Respiratory Infectious Diseases Research Articles

Work stress and caring intention among health care workers in Taiwan during the COVID-19 pandemic

Abstract Background Healthcare workers may feel stress when caring for patients suspected as having a highly infectious and novel disease, such as the coronavirus disease 2019 (COVID-19). Objectives This study aimed to identify the psychological responses and factors affecting these responses among healthcare workers in Taiwan during the COVID-19 pandemic. Methods Healthcare workers regardless of their experience in caring for COVID-19 patients in our hospital voluntarily participated in this cross-sectional study in April 2021. We used a self-assessment questionnaire with 70 items to identify the psychological responses and affecting factors. Results The experience of caring for COVID-19 patients was significantly associated with eight stressors, including “frequent modification of infection control procedures,” “worrying about being negligent and endangering coworkers,” “worrying about lack of manpower,” “being without a properly fitted environment,” “protective gears being a drag in providing quality care,” “protective gears causing physical discomfort,” “worrying about inflicting COVID-19 on family” and “worrying about nosocomial spread.” Using multivariate logistic regression, “switching thoughts and facing the situation with positive attitudes” (odds ratio: 2.974, P = 0.011), “ever caring COVID-19 patients” (odds ratio: 1.990, P = 0.018), “I felt scared” (odds ratio: 0.180, P < 0.001), and “I thought it is unlucky” (odds ratio: 0.492, P = 0.029) were identified as independent factors for the healthcare workers’ willingness to participate in future missions regarding infectious respiratory diseases. Conclusion The experience of caring for COVID-19 patients was significantly associated with several stressors related to psychological, practical, and environmental aspects, but not with immediate reactions to the mission. Experiences in caring for COVID-19 patients and positive attitudes could increase the healthcare workers’ willingness to participate in future missions regarding infectious respiratory diseases, and feeling scared and unlucky can reduce this willingness.

Association between ambient temperature and risk of notifiable infectious diseases in China from 2011 to 2019

ABSTRACT Previous studies on temperature and infectious diseases primarily focused on individual disease types, yielding inconsistent conclusions. This study collected monthly data on notifiable infectious disease cases and meteorological variables across 7 provinces in China from 2011 to 2019. A distributed lag nonlinear model was used to evaluate the association between ambient temperature and infectious diseases within each province, and random meta-analysis was applied to evaluate the pooled effect. Extreme hot temperature (the 97.5th percentile) was positively associated with the risk of respiratory infectious diseases with the relative risk (RR) of 1.45 (95%CI: 1.01–2.08). Conversely, extreme cold temperature (the 2.5th percentile) was negatively associated with intestinal infectious diseases and zoonotic diseases and vector-borne diseases, reporting RRs of 0.43 (95%CI: 0.30–0.60) and 0.46 (95%CI: 0.38–0.57), respectively. This study described the nonlinear association between ambient temperature and infectious diseases with different transmission routes, informing comprehensive prevention and control strategies for temperature-related infectious diseases.

Epidemic Features and Megagenomic Analysis of Childhood Mycoplasma Pneumoniae post COVID-19 Pandemic: A 6-year Study in Southern China

ABSTRACT With the atypical rise of Mycoplasma pneumoniae infection (MPI) in 2023, prompt studies are needed to determine the current epidemic features and risk factors with emerging trends of MPI to furnish a framework for subsequent investigations. This multicentre, retrospective study was designed to analyse the epidemic patterns of MPI before and after the COVID-19 pandemic, as well as genotypes and the macrolide resistance-associated mutations in MP sampled from pediatric patients in Southern China. Clinical data was collected from 133674 patients admitted into investigational hospitals from June 1, 2017, to November 30, 2023. Metagenomic next-generation sequencing (mNGS) data were retrieved based on MP sequence positive samples from 299 pediatric patients for macrolide resistance-associated mutations analysis. Pearson’s chi-squared test was used to compare categorical variables between different time frames. The monthly average cases of pediatric common respiratory infection diseases were increased without enhanced public health measures after the pandemic, especially for influenza, respiratory syncytial virus infection, and MPI. The contribution of MPI to pneumoniae was similar to that in the outbreak in 2019. Compared mNGS data between 2019-2022 and 2023, the severity of MP did not grow stronger despite higher rates of macrolide-resistance hypervariable sites, including loci 2063 and 2064, were detected in childhood MP samples of 2023. Our findings indicated ongoing surveillance is necessary to understand the impact of post pandemic on MP transmission disruption on epidemic season and severity of clinical outcomes in different scenarios.

Development and Evaluation of Monoclonal Antibodies against CBPP Antigen with the End Goal of Developing an ELISA Kit.

Contagious bovine pleuropneumonia (CBPP) is an infectious and contagious bacterial respiratory disease that affects cattle with significant economic losses to the African animal industry. The use of ELISA kits based on monoclonal antibodies (mAbs) will aid in quick and precise diagnosis of CBPP, contributing to disease control and prevention in cattle. Thus, this research aims to develop and evaluate monoclonal antibodies against CBPP (T1/44) antigen for use in ELISA kits for CBPP diagnosis. Hybridoma technology was used to develop monoclonal antibodies that recognize and bind to the CBPP (T1/44) antigen. The antibody-secreting hybridomas were produced after immunizing mice with purified CBPP antigens. The hybridomas were screened for high sensitivity, specificity, and liking to the antigen. The selected mAbs were assessed for sensitivity and specificity against CBPP antigen using different immunoassays, dot-blot, ELISA, and mouse mAb isotyping. The monoclonal antibodies were profoundly specific, with a higher hindrance to CBPP antigen (<0.50 OD) while lacking cross-reactivity to other antigens. The monoclonal antibodies could distinguish CBPP antigen at low concentrations, showing their high sensitivity (>80% PI). The isotyped mAbs of intrigued appeared to have a place in the IgG class. These identified monoclonal antibodies can be utilized to develop an ELISA kit for CBPP diagnosis, which would give a fast, precise, and cost-effective strategy for screening and checking CBPP in cattle herds.

Respiratory viral infections before the COVID-19 in Portugal: A single center study

ObjectivesWe aimed to describe the respiratory viruses (RV) found in respiratory samples from patients admitted to Hospital de São Bernardo, Setúbal, Portugal, between October 2019 and March 2020, and to correlate these with clinical features. DesignThis retrospective study explored 948 fresh frozen naso/oropharyngeal swabs, tested by reverse transcription-polymerase chain reaction. ResultsRhinovirus/enterovirus, influenza, and respiratory syncytial virus (hRSV) were the most prevalent RV. Half of the patients fulfilled the acute respiratory infection (ARI) and/or influenza-like illness (ILI) criteria, with increasing age significantly reducing the risk of ARI and/or ILI. Hospital admission was more frequently observed in symptomatic patients, but the length of stay and mortality were significantly lower. Most (96.5 %) patients had a main respiratory diagnosis. In adults, the most prevalent was pneumonia, which particularly affected older patients, while in children, the most common was bronchiolitis. The number of hospital admissions was high. Sudden onset, shortness of breath, older age, and hRSV detection significantly increased the risk of hospital admission overall. In bronchiolitis, female gender significantly increased the risk of hospital admission, while older age significantly reduced this risk. Twenty patients died within the first month of sampling, and all were older adults. Older age and male gender significantly increased the risk of death. ConclusionsRespiratory viral infections can have a significant clinical impact, particularly in young infants with bronchiolitis and older adults with pneumonia. This study provides the first snapshot of the respiratory viral infections just before the outbreak of SARS-CoV-2 in Portugal, providing relevant clinical insights.

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.

Predominance of A2063G mutant strains in the Mycoplasma pneumoniae epidemic in children–a clinical and epidemiological study in 2023 in Wuhan, China

ObjectivesThe prevalence of respiratory infectious diseases has changed in the post Covid-19 epidemic era, and mycoplasma pneumoniae (MP) infection in children has attracted wide attention. MethodsChildren hospitalized for pneumonia in Wuhan, China, in 2023 were enrolled. Respiratory secretions were obtained for the targeted next-generation sequencing (tNGS) including mutation of MP. Pulmonary inflammation was divided into bronchopneumonia and pulmonary consolidation/atelectasis according to lung CT imaging. ResultsOf the 667 pediatric pneumonia, 478 were MP positive (72%). The positive rate of MP detected by tNGS increased from April, and MP had become the primary pathogen of pneumonia in children in year 2023. The 23S rRNA mutations were all A2063G, accounting for 85% of detected MP. The clinical symptoms of the mutant and wild type strains were similar, with half of them experiencing atelectasis and lung consolidation. Early bronchoscopic lavage combined with azithromycin in pediatric pulmonary consolidation was an effective therapy strategy, which could be an alternative selection to MPP treatment. ConclusionA2063G mutant strain MP was the primary pathogen of mycoplasma pneumoniae in children recently, which was often complicated by extra-pulmonary symptoms and complications.

Evaluating Seasonal Variations in Human Contact Patterns and Their Impact on the Transmission of Respiratory Infectious Diseases.

Human contact patterns are a key determinant driving the spread of respiratory infectious diseases. However, the relationship between contact patterns and seasonality as well as their possible association with the seasonality of respiratory diseases is yet to be clarified. We investigated the association between temperature and human contact patterns using data collected through a cross-sectional diary-based contact survey in Shanghai, China, between December 24, 2017, and May 30, 2018. We then developed a compartmental model of influenza transmission informed by the derived seasonal trends in the number of contacts and validated it against A(H1N1)pdm09 influenza data collected in Shanghai during the same period. We identified a significant inverse relationship between the number of contacts and the seasonal temperature trend defined as a spline interpolation of temperature data (p = 0.003). We estimated an average of 16.4 (95% PrI: 15.1-17.5) contacts per day in December 2017 that increased to an average of 17.6 contacts (95% PrI: 16.5-19.3) in January 2018 and then declined to an average of 10.3 (95% PrI: 9.4-10.8) in May 2018. Estimates of influenza incidence obtained by the compartmental model comply with the observed epidemiological data. The reproduction number was estimated to increase from 1.24 (95% CI: 1.21-1.27) in December to a peak of 1.34 (95% CI: 1.31-1.37) in January. The estimated median infection attack rate at the end of the season was 27.4% (95% CI: 23.7-30.5%). Our findings support a relationship between temperature and contact patterns, which can contribute to deepen the understanding of the relationship between social interactions and the epidemiology of respiratory infectious diseases.

Bioinformation Analysis of Differential Expression Proteins in Different Processes of COVID-19.

COVID-19 is a highly infectious respiratory disease whose progression has been associated with multiple factors. From SARS-CoV-2 infection to death, biomarkers capable of predicting different disease processes are needed to help us further understand the molecular progression of COVID-19 disease. The aim is to find differentially expressed proteins that are associated with the progression of COVID-19 disease or can be potential biomarkers, and to provide a reference for further understanding of the molecular mechanisms of COVID-19 occurrence, progression, and treatment. Data-independent Acquisition (DIA) proteomics to obtain sample protein expression data, using R language screening differentially expressed proteins. Gene Ontology and Kyoto Encyclopedia for Genes and Genomes analysis was performed on differential proteins and protein-protein interaction (PPI) network was constructed to screen key proteins. A total of 47 differentially expressed proteins were obtained from COVID-19 incubation patients and healthy population (L/H), mainly enriched in platelet-related functions, and complement and coagulation cascade reaction pathways, such as platelet degranulation and platelet aggregation. A total of 42 differential proteins were obtained in clinical and latent phase patients (C/L), also mainly enriched in platelet-related functions and in complement and coagulation cascade reactions, platelet activation pathways. A total of 10 differential proteins were screened in recovery and clinical phase patients (R/C), mostly immune-related proteins. The differentially expressed proteins in different stages of COVID-19 are mostly closely associated with coagulation, and key differential proteins, such as FGA, FGB, FGG, ACTB, PFN1, VCL, SERPZNCL, APOC3, LTF, and DEFA1, have the potential to be used as early diagnostic markers.

Exploring post-COVID-19 health effects and features with advanced machine learning techniques

COVID-19 is an infectious respiratory disease that has had a significant impact, resulting in a range of outcomes including recovery, continued health issues, and the loss of life. Among those who have recovered, many experience negative health effects, particularly influenced by demographic factors such as gender and age, as well as physiological and neurological factors like sleep patterns, emotional states, anxiety, and memory. This research aims to explore various health factors affecting different demographic profiles and establish significant correlations among physiological and neurological factors in the post-COVID-19 state. To achieve these objectives, we have identified the post-COVID-19 health factors and based on these factors survey data were collected from COVID-recovered patients in Bangladesh. Employing diverse machine learning algorithms, we utilised the best prediction model for post-COVID-19 factors. Initial findings from statistical analysis were further validated using Chi-square to demonstrate significant relationships among these elements. Additionally, Pearson’s coefficient was utilized to indicate positive or negative associations among various physiological and neurological factors in the post-COVID-19 state. Finally, we determined the most effective machine learning model and identified key features using analytical methods such as the Gini Index, Feature Coefficients, Information Gain, and SHAP Value Assessment. And found that the Decision Tree model excelled in identifying crucial features while predicting the extent of post-COVID-19 impact.

Design of convertible patient care unit for both non-pandemic and pandemic times: Prototype, building spatial layout, and ventilation design

Convertible patient care units can accommodate non-respiratory infectious disease patients in non-pandemic times and provide isolated treatment for respiratory infectious disease patients during pandemic times. A prototype convertible patient care unit covering a floor area of 1518 m2, featuring 16 wards, and accommodating 40 beds was developed to examine the impact of building spatial layout and ventilation design on the inter-zonal airborne transmission and energy use intensity (EUI) during both non-pandemic and pandemic times. Building spatial layout referred to the presence of patient corridors and anterooms, while ventilation design referred to the location of air terminals and the calculation method of residual air volume (namely, difference between supply and exhaust airflow rates). Adding anterooms provided an 18 % reduction in pressure gradient fluctuations during door-opening events. The absence of exhaust in the medical corridor, anterooms, and wards increased contamination leakages to the patient corridors. Using the differential pressure method to calculate residual air volume was more effective in controlling the inter-zonal pressure gradient than the fixed residual air volume method. Various conversion methods resulted in an 84%–134 % increase of EUI compared to non-pandemic times, without, however, corresponding reduction in inter-zonal airborne transmission risk. The condition of adding both patient corridors and anterooms, exhaust-only patient corridors, anterooms with balanced supply-exhaust airflow rates, and differential pressure method to calculate residual air volume were effective conversion strategies to simultaneously address both the inter-zonal airborne transmission and EUI. These findings provide fundamental information for designing convertible patient care units and revising related guidelines in China.

Investigating the Impact of Green Space Ratio and Layout on Bioaerosol Concentrations in Urban High-Density Areas: A Simulation Study in Beijing, China

The COVID-19 pandemic significantly impacted global development. Through bioaerosols emitted by human respiration, respiratory infectious diseases, including COVID-19, are transmitted. The bioaerosol concentrations can be affected by the urban climate and morphology. However, the effects of urban green spaces on bioaerosol concentrations remain unclear. Focusing on the dormitory area of Beijing Forestry University, this study first investigated the influence of different green space ratios on the average bioaerosol concentrations using the ENVI-met software. Moreover, both overall and local green space layouts were analyzed for their impact on bioaerosol concentrations. The results indicated that ventilation conditions were the primary factor influencing bioaerosol concentrations. During peak congestion, a 10% increase in the green space ratio resulted in a 2% rise in the average bioaerosol concentration. Furthermore, a distributed layout resulted in a 1.3% higher average bioaerosol concentration than a concentrated layout with an equivalent green space ratio. Enacting strategies such as Roadside Green Spaces Retreat, Road Spaces Expansion, and Intersection Green Spaces Chamfering led to reductions in local bioaerosol concentrations by up to 17.7%, 18.44%, and 12.69%, respectively. This study highlights the importance of adjusting green space layouts in urban high-density areas after the pandemic, reducing the risk of population exposure to bioaerosol concentrations.

Mask-Wearing Detection in Complex Environments Based on Improved YOLOv7

Wearing masks is an effective protective measure for residents to prevent respiratory infectious diseases when going out. Due to issues such as a small target size, target occlusion leading to information loss, false positives, and missed detections, the effectiveness of face mask-wearing detection needs improvement. To address these issues, an improved YOLOv7 object detection model is proposed. Firstly, the C2f_SCConv module is introduced in the backbone network to replace some ELAN modules for feature extraction, enhancing the detection performance of small targets. Next, the SPPFCSPCA module is proposed to optimize the spatial pyramid pooling structure, accelerating the model convergence speed and improving detection accuracy. Finally, the HAM_Detect decoupled detection head structure is introduced to mitigate missed and false detections caused by target occlusion, further accelerating model convergence and improving detection performance in complex environments. The experimental results show that improved YOLOv7 achieved an mAP of 90.1% on the test set, a 1.4% improvement over the original YOLOv7 model. The detection accuracy of each category improved, effectively providing technical support for mask-wearing detection in complex environments.

Gut microbial features may influence antiviral IgG levels after vaccination against viral respiratory infectious diseases: the evidence from two-sample bidirectional mendelian randomization

BackgroundVaccination is effective in preventing viral respiratory infectious diseases through protective antibodies and the gut microbiome has been proven to regulate human immunity. This study explores the causal correlations between gut microbial features and serum-specific antiviral immunoglobulin G (IgG) levels.MethodsWe conduct a two-sample bidirectional Mendelian randomization (MR) analysis using genome-wide association study (GWAS) summary data to explore the causal relationships between 412 gut microbial features and four antiviral IgG (for influenza A, measles, rubella, and mumps) levels. To make the results more reliable, we used four robust methods and performed comprehensive sensitivity analyses.ResultsThe MR analyses revealed 26, 13, 20, and 18 causal associations of the gut microbial features influencing four IgG levels separately. ​Interestingly, ten microbial features, like genus Collinsella, species Bifidobacterium longum, and the biosynthesis of L-alanine have shown the capacity to regulate multiple IgG levels with consistent direction (rise or fall). The ​reverse MR analysis suggested several potential causal associations of IgG levels affecting microbial features.ConclusionsThe human immune response against viral respiratory infectious diseases could be modulated by changing the abundance of gut microbes, which provided new approaches for the intervention of viral respiratory infections.

Genomic analysis of canine pneumoviruses and canine respiratory coronavirus from New Zealand

ABSTRACT Aims To isolate canine respiratory coronavirus (CRCoV) and canine pneumovirus (CnPnV) in cell culture and to compare partial genomic sequences of CRCoV and CnPnV from New Zealand with those from other countries. Methods Oropharyngeal swab samples from dogs affected by canine infectious respiratory disease syndrome that were positive for CnPnV (n = 15) or CRCoV (n = 1) by virus-specific reverse transcriptase quantitative PCR (RT-qPCR) in a previous study comprised the starting material. Virus isolation was performed in HRT-18 cells for CRCoV and RAW 264.7 and Vero cells for CnPnV. The entire sequence of CnPnV G protein (1,266 nucleotides) and most (8,063/9,707 nucleotides) of the 3’ region of CRCoV that codes for 10 structural and accessory proteins were amplified and sequenced. The sequences were analysed and compared with other sequences available in GenBank using standard molecular tools including phylogenetic analysis. Results Virus isolation was unsuccessful for both CRCoV and CnPnV. Pneumovirus G protein was amplified from 3/15 (20%) samples that were positive for CnPnV RNA by RT-qPCR. Two of these (NZ-048 and NZ-049) were 100% identical to each other, and 90.9% identical to the third one (NZ-007). Based on phylogenetic analysis of the G protein gene, CnPnV NZ-048 and NZ-049 clustered with sequences from the USA, Thailand and Italy in group A, and CnPnV NZ-007 clustered with sequences from the USA in group B. The characteristics of the predicted genes (length, position) and their putative protein products (size, predicted structure, presence of N- and O-glycosylation sites) of the New Zealand CRCoV sequence were consistent with those reported previously, except for the region located between open reading frame (ORF)3 (coding for S protein) and ORF6 (coding for E protein). The New Zealand virus was predicted to encode 5.9 kDa, 27 kDa and 12.7 kDa proteins, which differed from the putative coding capacity of this region reported for CRCoV from other countries. Conclusions This report represents the first characterisation of partial genomic sequences of CRCoV and CnPnV from New Zealand. Our results suggest that the population of CnPnV circulating in New Zealand is not homogeneous, and that the viruses from two clades described overseas are also present here. Limited conclusions can be made based on only one CRCoV sequence, but the putative differences in the coding capacity of New Zealand CRCoV support the previously reported variability of this region. The reasons for such variability and its biological implications need to be further elucidated.

Intranasal neomycin evokes broad-spectrum antiviral immunity in the upper respiratory tract

Respiratory virus infections in humans cause a broad-spectrum of diseases that result in substantial morbidity and mortality annually worldwide. To reduce the global burden of respiratory viral diseases, preventative and therapeutic interventions that are accessible and effective are urgently needed, especially in countries that are disproportionately affected. Repurposing generic medicine has the potential to bring new treatments for infectious diseases to patients efficiently and equitably. In this study, we found that intranasal delivery of neomycin, a generic aminoglycoside antibiotic, induces the expression of interferon-stimulated genes (ISGs) in the nasal mucosa that is independent of the commensal microbiota. Prophylactic or therapeutic administration of neomycin provided significant protection against upper respiratory infection and lethal disease in a mouse model of COVID-19. Furthermore, neomycin treatment protected Mx1 congenic mice from upper and lower respiratory infections with a highly virulent strain of influenza A virus. In Syrian hamsters, neomycin treatment potently mitigated contact transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In healthy humans, intranasal application of neomycin-containing Neosporin ointment was well tolerated and effective at inducing ISG expression in the nose in a subset of participants. These findings suggest that neomycin has the potential to be harnessed as a host-directed antiviral strategy for the prevention and treatment of respiratory viral infections.

Epidemiological and etiological characteristics of 1266 patients with severe acute respiratory infection in central China, 2018–2020: a retrospective survey

Epidemiological and etiological characteristics of 1266 patients with severe acute respiratory infection in central China, 2018–2020: a retrospective survey

A Markov chain-based approach for assessing respiratory infection risk in a multi-zone office building

Most respiratory infectious disease transmission events occur in indoor environments, and examining the infection risk in different types of multi-zone buildings is critical to the safe reopening and use of public buildings. Appropriate space design influences occupant behavior and virus spread, thereby aiding in mitigating indoor infection risk. This study aims to quickly evaluate the multi-route infection risk in multi-zone buildings with relatively stable occupant populations, and to quantify the effectiveness of spatial interventions at different levels. A Markov chain-based approach was proposed to characterize occupants' time-activity trajectories with low time cost and relatively high accuracy. Four transmission routes are considered, especially for the fine-grained characterization of close contact. A real university office building was selected as a case study to quantitatively evaluate the effects of three non-pharmacological interventions including spatial layout, ventilation, and occupant behavioral control. Results showed that short-range airborne transmission dominated, and optimized combination spatial design interventions reduced the indoor infection risk by up to 10 %. Zone layout intervention was the most effective, with the division of the open-plan office area into three subzones, reducing the risk by 9.6 %, which was superior to the intervention of maintaining a one-meter interpersonal distance. Followed by the furniture layout, without changing the seating capacity and without desktop baffles, the L-shaped table layout worked better reducing the risk by 2.78 %. This study can help architects and managers better understand the risk of indoor transmission in multizone buildings from a spatial design perspective, to select appropriate interventions to reduce the risk.

Dynamics of respiratory infectious diseases under rapid urbanization and COVID-19 pandemic in the subcenter of Beijing during 2014–2022

ObjectiveThe study analyzed the impact of urbanization on epidemiological characteristics of respiratory infectious disease in Tongzhou District, Beijing during 2014–2022 to provide reference for prevention and control priorities of respiratory infectious diseases during the innovative urbanization process in China. MethodsThe incidence data of notifiable respiratory infectious diseases (NRIDs) in Tongzhou Beijing during 2014–2022 were summarized. The trend of incidence rate was analyzed by Joinpoint regression model, and entropy method was performed to construct the comprehensive index of urbanization (CIU) and generalized linear model was used to analyze the influence of CIU on the incidence rate of respiratory infectious diseases. ResultsTotally 72616 NRIDs cases were reported in Tongzhou District during 2014–2022, and the incidence rate of NRIDs was higher during 2017–2019 (153/100 000) than during 2014–2016 (930/100 000) and during 2020–2022 (371/100 000), respectively (both P < 0.001). The CIU constantly increased with slight fluctuation in 2016 and 2018, respectively. The incidence rate of NRIDs showed an increase along with the CIU during 2014–2019 (r = 0.95, P = 0.004), while the incidence rate's tendency was interrupted by COVID-19 during 2020 with slight decrease in 2020–2021 and rebounded in 2022. For the patients aged <15 years, the incidence rate of NRIDs revealed a very sharp rise at the urbanization period without COVID-19 pandemic compared with that under pre-urbanization period (RR = 7.93, 95 % CI 7.63−8.24), and dropped off to the similar level as of pre-urbanization period when COVID-19 pandemic spread. ConclusionsUrbanization process may increase the incidence of NRIDs but constrained by COVID-19. Certain measures should be taken to prevent and control the effects by urbanization process, such as good natural environment with less population density, ecological environment with good air quality, promoted hand hygiene, mask wearing, keeping interpersonal distance, vaccination, media publicity for NRIDs’ prevention and control.

Occupation and Covid-19: Lessons from the Pandemic

Recognition that an individual's job could impact their likelihood of contracting coronavirus disease 2019 created challenges for investigators who sought to better understand and prevent transmission of the severe acute respiratory syndrome coronavirus 2. Considerable research resources were devoted to separating the effects of occupational from non-occupational risk factors. This commentary highlights results from studies that adjusted for multiple non-occupational risk factors while estimating the effects of occupations and occupational risk factors. Methods used in these studies will prove useful in future infectious disease epidemics and pandemics, and could potentially enrich studies of other occupational infectious and non-infectious respiratory diseases as well.