Wuhan Research Articles

Safety Evaluation for Fabricated Small Box Girder Bridges Based on Fuzzy Analytic Hierarchy Process and Monitoring Data.

During the operation of fabricated small box girder bridges, which face safety issues such as structural degradation and failure, there is an urgent need to propose a safety evaluation method to cope with the possible risks. This article quantitatively evaluates the safety state of a fabricated small box girder bridge in Wuhan City based on Fuzzy Analytic Hierarchy Process (FAHP) and structural health monitoring (SHM) data. Firstly, the FAHP model is established, and stress, deformation, and temperature are selected as evaluation factors. The safety thresholds of stress and deformation are determined by combining the industry specifications and the historical statistical patterns of the massive SHM data. The temperature field of the bridge is simulated and analyzed by combining ANSYS, HYPERMESH, and TAITHREM, and the most unfavorable temperature gradient is determined as a threshold for the safety evaluation. Finally, the scores of indexes of the bridge are determined based on the measured SHM data, which in turn provides a quantitative description of the safety state. The results show that the thresholds determined by the joint industry specifications and the massive SHM data are reasonable; the temperature field simulation model established in this article is consistent with the measured results, and can accurately determine the temperature gradient of the bridge. The safety evaluation result from the FAHP model is the same as the field test results, which verifies the effectiveness and applicability of the proposed method to actual bridge projects.

Study on the Distribution Characteristics and Risk Assessment of Antibiotics and Resistance Genes in Water Sources of Wuhan.

In contemporary society, the improper use of antibiotics leads to their persistent presence in the ecological environment. Due to the diverse physical and chemical properties of antibiotics, their spatial and temporal distribution in the environment varies. Moreover, antibiotics can stimulate the emergence of antibiotic resistance genes (ARGs), which complicates the monitoring and regulation of antibiotics and poses a significant threat to both aquatic and terrestrial environments. This study investigated the distribution of 15 antibiotics and 11 typical ARGs across four categories at 19 sites of drinking water sources in Wuhan, China. The findings revealed that the concentration of antibiotics during the dry season (nd~61,883 ng/L) was significantly higher compared to both the normal water season (nd~49,883 ng/L) and the wet season (nd~28,686 ng/L). Sulfamethoxazole (SMX), sulfamethoxazole (SMD), sulfadiazine (SD), and roxithromycin (RTM) were the predominant antibiotics in the target water environments. The study indicated that most of the antibiotics analyzed posed little to no risk to aquatic organisms. The primary ARGs detected in the surface water of the study area were sul1, qnrD, and tetO. Furthermore, some ARGs showed a negative correlation with their respective antibiotics. Additional research is necessary to evaluate the impact of these emerging pollutants (antibiotics and ARGs) on the safety of high-quality drinking water for residents in Wuhan City.

Pano2Geo: An efficient and robust building height estimation model using street-view panoramas

Building height serves as a crucial parameter in characterizing urban vertical structure, which has a profound impact on urban sustainable development. The emergence of street-view data offers the opportunity to observe urban 3D scenarios from the human perspective, benefiting the estimation of building height. In this paper, we propose an efficient and robust building height estimation model, which we call the Pano2Geo model, by precisely projecting street-view panorama (SVP) coordinates to geospatial coordinates. Firstly, an SVP refinement stratagem is designed, incorporating NENO rules for observation quality assessment from four aspects: number of buildings, extent of the buildings, number of nodes, and orthogonal observations, followed by the application of the art gallery theorem to further refine the SVPs. Secondly, the Pano2Geo model is constructed, which provides a pixel-level projection transformation from SVP coordinates to 3D geospatial coordinates for locating the height features of buildings in the SVP. Finally, the valid building height feature points in the SVP are extracted based on a slope mutation test, and the 3D geospatial coordinates of the building height feature points are projected using the Pano2Geo model, so as to obtain the building height. The proposed model was evaluated in the city of Wuhan in China, and the results indicate that the Pano2Geo model can accurately estimate building height, with an average error of 1.85 m. Furthermore, compared with three state-of-the-art methods, the Pano2Geo model shows superior performance, with only 10.2 % of buildings have absolute errors exceeding 2 m, compared to the Map-image-based (27.2 %), Corner-based (16.8 %), and Single-view-based (13.9 %) height estimation methods. The SVP refinement method achieves optimal observation quality with less than 50 % of existing SVPs, leading to highly efficient building height estimation, particularly in areas of a high building density. Moreover, the Pano2Geo model exhibits robustness in building height estimation, maintaining errors within 2 m even as building shape complexity and occlusion degree increase within the SVP. Our source dataset and code are available at https://github.com/Giser317/Pano2Geo.git.

Integrating key ecosystem services to study the spatio-temporal dynamics and determinants of ecosystem health in Wuhan’s central urban area

The central areas of many Chinese cities have experienced large-scale urbanization in recent decades, a trend that is affecting the quality of life of residents and posing challenges to the sustainable development of urban ecosystems. Hence, it is vital to conduct assessments of urban ecosystems’ health conditions to ensure their sustainability. In this study, the spatial and temporal dynamics of ecosystem health in the central city of Wuhan were analyzed using the Vigor-Organization-Resilience-Service (VORS) model. The sensitivity of ecosystem health at different scales was also investigated using hierarchical health assessment delineation and random forest regression methods. The results showed that the composite index of ecosystem health has been declining since 2000, highlighting the negative impacts of shrinking ecological space, declining service capacity and urban expansion. Health zoning divides areas into five categories. Meanwhile, the health zones are located in areas of dense shrubs, cropland and water bodies on the edge of the central city, while the weak zones are mainly in the core of the city, which is 99.33 % impervious surface. The main factors influencing ecosystem health, including impervious surface area, water bodies and topography, vary from region to region. The study proposes targeted ecological management strategies for different health zones in Wuhan, emphasizing ecosystem protection and providing guidance for sustainable urban development.

Evaluation of Ecological Environment Quality and Analysis of Influencing Factors in Wuhan City Based on RSEI

It is crucial to assess the quality of ecological environments in urban areas and investigate the driving forces that would affect urban ecological environments. Utilizing the GEE platform, RSEI was computed by us for Wuhan from 1990 to 2020. Employing geodetector tools and the PLS-SEM approach, driving factors for ecological environment quality in Wuhan were discussed. The overall trend of ecological environment quality in Wuhan was to decline at first and then rise from 1990 to 2020 spatial aggregation characteristics of RSEI were significant; moreover, land use, location, population density, and GDP were included as the main influence factors causing spatial differentiation of RSEI; each influence factor’s effect was also different. Over the past three decades, a fluctuating decline has been exhibited by ecological environment quality in Wuhan. Central urban areas have poor ecological environment quality, while southern and northern distant urban zones have superior ecological environment quality. Clustering is shown to be significant spatially by both. The main influencers of ecological quality in Wuhan are human geographic factors, while natural geographic factors have comparatively minor impacts.

Roles and Responsibilities of Coaches Towards Their Players in a Physical Education Institution in Wuhan China: Basis for Coaches Training Program

Roles and Responsibilities of Coaches Towards Their Players in a Physical Education Institution in Wuhan China: Basis for Coaches Training Program

Evaluating the Impact of Different Genetic Variants on the Prognosis of Patient with COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in December 2019 in Wuhan (China). It soon became widespread so that the World Health Organization (WHO) declared the outbreak of COVID-19 as a pandemic crisis. This disease has caused significant morbidity and mortality in the world. Clinical studies reported that there is a significant correlation between genders, immunogenetic variants, serum levels of some circulating factors, blood groups, and different races with severity and mortality of COVID-19 patients. Hence, some studies have investigated the role of individual genetic background in the susceptibility and vulnerability to COVID-19 infection. It is proposed that host genetic polymorphisms affect the onset and progression of COVID-19 infection and could dramatically impact the virus life cycle. This paper aims to review the state-of-the-art research on the roles of genetic variants in host cell membrane proteins and blood circulation factors in the prognosis of patients with COVID-19.

Layout Optimization of Logistics and Warehouse Land Based on a Multi-Objective Genetic Algorithm—Taking Wuhan City as an Example

Layout Optimization of Logistics and Warehouse Land Based on a Multi-Objective Genetic Algorithm—Taking Wuhan City as an Example

Measurement of Vitamin D Level among Covid-19 Patients and its Correlation with Severity of the Disease

Abstract Background Coronavirus disease 2019 (covid-19) is defined as illness caused by a novel coronavirus now called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which was first identified among an outbreak of respiratory illness cases in Wuhan City, China. Vitamin D is known to play a key role in the maintenance of bone health and calcium–phosphorus metabolism, yet many other functions of this vitamin have been recently postulated, such as modulation of the immune response in both infectious and autoimmune diseases. Different studies showed that severity of covid-19 infection is directly related to vitamin D level. Methods This is an observational cross-sectional study, which includes 80 COVID-19 patients, and admitted in the ward and ICU of EL Medany Hospital, EL Demerdash and EL Obour specialized hospital. All patients had positive PCR for COVID-19. Chest CT without contrast was done for all patients and categorized according to CORAD staging. Serum vitamin D level was measured, besides laboratory inflammatory markers (CRP, ferritin, d-dimer), kidney and liver function tests, and complete blood picture. Results Our study included 80 patients; 33 males and 47 females with mean age of (51±10.5 years). Measured Vitamin D level range was (10±9 ng/mL). It was found that male patients had higher level of serum vitamin D (12.6±8.6 ng/mL) than female patients (11.5±9.5 ng/mL) but with no statistically significant difference. The commonest presentations were sore throat (97.5%), and fever (93.75%). COVID-19 patients presenting with cough and fever had highly significantly lower levels of vitamin D than patients not presenting by these symptoms (P-value 0.006, 0.032) respectively. In the current study, patients with CORAD 5 in chest CT had the lowest vitamin D level (9.6±7.8 ng/mL), compared to patients with CORAD 3 (13.6±9.7 ng/mL), and CORAD 4 (11.8 ±8.8 ng/mL). According to the correlation analysis, a decrease in vitamin D levels was associated with more severe COVID-19 cases, with significantly higher blood levels of inflammatory markers CRP and ferritin (P-value 0.02, 0.01). No correlation was found between vitamin D levels and hemoglobin level, white cell count, platelet count, or D-Dimer. Conclusion Our findings suggest that the COVID-19-positive individuals with lower vitamin D levels, had significantly higher blood levels of inflammatory markers (Ferritin and CRP), and increased frequencies of ground-glass opacity appearance in chest CT scans. Accordingly, vitamin D deficiency may be a marker of poor prognosis in COVID-19 patients.

Elevation in Liver Enzymes as a Predictor for COVID-19 Severity

Abstract Background The coronavirus disease 2019 (COVID-19) started in December of 2019 as a cluster of pneumonia cases of unclear etiology in Wuhan city of Hubei province in China. Later, it was found to be caused by a coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease rapidly spread throughout the world, becoming a pandemic, and as of April, 2022, there were more than 500 million cases worldwide with more than 6 million deaths. It is postulated that the virus enters the human body by binding to the angiotensin-converting enzyme receptor-2 (ACE-2) with the help of spike protein on its cell membrane. Aim of the Work To compare the serum liver chemistries such as hepatic transaminases to evaluate whether they can predict severity and mortality in COVID-19. Patients and Methods A comparative cross-sectional study for 6 months in Ain-Shams University hospitals, we studied 100 hospitalized patients with confirmed COVID-19 by RT- PCR for SARS- CoV-2. They included 70 patients with non-severe COVID-19 and 30 patients with severe COVID- 19 on hospital admission. This classification was based on the quick COVID-19 severity index (qCSI) and CT- severity index. Results The results of our study showed that levels of inflammatory markers such as CRP, serum ferritin, d-dimer, and procalcitonin were significantly higher in the severe group when compared to the non-severe group. This could be an indicator of a more intense inflammatory state in patients with severe COVID- 19 admitted to ICU. Our study showed that 40% of the severe group admitted to the ICU passed away. In our study, the median levels for ALT, AST at admission were 51 and 46 U/L, respectively, which are considered higher than the upper limit of normal levels. Our study showed that during hospitalization, the group of patients with severe COVID-19 who were admitted to ICU had significantly higher prevalence of abnormal ALT levels when compared to the non- severe group (86% versus 32%, respectively). Conclusion Our study showed that patients with severe COVID-19 have significantly higher levels of AST and ALT and that, on admission, patients with abnormal ALT and AST levels have significantly higher odds for developing severe COVID-19 compared to patients with normal levels. We confirm the importance of monitoring liver enzymes in hospitalized patients with COVID-19 as patients with abnormally elevated AST and ALT are more expected to progress to severe COVID- 19 which have prognostic implications in the COVID-19 disease course.

Resilience analysis of urban commercial area under the COVID-19 epidemic using night-time light remote sensing data

ABSTRACT The global outbreak of the novel coronavirus has had a great impact on commercial areas, particularly in Wuhan, the first city in China affected by the epidemic. Exploring the changing pattern of these areas during the epidemic period is crucial for effectively restoring the urban economic level and promoting economic development on the basis of epidemic prevention and control in the post-epidemic era. The paper proposes a resilience analysis of urban commercial areas during the COVID-19 epidemic using time-series night-time light remote sensing data. Based on the constructed time-series night-time light remote sensing dataset and considering the urban impervious surface, the urban commercial area was extracted under multi-scale segmentation. Based on night-time light data before and after the epidemic, the resilience of representative commercial areas in Wuhan City, Hubei Province during the COVID-19 epidemic was analysed using a modified improved resilience assessment framework. The results showed that the lighting values of commercial areas and impervious areas decreased by up to 30% following the implementation of city lockdown measures. The change of light brightness in the commercial areas was more prominent, and the range of change is larger than that in the non-commercial areas. The lighting brightness of the commercial areas exhibited a significant downward trend throughout the entire lockdown period, and the downward trend will still remain for a period of time after unlocking. Among all the commercial areas, Wuguang commercial area demonstrated the highest recovery rate during the lockdown period and instantaneous recovery rate after the lockdown, with relatively low closure loss and the highest level of resilience.

Obstetric Outcomes of pregnant women with Covid-19 infection during first and second waves of Covid Pandemic in Lagos Nigeria

Background: Coronaviruses are a group of enveloped positive-stranded RNA viruses. They constitute a very important human and animal pathogens. COVID-19, a novel coronavirus was identified towards the end of 2019 following a cluster of pneumonia in Wuhan city in China. Our study aims to document the obstetrics parameters and outcomes of pregnant women diagnosed and managed at the Lagos University Teaching Hospital, Nigeria. Methods: The study was a retrospective review of the medical records of all pregnant women admitted to the Lagos University Teaching Hospital (LUTH) COVID 19 Isolation and Treatment Centre during the first wave (from April 2020 to October 2020) and second wave (from December 2020 to April 2021). The clinical characteristics (including COVID severity) and outcomes were retrieved. Results: During the study period thirty-four pregnant women with suspected COVID-19 symptoms for which nasopharyngeal samples for RTPCR for SARS-CoV-2 nucleic acid were positive were seen and managed following their admission into the isolation ward for COVID-19. Of the 34 women, 50.0% (17) of them were discharged to the antenatal clinic following recovery, 44.1% (15) had childbirth while on admission, and 5.9% (2) had maternal death. Of the 15 deliveries, 14 occurred at term with 15 babies (a set of twins) and one preterm stillbirth. Conclusion: The clinical manifestations of COVID-19 in pregnant mothers are similar to those described in the non-pregnant population as pregnancy does not seem to worsen the severity of the disease. Noticeably, severe infection occurred in women with comorbidities such as asthma and hypertensive disorders.

Ambient Ozone Exposure, Semen Plasma Metabolites, and Sperm Quality Decline among Adult Men in Wuhan China.

Ambient ozone (O3) exposure may be associated with a reduction of semen quality, yet the potential biological mechanisms remain unclear. We investigated the effects of certain seminal plasma metabolites on mediating the links between O3 exposure and the deterioration of semen quality. The untargeted metabolomics analysis was performed on semen samples of 200 Chinese adult men to determine candidate metabolites associated with characteristics of semen quality. Mediation analysis was adopted to examine whether these metabolites modulated the links between O3 exposure and semen quality. We found a significant reduction in sperm concentration by -28.1% (95% CI: -41.7%, -11.3%), and sperm count by -29.2% (95% CI: -43.7%, -11.0%) associated with each 10 μg/m3 increase in ambient O3 concentration during the period of sperm development. We delineated 7 metabolites in seminal fluid that substantially mediated the links between O3 exposure and declined semen quality, including myristoleic acid, aspartyl-isoleucine, phenylethyl primeveroside, ACar (18:2), ACar (18:1), FAHFA (22:6/22:3), and LPS (22:5). Among these, myristoleic acid exhibited the most pronounced mediation effects, with its indirect effect of which accounts for 46.4% of the overall association. Our findings suggested that exposure to ozone decreased sperm quality by disrupting fatty acid metabolism, particularly myristoleic acid.

A Review Study on Outbreak Prediction of Covid19 By using Machine Learning

In December 2019, Wuhan City, China, discovered a new infectious disease, COVID-19. Over 70 million people have been infected and one million people have died as a result of COVID-19. Defeating such a deadly, infectious disease requires accurate models that predict COVID-19 outbreaks. Using prediction models, governments can plan budgets and facilities for fighting diseases, and take control measures to make better decisions and take control measures. For example, they can determine how many medicines and medical equipment to manufacture or import, as well as how many medical personnel are needed to fight the disease. The COVID-19 outbreak has subsequently been predicted in several countries and continents using regression and classification models. A recent study that incorporated statistical and machine learning techniques was reviewed to predict COVID-19 outbreaks in the future. Ground truth datasets are used, their characteristics are investigated, models are developed, predictor variables are identified, statistical and machine learning methods are applied, performance metrics are calculated, and finally comparisons are made. By applying machine learning methods, the survey results indicate that we can make predictions about whether a patient will become infected with COVID-19, how outbreak trends will develop, and which age groups will be affected the most

SARS-CoV-2 Induced Interleukin -18 Response among Presumptive Covid-19 Patients in Kano State, Nigeria

Study’s Novelty/Excerpt This study evaluates Interleukin-18 (IL-18) as a potential biomarker for COVID-19 by comparing its serum levels in COVID-19-positive patients and healthy controls. The research uniquely identifies significantly elevated IL-18 levels in COVID-19 patients, demonstrating a strong statistical association with the infection (t value 6.16, p <0.00010). These findings underscore the potential of IL-18 in the prognosis and clinical management of COVID-19, offering new insights into its role in the disease's pathophysiology and its utility as a biomarker. Full Abstract Coronaviruses have a history of causing severe outbreaks with life-threatening consequences, including Severe Acute Respiratory Syndrome (SARS), Middle East Respiratory Syndrome (MERS), and the recent coronavirus disease 2019 (COVID-19). COVID-19 first broke out in Wuhan (China) in December 2019). The disease was later declared a pandemic, and so far, more than 222 countries have been affected, with over 771 million confirmed cases and total deaths of over 7.05 million. Some immunological markers were reported elsewhere as directly related to COVID-19 pathophysiology and stand a chance to be considered biomarkers. Interleukin 18 (IL-18) is a proinflammatory cytokine and a member of the interleukin-1 family, produced by macrophages at the early stage of viral infections. However, aberrant IL-18 production can lead to severe pathological injury. Hence, there is a need to assess the feasibility of interleukin -18 as a biomarker for COVID-19. Forty-five individuals diagnosed with COVID-19 and 45 healthy controls screened using a COVID-19 antigen rapid test kit and confirmed by one-step real-time PCR were recruited for this study. Blood samples were collected from the patients and controls, and the samples were analyzed for IL-18 using the ELISA technique. This study revealed a higher level of IL-18 in COVID-19-positive patients (206.42 ± 13.2 pg/mL) compared to the control group (97.96 ± 14.4 pg/mL). Serum level IL-18 was statistically associated with COVID-19 infection (t value 6.16, p <0.00010). The study demonstrates the importance of IL-18 in the COVID-19 cohort, inferentially implying its potential in the prognosis and clinical management of COVID-19.

The "sponge city" program as a system of adaptation methods to climate changes in reforming and forming the architectural environment

This article analyzes the implementation of the «Sponge city» concept in the formation and reform of the urban and architectural environment, as a comprehensive method of adaptation to the problems caused by climate change, which was caused by the global warming of our planet. In this concept, the emphasis is on the regulation of all types of water resources in the aspects of floods, swamps and inundations. One of the main reasons for accelerating the pace of global warming is rapid industrial development and urbanization. This led to increased use of resources, including water, which created major environmental risks. The problems of climate change have worsened not only due to the growth of gas emissions into the atmosphere, but also due to the rapid and unplanned urbanization of the urban environment, which was formed in the post-industrial period and reflects the greedy approach of society to the limited resources of the planet. Due to this, large-scale post-industrial processes took place in many countries of the world, which led to significant environmental problems. The urban population grew at a rapid rate, with the simultaneous construction of the necessary infrastructure, including housing, factories and roads. Such processes also took place in the People's Republic of China, due to which the issue of regulating water resources was raised in the country, and the concept of "Sponge city" was applied as an answer. On the example of several Chinese cities of Wuhan, Pingxiang and Haikou, where this concept was successfully applied, adaptation methods and complex approaches for reforming the existing urban and forming a new architectural environment were systematized. Based on them, an action algorithm for the implementation of these methods and technologies was developed as a program of communication of all large-scale levels among themselves. Applying this program, at the levels from the region to an individual building and vice versa. A self-regenerating system is formed - a "sponge city-region-ecosystem" as a complex of innovative methods of combating floods, inundation, wetlands, excess precipitation, which promotes adaptation to climate changes and ensures sustainability , safety and harmony of the environment.

Application of Image Processing for COVID-19: A Review

Abstract: The outburst of COVID-19 was first detected in Wuhan city of China as an unidentified viral disease at the end of 2019, and consequently it has spread all over the world as a pandemic. COVID-19 mostly spreads through close contact, respiratory droplets through coughing, talking and sneezing, and cluster infections. Different countries have invented different vaccines to stabilize the pandemic situation. But until now, it is not stabilized and every day, a large percentage of people are getting infected and sometimes, in severe cases, it results in the loss of life. Many researchers are working in different ways to protect, diagnose, and early detection of coronavirus disease (COVID- 19). Different image processing techniques, along with modern technologies like machine learning, Artificial Intelligence, Deep Learning, have already been used to fight against this disease. In this study, we have reviewed all applications of image processing for the diagnosis of COVID-19 patients in detail. At first, we reviewed X-ray image-based techniques to diagnose COVID-19 patients along with their drawbacks and results. Then CT scan picture-based various techniques are discussed for the diagnosis and for the treatment of this disease. At last, we have reviewed different ultrasound images based on various techniques to measure the severity of COVID-19 patients. All techniques are discussed with their merits and demerits along with their applications.

A study on the monitoring of heatwaves and bivariate frequency analysis based on mortality risk assessment in Wuhan, China.

The increasingly frequent occurrence of urban heatwaves has become a significant threat to human health. To quantitatively analyze changes in heatwave characteristics and to investigate the return periods of future heatwaves in Wuhan City, China, this study extracted 9 heatwave definitions and divided them into 3 mortality risk levels to identify and analyze historical observations and future projections of heatwaves. The copula functions were employed to derive the joint distribution of heatwave severity and duration and to analyze the co-occurrence return periods. The results demonstrate the following. (1) As the concentration of greenhouse gas emissions increases, the severity of heatwaves intensifies, and the occurrence of heatwaves increases significantly; moreover, a longer duration of heatwaves correlated with higher risk levels in each emission scenario. (2) Increasing concentrations of greenhouse gas emissions result in significantly shorter heatwave co-occurrence return periods at each level of risk. (3) In the 3 risk levels under each emission scenario, the co-occurrence return periods for heatwaves become longer as heatwave severity intensifies and duration increases. Under the influence of climate change, regional-specific early warning systems for heatwaves are necessary and crucial for policymakers to reduce heat-related mortality risks in the population, especially among vulnerable groups.

Uniform or demand-driven allocation? Optimal management of social donations distribution in response to sudden outbreaks

PurposeThis study aims to address challenges in the distribution of social donations during epidemic emergencies, focusing on issues such as uneven distribution and material stacking. The goal is to propose optimized strategies that enhance equity and efficiency in the allocation of donated resources.Design/methodology/approachFirstly, the satisfaction function is constructed from two perspectives of the designated hospital and the Red Cross. On this basis, the fairness perception level of the two is portrayed. Then, we set the time weights, and construct a multi-objective programming model by combining the resource constraints in the social donation distribution process. The combined algorithm of NSGA-II and TOPSIS is also designed for model solving. Finally, an example of social donation distribution of the Red Cross Society of China Wuhan Branch is conducted for numerical analysis.FindingsNumerical analysis reveals that timely transmission of demand information favors a demand-oriented distribution strategy for optimal efficiency. However, in scenarios with poor demand information transmission, an equal distribution of social donations proves to be a more effective strategy. Equal distribution ensures rapid allocation while minimizing perceived unfairness at designated hospitals, ultimately improving overall satisfaction levels and emergency response effectiveness.Practical implicationsThe findings provide practical insights for emergency response planners. These include translating the developed methods into guiding principles, establishing real-time monitoring systems, enhancing training for relevant departments, and implementing evaluation mechanisms. Practitioners can utilize this knowledge to optimize the efficiency of social donation distribution during sudden outbreaks.Social implicationsThe equitable distribution of social donations ensures efficient resource allocation and minimizes perceived unfairness, contributing to improved social satisfaction levels. This has broader implications for community resilience and support during emergencies.Originality/valueThis research contributes to the field by proposing a comprehensive model for optimizing social donation distribution in emergencies. The integration of fairness perception, time weights, and a multi-objective planning approach, along with the application of the combined algorithm of NSGA-II and TOPSIS, adds novelty and practical value to the existing literature. The study serves as a decision-making reference for enhancing emergency response theories in sudden event.

Evolutionary and Phylogenetic Dynamics of SARS-CoV-2 Variants: A Genetic Comparative Study of Taiyuan and Wuhan Cities of China.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-sense, single-stranded RNA genome-containing virus which has infected millions of people all over the world. The virus has been mutating rapidly enough, resulting in the emergence of new variants and sub-variants which have reportedly been spread from Wuhan city in China, the epicenter of the virus, to the rest of China and all over the world. The occurrence of mutations in the viral genome, especially in the viral spike protein region, has resulted in the evolution of multiple variants and sub-variants which gives the virus the benefit of host immune evasion and thus renders modern-day vaccines and therapeutics ineffective. Therefore, there is a continuous need to study the genetic characteristics and evolutionary dynamics of the SARS-CoV-2 variants. Hence, in this study, a total of 832 complete genomes of SARS-CoV-2 variants from the cities of Taiyuan and Wuhan in China was genetically characterized and their phylogenetic and evolutionary dynamics studied using phylogenetics, genetic similarity, and phylogenetic network analyses. This study shows that the four most prevalent lineages in Taiyuan and Wuhan are as follows: the Omicron lineages EG.5.1.1, followed by HK.3, FY.3, and XBB.1.16 (Pangolin classification), and clades 23F (EG.5.1), followed by 23H (HK.3), 22F (XBB), and 23D (XBB.1.9) (Nextclade classification), and lineage B followed by the Omicron FY.3, lineage A, and Omicron FL.2.3 (Pangolin classification), and the clades 19A, followed by 22F (XBB), 23F (EG.5.1), and 23H (HK.3) (Nextclade classification), respectively. Furthermore, our genetic similarity analysis show that the SARS-CoV-2 clade 19A-B.4 from Wuhan (name starting with 412981) has the least genetic similarity of about 95.5% in the spike region of the genome as compared to the query sequence of Omicron XBB.2.3.2 from Taiyuan (name starting with 18495234), followed by the Omicron FR.1.4 from Taiyuan (name starting with 18495199) with ~97.2% similarity and Omicron DY.3 (name starting with 17485740) with ~97.9% similarity. The rest of the variants showed ≥98% similarity with the query sequence of Omicron XBB.2.3.2 from Taiyuan (name starting with 18495234). In addition, our recombination analysis results show that the SARS-CoV-2 variants have three statistically significant recombinant events which could have possibly resulted in the emergence of Omicron XBB.1.16 (recombination event 3), FY.3 (recombination event 5), and FL.2.4 (recombination event 7), suggesting some very important information regarding viral evolution. Also, our phylogenetic tree and network analyses show that there are a total of 14 clusters and more than 10,000 mutations which may have probably resulted in the emergence of cluster-I, followed by 47 mutations resulting in the emergence of cluster-II and so on. The clustering of the viral variants of both cities reveals significant information regarding the phylodynamics of the virus among them. The results of our temporal phylogenetic analysis suggest that the variants of Taiyuan have likely emerged as independent variants separate from the variants of Wuhan. This study, to the best of our knowledge, is the first ever genetic comparative study between Taiyuan and Wuhan cities in China. This study will help us better understand the virus and cope with the emergence and spread of new variants at a local as well as an international level, and keep the public health authorities informed for them to make better decisions in designing new viral vaccines and therapeutics. It will also help the outbreak investigators to better examine any future outbreak.