used globally could prevent COVID-19 infection and restrict the spread of variants to a great extent. We would also support maximizing vaccine uptake with two doses, as the effectiveness of which was more marked compared with one dose. Although the mRNA vaccine was the most effective against variants according to our study, specific vaccines should be taken into account based on the local dominant prevalence of variants.

A comprehensive evaluation of the potential binding poses of fentanyl and its analogs at the µ-opioid receptor.

Fentanyl and its analogs are selective agonists of the µ-opioid receptor (MOR). Among novel synthetic opioids (NSOs), they dominate the recreational drug market and are the main culprits for the opioid crisis, which has been exacerbated by the COVID-19 pandemic. By taking advantage of the crystal structures of the MOR, several groups have investigated the binding mechanism of fentanyl, but have not reached a consensus, in terms of both the binding orientation and the fentanyl conformation. Thus, the binding mechanism of fentanyl at the MOR remains an unsolved and challenging question. Here, we carried out a systematic computational study to investigate the preferred fentanyl conformations, and how these conformations are being accommodated in the MOR binding pocket. We characterized the free energy landscape of fentanyl conformations with metadynamics simulations, and compared and evaluated several possible fentanyl binding conditions in the MOR with long-timescale molecular dynamics simulations. Our results indicate that the most preferred binding pose in the MOR binding pocket corresponds well with the global minimum on the energy landscape of fentanyl in the absence of the receptor, while the energy landscape can be reconfigured by modifying the fentanyl scaffold. The interactions with the receptor may stabilize a slightly unfavored fentanyl conformation in an alternative binding pose. By extending similar investigations to fentanyl analogs, our findings establish a structure-activity relationship of fentanyl binding at the MOR. In addition to providing a structural basis to understand the potential toxicity of the emerging NSOs, such insights will contribute to developing new, safer analgesics.

Effective Radiative Forcings Due To Anthropogenic Emission Changes Under Covid-19 and Post-Pandemic Recovery Scenarios.

With the continuation of the Coronavirus Disease 2019 (Covid-19) pandemic, the impacts of this catastrophe on anthropogenic emissions are no longer limited to its early stage. This study quantitatively estimates effective radiative forcings (ERFs) due to anthropogenic well-mixed greenhouse gases (WMGHGs) and aerosols for the period 2020-2050 under the three latest Covid-19 economic-recovery scenarios using an aerosol-climate model. The results indicate that reductions in both WMGHG and aerosol emissions under the Covid-19 green recoveries lead to increases ranging from 0 to 0.3 W m-2 in global annual mean anthropogenic ERF over the period 2020-2050 relative to the Shared Socioeconomic Pathway 2-4.5 scenario (the baseline case). These positive ERFs are mainly attributed to the rapid and dramatic decreases in atmospheric aerosol content that increase net shortwave radiative flux at the top of atmosphere via weakening the direct aerosol effect and low cloud cover. At the regional scale, reductions in aerosols contribute to positive ERFs throughout the Northern Hemisphere, while the decreased WMGHGs dominate negative ERFs over the areas away from aerosol pollution, such as the Southern Hemisphere oceans. This drives a strong interhemispheric contrast of ERFs. In contrast, the increased anthropogenic emissions under the fossil-fueled recovery scenario lead to an increase of 0.3 W m-2 in global annual mean ERF in 2050 compared with the baseline case, primarily due to the contribution of WMGHG ERFs. The regional ERF changes are highly dependent on local cloud radiative effects.

Current status of potential therapeutic candidates for the COVID-19 crisis.

As of April 15, 2020, the ongoing coronavirus disease 2019 (COVID-2019) pandemic has swept through 213 countries and infected more than 1,870,000 individuals, posing an unprecedented threat to international health and the economy. There is currently no specific treatment available for patients with COVID-19 infection. The lessons learned from past management of respiratory viral infections have provided insights into treating COVID-19. Numerous potential therapies, including supportive intervention, immunomodulatory agents, antiviral therapy, and convalescent plasma transfusion, have been tentatively applied in clinical settings. A number of these therapies have provided substantially curative benefits in treating patients with COVID-19 infection. Furthermore, intensive research and clinical trials are underway to assess the efficacy of existing drugs and identify potential therapeutic targets to develop new drugs for treating COVID-19. Herein, we summarize the current potential therapeutic approaches for diseases related to COVID-19 infection and introduce their mechanisms of action, safety, and effectiveness.

Exploration of severe Covid-19 associated risk factor in China: Meta-analysis of current evidence.

AIM: This meta-analysis aimed to explore potential risk factors for severe Covid-19. METHODS: We systemically and comprehensively retrieved the eligible study evaluating clinical differences between severe vs non-severe Covid-19. Main effect sizes were demographic characteristics, comorbidities, signs and symptoms, laboratory findings as well as radiological features of chest CT. RESULTS: A total of 2566 Covid-19 people (771 in the severe group and 1795 in the non-severe group) from 14 studies were eligible for this meta-analysis. It was demonstrated that older age and males were more likely to have severe Covid-19. Patients with underlying comorbidities, such as hypertension, diabetes, heart disease and COPD were significantly more susceptible to severe Covid-19. Patients with dyspnoea were more likely to be severely ill. Depressed total lymphocytes were observed in this article. Meanwhile, although reticulation (30.8%), intrathoracic lymph node enlargement (20.5%) and pleural effusions (30.8%) were relatively infrequent, meta-analysis revealed that patients with these presentations in chest CT were associated with increased risk of severe Covid-19. CONCLUSIONS: There are significant differences in clinical characteristics between the severe and non-severe Covid-19 patients. Many factors are related to the severity of the disease, which can help clinicians to differentiate severe patients from non-severe patients.

COVID-19: Imbalanced Immune Responses and Potential Immunotherapies.

The ongoing pandemic coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is rapidly spreading and has resulted in grievous morbidity and mortality worldwide. Despite the high infectiousness of SARS-CoV-2, the majority of infected individuals are asymptomatic or have mild symptoms and could eventually recover as a result of their balanced immune function. On the contrary, immuno-compromised patients are prone to progress into severe or critical types underpinned by the entanglement of an overexuberant proinflammatory response and injured immune function. Therefore, well-coordinated innate and adaptive immune systems are pivotal to viral eradication and tissue repair. An in-depth understanding of the immunological processes underlying COVID-19 could facilitate rapidly identifying and choosing optimal immunotherapy for patients with severe SARS-CoV-2 infection. In this review, based on current immunological evidence, we describe potential immune mechanisms and discuss promising immunotherapies for COVID-19, including IL-6R blockades, convalescent plasma, intravenous gamma globulin, thymosin alpha1, corticosteroids, and type-I interferon, and recent advances in the development of COVID-19 vaccines.

Comparison of detection rate of 16 sampling methods for respiratory viruses: a Bayesian network meta-analysis of clinical data and systematic review.

BACKGROUND: Respiratory viruses (RVs) is a common cause of illness in people of all ages, at present, different types of sampling methods are available for respiratory viral diagnosis. However, the diversity of available sampling methods and the limited direct comparisons in randomised controlled trials (RCTs) make decision-making difficult. We did a network meta-analysis, which accounted for both direct and indirect comparisons, to determine the detection rate of different sampling methods for RVs. METHODS: Relevant articles were retrieved comprehensively by searching the online databases of PubMed, Embase and Cochrane published before 25 March 2020. With the help of R V.3.6.3 software and 'GeMTC V.0.8.2' package, network meta-analysis was performed within a Bayesian framework. Node-splitting method and I2 test combined leverage graphs and Gelman-Rubin-Brooks plots were conducted to evaluate the model's accuracy. The rank probabilities in direct and cumulative rank plots were also incorporated to rank the corresponding sampling methods for overall and specific virus. RESULTS: 16 sampling methods with 54 438 samples from 57 literatures were ultimately involved in this study. The model indicated good consistency and convergence but high heterogeneity, hence, random-effect analysis was applied. The top three sampling methods for RVs were nasopharyngeal wash (NPW), mid-turbinate swab (MTS) and nasopharyngeal swab (NPS). Despite certain differences, the results of virus-specific subanalysis were basically consistent with RVs: MTS, NPW and NPS for influenza; MTS, NPS and NPW for influenza-a and b; saliva, NPW and NPS for rhinovirus and parainfluenza; NPW, MTS and nasopharyngeal aspirate for respiratory syncytial virus; saliva, NPW and MTS for adenovirus and sputum; MTS and NPS for coronavirus. CONCLUSION: This network meta-analysis provides supporting evidences that NPW, MTS and NPS have higher diagnostic value regarding RVs infection, moreover, particular preferred methods should be considered in terms of specific virus pandemic. Of course, subsequent RCTs with larger samples are required to validate our findings.

Poor-sleep is associated with slow recovery from lymphopenia and an increased need for ICU care in hospitalized patients with COVID-19: A retrospective cohort study.

Sleep is known to play an important role in immune function. However, the effects of sleep quality during hospitalization for COVID-19 remain unclear. This retrospective, single-center cohort study was conducted to investigate the effects of sleep quality on recovery from lymphopenia and clinical outcomes in hospitalized patients with laboratory-confirmed COVID-19 admitted to the West District of Wuhan Union Hospital between January 25 and March 15, 2020. The Richards-Campbell sleep questionnaire (RCSQ) and Pittsburgh Sleep Quality Index (PSQI) were used to assess sleep quality. The epidemiological, demographic, clinical, laboratory, treatment, and outcome data were collected from electronic medical records and compared between the good-sleep group and poor-sleep group. In all, 135 patients (60 in good-sleep group and 75 in poor-sleep group) were included in this study. There were no significant between-group differences regarding demographic and baseline characteristics, as well as laboratory parameters upon admission and in-hospital treatment. Compared with patients in the good-sleep group, patients in the poor-sleep group had lower absolute lymphocyte count (ALC) (day 14: median, 1.10 vs 1.32, P = 0.0055; day 21: median, 1.18 vs 1.48, P = 0.0034) and its reduced recovery rate (day 14: median, 56.91 vs 69.40, P = 0.0255; day 21: median, 61.40 vs 111.47, P = 0.0003), as well as increased neutrophil-to-lymphocyte ratio (NLR; day 14: median, 3.17 vs 2.44, P = 0.0284; day 21: median, 2.73 vs 2.23, P = 0.0092) and its associated deterioration rate (day 14: median, -39.65 vs -61.09, P = 0.0155; day 21: median, -51.40% vs -75.43, P = 0.0003). Nine [12.0%] patients in the poor-sleep group required ICU care (P = 0.0151); meanwhile, none of the patients in good-sleep group required ICU care. Patients in the poor-sleep group had increased duration of hospital stay (33.0 [23.0-47.0] days vs 25.0 [20.5-36.5] days, P = 0.0116) compared to those in the good-sleep group. An increased incidence of hospital-acquired infection (seven [9.3%] vs one [1.7%]) was observed in the poor-sleep group compared to the good-sleep group; however, this difference was not significant (P = 0.1316). In conclusion, poor sleep quality during hospitalization in COVID-19 patients with lymphopenia is associated with a slow recovery from lymphopenia and an increased need for ICU care.