Acute Respiratory Infectious Disease Research Articles

Community-acquired pneumonia associated with immunosuppression due to follicular thyroid cancer: a case report

BackgroundWe present the case of a woman with cancer, which weakened the immune system and increased the risk of infection. Thus, infections are a frequent complication of cancer. The development of community-acquired pneumonia, an acute respiratory infectious disease that damages the lung parenchyma, caused by the invasion of pathogenic microorganisms, can lead to respiratory failure with multiorgan failure due to respiratory sepsis.Case presentationCase report of a 38-year-old mixed-race woman with diabetes mellitus and irregular treatment, who was admitted with community-acquired pneumonia complicated by type I respiratory failure requiring mechanical ventilation. During her hospital stay, she developed ventilator-associated pneumonia, recurrent empyema, bronchopleural fistula, refractory septic shock and multiorgan dysfunction despite multiple interventions. The patient required prolonged mechanical ventilation, vasopressor support and antibiotic therapy. After 62 days, metastatic papillary thyroid carcinoma was diagnosed. She presented with hypoparathyroidism and permanent hypocalcemia. She died after multiple complications and a refractory critical condition.ConclusionThe case exemplifies the potential severity of community-acquired pneumonia in a patient with risk factors such as diabetes and immunosuppression. It highlights the complexity of treating multiple comorbidities and the importance of multidisciplinary management with close surveillance for timely interventions for complications.

Telemedical management of symptomatic Covid-19 outpatients

BackgroundCovid-19 remains a challenge to individual health and health care resources worldwide. Telemedical surveillance might minimize hospitalization and direct patient-physician-contacts. Yet, randomized clinical trials evaluating telemedical management of Covid-19 patients are lacking.MethodsCOVID SMART is a randomized, open label, controlled clinical trial investigating whether telemedicine reduces the primary endpoint of hospitalization or any unscheduled utilization of an emergency medical service within 30 days of follow-up. Key secondary endpoints included mortality and primary endpoint components. We enrolled acutely infected SARS-CoV2 patients suitable for outpatient care. All presented with ≥1 risk factor for an adverse Covid-19 course. Patients were randomized 1:1 into a control group receiving standard of care and an intervention group receiving smartphone-based assessment of oxygen saturation, heart rate and electrocardiogram, and telemedical counsellingviaa 24/7 emergency hotline.ResultsOf 607 enrolled patients (mean age 46.7±13.5 years), 304 were randomized into the intervention and 303 into the control group. The primary endpoint occurred in 6.9% (n=21) of the intervention and in 9.6% (n=29) of the control group (hazard ratio 0.72, 95% confidence interval 0.41–1.26; p=0.24). No deaths occurred during follow-up. Fewer intervention group participants utilized outpatient-based emergency medical services (hazard ratio 0.43, 95% confidence interval 0.20–0.90; p=0.03).ConclusionsCOVID SMART is the first randomized clinical trial assessing the benefit of telemedicine in an acute respiratory infectious disease. Whereas telemedical management did not reduce the primary endpoint of hospitalization, fewer intervention group patients used outpatient-based emergency services, suggesting a potential benefit for less-acutely infected individuals.Trial registrationclinicaltrials.gov (NCT04471636)

A Prediction Model for Prolonged Hospital Length of Stay (ProLOS) in Coronavirus Disease 2019 (COVID-19) Patients.

Coronavirus disease 2019 (COVID-19) is an acute respiratory infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). With the normalization of COVID-19 globally, it is crucial to construct a prediction model that enables clinicians to identify patients at risk for ProLOS based on demographics and serum inflammatory biomarkers. The study included hospitalized patients with a confirmed diagnosis of COVID-19. These patients were randomly grouped into a training (80%) and a test (20%) cohort. The LASSO regression and ten-fold cross-validation method were applied to filter variables. The training cohort utilized multifactorial logistic regression analyses to identify the independent factors of ProLOS in COVID-19 patients. A 4-variable nomogram was created for clinical use. ROC curves were plotted, and the area under the curve (AUC) was calculated to evaluate the model's discrimination; calibration analysis was planned to assess the validity of the nomogram, and decision curve analysis (DCA) was used to evaluate the clinical usefulness of the model. The results showed that among 310 patients with COVID-19, 80 had extended hospitalization (80/310). Four independent risk factors for COVID-19 patients were identified: age, coexisting chronic respiratory diseases, white blood cell count (WBC), and serum albumin (ALB). A nomogram based on these variables was created. The AUC in the training cohort was 0.808 (95% CI: 0.75 - 0.8671), and the AUC in the test cohort was 0.815 (95% CI: 0.7031 - 0.9282). The model demonstrates good calibration and can be used with threshold probabilities ranging from 0% to 100% to obtain clinical net benefits. A predictive model has been created to accurately predict whether the hospitalization duration of COVID-19 patients will be prolonged. This model incorporates serum WBC, ALB levels, age, and the presence of chronic respiratory system diseases.

Fim3–24/ptxP-3 genotype is associated to whooping cough outbreak in Brazilian Midwest: The selection of Bordetella pertussis strains driven by vaccine immunization

Whopping cough (or Pertussis) is an acute infectious respiratory disease caused by Bordetella pertussis bacteria. The disease is highly transmissible and can be fatal in children under two years old. Since the introduction of vaccine immunization in 1940, Pertussis incidence decreased worldwide. In Brazil, the immunization was introduced in 1977 using the whole cell (wP) vaccine. Despite the high vaccination coverage, an unexpected increase in the number of observed Pertussis cases was observed in 2012. In this year, 2257 cases were reported exceeding the average incidence rate of <1000 cases per year until 2010. This outbreak reached a peak level in 2014 and ended in 2018 according to the Brazilian National Surveillance System (SINAN). To understand the relationship between the outbreak and the vaccination, bacterial isolates (n = 136) from the Brazilian Midwest region obtained during the outbreak were submitted to genotyping of two vaccine loci: ptxP and fim3. Most of isolates (102) were obtained from nursing children (29 days to 2 years old). Genotyping of 94 isolates revealed that fim3–24/ptxP-3 was the most prevalent genotype (68%) associated with the outbreak peak. Two additional genotypes were also observed: fim3–1/ptxP-3 (15%) and fim3–3/ptxP-3 (17%). Conversely, the fim3–1/ptxP-2 genotype, which is harbored by the strain used in the wP vaccine (Bp137), was not observed. These results showed that B. pertussis circulating strains in the outbreak analyzed were different from the strain used for Pertussis immunization in Brazil. These observations provide insights that could be used to target vaccination programs to prevent future whooping cough outbreaks in Brazil.

Predictive health monitoring: Leveraging artificial intelligence for early detection of infectious diseases in nursing home residents through discontinuous vital signs analysis

This research addresses the problem of detecting acute respiratory, urinary tract, and other infectious diseases in elderly nursing home residents using machine learning algorithms. The study analyzes data extracted from multiple vital signs and other contextual information for diagnostic purposes. The daily data collection process encounters sampling constraints due to weekends, holidays, shift changes, staff turnover, and equipment breakdowns, resulting in numerous nulls, repeated readings, outliers, and meaningless values. The short time series generated also pose a challenge to analysis, preventing the extraction of seasonal information or consistent trends. Blind data collection results in most of the data coming from periods when residents are healthy, resulting in excessively imbalanced data. This study proposes a data cleaning process and then builds a mechanism that reproduces the basal activity of the residents to improve the classification of the disease. The results show that the proposed basal module-assisted machine learning techniques allow anticipating diagnostics 2, 3 or 4 days before doctors decide to start treatment with antibiotics, achieving a performance measured by the area-under-the-curve metric of 0.857. The contributions of this work are: (1) a new data cleaning process; (2) the analysis of contextual information to improve data quality; (3) the generation of a baseline measure for relative comparison; and (4) the use of either binary (disease/no disease) or multiclass classification, differentiating among types of infections and showing the advantages of multiclass versus binary classification. From a medical point of view, the anticipated detection of infectious diseases in institutionalized individuals is brand new.

Prevalence and genomic-based antimicrobial resistance analysis of Avibacterium paragallinarum isolates in Guangdong Province, China

Infectious coryza (IC) is an acute infectious respiratory disease in chickens that is caused by Avibacterium paragallinarum (A. paragallinarum). A. paragallinarum poses a significant threat to poultry health due to its virulence and multidrug resistance. This study isolated and identified 21 A. paragallinarum isolates from Guangdong between 2022 and 2023. Biochemical tests showed that 100% of A. paragallinarum isolates fermented glucose but did not ferment alginate and galactose, and only YZ18 was nicotinamide adenine dinucleotide independent. To determine the genetic relatedness between these isolates and NCBI reference strains, whole-genome-based phylogenetic analysis was employed. In addition, analysis of the 2,000 bp-length hmtp210 gene showed that the hmtp210 gene was strongly associated with A. paragallinarum serotypes. Meanwhile, a PCR assay for serotyping A. paragallinarum was developed based on the hmtp210 gene, this assay has high sensitivity and specificity. The antimicrobial susceptibility of isolates was assessed using the disk diffusion method. The antibiotic resistance genes of isolates were analyzed using the genomic method. Phenotypic resistance to ampicillin (95.2%), streptomycin (95.2%), methotrexate-sulfamethoxazole (90.5%), and tetracycline (85.7%) was most frequent among the isolates. All of the isolates exhibited resistance to multiple drugs, and furthermore, the isolates possessed a collective total of 14 genes associated with antibiotic resistance. This study will contribute to advancing our knowledge of A. paragallinarum antibiotic resistance and provide a scientific basis for the prophylaxis and treatment of IC, and the subsequent rational design of potential clinical therapeutics.

A Study of Knowledge and Attitudes of Health Students towards Acute Respiratory Infections (ARI) in Lubuklinggau City

Purpose of the study: The aim of this research was to determine the relationship between knowledge and attitudes of health students towards Acute Respiratory Tract Infections in Lubuklinggau City.&#x0D; Methodology: This research method uses quantitative correlational research. The population in this study were all health students in semester 1 and semester 3 in the city of Lubuklinggau. The samples taken were 72 respondents. The sampling technique uses simple random sampling through questions that have been tested for validity and reliability. The data analysis technique uses a correlation test.&#x0D; Main Findings: The results of this research are that there is a relationship between knowledge and attitudes of health students, the results of knowledge and attitudes have good value for acute respiratory infections.&#x0D; Novelty/Originality of this study: This research provides valuable insight into efforts that may be needed to increase awareness and engagement in fighting this Acute Respiratory Infection disease at the local level. It is hoped that the findings from this research can help in designing more effective educational programs and more focused prevention strategies to mitigate Acute Respiratory Infections in Lubuk Linggau and the surrounding area.

Activated Leukocyte Cell Adhesion Molecule Regulates the Expression of Interleukin-33 in RSV Induced Airway Inflammation by Regulating MAPK Signaling Pathways.

The respiratory syncytial virus (RSV) is a common respiratory virus that causes acute lower respiratory tract infectious diseases, particularly in young children and older individuals. Activated leukocyte cell adhesion molecule (ALCAM) is a membrane glycoprotein expressed in various cell types, including epithelial cells, and is associated with inflammatory responses and various cancers. However, the precise role of ALCAM in RSV-induced airway inflammation remains unclear, and our study aimed to explore this gap in the literature. C57BL/6 wild-type, ALCAM knockout mice and airway epithelial cells were infected with RSV and the expression of ALCAM and inflammatory cytokines were measured. We also conducted further experiments using Anti-ALCAM antibody and recombinant ALCAM in airway epithelial cells. The expression levels of ALCAM and inflammatory cytokines increased in both RSV-infected mice and airway epithelial cells. Interestingly, IL-33 expression was significantly reduced in ALCAM-knockdown cells compared to control cells following RSV infection. Anti-ALCAM antibody treatment also reduced IL-33 expression following RSV infection. Furthermore, the phosphorylation of ERK1/2, p38, and JNK was diminished in ALCAM-knockdown cells compared to control cells following RSV infection. Notably, in the control cells, inhibition of these pathways significantly decreased the expression of IL-33. In vivo study also confirmed a reduction in inflammation induced by RSV infection in ALCAM deficient mice compared to wild-type mice. These findings demonstrate that ALCAM contributes to RSV-induced airway inflammation at least partly by influencing IL-33 expression through mitogen-activated protein kinase signaling pathways. These results suggest that targeting ALCAM could be a potential therapeutic strategy for alleviating IL-33-associated lung diseases.

Evaluation of the District Health Information System in District Kotli, Azad Jammu and Kashmir: A Retrospective Analysis.

It is essential to implement a high-quality electronic database for keeping important information. The District Health Information System (DHIS) is an active data-keeping system in Pakistan. This study aimed to evaluate the patients' data from the DHIS dashboard for the District Headquarters Hospital, Kotli, Azad Jammu and Kashmir (AJK). The data was requested from the hospital administration at District Headquarters Hospital, Kotli, AJK, and the data was analyzed after permission was granted. The data was given in two forms; one was a hard copy of the data for August and September and the other was a comma-separated values file for October and November, 2023. The highest frequency of patients was received in the department of emergency and trauma and the patient's median age was between 15 and 49 years. The second department was medicine with the >50 years of age. Common conditions that needed more attention were chronic obstructive pulmonary disease, acute respiratory infection, diarrhea, pneumonia, diabetes mellitus, hypertension, and ischemic heart disease. For nations with constrained healthcare systems and funds, primary health care (PHC) is the only viable approach for managing non-communicable diseases (NCDs). However, PHC systems intended for infectious diseases have not sufficiently adapted to the growing requirement of chronic care for NCD. Research using health information databases offers numerous benefits, such as the evaluation of large data sets and unexpected prevalence of disease in certain populations, such as a higher prevalence of disease in one gender or age group. Health information system-based data analysis or studies are less expensive and faster but lack scientific control over data collection.

Challenges and opportunities for online education of veterinary sciences in Kazakhstan

The Severe Acute Respiratory Syndrome Coronavirus Infectious Disease 2019 (SARS-COVID-19) pandemic has dramatically improved the attitude that society has toward educational opportunities that are administered online. In many cases, digital platforms were adapted and utilized without formal evaluation of the needs, constraints, and opportunities associated with their use. Here, the eight historical faculties of veterinary sciences of Kazakhstan were surveyed to gather data on the use of online technology for the discipline in the country and the limitations, opportunities, and challenges associated with its use. Results show that technological resources, institutional support, and faculty and instructors' attitudes are highly favorable for the implementation of online education programs consistently throughout the country. In contrast, students' motivations and skills are perceived as variable, although generally favorable, at different locations. The results here provide insights into the challenges and opportunities associated with using online technology for instruction in veterinary sciences in Kazakhstan, which will help create the foundations for implementing this type of program in the country and region.

Allergic Reaction to Aminophylline in a Case of Lower Respiratory Tract Infection with Measles: A Rare Case Report

Measles is an acute respiratory infectious disease caused by the measles virus. It leads to respiratory involvement with manifestations such as pneumonia, laryngobronchitis, pneumonitis, etc. It can also cause secondary bacterial and fungal infections. Aminophylline is a methylxanthine bronchodilator composed of theophylline and ethylenediamine. Airway blockage is reversed by bronchial smooth muscle relaxation, increased myosin light chain kinase activity, and decreased intracellular calcium concentration. It relaxes the smooth muscle of the bronchial airways and pulmonary blood vessels, reducing airway responsiveness to histamine, methacholine, adenosine, and allergens. Allergic skin reactions secondary to aminophylline administration have been rarely seen. Aminophylline can be given orally as well as intravenously. A seven-month-old male infant presented with a lower respiratory tract infection and a maculopapular rash involving the face and trunk. A history of contact with measles was present. Intravenous aminophylline was administered for persistent wheezing. The infant developed a generalised erythematous papular rash with a more widespread distribution than before within one hour of administration. The child was treated with antihistamines for the same. After a detailed physical examination, looking at the pattern of the rash and excluding other causes like environmental factors and drug history, the diagnosis of an allergic reaction to aminophylline was made. Early identification of allergic reactions is paramount, as prompt cessation of the offending agent and initiation of appropriate medical interventions can significantly mitigate the severity of the reaction and prevent potential life-threatening complications.

Mortality Associated with Priority Diseases in Flood-Affected Areas Using District Health Information System (DHIS2) During September-December 2022: Pakistan Experience.

To quantify the burden of communicable diseases and characterize the most reported infections during public health emergency of floods in Pakistan. The study's design is a descriptive trend analysis. The study utilized the disease data reported to District Health Information System (DHIS2) for the 12 most frequently reported priority diseases under the Integrated Disease Surveillance and Response (IDSR) system in Pakistan. In total, there were 1,532,963 suspected cases during August to December 2022 in flood-affected districts (n = 75) across Pakistan; Sindh Province reported the highest number of cases (n = 692,673) from 23 districts, followed by Khyber Pakhtunkhwa (KP) (n = 568,682) from 17 districts, Balochistan (n = 167,215) from 32 districts, and Punjab (n = 104,393) from 3 districts. High positivity was reported for malaria (79,622/201,901; 39.4%), followed by acute diarrhea (non-cholera) (23/62; 37.1%), hepatitis A and E (47/252; 18.7%), and dengue (603/3245; 18.6%). The crude mortality rate was 11.9 per 10 000 population (1824/1,532,963 [deaths/cases]). The study identified acute respiratory infection, acute diarrhea, malaria, and skin diseases as the most prevalent diseases. This suggests that preparedness efforts and interventions targeting these diseases should be prioritized in future flood response plans. The study highlights the importance of strengthening the IDSR as a Disease Early Warning System through the implementation of the DHIS2.

Trends and Age-Period-Cohort Effect on Incidence of Varicella Under Age 35 - China, 2005-2021.

Varicella is an acute respiratory infectious disease primarily affecting children. However, recent studies have indicated an increasing susceptibility to varicella among older age groups. The findings demonstrate a significant rise in the incidence rate among individuals aged 15-19. Males under 20 years old were found to have a higher risk compared to females, whereas males had a lower risk compared to females aged 20-35 years. This study is the first comparative analysis using varicella data reported between 2005 and 2021 to examine the contributions of age, period, and birth cohort to varicella incidence in China. This study aims to provide a comprehensive analysis of the epidemiological characteristics of varicella in China and identify high-risk groups. The results of this study will contribute valuable information for the development of varicella prevention policies.

MODELING PNEUMONIA CASES IN TODDLERS IN INDONESIA USING GENERALIZED ADDITIVE MODEL FOR LOCATION, SCALE, AND SHAPE (GAMLSS) WITH LOESS SMOOTHING

Pneumonia is an acute respiratory infectious disease that is the primary death cause due to infection in children worldwide, including Indonesia. Pneumonia case modeling is necessary to predict the incidence, especially pneumonia in toddlers. In this study, case modeling using the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) method with LOESS smoothing to determine the model form and the factors influencing pneumonia cases in toddlers in Indonesia in 2021. The research results obtained indicate that with the Inverse Gaussian distribution, the model form for the location parameter is 9,719 + 0,013 + 0,001 + 0,031 and for the scale parameter is -10,897 + 0,125. The resulting model is accurate and suitable for use because the model residuals follow a normal distribution. Along with factors that influence pneumonia cases in toddlers in Indonesia are the percentage of babies receiving exclusive breastfeeding (), population density (), and the percentage of toddlers receiving measles immunization ().

Relationship Between Occupancy Density, Education, And Diet To The Incidence Of ARI Disease In Patients At The Medan Satria Public Health Center In Bekasi City In 2023

Acute Respiratory Infection (ARI) in Indonesia has increased with a prevalence of 1 million cases in 2018. West Java province occupies the 7th position with a percentage of 11.2% cases with the number continuing to grow. The high number of ARI cases is influenced by residential density, education, and a person's diet. This study aims to determine the relationship between residential density, education, and diet with the incidence of ARI at the Medan Satria Health Center, Bekasi City in 2023. This research method is quantitative using a cross-sectional approach. The subjects in this study were patients of Puskesmas Medan Satria Bekasi City, the sampling technique used was accidental sampling of as many as 100 respondents who were targeted. The data used are primary and secondary data. Data analysis was carried out univariate and bivariate with the chi-square test. Based on statistical tests, there are two variables that show a relationship, namely education with a p-value = 0.011 with OR = 3.122, diet with a p-value = 0.023 with OR = 0.340, while there is one variable that does not show a relationship, namely residential density with a p-value = 1.000 with the incidence of ARI at the Medan Satria Health Center, Bekasi City. It is expected that the Medan Satria Health Center will conduct health promotion on the risk factors that cause ARI by activating cadres to provide education to the community in the Medan Satria area. This aims to reduce ARI cases in the Medan Satria Health Center area

The implication of infection with respiratory syncytial virus in pediatric recurrent wheezing and asthma: knowledge expanded post-COVID-19 era.

Respiratory syncytial virus (RSV) infection has been identified to serve as the primary cause of acute lower respiratory infectious diseases in children under the age of one and a significant risk factor for the emergence and development of pediatric recurrent wheezing and asthma, though the exact mechanism is still unknown. In this study, we discuss the key routes that lead to recurrent wheezing and bronchial asthma following RSV infection. It is interesting to note that following the coronavirus disease 2019 (COVID-19) epidemic, the prevalence of RSV changes significantly. This presents us with a rare opportunity to better understand the associated mechanism for RSV infection, its effects on the respiratory system, and the immunological response to RSV following the COVID-19 epidemic. To better understand the associated mechanisms in the occurrence and progression of pediatric asthma, we thoroughly described how the RSV infection directly destroys the physical barrier of airway epithelial tissue, promotes inflammatory responses, enhances airway hyper-responsiveness, and ultimately causes the airway remodeling. More critically, extensive discussion was also conducted regarding the potential impact of RSV infection on host pulmonary immune response. In conclusion, this study offers a comprehensive perspective to better understand how the RSV infection interacts in the control of the host's pulmonary immune system, causing recurrent wheezing and the development of asthma, and it sheds fresh light on potential avenues for pharmaceutical therapy in the future.

Association between COVID-19 and outstanding academic performance at a Spanish university

BackgroundSARS-CoV-2 is the causative agent of COVID-19 identified in December 2019, an acute infectious respiratory disease that can cause persistent neurological and musculoskeletal symptoms such as headache, fatigue, myalgias difficulty concentrating, among others including acute cerebrovascular disease with a prevalence of 1–35%. The aim of this study is to evaluate the impact of COVID-19 in undergraduate students on their academic performance as an indicator of their intellectual ability and performance in a university that maintained 100% face-to-face teaching during the 2020–2021 academic year.MethodsA total of 7,039 undergraduate students were analyzed in a prospective cohort study at the University of Navarra. A questionnaire including sociodemographic and behavioral questions was sent. PCRs were performed throughout the academic year for the diagnosis of SARS-CoV-2 infection and students’ academic results were provided by the academic center, adjusted descriptive and multivariate models were performed to assess the association.ResultsA total of 658 (9.3%) participants were diagnosed with COVID-19, almost 4.0% of them achieved outstanding academic results, while uninfected students did so in 7.3%. SARS-CoV-2 infection was associated with a significant decrease in having outstanding academic results (OR = 0.57; 95% CI: 0.38–0.86).ConclusionHaving COVID-19 disease, decreased academic performance in undergraduate students. Therefore, it is necessary to prevent infection even in the youngest sections of the population.

Geographical characteristics and influencing factors of the influenza epidemic in Hubei, China, from 2009 to 2019.

Influenza is an acute respiratory infectious disease that commonly affects people and has an important impact on public health. Based on influenza incidence data from 103 counties in Hubei Province from 2009 to 2019, this study used time series analysis and geospatial analysis to analyze the spatial and temporal distribution characteristics of the influenza epidemic and its influencing factors. The results reveal significant spatial-temporal clustering of the influenza epidemic in Hubei Province. Influenza mainly occurs in winter and spring of each year (from December to March of the next year), with the highest incidence rate observed in 2019 and an overall upward trend in recent years. There were significant spatial and urban-rural differences in influenza prevalence in Hubei Province, with the eastern region being more seriously affected than the central and western regions, and the urban regions more seriously affected than the rural region. Hubei's influenza epidemic showed an obvious spatial agglomeration distribution from 2009 to 2019, with the strongest clustering in winter. The hot spot areas of interannual variation in influenza were mainly distributed in eastern and western Hubei, and the cold spot areas were distributed in north-central Hubei. In addition, the cold hot spot areas of influenza epidemics varied from season to season. The seasonal changes in influenza prevalence in Hubei Province are mainly governed by meteorological factors, such as temperature, sunshine, precipitation, humidity, and wind speed. Low temperature, less rain, less sunshine, low wind speed and humid weather will increase the risk of contracting influenza; the interannual changes and spatial differentiation of influenza are mainly influenced by socioeconomic factors, such as road density, number of health technicians per 1,000 population, urbanization rate and population density. The strength of influenza's influencing factors in Hubei Province exhibits significant spatial variation, but in general, the formation of spatial variation of influenza in Hubei Province is still the result of the joint action of socioeconomic factors and natural meteorological factors. Understanding the temporal and spatial distribution characteristics of influenza in Hubei Province and its influencing factors can provide a reasonable decision-making basis for influenza prevention and control and public health development in Hubei Province and can also effectively improve the scientific understanding of the public with respect to influenza and other respiratory infectious diseases to reduce the influenza incidence, which also has reference significance for the prevention and control of influenza and other respiratory infectious diseases in other countries or regions.

Genomic surveillance of SARS-CoV-2 in Weihai, China, march 2022 to march 2023.

COVID-19 is an acute respiratory infectious disease caused by SARS-CoV-2. It was first reported in Wuhan, China in December 2019 and rapidly spread globally in early 2020, triggering a global pandemic. In December 2022, China adjusted the dynamic COVID-zero strategy that lasted for three years. The number of positive cases in China increased rapidly in the short term. Weihai was also affected during this period. We conducted genomic surveillance of SARS-CoV-2 variants in Weihai during this period, hoping to understand the changes in the genomic characteristics of SARS-CoV-2 before and after the adjustment of the epidemic policy. In this study,we collected SARS-CoV-2 positive samples from March 2022 to March 2023 in Weihai and performed SARS-CoV-2 whole genome sequencing on these samples using next-generation sequencing technology. we obtained a total of 704 SARS-CoV-2 whole genome sequences, and selected 581 high-quality sequences for further analysis. The analysis results showed that from March 2022 to November 2022, before the adjustment of epidemic policy, the COVID-19 cases in Weihai were mainly from four local clusters,which were caused by four variants, including BA.2,BA.1.1,P.1.15 and BA.5.2.1. Phylogenetic analysis showed that: In the same cluster,the sequences between each other were highly homologous, and the whole genome sequence were almost identical. After December 2022, the epidemic policy was adjusted, BF.7 and BA.5.2 became the dominant variants in Weihai, consistent with the main domestic strains in China during the same period. Phylodynamic analysis showed that BF.7 and BA.5.2 had a large amount of genetic diversities in December, and the effective population size of BF.7 and BA.5.2 also showed explosive growth in December. In conclusion, we reported the composition and dynamic trend of SARS-CoV-2 variants in Weihai from March 2022 to March 2023. We found that there have been significant changes in the variants and expansion patterns of SARS-CoV-2 before and after the adjustment of epidemic policies. But the dominant variants in Weihai were the same as the SARS-CoV-2 variants circulating globally at the same time and we found no persistently dominant variants or new lineages during this period.

Ginsenoside Rb1 enhanced immunity and altered the gut microflora in mice immunized by H1N1 influenza vaccine.

Influenza is an acute infectious respiratory disease caused by the influenza virus that seriously damages human health, and the essential way to prevent influenza is the influenza vaccine. Vaccines without adjuvants produce insufficient specific antibodies and therefore require adjuvants to boost antibody titers. Microbes and hosts are a community that needs to "promote bacteria," which could provide new value for the immune effect. (1) The H1N1 influenza vaccine, in combination with Ginsenoside Rb1, was co-injected into mice intraperitoneally (I.P.). Then, immunoglobulin G and antibody subtype levels were tested by enzyme-linked immunosorbent assay (ELISA). Moreover, mice were infected with a lethal dose of the H1N1 influenza virus (A/Michigan/45/2015), and survival status was recorded for 14 days. Lung tissues were stained by hematoxylin and eosin (H&E), and ELISA detected inflammatory factor expression levels. (2) Mice were immunized with Ginsenoside Rb1 combined with quadrivalent influenza inactivated vaccine(IIV4), and then IgG levels were measured by ELISA. (3) Fresh stool was collected for fecal 16S rDNA analysis. Ginsenoside Rb1 boosted IgG and antibody subtypes in the H1N1 influenza vaccine, improved survival of mice after virus challenge, attenuated lung histopathological damage, and reduced inflammatory cytokines expression in IL-6 and TNF-α. The results of 16S rDNA showed that Rb1 decreased species diversity but increased species richness compared to the PBS group and increased the abundance of Akkermansiaceae and Murbaculaceae at the Family and Genus levels compared with the HA+Alum group. Ginsenoside Rb1 has a boosting effect on the immune efficacy of the H1N1 influenza vaccine and is promising as a novel adjuvant to regulate the microecological balance and achieve an anti-infective effect.