A stochastic SIQR epidemic model with Lévy jumps and three-time delays.

Isolation and vaccination are the two most effective measures in protecting the public from the spread of illness. The SIQR model with vaccination is widely used to investigate the dynamics of an infectious disease at population level having the compartments: susceptible, infectious, quarantined and recovered. The paper mainly aims to extend the deterministic model to a stochastic SQIR case with Lévy jumps and three-time delays, which is more suitable for modeling complex and instable environment. The existence and uniqueness of the global positive solution are obtained by using the Lyapunov method. The dynamic properties of stochastic solution are studied around the disease-free and endemic equilibria of the deterministic model. Our results reveal that stochastic perturbation affect the asymptotic properties of the model. Numerical simulation shows the effects of interested parameters of theoretical results, including quarantine, vaccination and jump parameters. Finally, we apply both the stochastic and deterministic models to analyze the outbreak of mutant COVID-19 epidemic in Gansu Province, China.

Chinese expert consensus on intestinal microecology and management of digestive tract complications related to tumor treatment (version 2022).

The human gut microbiota represents a complex ecosystem that is composed of bacteria, fungi, viruses, and archaea. It affects many physiological functions including metabolism, inflammation, and the immune response. The gut microbiota also plays a role in preventing infection. Chemotherapy disrupts an organism's microbiome, increasing the risk of microbial invasive infection; therefore, restoring the gut microbiota composition is one potential strategy to reduce this risk. The gut microbiome can develop colonization resistance, in which pathogenic bacteria and other competing microorganisms are destroyed through attacks on bacterial cell walls by bacteriocins, antimicrobial peptides, and other proteins produced by symbiotic bacteria. There is also a direct way. For example, Escherichia coli colonized in the human body competes with pathogenic Escherichia coli 0157 for proline, which shows that symbiotic bacteria compete with pathogens for resources and niches, thus improving the host's ability to resist pathogenic bacteria. Increased attention has been given to the impact of microecological changes in the digestive tract on tumor treatment. After 2019, the global pandemic of novel coronavirus disease 2019 (COVID-19), the development of novel tumor-targeting drugs, immune checkpoint inhibitors, and the increased prevalence of antimicrobial resistance have posed serious challenges and threats to public health. Currently, it is becoming increasingly important to manage the adverse effects and complications after chemotherapy. Gastrointestinal reactions are a common clinical presentation in patients with solid and hematologic tumors after chemotherapy, which increases the treatment risks of patients and affects treatment efficacy and prognosis. Gastrointestinal symptoms after chemotherapy range from nausea, vomiting, and anorexia to severe oral and intestinal mucositis, abdominal pain, diarrhea, and constipation, which are often closely associated with the dose and toxicity of chemotherapeutic drugs. It is particularly important to profile the gastrointestinal microecological flora and monitor the impact of antibiotics in older patients, low immune function, neutropenia, and bone marrow suppression, especially in complex clinical situations involving special pathogenic microbial infections (such as clostridioides difficile, multidrug-resistant Escherichia coli, carbapenem-resistant bacteria, and norovirus).

Beyond Accessibility: A Multidimensional Evaluation of Urban Park Equity in Yangzhou, China

Evaluating park equity can help guide the advancement of sustainable and equitable space policies. Previous studies have mainly considered accessibility when evaluating park equity while ignoring the selectivity and convenience of entering parks and residents’ recognition of parks. Measuring equity based mainly on spatial thinking has resulted in the social aspects of parks receiving insufficient attention. In this study, we therefore integrated the spatial and social equity of parks and developed a multidimensional framework to evaluate park equity in four dimensions: accessibility (Ai), diversity (Di), convenience (Ci), and satisfaction (Si). Empirical analysis from Yangzhou, China showed that: (1) in Yangzhou’s built-up districts, 23.43% of the communities received high- or relatively high-level park access but 17.72% received little or no park access. (2) The Gini coefficient indicated that all three dimensions showed a mismatch with population distribution, except for satisfaction (Si), which showed a relatively reasonable match. (3) Park access was generally better in communities with better locations, environments, and facilities. High-income groups enjoyed significantly better park access than low- and middle-income groups. These findings could help urban planners and policymakers develop effective policies to reduce inequality in park access.

A Smartphone-Based Detection Method of Colloidal Gold Immunochromatographic Strip

The outbreak of the new coronavirus (SARS-CoV-2) infection has become a global public health crisis. Antigen detection strips (colloidal gold) can be widely used in novel coronavirus clinical screening and can even be extended to home self-testing, which provides a practical and effective way for people to obtain health status information away from the crowd. In this paper, a colloidal gold detection system without complex devices is proposed, which is based on smartphone usage along with a mobile-phone software embedded with normalization algorithms and a special designed background paper. The basic principle of the device relies on image processing. First, the data of the green channel of the image captured by a smartphone are selected to be processed. Second, the calibration curves are established using standard black and white card, and the calibration values under different detection environments are obtained by calibration curves. Finally, to verify the validity of the proposed method, various standard solutions with different concentrations are tested. Results show that this method can eliminate the influence of different environments on the test results, the test results in different detection environments have good stability and the variation coefficients are less than 5%. It fully proves that the detection system designed in this paper can detect the result of colloidal gold immunochromatographic strip in time, conveniently and accurately in different environments.

Multi-Model Selection and Analysis for COVID-19

In the face of an increasing number of COVID-19 infections, one of the most crucial and challenging problems is to pick out the most reasonable and reliable models. Based on the COVID-19 data of four typical cities/provinces in China, integer-order and fractional SIR, SEIR, SEIR-Q, SEIR-QD, and SEIR-AHQ models are systematically analyzed by the AICc, BIC, RMSE, and R means. Through extensive simulation and comprehensive comparison, we show that the fractional models perform much better than the corresponding integer-order models in representing the epidemiological information contained in the real data. It is further revealed that the inflection point plays a vital role in the prediction. Moreover, the basic reproduction numbers R0 of all models are highly dependent on the contact rate.

Gut Microbiota May Not Be Fully Restored in Recovered COVID-19 Patients After 3-Month Recovery.

Coronavirus disease 2019 (COVID-19) has infected over 124 million people worldwide. In addition to the development of therapeutics and vaccines, the evaluation of the sequelae in recovered patients is also important. Recent studies have indicated that COVID-19 has the ability to infect intestinal tissues and to trigger alterations of the gut microbiota. However, whether these changes in gut microbiota persist into the recovery stage remains largely unknown. Here, we recruited seven healthy Chinese men and seven recovered COVID-19 male patients with an average of 3-months after discharge and analyzed their fecal samples by 16S rRNA sequencing analysis to identify the differences in gut microbiota. Our results suggested that the gut microbiota differed in male recovered patients compared with healthy controls, in which a significant difference in Chao index, Simpson index, and ß-diversity was observed. And the relative abundance of several bacterial species differed clearly between two groups, characterized by enrichment of opportunistic pathogens and insufficiency of some anti-inflammatory bacteria in producing short chain fatty acids. The above findings provide preliminary clues supporting that the imbalanced gut microbiota may not be fully restored in recovered patients, highlighting the importance of continuous monitoring of gut health in people who have recovered from COVID-19.

Longitudinal multi-omics transition associated with fatality in critically ill COVID-19 patients.

PURPOSE: Critically ill COVID-19 patients have significantly increased risk of death. Although several circulating biomarkers are thought to be related to COVID-19 severity, few studies have focused on the characteristics of critically ill patients with different outcomes. The objective of this study was to perform a longitudinal investigation of the potential mechanisms affecting the prognosis of critically ill COVID-19 patients. METHODS: In addition to clinical data, 113 whole blood samples and 85 serum samples were collected from 33 severe and critical COVID-19 patients without selected comorbidities. Multi-omics analysis was then performed using longitudinal samples. RESULTS: Obvious transcriptional transitions were more frequent in critical survivors than in critical non-survivors, indicating that phase transition may be related to survival. Based on analysis of differentially expressed genes during transition, the erythrocyte differentiation pathway was significantly enriched. Furthermore, clinical data indicated that red blood cell counts showed greater fluctuation in survivors than in non-survivors. Moreover, declining red blood cell counts and hemoglobin levels were validated as prognostic markers of poor outcome in an independent cohort of 114 critical COVID-19 patients. Protein-metabolite-lipid network analysis indicated that tryptophan metabolism and melatonin may contribute to molecular transitions in critical COVID-19 patients with different outcomes. CONCLUSIONS: This study systematically and comprehensively depicted the longitudinal hallmarks of critical COVID-19 patients and indicated that multi-omics transition may impact the prognosis. TAKE HOME MESSAGE: Frequent transcriptional phase transitions may contribute to outcome in critically ill COVID-19 patients. Furthermore, fluctuation in red blood cell and hemoglobin levels may relate to poor prognosis. The biological function of melatonin was suppressed in COVID-19 non-survivors, which may provide a potential theoretical basis for clinical administration.

2019-nCoV Transmission in Hubei Province, China: Stochastic and Deterministic Analyses

Currently, a novel coronavirus (2019-nCoV) causes an outbreak of viral pneumonia in Hubei province, China. In this paper, stochastic and deterministic models are proposed to investigate the transmission mechanism of 2019-nCoV from 15 January to 5 February 2020 in Hubei province. For the deterministic model, basic reproduction number R-0 is defined and endemic equilibrium is given. Under R-0>1, quasi-stationary distribution of the stochastic process is approximated by Gaussian diffusion. Residual, sensitivity, dynamical, and diffusion analyses of the models are conducted. Further, control variables are introduced to the deterministic model and optimal strategies are provided. Based on empirical results, we suggest that the first and most important thing is to control input, screening, treatment, and isolation.

A comparison of mortality-related risk factors of COVID-19, SARS, and MERS: A systematic review and meta-analysis.

OBJECTIVE: Coronavirus Disease 2019 (COVID-19) is a pandemic. This systematic review compares mortality risk factors including clinical, demographic and laboratory features of COVID-19, Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS). The aim is to provide new strategies for COVID-19 prevention and treatment. METHODS: We performed a systematic review with meta-analysis, using five databases to compare the predictors of death for COVID-19, SARS and MERS. A random-effects model meta-analysis calculated odds ratios (OR) and 95% confidence intervals (95% CI). RESULTS: 845 articles up through 11/4/2020 were retrieved, but only 28 studies were included in this meta-analysis. The results showed that males had a higher likelihood of death than females (OR = 1.82, 95% CI 1.56-2.13). Age (OR = 7.86, 95% CI 5.46-11.29), diabetes comorbidity (OR = 3.73, 95% CI 2.35-5.90), chronic lung disease (OR = 3.43, 95% CI 1.80-6.52) and hypertension (OR = 3.38, 95% CI 2.45-4.67) were the mortality risk factors. The laboratory indicators lactic dehydrogenase (OR = 37.52, 95% CI 24.68-57.03), C-reactive protein (OR = 12.11, 95% CI 5.24-27.98), and neutrophils (OR = 17.56, 95% CI 10.67-28.90) had stronger correlations with COVID-19 mortality than with SARS or MERS mortality. Consolidation and ground-glass opacity imaging features were similar among COVID-19, SARS, and MERS patients. CONCLUSIONS: COVID-19's mortality factors are similar to those of SARS and MERS. Age and laboratory indicators could be effective predictors of COVID-19 mortality outcomes.