Application of a time-delay SIR model with vaccination in COVID-19 prediction and its optimal control strategy

In the classical infectious disease compartment model, the parameters are fixed. In reality, the probability of virus transmission in the process of disease transmission depends on the concentration of virus in the environment, and the concentration depends on the proportion of patients in the environment. Therefore, the probability of virus transmission changes with time. Then how to fit the parameters and get the trend of the parameters changing with time is the key to predict the disease course with the model. In this paper, based on the US COVID-19 epidemic statistics during calibration period, the parameters such as infection rate and recovery rate are fitted by using the linear regression algorithm of machine science, and the laws of these parameters changing with time are obtained. Then a SIR model with time delay and vaccination is proposed, and the optimal control strategy of epidemic situation is analyzed by using the optimal control theory and Pontryagin maximum principle, which proves the effectiveness of the control strategy in restraining the transmission of COVID-19. The numerical simulation results show that the time-varying law of the number of active cases obtained by our model basically conforms to the real changing law of the US COVID-19 epidemic statistics during calibration period. In addition, we have predicted the changes in the number of active cases in the COVID-19 epidemic in the USA over time in the future beyond the calibration cycle, and the predicted results are more in line with the actual epidemic data.

Application of a time-delay SIR model with vaccination in COVID-19 prediction and its optimal control strategy.

In the classical infectious disease compartment model, the parameters are fixed. In reality, the probability of virus transmission in the process of disease transmission depends on the concentration of virus in the environment, and the concentration depends on the proportion of patients in the environment. Therefore, the probability of virus transmission changes with time. Then how to fit the parameters and get the trend of the parameters changing with time is the key to predict the disease course with the model. In this paper, based on the US COVID-19 epidemic statistics during calibration period, the parameters such as infection rate and recovery rate are fitted by using the linear regression algorithm of machine science, and the laws of these parameters changing with time are obtained. Then a SIR model with time delay and vaccination is proposed, and the optimal control strategy of epidemic situation is analyzed by using the optimal control theory and Pontryagin maximum principle, which proves the effectiveness of the control strategy in restraining the transmission of COVID-19. The numerical simulation results show that the time-varying law of the number of active cases obtained by our model basically conforms to the real changing law of the US COVID-19 epidemic statistics during calibration period. In addition, we have predicted the changes in the number of active cases in the COVID-19 epidemic in the USA over time in the future beyond the calibration cycle, and the predicted results are more in line with the actual epidemic data.

Real-world Effectiveness of Sotrovimab for the Early Treatment of COVID-19 During SARS-CoV-2 Delta and Omicron Waves in the United States (preprint)

Background Sotrovimab, a recombinant human monoclonal antibody (mAb) against SARS-CoV-2 had US FDA Emergency Use Authorization (EUA) for the treatment of high-risk outpatients with mild-to-moderate COVID-19 from May 26, 2021, to April 5, 2022. The study objective was to evaluate the real-world effectiveness of sotrovimab in reducing the risk of 30-day all-cause hospitalization and/or mortality during the time period when the prevalence of circulating SARS-CoV-2 variants was changing between Delta and Omicron sub-lineages in the US. Methods A retrospective analysis was conducted on de-identified claims data for 1,530,501 patients diagnosed with COVID-19 (ICD-10: U07.1) from September 1, 2021, to April 30, 2022, in the FAIR Health National Private Insurance Claims (FH NPIC(R)) database. Patients meeting EUA high-risk criteria were identified via pre-specified ICD-10-CM diagnoses in records [≤]24 months prior to their first COVID-19 diagnosis and divided into two cohorts based on claimed procedural codes: treated with sotrovimab (''sotrovimab'') and not treated with a mAb (''no mAb''). All-cause hospitalizations and facility-reported all-cause mortality within 30 days of diagnosis (''30-day hospitalization or mortality'') were identified. Multivariable and propensity score-matched Poisson and logistic regressions were conducted to estimate the adjusted relative risk (RR) and odds of 30-day hospitalization or mortality among those treated with sotrovimab compared with those not treated with a mAb. Results Of the high-risk COVID-19 patients identified, 15,633 were treated with sotrovimab and 1,514,868 were not treated with a mAb. Compared with the no mAb cohort, the sotrovimab cohort was older and had a higher proportion of patients across the majority of high-risk conditions. In the no mAb cohort, 84,307 (5.57%) patients were hospitalized and 8,167 (0.54%) deaths were identified, while in the sotrovimab cohort, 418 (2.67%) patients were hospitalized and 13 (0.08%) deaths were identified. After adjusting for potential confounders, high-risk COVID-19 patients treated with sotrovimab had a 55% relative risk reduction of 30-day hospitalization or mortality (RR: 0.45, 95% CI: 0.41,0.49) and an 85% relative risk reduction of 30-day mortality (RR: 0.15, 95% CI: 0.08, 0.29) compared with high-risk patients not treated with a mAb. From September 2021 to April 2022, sotrovimab maintained clinical effectiveness with relative risk reductions of 30-day hospitalization or mortality ranging from 46% to 71%. Stratifying by high-risk condition, sotrovimab-treated patients exhibited statistically significant relative risk reductions of 30-day hospitalization or mortality compared with the no mAb cohort across all high-risk conditions (P<0.0001), ranging from 44% among pregnant women to 70% among patients 65 years and older. Conclusion In this large, US real-world, observational study of high-risk COVID-19 patients with reported diagnosis between September 2021 and April 2022 during the Delta and early Omicron variant waves, treatment with sotrovimab was associated with reduced risk of 30-day all-cause hospitalization and facility-reported mortality compared with no mAb treatment. Sotrovimab clinical effectiveness persisted throughout the months when Delta and early Omicron sub-lineages were the predominant circulating variants in the US, though there was an uncertain RR estimate in April 2022 with wide confidence intervals due to the small sample size. Sotrovimab clinical effectiveness also persisted among all high-risk subgroups assessed.

Human Nasal Organoids Model SARS-CoV-2 Upper Respiratory Infection and Recapitulate the Differential Infectivity of Emerging Variants.

The human upper respiratory tract, specifically the nasopharyngeal epithelium, is the entry portal and primary infection site of respiratory viruses. Productive infection of SARS-CoV-2 in the nasal epithelium constitutes the cellular basis of viral pathogenesis and transmissibility. Yet a robust and well-characterized in vitro model of the nasal epithelium remained elusive. Here we report an organoid culture system of the nasal epithelium. We derived nasal organoids from easily accessible nasal epithelial cells with a perfect establishment rate. The derived nasal organoids were consecutively passaged for over 6 months. We then established differentiation protocols to generate 3-dimensional differentiated nasal organoids and organoid monolayers of 2-dimensional format that faithfully simulate the nasal epithelium. Moreover, when differentiated under a slightly acidic pH, the nasal organoid monolayers represented the optimal correlate of the native nasal epithelium for modeling the high infectivity of SARS-CoV-2, superior to all existing organoid models. Notably, the differentiated nasal organoid monolayers accurately recapitulated higher infectivity and replicative fitness of the Omicron variant than the prior variants. SARS-CoV-2, especially the more transmissible Delta and Omicron variants, destroyed ciliated cells and disassembled tight junctions, thereby facilitating virus spread and transmission. In conclusion, we establish a robust organoid culture system of the human nasal epithelium for modeling upper respiratory infections and provide a physiologically-relevant model for assessing the infectivity of SARS-CoV-2 emerging variants. IMPORTANCE An in vitro model of the nasal epithelium is imperative for understanding cell biology and virus-host interaction in the human upper respiratory tract. Here we report an organoid culture system of the nasal epithelium. Nasal organoids were derived from readily accessible nasal epithelial cells with perfect efficiency and stably expanded for more than 6 months. The long-term expandable nasal organoids were induced maturation into differentiated nasal organoids that morphologically and functionally simulate the nasal epithelium. The differentiated nasal organoids adequately recapitulated the higher infectivity and replicative fitness of SARS-CoV-2 emerging variants than the ancestral strain and revealed viral pathogenesis such as ciliary damage and tight junction disruption. Overall, we established a human nasal organoid culture system that enables a highly efficient reconstruction and stable expansion of the human nasal epithelium in culture plates, thus providing a facile and robust tool in the toolbox of microbiologists.

A bipotential organoid model of respiratory epithelium recapitulates high infectivity of SARS-CoV-2 Omicron variant.

The airways and alveoli of the human respiratory tract are lined by two distinct types of epithelium, which are the primary targets of respiratory viruses. We previously established long-term expanding human lung epithelial organoids from lung tissues and developed a 'proximal' differentiation protocol to generate mucociliary airway organoids. However, a respiratory organoid system with bipotential of the airway and alveolar differentiation remains elusive. Here we defined a 'distal' differentiation approach to generate alveolar organoids from the same source for the derivation of airway organoids. The alveolar organoids consisting of type I and type II alveolar epithelial cells (AT1 and AT2, respectively) functionally simulate the alveolar epithelium. AT2 cells maintained in lung organoids serve as progenitor cells from which alveolar organoids derive. Moreover, alveolar organoids sustain a productive SARS-CoV-2 infection, albeit a lower replicative fitness was observed compared to that in airway organoids. We further optimized 2-dimensional (2D) airway organoids. Upon differentiation under a slightly acidic pH, the 2D airway organoids exhibit enhanced viral replication, representing an optimal in vitro correlate of respiratory epithelium for modeling the high infectivity of SARS-CoV-2. Notably, the higher infectivity and replicative fitness of the Omicron variant than an ancestral strain were accurately recapitulated in these optimized airway organoids. In conclusion, we have established a bipotential organoid culture system able to reproducibly expand the entire human respiratory epithelium in vitro for modeling respiratory diseases, including COVID-19.

Antibody therapy reverses biological signatures of COVID-19 progression (preprint)

Understanding who is at risk of progression to severe COVID-19 is key to effective treatment. We studied correlates of disease severity in the COMET-ICE clinical trial that randomized 1:1 to placebo or to sotrovimab, a monoclonal antibody for the treatment of SARS-CoV-2 infection. Several laboratory parameters identified study participants at greater risk of severe disease, including a high neutrophil-lymphocyte ratio (NLR), a negative SARS-CoV-2 serologic test and whole blood transcriptome profiles. Sotrovimab treatment in these groups was associated with normalization of NLR and the transcriptomic profile, and with a decrease of viral RNA in nasopharyngeal samples. Transcriptomics provided the most sensitive detection of participants who would go on to be hospitalized or die. To facilitate timely measurement, we identified a 10-gene signature with similar predictive accuracy. In summary, we identified markers of risk for disease progression and demonstrated that normalization of these parameters occurs with antibody treatment of established infection.

Novel pectin from crude polysaccharide of Syzygium aromaticum against SARS-CoV-2 activities by targeting 3CLpro (preprint)

To date, COVID-19 is still a severe threat to public health, hence specific effective therapeutic drugs development against SARS-CoV-2 is urgent needed. 3CLpro and PLpro and RdRp are the enzymes required for the SARS-CoV-2 RNA synthesis. Therefore, binding to the enzyme may interfere the enzyme function. Before, we found that sulfated polysaccharide binding to 3CLpro might block the virus replication. Hence, we hypothesize that negative charged pectin glycan may also impede the virus replication. Here we show that 922 crude polysaccharide from Syzygium aromaticum may near completely block SARS-CoV-2 replication. The inhibition rate was 99.9% (EC50 : 0.90 muM). Interestingly, 922 can associates with 3CLpro, PLpro and RdRp. We further show that the homogeneous glycan 922211 from 922 may specifically attenuate 3CL protease activity. The IC50s of 922 and 922211 against 3CLpro are 4.73 plusmn 1.05 muM and 0.18 plusmn 0.01 muM, respectively. Monosaccharide composition analysis reveals that 922211 with molecular weight of 78.7 kDa is composed of rhamnose, galacturonic acid, galactose and arabinose in the molar ratio of 8.21 : 37.81 : 3.58 : 4.49. The structure characterization demonstrated that 922211 is a homogalacturonan linked to RG-I pectin polysaccharide. The linear homogalacturonan part in the backbone may be partly methyl esterified while RG-I type part bearing 1, 4-linked alpha-GalpA, 1, 4-linked alpha-GalpAOMe and 1, 2, 4-linked alpha-Rhap. There are four branches attached to C-1 or C4 position of Rhamnose glycosyl residues on the backbone. The branches are composed of 1, 3-linked beta-Galp, terminal (T)-linked beta-Galp, 1, 5-linked alpha-Araf, T-linked alpha-Araf, 4-linked alpha-GalpA and/or 4-linked beta-GalpA. The above results suggest that 922 and 922211 might be a potential novel leading compound for anti-SARS-CoV-2 new drug development.

Mutations, Recombination and Insertion in the Evolution of 2019-nCoV (preprint)

BackgroundThe 2019 novel coronavirus (2019-nCoV or SARS-CoV-2) has spread more rapidly than any other betacoronavirus including SARS-CoV and MERS-CoV. However, the mechanisms responsible for infection and molecular evolution of this virus remained unclear. MethodsWe collected and analyzed 120 genomic sequences of 2019-nCoV including 11 novel genomes from patients in China. Through comprehensive analysis of the available genome sequences of 2019-nCoV strains, we have tracked multiple inheritable SNPs and determined the evolution of 2019-nCoV relative to other coronaviruses. ResultsSystematic analysis of 120 genomic sequences of 2019-nCoV revealed co-circulation of two genetic subgroups with distinct SNPs markers, which can be used to trace the 2019-nCoV spreading pathways to different regions and countries. Although 2019-nCoV, human and bat SARS-CoV share high homologous in overall genome structures, they evolved into two distinct groups with different receptor entry specificities through potential recombination in the receptor binding regions. In addition, 2019-nCoV has a unique four amino acid insertion between S1 and S2 domains of the spike protein, which created a potential furin or TMPRSS2 cleavage site. ConclusionsOur studies provided comprehensive insights into the evolution and spread of the 2019-nCoV. Our results provided evidence suggesting that 2019-nCoV may increase its infectivity through the receptor binding domain recombination and a cleavage site insertion. One Sentence SummaryNovel 2019-nCoV sequences revealed the evolution and specificity of betacoronavirus with possible mechanisms of enhanced infectivity.