COVID-19 Cases Research Articles

Scale-specific effects of urban landscape pattern on the COVID-19 epidemic in Hangzhou, China

Abstract Context Understanding the scale-specific effects of different landscape variables on the COVID-19 epidemics is critical for developing the precise and effective prevention and control strategies within urban areas. Objective Based on the landscape epidemiology framework, we analyzed the scale-specific effects of urban landscape pattern on COVID-19 epidemics in Hangzhou, China. Methods We collected COVID-19 cases in Hangzhou from 2020‒2022 and combined the datasets of land use and land cover (LULC) and social gathering point (SGP) to quantify the urban landscape pattern. Optimal general linear model with stepwise regression was applied to explore the dominant landscape factors driving the COVID-19 transmission in the city. Furthermore, multi-scale geographically weighted regression illustrated the spatial heterogeneity and scale specificity of these landscape variables’ effects to COVID-19 epidemic. Results Eight landscape variables of LULC and SGP patterns were identified which explained 68.5% of the variance in spatial risk of COVID-19. Different optimal bandwidths across these variables in MGWR indicated their scale-specific effects. LSI of green space enhanced the spatial risk across the entire region. The effects of landscape contagion, the number of water bodies, LSI of cropland and built-up areas, and the density of commercial houses were detected to vary between urban and suburban areas. The effects of LSI of water bodies and the density of shopping malls were found to vary among different districts. Conclusions In this study, we firstly discriminated the scale-specific effects of different landscape variables on the COVID-19 epidemic in the urban region. These findings can help to optimize the differentiated zoning prevention and control strategies for COVID-19 in cities and guide policy-making and urban planning at a multi-scale hierarchical perspective to improve public health and urban sustainability.

A study of the enablers and barriers to the collection of sociodemographic data by public health units in Ontario, Canada during the COVID-19 pandemic.

Collection and use of sociodemographic data (SDD), including race, ethnicity and income, are foundational to understanding health inequities. Ontario's public health units collected SDD as part of COVID-19 case management and vaccination activities. This research aimed to identify enablers and barriers to collecting SDD during COVID-19 case management and vaccination. As part of a larger mixed-method research study [1], qualitative methods were used to identify enablers and barriers to SDD collection during the COVID-19 pandemic. Purposive sampling was used to recruit participants from Ontario's 34 public health units. Sixteen focus groups and eight interviews were conducted virtually using Zoom. Interview data were transcribed and analyzed using inductive and deductive qualitative description. SDD collection enablers included: legally mandating SDD collection and having dedicated data systems, technological and legal supports, senior management championing SDD collection, establishing rapport and trust between staff and clients, and gaining insight from the experiences from local communities and other jurisdictions. Identified barriers to SDD collection included: provincial data systems being perceived as lacking user-friendliness, SDD collection "was not a priority," time and other constraints on building staff and client rapport, and perceived discomfort with asking and answering personal SDD questions. A combination of provincial and local organizational strategies including supportive data systems, training, and frameworks for data collection and use, are needed to normalize and scale up SDD collection by local health units beyond the context of the COVID-19 pandemic.

Transient anti-interferon autoantibodies in the airways are associated with recovery from COVID-19.

Preexisting anti-interferon-α (anti-IFN-α) autoantibodies in blood are associated with susceptibility to life-threatening COVID-19. However, it is unclear whether anti-IFN-α autoantibodies in the airways, the initial site of infection, can also determine disease outcomes. In this study, we developed a multiparameter technology, FlowBEAT, to quantify and profile the isotypes of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and anti-IFN-α antibodies in longitudinal samples collected over 20 months from the airways and blood of 129 donors spanning mild to severe COVID-19. We found that nasal IgA1 anti-IFN-α autoantibodies were induced after infection onset in more than 70% of mild and moderate COVID-19 cases and were associated with robust anti-SARS-CoV-2 immunity, fewer symptoms, and efficient recovery. Nasal anti-IFN-α autoantibodies followed the peak of host IFN-α production and waned with disease recovery, revealing a regulated balance between IFN-α and anti-IFN-α response. In contrast, systemic IgG1 anti-IFN-α autoantibodies appeared later and were detected only in a subset of patients with elevated systemic inflammation and worsening symptoms. These data reveal a protective role for nasal anti-IFN-α in the immunopathology of COVID-19 and suggest that anti-IFN-α autoantibodies may serve a homeostatic function to regulate host IFN-α after viral infection in the respiratory mucosa.

Clinical characteristics and antibody response to Omicron variants among solid carcinoma patients in China on the 2022.12–2023.4 wave of the COVID-19 pandemic

BackgroundChina experienced a surge of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variants after adjusting its zero-coronavirus disease 2019 (COVID-19) policy. Although infections with Omicron variants are generally less severe than infections with previous SARS-CoV-2 variants, the clinical characteristics, persistent symptoms, and antibody responses in solid carcinoma patients (SCPs) with COVID-19 during the Omicron wave are unclear.MethodsWe conducted a cross-sectional study in April 2023, recruiting healthy controls (HCs) from the community and SCPs from Zhejiang Provincial People’s Hospital. Serum samples were collected, and a questionnaire was used to assess SARS-CoV-2 infection status, including demographic characteristics, clinical manifestations, and “long COVID” symptoms. Humoral immune responses were analyzed by enzyme-linked immunosorbent assays (ELISAs) targeting immunoglobulin G (IgG) antibodies against the receptor-binding domain (RBD; Omicron BA.4/5) protein and cell culture-based neutralization assays against Omicron variants (BA.4/5, BF.7, XBB.1.5, and EG.5).ResultsIn total, 298 SCPs and 258 HCs were enrolled. Self-reported COVID-19 case rates were significantly lower in SCPs than in HCs (78.5% vs. 93.8%, P<0.001). Common COVID-19 symptoms were similar between the two groups, primarily comprising general (92.6% vs. 84.9%) and respiratory symptoms (51.9% vs. 48.2%) after acute infection. There was no significant difference in persistent symptoms at 1–3 months post-infection (P=0.353); fatigue was the most common symptom (45.0% vs. 44.8%). SCPs exhibited lower anti-RBD-IgG titers compared with HCs (1.061 vs. 1.978, P=0.001). The 50% pseudovirus neutralization titer (pVNT50) values for prevalent Omicron strains (BA.4/5 and BF.7) were lower in SCPs than in HCs (621.0 [288.8, 1333.0] vs. 894.1 [458.5, 1637.0] and 529.6 [215.3, 1264.5] vs. 463.1 [185.2, 914.0], respectively). Levels of antibodies against subsequent variants (XBB.1.5 and EG.5) also were reduced. There were no significant differences among carcinoma types in the levels of antibodies against Omicron variants. However, SCPs who received the SARS-CoV-2 vaccine or had COVID-19 during the Omicron wave displayed higher antibody levels.ConclusionsThis study elucidated the clinical and immunological characteristics of SCPs during the Omicron wave in China after the shift away from a zero-COVID-19 policy. Our findings provide insights regarding factors that influence COVID-19 symptoms and antibody levels in this population.

The Effect of Vitamin D Supplementation Post COVID-19 Infection and Related Outcomes: A Systematic Review and Meta-Analysis

Background: Vitamin D’s role in COVID-19 management remains controversial. This meta-analysis aimed to evaluate the efficacy of vitamin D supplementation in patients with SARS-CoV-2 infection, focusing on mortality, intensive care unit (ICU) admissions, intubation rates, and hospital length of stay (LOS). Methods: A systematic review of PubMed/MEDLINE, Scopus, Cochrane, and Google Scholar databases was conducted. Randomized controlled trials (RCTs) and analytical studies investigating vitamin D supplementation in COVID-19 patients were included. The meta-analysis was performed using STATA MP 18.5, employing random-effect or fixed-effect models based on heterogeneity. Results: Twenty-nine studies (twenty-one RCTs, eight analytical) were analyzed. Vitamin D supplementation significantly reduced ICU admissions (OR = 0.55, 95% CI: 0.37 to 0.79) in RCTs and analytical studies (OR = 0.35, 95% CI: 0.18 to 0.66). Intubation rates were significantly reduced in RCTs (OR = 0.50, 95% CI: 0.27 to 0.92). Mortality reduction was significant in analytical studies (OR = 0.45, 95% CI: 0.24 to 0.86) but not in RCTs (OR = 0.80, 95% CI: 0.61 to 1.04). Subgroup analyses revealed more pronounced effects in older patients and severe COVID-19 cases. LOS showed a non-significant reduction (mean difference = −0.62 days, 95% CI: −1.41 to 0.18). Conclusions: This meta-analysis suggests potential benefits of vitamin D supplementation in COVID-19 patients, particularly in reducing ICU admissions. However, the evidence varies across outcomes and patient subgroups. Discrepancies between RCTs and analytical studies highlight the need for further large-scale, well-designed trials accounting for baseline vitamin D status, standardized supplementation protocols, and patient characteristics to inform clinical guidelines for vitamin D use in COVID-19 management.

Pulmonary diffusing capacity among individuals recovering from mild to moderate COVID-19: a cross-sectional study

Impaired pulmonary diffusing capacity for carbon monoxide (DLCO) following COVID-19 has been consistently reported among individuals recovering from severe-critical infection. However, most long COVID cases follow non-severe COVID-19. We assessed DLCO among individuals with long COVID recovering from mild to moderate acute illness. A cross-sectional study of adults with long COVID, assessed at a COVID recovery clinic > 3 months following the onset of acute infection, during 2020–2021. Participants subjectively ranked their dyspnea severity based on its impact on their daily living and underwent comprehensive pulmonary function testing (PFT). Clinical correlates for impaired DLCO (defined as < 80%) were assessed using multivariable logistic regression models. A total of 458 individuals, their mean age 45 (SD 16) and 246 (54%) of whom are women, were evaluated at an average of ~ 4 months following acute COVID-19. The most frequent PFT impairment was reduced DLCO, identified among 67 (17%) of the cohort. Clinical correlates of impaired DLCO included women (odds ration [OR] 3.64, 95% confidence interval [CI] 1.78–7.45, p < 0.001), cigarette smoking (OR 2.25, 95% CI 1.14–4.43, p = 0.019), and moderate-severe dyspnea (OR 2.77, 95% CI 1.39–5.50, p = 0.004). BMI inversely correlated with DLCO (OR 0.90, 95% CI 0.85–0.96 per 1 unit, p = 0.002). Impaired DLCO was not uncommon among individuals recovering from mild to moderate COVID-19. Women are at a greater risk, and subjective dyspnea correlated with impaired DLCO. Clinicians can rely on self-reported significant dyspnea to guide further assessment.

Comprehensive In silico and In vitro evaluation of Plectranthus amboinicus essential oil: A promising inhibitor of SARS-CoV-2 B.1.1.529 Omicron variant, proinflammatory biomarkers and diabetes-related enzymes

Existing challenges, such as the viral SARS-CoV-2 B.1.1.529 Omicron variants, adverse reactions, and limited availability of drugs for COVID-19 continue to challenge global health. Severe inflammatory response associated with COVID-19 has been shown to worsen diabetic conditions and finding a range of treatment options for COVID-19 is significant. The research investigated the potential of Plectranthus amboinicus (Lour.) Spreng. (Lamiaceae) essential oil (PEO), known for its bioactive terpene content, as a multifaceted therapeutic agent. In silico and in vitro approaches were conducted to evaluate its inhibitory effects on the replication of Omicron variant, its ability to modulate proinflammatory biomarkers, and its impact on diabetes-related enzymes. PEO was extracted by hydrodistillation method. GC-MS analysis revealed 62 compounds. In silico molecular docking showed that the top ten PEO major components exhibited strong binding affinities with Omicron 3CL protease (-4.0 to −6.1 kcal/mol) and spike-RBD protein (-6.1 to −9.2 kcal/mol). PEO (6.25–200 μg mL⁻¹) significantly inhibited the B.1.1.529 Omicron SARS-CoV-2 3CL protease and Spike-RBD. PEO showed a cytotoxic effect at >80 μg mL⁻¹ in LPS-induced macrophage and inhibited production of TNF-α from 6.25 to 50 μg mL⁻¹, indicating its potential to mitigate the cytokine storm in link with severe COVID-19 cases. In vitro, PEO at 6.25–200 μg mL⁻¹ significantly inhibited α-amylase and α-glucosidase enzymes, suggesting that PEO components could modulate key enzymes involved in glucose metabolisms. These findings showed the potential of PEO as an antiviral, anti-inflammatory, and antidiabetic agent and offer an opportunity to further clinical investigations in testing the efficacy as an alternative approach to managing COVID-19 and its complications.

An integrated approach for decomposing time series data into trend, cycle and seasonal components

ABSTRACT This study presents a methodology for decomposing time series data into trend, seasonal, and cyclical components using the moving linear model approach by Kyo and Kitagawa (Journal of Business Cycle Research, 19(3): 373-397, 2023). Our approach integrates seasonal adjustment and decomposition into a single framework. We evaluated our approach with two case studies: examining daily COVID-19 case data and the Index of Industrial Production (IIP) in Japan, comparing the results to seasonally adjusted IIP data. Performance metrics included the discrimination power index and the variance of the adjusted cyclical component. Our findings show that our method effectively extracts business cycle information, achieving higher discrimination power and greater adjusted variance compared to seasonally adjusted IIP data, highlighting the superior performance of our integrated seasonal adjustment method. We compared the proposed approach with a state-space modelling method by introducing an overall stability as a new indicator. The results demonstrated the stability of the estimations obtained with our proposed method.

Clinical characteristics of COVID-19 patients admitted to the intensive care unit of the largest public-sector hospital in Karachi: A retrospective, observational study.

Objective: To characterize the clinical features of critically ill COVID-19 patients admitted to COVID-ICU and describe their outcomes. Study Design: Retrospective Observational study. Setting: Dr. Ruth K. M. Pfau Civil Hospital Karachi, Pakistan. Period: May 2020 to September 2021. Methods: The study aimed to investigate the clinical characteristics and outcomes of patients with confirmed or suspected COVID-19 who were admitted to the ICU. Patients in the study period confirmed or suspected COVID-19, admitted to the ICU for more than 24 hours, and committed to full treatment were included this study. Patients with COVID-19 discharged or died within 24 hours of admission were excluded. Results: The most commonly observed symptoms among the patients were shortness of breath (92.5%), fever (91.2%), cough without sputum (39.2%), altered consciousness (11.9%), and muscle aches (8.8%). Acute respiratory distress syndrome (ARDS) was identified as the most prevalent complication among COVID-19 patients, impacting 40.8% of the study population. A significant proportion of COVID-19 patients required mechanical ventilation and cardiac support. Specifically, (41.4%) of the patients required invasive mechanical ventilation, (47.4%) required non-invasive ventilation, and (26.3%) received cardiac support. Laboratory assessment showed that platelet counts varied significantly between survivors and non-survivors, with non-survivors exhibiting lower platelet counts. Gender differences were also observed among COVID-19 patients by age, with males having a higher mean age than females in all age categories, and the difference was statistically significant (p &lt; 0.001) in all age categories except for the 30-44 years age category (p = 0.087). Age-wise recovery and mortality rates were analyzed, and the results showed that among both deceased and recovered patients, the proportion of deceased patients increased with age, while the proportion of recovered patients increased until the age range of 45-59 years for both males and females. The study found that 136 of the patients survived while 275 of the patients succumbed to the disease. Among the survivors, (31.3%) were male, and (36.2%) were female. Conclusion: The study emphasizes the importance of monitoring patients for potential complications and providing them with supportive care. Early detection and management of severe cases of COVID-19 are critical in preventing complications and improving patient outcomes.

The impact of radiologists’ characteristics on the detection of COVID-19 in chest CT scans

PurposeTo retrospectively assess the relationships between radiologists’ characteristics and their performance in interpreting chest CTs for COVID-19 detection. MethodsUsing DetectedX software, performance data were collected online from 74 radiologists from 29 countries, who each interpreted 30 anonymized digital chest CTs (15 positive and 15 negative scans for COVID-19). Radiologist-specific information was also collected: radiology experience, radiological specialty, number of lung CTs read weekly, familiarity with and education about COVID-19 presentation, and suspected COVID-19 cases seen weekly. The influence of this radiologist-specific information on the radiologists’ sensitivity, specificity, and ROC AUC was determined using regression analysis. ResultsRadiologists without respiratory imaging specialization had greater ROC AUCs (0.83 vs. 0.70, p = .006) and sensitivities (74.0% vs. 47.7%, p = .002) than their specialized peers. Radiologists without COVID-19 case encounters had greater sensitivity (80.6% vs. 63.1%, p = .017) but lower specificity (71.1% vs. 83.4%, p = .014) than those who encountered at least one case weekly. ConclusionSpecialization and prior experience with COVID-19 may impact the interpretation of suspected COVID-19 chest CTs. Clinical significanceThese results show the importance of diverse expertise and continuous training in managing novel diseases like COVID-19. Incorporating varied perspectives and experiences could enhance diagnostic accuracy and ensure a more comprehensive approach to disease management. In the case of novel diseases, specialization may not provide the same advantage as with more familiar disorders. The diagnostic value of specific experience with a novel disorder may help to compensate for a lack of specialization in the field, particularly in emergent situations. While specialization is important, generalization also holds value and utility in appropriate contexts.

Can Massive Religious Festival Celebrations Encourage a Faster Spread of a Pandemic? The Case of COVID-19 in Israel.

This paper attempts to evaluate how massive religious festivalcelebrations can encourage the faster spread of any pandemic according to our problem statement, such as the case of COVID-19. For example, we evaluate Israel's three major religions, namely Judaism, Christianity, and the Islamic festival celebrations, respectively. Firstly, we have the traditional Jewish festivities such asHanukkah, Yom Kippur, Sukkot, and Rosh Hashanah. In the Christian's traditional festivities celebrations, we identified Christmas, Easter Day, and All Saints Day. Finally, the Muslim festivities ofMuharram and the Birthday of theHoly Prophet Mohamad. Thepurpose of thisstudy wasto evaluate if these nine massive religious festival celebrations are the main reasons for the large spread of COVID-19 in Israel directly or indirectly. In fact, we propose a new methodology to evaluate the impact of any massive religious festivalcelebration andthe fast spread of any pandemic everywhere and anytime. The new indicator is entitled "The National Spread Levels of Infectious Diseases Risk from Massive Religious Festivities Index" (National-SLIDRMRF-Index). Finally, the major finding in this research is that any massive religious events can generate an exponential number of COVID-19 cases constantly. Therefore, this research concluded that we urgentlyneed a standardized index to monitor and control the expansion of any pandemic such as COVID-19 among different religious groups in the same country. At the same time, we give different policy recommendations to the Israeli government to constantlykeep major controls and measures ofdifferent religious events inJerusalem.

Assessing the influence of nursing home size and care models on COVID-19 case and mortality rates

IntroductionThis study examines the impact of COVID-19 on older adults in traditional nursing homes, Green Houses (GHs), and Continuing Care Retirement Communities-Nursing Homes (CCRCNHs). MethodsCOVID-19 cases and deaths from CMS and LTCFocus data across 11 states from 6/2020 to 9/2022 were used, and Poisson regressions to compare care settings while adjusting for covariates. ResultsCCRCNH and GH residents were older (84.4 and 83.1 years) than those in traditional NHs (77.5 and 77.6 years, p < 0.0001), with more female and White individuals. COVID-19 risk was higher in CCRCNHs (RR 1.51, 95 % CI 1.10–2.07), large NHs (RR 1.57, 95 % CI 1.14–2.15), and highest in small NHs (RR 1.80, 95 % CI 1.32–2.47). Mortality rates across NH types showed no significant difference. ConclusionThe study shows that smaller, person-centered GHs are more effective in controlling COVID-19 infection, suggesting a need to rethink care models to incorporating GH features for better outcomes.GEORGE2 07-AUG-2024 11:31.

Spatiotemporal Ecologic Analysis of COVID-19 Vaccination Coverage and Outcomes, Oklahoma, USA, February 2020-December 2021.

Data on COVID-19 cases, deaths, hospitalizations, and vaccinations in Oklahoma, USA, have not been systematically described. The relationship between vaccination and COVID-19-related outcomes over time has not been investigated. We graphically described data collected during February 2020-December 2021 and conducted spatiotemporal modeling of monthly increases in COVID-19 cumulative death and hospitalization rates, adjusting for cumulative case rate, to explore the relationship. A 1 percentage point increase (absolute change) in the cumulative vaccination rate was associated with a 6.3% (95% CI 1.4%-10.9%) relative decrease in death outcome during April-June 2021, and a 1.9% (95% CI 1.1%-2.6%) relative decrease in death outcome and 1.1% (95% CI 0.5%-1.7%) relative decrease in hospitalization outcome during July-December 2021; the effect on hospitalizations was driven largely by data from urban counties. Our findings from Oklahoma suggest that increasing cumulative vaccination rates might reduce the increase in cumulative death and hospitalization rates from COVID-19.

In silico exploration of phytocompounds from AYUSH-64 medicinal plants against SARS CoV-2 RNA-dependent RNA polymerase

BackgroundThe AYUSH 64 formulation helps to treat mild to moderate cases of COVID-19. Although several drugs have been proposed to combat COVID-19, no medication is available for SARS-CoV-2 infection. The RNA-dependent RNA polymerase (RdRp) is the pivotal enzyme of SARS-CoV-2 replication, so it could be considered a better drug target for experimental studies. ObjectiveThe AYUSH-64 formulation plants exhibited multiple therapeutic properties; thus, the present study aims to screen the phytocompounds of these plants against SARS CoV2 RdRp to identify specific compounds that could potentially affect COVID-19 infection. Materials and methodsPatchDock and AutoDock tools were used for docking experiments. MD simulations and Density Functional Theory (DFT) calculations of protein-ligand Picroside-I and Remdesivir complexes were carried out in GROMACS v2019.4 and Gaussian 09 software, respectively. ResultsAmong the tested, five phytocompounds (Picroside I, Oleanolic acid, Arvenin I, II, and III) from AYUSH-64 medicinal plants showed possible binding with RdRp catalytic residues (Ser759, Asp760, and Asp761). Of these, Picroside I exhibited hydrogen bond interactions with NTP entry channel residues (Arg553 and Arg555). The MM-PBSA free energy, RMSD, Rg, PCA, and RMSF analysis suggested that the Picroside I complex showed stable binding interactions with RdRp in the 50 ns simulation. In addition to this, Picroside I revealed its robust and attractive nature toward the target protein, as confirmed by DFT. ConclusionThe results of this study have proposed that Picroside I from AYUSH 64 medicinal plant compounds was the selective binder of catalytic and NTP entry channel residues of SARS-CoV2 RdRp thereby; it may considered as a potential inhibitor of SARS-CoV2 RdRp.

Effectiveness of Original Monovalent and Bivalent COVID-19 Vaccines Against COVID-19-Associated Hospitalization and Severe In-Hospital Outcomes Among Adults in the United States, September 2022-August 2023.

Assessments of COVID-19 vaccine effectiveness are needed to monitor the protection provided by updated vaccines against severe COVID-19. We evaluated the effectiveness of original monovalent and bivalent (ancestral strain and Omicron BA.4/5) COVID-19 vaccination against COVID-19-associated hospitalization and severe in-hospital outcomes. During September 8, 2022 to August 31, 2023, adults aged ≥ 18 years hospitalized with COVID-19-like illness were enrolled at 26 hospitals in 20 US states. Using a test-negative case-control design, we estimated vaccine effectiveness (VE) with multivariable logistic regression adjusted for age, sex, race/ethnicity, admission date, and geographic region. Among 7028 patients, 2924 (41.6%) were COVID-19 case patients, and 4104 (58.4%) were control patients. Compared to unvaccinated patients, absolute VE against COVID-19-associated hospitalization was 6% (-7%-17%) for original monovalent doses only (median time since last dose [IQR] = 421 days [304-571]), 52% (39%-61%) for a bivalent dose received 7-89 days earlier, and 13% (-10%-31%) for a bivalent dose received 90-179 days earlier. Absolute VE against COVID-19-associated invasive mechanical ventilation or death was 51% (34%-63%) for original monovalent doses only, 61% (35%-77%) for a bivalent dose received 7-89 days earlier, and 50% (11%-71%) for a bivalent dose received 90-179 days earlier. Bivalent vaccination provided protection against COVID-19-associated hospitalization and severe in-hospital outcomes within 3 months of receipt, followed by a decline in protection to a level similar to that remaining from previous original monovalent vaccination by 3-6 months. These results underscore the benefit of remaining up to date with recommended COVID-19 vaccines.

Comparison of the therapeutic effect of Paxlovid and Azvudine in the treatment of COVID-19: A retrospective study

BackgroundCOVID-19 pneumonia has spread across China and globally since late 2019, becoming a pandemic. Its extremely contagious nature as well as high morbidity and mortality rates have attracted widespread attention globally. For the treatment of SARS-CoV-2 pneumonia, two commonly used antiviral drugs in the clinic are nirmatrelvir/ritonavir(Paxlovid) and Azvudine, while the therapeutic efficacy of the two drugs and their impact on patient prognosis remain inconclusive. Therefore, the aim of this study is to investigate the effects of two antiviral drugs, Azvudine and Paxlovid, on the disease development and prognosis of patients with COVID-19. MethodsThis study collected and analyzed in Inner Mongolia hospital treated 267 cases of COVID - 19 patients. According to the use of antiviral medications, the participants in this experiment were split into the Azvudine and Paxlovid groups. The effectiveness of the medications was evaluated using the length of hospitalization, Nucleic acid into negative time for the first time, and laboratory indices such as total protein, lymphocytes, leukocytes, albumin, creatinine, and platelets. ResultsCompared with the Azvudine group, patients in the Paxlovid group had a shorter recovery time, a higher degree of rise in lymphocytes, a faster recovery of the immune system, a lower rise in creatinine, and a lesser renal burden, but patients in the Paxlovid group had a greater decrease in total protein. ConclusionIn assessing patient conditions for treatment selection, Paxlovid may be preferable for individuals with renal insufficiency or those exhibiting compromised immune responses. Conversely, for patients experiencing malnutrition or cirrhotic hypoproteinemia, Azvudine could be considered to mitigate the reduction in protein levels.

Mutational and evolutionary dynamics of non-structural and spike proteins from variants of concern (VOC) of SARS-CoV-2 in India

Monitoring the genetic diversity and emerging mutations in SARS-CoV-2 remains crucial for understanding its evolution, given the virus's persistence in India. This study analyzes lineage dynamics, mutation screening, structural analysis, and phylodynamics of SARS-CoV-2 variants of concern (VOC) in India from October 2020 to September 2023. The predominant variants identified were alpha, beta, delta, and omicron, with delta and omicron making up 76.05 % of sequenced genomes. The B.1.617.2 lineage of the delta variant was the major contributor to COVID-19 cases before the rise of omicron. Mutation screening of non-structural proteins (NSPs) and spike proteins revealed distinct profiles for each VOC. Co-mutation patterns were analyzed, showing structural and energetic alterations. Phylogenetic analysis indicated that nsp1, nsp3, nsp4, nsp13, and nsp14 were strongly associated with increased mutation load. The study also highlighted that nsp14 and spike have similar mutability patterns, underscoring nsp14's critical role in SARS-CoV-2 infectivity and persistence. This research provides a comprehensive view of SARS-CoV-2's evolution and persistence in India.

ANALYSIS FACTORS AFFECTING COVID-19 MORTALITY USING COUNT REGRESSION

The ”2019 novel coronavirus” known as “ the 2019-nCoV” or simply“COVID-19” has been declared by the World Health organization (WHO), in first quarter of 2020, as a world pandemic and a public health emergency of international concern. Alas, many details related to the COVID-19 have remained unsolved completely. The success of government strategies in fighting the COVID-19 relays mainly on the results from epidemiological or statistical studies. Statistical models play a major role in providing reliable results based on appropriate analyses. Traditional (one-part) models, mixture models and mixed-effects models for counts are used to investigate effects of the WHO-regions and Cumulated COVID-19 cases on the outcome variable COVID-19 new deaths tolls. Overall result reveals there is a strong association between number of new deaths COVID-19 with predictors including the WHO regions and cumulated cases.Besides, models that account for the overdispersion feature have smallest AICs and have reasonable regression model fits.

Exploring the air pollution with particulate matter - PM10, COVID-19 cases evolution in Romania and exposure to aeroallergens

Exploring the air pollution with particulate matter - PM10, COVID-19 cases evolution in Romania and exposure to aeroallergens

Estimation of Epidemiological Parameters for COVID-19 Cases in Burkina Faso Using African Vulture Optimization Algorithm (AVOA)

In this paper, we present a mathematical model that accounts for virus transmission through deceased individuals to simulate the dynamics of COVID-19 spread in Burkina Faso. The existence and uniqueness of the model’s solution have been proven. The basic reproduction number was calculated using the Jacobian determinant method. The stability of the disease-free and endemic equilibrium points was studied. To estimate the model parameters, we used African Vulture Optimization Algorithm (AVOA). We then used this algorithm to estimate the parameters of the developed model using daily reported COVID-19 cases in Burkina Faso from March 11 to April 20, 2020. The results obtained show that the proposed model is more realistic for simulating the spread of COVID-19 in Burkina Faso.