Epidemic Trends Research Articles

Variability in competitive fitness among environmental and clinical azole-resistant Aspergillus fumigatus isolates.

Azole resistance in the human fungal pathogen Aspergillus fumigatus presents a global public health challenge. Understanding the epidemic trends and evolutionary patterns of azole resistance is critical to prevent and control the spread of azole-resistant isolates. The primary cause is the mutation of the drug target 14α-sterol-demethylase Cyp51A, yet its impact on competitive ability remains uncertain. Our competition assays revealed a diverse range of fitness outcomes for environmental and clinical cyp51A-mutated isolates. We have shown that this fitness cost is not reliant on cyp51A mutations but might be linked to unknown mutations induced by stress conditions. Among these isolates, the majority displayed fitness costs, while a few displayed enhanced competitive ability, which may have a potential risk of spread and the need to closely monitor these isolates. Our observation reveals the variation in fitness costs among azole-resistant isolates of A. fumigatus, highlighting the significant role of fitness cost in the spread of resistant strains.

A mathematical model for evaluating the impact of nonpharmaceutical interventions on the early COVID-19 epidemic in the United Kingdom

The coronavirus disease 2019 (COVID-19) presents a severe and urgent threat to global health. In response to the COVID-19 pandemic, many countries have implemented nonpharmaceutical interventions (NPIs), including national workplace and school closures, personal protection, social distancing, contact tracing, testing, home quarantine, and isolation. To evaluate the effectiveness of these NPIs in mitigating the spread of early COVID-19 and predict the epidemic trend in the United Kingdom, we developed a compartmental model to mimic the transmission with time-varying transmission rate, contact rate, disease-induced mortality rate, proportion of quarantined close contacts, and hospitalization rate. The model was fitted to the number of confirmed new cases and daily number of deaths in five stages with a Markov Chain Monte Carlo method. We quantified the effectiveness of NPIs and found that if the transmission rate, contact rate, and hospitalization rate were approximately equal to those in the second stage of the most strict NPIs, and the proportion of quarantined close contacts increased by 3%, then the epidemic would die out as early as January 12, 2021, with around 1,533,000 final cumulative number of confirmed cases, and around 55,610 final cumulative number of deaths.

Case fatality rates of COVID‐19 during epidemic periods of variants of concern: A meta-analysis by continents

ObjectivesTo calculate the case fatality rates (CFR) of COVID‐19 during epidemic periods of different variants of concern (VOC) by continents. MethodsWe systematically searched five authoritative databases (Web of Science, PubMed, Embase, Cochrane Library, and MedRxiv) for epidemiological studies on the CFR of COVID-19 published between January 1, 2020, and March 31, 2023. After identifying the epidemic trends of variants, we used a random-effects model to calculate the pooled CFRs during periods of different VOCs. This meta-analysis was conducted following the guidelines of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and registered with PROSPERO (CRD42023431572). ResultsThere were variations in the CFRs among different variants of COVID-19 (Alpha: 2.62%, Beta: 4.19%, Gamma: 3.60%, Delta: 2.01%, Omicron: 0.70%), and disparities in CFRs also existed among continents. On the whole, the CFRs of COVID-19 in Europe and Oceania were slightly lower than in other continents. There was a statistically significant association between the variant, HDI value, age distribution, coverage of full vaccination of cases, and the CFR. ConclusionsThe CFRs of COVID-19 varied across the epidemic periods of different VOCs, and disparities existed among continents. The CFR value reflected combined effects of various factors within a certain context. Caution should be exercised when comparing CFRs due to disparities in testing capabilities and age distribution among countries, etc.

Inferring community transmission of SARS-CoV-2 in the United Kingdom using the ONS COVID-19 Infection Survey

Key epidemiological parameters, including the effective reproduction number, R(t), and the instantaneous growth rate, r(t), generated from an ensemble of models, have been informing public health policy throughout the COVID-19 pandemic in the four nations of the United Kingdom of Great Britain and Northern Ireland (UK). However, estimation of these quantities became challenging with the scaling down of surveillance systems as part of the transition from the “emergency” to “endemic” phase of the pandemic.The Office for National Statistics (ONS) COVID-19 Infection Survey (CIS) provided an opportunity to continue estimating these parameters in the absence of other data streams. We used a penalised spline model fitted to the publicly-available ONS CIS test positivity estimates to produce a smoothed estimate of the prevalence of SARS-CoV-2 positivity over time. The resulting fitted curve was used to estimate the “ONS-based” R(t) and r(t) across the four nations of the UK. Estimates produced under this model are compared to government-published estimates with particular consideration given to the contribution that this single data stream can offer in the estimation of these parameters.Depending on the nation and parameter, we found that up to 77% of the variance in the government-published estimates can be explained by the ONS-based estimates, demonstrating the value of this singular data stream to track the epidemic in each of the four nations. We additionally find that the ONS-based estimates uncover epidemic trends earlier than the corresponding government-published estimates.Our work shows that the ONS CIS can be used to generate key COVID-19 epidemiological parameters across the four UK nations, further underlining the enormous value of such population-level studies of infection. This is not intended as an alternative to ensemble modelling, rather it is intended as a potential solution to the aforementioned challenge faced by public health officials in the UK in early 2022.

The cases of tracing the source of patients infected with Omicron variant of SARS-CoV-2 based on wastewater-based epidemiology in Shenzhen

Wastewater-based epidemiology (WBE) is an emerging discipline, which has been applied to drug abuse tracking and infectious disease pathogen surveillance. During the COVID-19 epidemic, WBE has been applied to monitor the epidemic trend and SARS-CoV-2 variants etc. In order to detect hidden COVID-19 cases and prevent transmission in the community, wastewater surveillance system for monitoring SARS-CoV-2 RNA was developed in Shenzhen. The sewage sampling sites were set up in key places such as the port areas, urban villages and residential communities of Futian, Nanshan, Luohu and Yantian districts. From July 26 to November 30, 2022, a total of 369 sewage sampling sites were set up, covering 1.93 million people. Continuous sampling was carried out for 3 hours in the peak period of water use every day. Sewage virus enrichment and SARS-CoV-2 nucleic acid detection were carried out by polyethylene glycol precipitation method and RT-qPCR, and a positive water sample disposal process was molded. This article aims to introduce the case of source tracing of COVID-19 infected patients based on urban sewage in Shenzhen. The sewage monitoring of Honghu water treatment plant in Luohu District played an early warning role, and the source of infection was traced. In the disposal of positive water samples in Futian South Road, Futian District, the important experience of monitoring point layout was obtained. In the sewage monitoring of Nanshan village, Nanshan District, the existence of occult infection was revealed. Sharing the experience of tracing the source of COVID-19 patients to avoid the spread of COVID-19 in the community based on wastewater surveillance of SARS-CoV-2 RNA in Shenzhen, and summarizing the advantages and application prospects of sewage surveillance can provide new ideas for monitoring emerging or re-emerging pathogens that are known to exhibit gastrointestinal excretion in the future.

Reviewed the Research Strategy and Progress of SARS-CoV-2 Live Attenuated Vaccine Under the Global Omicron Epidemic Trend

Reviewed the Research Strategy and Progress of SARS-CoV-2 Live Attenuated Vaccine Under the Global Omicron Epidemic Trend

Global burden and epidemic trends of gout attributable to high body mass index from 1990 to 2019.

Gout is an inflammatory and metabolic disease characterized by arthritis and elevation of the serum uric acid (SUA) level. More and more studies have shown that high body mass index (BMI) has become one of the most important risk factors for gout. We used the data of gout burden attributed to high body mass index (BMI) from global burden of disease (GBD) study 2019 to provide insights for reducing the global burden of gout. From 1990 to 2019, the prevalence and DALYs of gout caused by high BMI worldwide has been increasing. The burden of gout caused by high BMI is heavier in the elderly male group and regions with high SDI worldwide. Our findings provide evidence for the burden of gout caused by high BMI. Developing a weight management plan and lifestyle habits for groups severely affected by gout will effectively reduce the global disease and economic burden.

Quantitative Study on American COVID-19 Epidemic Predictions and Scenario Simulations

The COVID-19 pandemic has had a profound impact on people’s lives, making accurate prediction of epidemic trends a central focus in COVID-19 research. This study innovatively utilizes a spatiotemporal heterogeneity analysis (GTNNWR) model to predict COVID-19 deaths, simulate pandemic prevention scenarios, and quantitatively assess their preventive effects. The results show that the GTNNWR model exhibits superior predictive capacity to the conventional infectious disease dynamics model (SEIR model), which is approximately 9% higher, and reflects the spatial and temporal heterogeneity well. In scenario simulations, this study established five scenarios for epidemic prevention measures, and the results indicate that masks are the most influential single preventive measure, reducing deaths by 5.38%, followed by vaccination at 3.59%, and social distancing mandates at 2.69%. However, implementing single stringent preventive measures does not guarantee effectiveness across all states and months, such as California in January 2025, Florida in August 2024, and March–April 2024 in the continental U.S. On the other hand, the combined implementation of preventive measures proves 5 to-10-fold more effective than any single stringent measure, reducing deaths by 27.2%. The deaths under combined implementation measures never exceed that of standard preventive measures in any month. The research found that the combined implementation of measures in mask wearing, vaccination, and social distancing during winter can reduce the deaths by approximately 45%, which is approximately 1.5–3-fold higher than in the other seasons. This study provides valuable insights for COVID-19 epidemic prevention and control in America.

Epidemic trend of tuberculosis in adolescents in China, 2000-2019

Objective: To analyze the epidemic trend of tuberculosis (TB) in adolescents in China from 2000 to 2019. Methods: We used data from Global Burden of Disease Study 2019 to describe the epidemic trend of TB. The estimated annual percentage changes (EAPC) of the morbidity and mortality were calculated to assess epidemic trends from 2000 to 2019. Results: In 2019, a total of 37 815.670 TB cases and 213.629 deaths were reported in adolescents in China, the morbidity was 25.938/100 000 and the mortality was 0.147/100 000. The cases and deaths of TB in 2019 decreased by 71.84% and 89.90% respectively compared with 2000. In 2019, the incident case number (21 371.747) was 1.30 times higher in male adolescents than in female adolescents (16 443.923), and was 4.11 times higher in age group 15-19 years (30 420.054) than in age group 10-14 years (7 395.616). From 2000 to 2019, the morbidity (EAPC=-3.95, 95%CI: -4.34- -3.55) and mortality (EAPC=-9.18, 95%CI: -9.33- -9.02) of TB in the adolescents showed decreasing trends. The morbidity and mortality of drug-sensitive TB, extensively drug-resistant TB and multidrug-resistant TB all showed decreasing trends. Conclusions: The morbidity and mortality of TB and its subtypes among adolescents in China decreased during 2000-2019. More attention should be paid to male adolescents and adolescents aged 15-19 years due to relatively higher incidence intensity of TB.

Spatial-temporal analysis of hepatitis E in Hainan Province, China (2013-2022): insights from four major hospitals.

Exploring the Incidence, Epidemic Trends, and Spatial Distribution Characteristics of Sporadic Hepatitis E in Hainan Province from 2013 to 2022 through four major tertiary hospitals in the Province. We collected data on confirmed cases of hepatitis E in Hainan residents admitted to the four major tertiary hospitals in Haikou City from January 2013 to December 2022. We used SPSS software to analyze the correlation between incidence rate and economy, population density and geographical location, and origin software to draw a scatter chart and SAS 9.4 software to conduct a descriptive analysis of the time trend. The distribution was analyzed using ArcMap 10.8 software (spatial autocorrelation analysis, hotspot identification, concentration, and dispersion trend analysis). SAS software was used to build an autoregressive integrated moving average model (ARIMA) to predict the monthly number of cases in 2023 and 2024. From 2013 to 2022, 1,922 patients with sporadic hepatitis E were treated in the four hospitals of Hainan Province. The highest proportion of patients (n = 555, 28.88%) were aged 50-59 years. The annual incidence of hepatitis E increased from 2013 to 2019, with a slight decrease in 2020 and 2021 and an increase in 2022. The highest number of cases was reported in Haikou, followed by Dongfang and Danzhou. We found that there was a correlation between the economy, population density, latitude, and the number of cases, with the correlation coefficient |r| value fluctuating between 0.403 and 0.421, indicating a linear correlation. At the same time, a scatter plot shows the correlation between population density and incidence from 2013 to 2022, with r2 values fluctuating between 0.5405 and 0.7116, indicating a linear correlation. Global Moran's I, calculated through spatial autocorrelation analysis, showed that each year from 2013 to 2022 all had a Moran's I value >0, indicating positive spatial autocorrelation (p < 0.01). Local Moran's I analysis revealed that from 2013 to 2022, local hotspots were mainly concentrated in the northern part of Hainan Province, with Haikou, Wenchang, Ding'an, and Chengmai being frequent hotspot regions, whereas Baoting, Qiongzhong, and Ledong were frequent cold-spot regions. Concentration and dispersion analysis indicated a clear directional pattern in the average density distribution, moving from northeast to southwest. Time-series forecast modeling showed that the forecast number of newly reported cases per month remained relatively stable in 2023 and 2024, fluctuating between 17 and 19. The overall incidence of hepatitis E in Hainan Province remains relatively stable. The incidence of hepatitis E in Hainan Province increased from 2013 to 2019, with a higher clustering of cases in the northeast region and a gradual spread toward the southwest over time. The ARIMA model predicted a relatively stable number of new cases each month in 2023 and 2024.

Screening, epidemic trends and drug sensitivity analysis of nontuberculous mycobacteria in a local area of China.

To analyze the isolation rate, prevalence trends, species distribution, and drug sensitivity of non-tuberculous mycobacteria (NTM) in Anhui Province, providing a reference for diagnosis and treatment strategies. Specimens from suspected mycobacterial infection patients at Anhui Chest Hospital (including outpatients and inpatients) from January 2021 to December 2023 were cultured. Identified NTM strains were analyzed for species distribution and drug sensitivity. Of 10,519 mycobacteria strains cultured, 1,589 were NTM (15.11%). The top four species were Mycobacterium intracellulare (75.36%), Mycobacterium abscessus (11.78%), Mycobacterium kansasii (7.09%), and Mycobacterium avium (2.85%). NTM strains showed high sensitivity to amikacin and clarithromycin (≥90%) and significant sensitivity to rifabutin, moxifloxacin, and rifampicin (89.03%-79.61%). They exhibited high resistance to imipenem/cilastatin, sulfamethoxazole, minocycline, and doxycycline (≥95%). NTM isolation rates in Anhui have remained stable, with the predominant species being M. intracellulare, M. kansasii, M. abscessus, and M. avium. NTM strains are highly sensitive to amikacin, clarithromycin, rifabutin, moxifloxacin, and rifampicin. These findings can guide diagnosis, treatment strategies, and drug selection for NTM disease in Anhui Province.

Epidemic trend, genetic characteristics, and transmission networks of HIV-1 among treatment-naive men who have sex with men in Hebei province, China.

Homosexual transmission has contributed greatly to the current HIV-1 epidemic in Hebei province, China. Dolutegravir (DTG) will be conditionally used as a component of free antiretroviral therapy (ART) according to manual for national free anti-AIDS treatment drugs (2023 edition) issued by China in June 2023. However, current genetic characteristics and pretreatment drug resistance (PDR) to proteinase inhibitors (PIs), reverse transcriptase inhibitors (RTs) and integrase strand transfer inhibitors (INSTIs) of HIV-1 in this population have remained unclear. Serial consecutive cross-sectional analyses for HIV- 1 infection trend, genetic characteristics, PDR and molecular transmission networks were conducted from 2018 to 2022. All of participants were HIV-1- infected MSM newly diagnosed at the HIV surveillance points (HSPs) in Hebei, China. Evidence of PDR was confirmed using the world health organization (WHO) list for surveillance of drug resistance mutations. In this study, a total of 14 HIV-1 subtypes were circulating in the HSPs of Hebei province, China. CRF01_ AE (51.9%, 350/675), CRF07_BC (30.4%, 205/675), B (6.2%, 42/675) and URFs (5.8%, 39/675) were the four most predominant subtypes among MSM. And, CRF07_BC (r > 0) and URFs (r > 0) indicated an increasing trend, respectively; however, CRF01_AE (r < 0) showed a decline trend. The overall prevalence of HIV-1 PDR showed a substantial increase from 6.3% in 2018 to 7.9% in 2022. The prevalence of NNRTI-PDR was the highest (5.8%, 39/675), followed by INSTIs (2.4%, 16/675), NRTIs (0.6%, 4/675) and PIs (0.3%, 2/675). Furthermore, extensive HIV-1 strains bearing PDR were circulating in the MSM population via molecular transmission networks for major HIV-1 subtypes, especially CRF01_AE and CRF07_BC. Our findings reflect that HIV-1 epidemic in the MSM population is complex and severe in Hebei, China. Therefore, it is urgent for us to implement more effective intervention measures to limit the further dissemination of HIV-1, especially the spread of HIV-1 INSTI-PDR strains.

Assessing the impact of vaccination and medical resource allocation on infectious disease outbreak management: a case study of COVID-19 in Taiyuan City.

Amidst an emerging infectious disease outbreak, the rational allocation of vaccines and medical resources is crucial for controlling the epidemic's progression. Analysing COVID-19 data in Taiyuan City from December 2022 to January 2023, this study constructed a dynamics model to assess the impact of COVID-19 vaccination and resource allocation on epidemic trends. Vaccination significantly reduces infection rates, hospitalisations, and severe cases, while also curtailing strain on medical resources by reducing congestion periods. An early and sufficient reserve of medical resources can delay the onset of medical congestion, and with increased maximum capacity of medical resources, the congestion's end can be accelerated. Stronger resource allocation capabilities lead to earlier congestion resolution within a fixed total resource pool. Integrating vaccination and medical resource allocation can effectively reduce medical congestion duration and alleviate the epidemic's strain on medical resource capacity (CCMR).

Cross-talk of MLST and transcriptome unveiling antibiotic resistance mechanism of carbapenem resistance Acinetobacter baumannii clinical strains isolated in Guiyang, China.

Acinetobacter baumannii (A. baumannii) is an important opportunistic pathogen causing nosocomial infection in the clinic. The occurrence rate of antibiotic resistance is increasing year by year, resulting in a highly serious situation of bacterial resistance. To better understand the local epidemiology of multidrug-resistant A. baumannii, an investigation was conducted on the antibiotic resistance of different types of A. baumannii and its relationship with the genes of A. baumannii. Furthermore, the molecular mechanism underlying antibiotic resistance in A. baumannii was investigated through transcriptome analysis. These results showed that a total of 9 STs were detected. It was found that 99% of the strains isolated in the hospital belonged to the same STs, and the clone complex CC208 was widely distributed in various departments and all kinds of samples. Furthermore, these A. baumannii strains showed high resistance to ertapenem, biapenem, meropenem, and imipenem, among which the resistance to ertapenem was the strongest. The detection rate of bla OXA-51 gene in these carbapenem resistance A. baumannii (CRAB) reached 100%; Additionally, the transcriptome results showed that the resistance genes were up-regulated in resistance strains, and these genes involved in biofilm formation, efflux pumps, peptidoglycan biosynthesis, and chaperonin synthesis. These results suggest that the CC208 STs were the main clonal complex, and showed high carbapenem antibiotic resistance. All these resistant strains were distributed in various departments, but most of them were distributed in intensive care units (ICU). The bla OXA-23 was the main antibiotic resistance genotype; In summary, the epidemic trend of clinical A. baumannii in Guiyang, China was analyzed from the molecular level, and the resistance mechanism of A. baumannii to carbapenem antibiotics was analyzed with transcriptome, which provided a theoretical basis for better control of A. baumannii.

ЭПИДЕМИОЛОГИЧЕСКИЕ АСПЕКТЫ НАРУШЕНИЙ МЕНТАЛЬНОГО ЗДОРОВЬЯ – ОТ ПРЕДИКТОРОВ К СЛЕДСТВИЮ

Introduction. Due to the high social significance of mental health disorders, the study of the spread and degree of influence of modifiable predictors of depressive psychoemotional status can contribute to the development of new approaches to active prevention. The purpose of the study. To study the epidemiological characteristics of mental health disorders and identify key predictors among students. Methods. To conduct the study, epidemiological diagnostic methods were used, such as: retrospective epidemiological analysis, descriptive and evaluative methods, as well as statistical methods, methods of epidemiological diagnostics using methods of clinical epidemiology and statistical analysis were used. Results. There was a moderate long-term epidemic trend towards an increase in the incidence of mental disorders (an increase rate of 3.68%) and a high long-term average (164.44+1.72о/оооо). The risk area is determined on the basis of the characteristic pronounced tendency to growth and an increased level of relative epidemiological risk: Minsk region, Minsk, Vitebsk and Mogilev regions (Tpr = 6.56%, 9.99%, 15.21%, and 15.57%, respectively. Consequently, the risks were: in Minsk – 0.77, in Vitebsk and Mogilev regions – 0.78 and 0.86, respectively). The result of our own original research was the identification of a depressive state in 59.25% of cases and generalized anxiety disorder – in 64.1% of cases. An aggravating circumstance is the fact of comorbidity in more than 80% of cases. When studying the epidemiological characteristics of these disorders, significant predictors were identified that increased the chance of developing a state by 2.5-11.5 times. Conclusion. The high levels of prevalence and comorbidity of depressive psychoemotional status and anxiety disorder characterize the general epidemiological situation within the mental health of students as unfavorable and require the development of preventive measures.

Prediction of SARS-CoV-2 infection cases based on the meta-SEIRS model

Abstract Predicting epidemic trends of coronavirus disease 2019 (COVID-19) remains a key public health concern globally today. However, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection rate in previous studies of the transmission dynamics model was mostly a fixed value. Therefore, we proposed a meta-Susceptible-Exposed-Infectious-Recovered-Susceptible (SEIRS) model by adding a time-varying SARS-CoV-2 reinfection rate to the transmission dynamics model to more accurately characterize the changes in the number of infected persons. The time-varying reinfection rate was estimated using random-effect multivariate meta-regression based on published literature reports of SARS-CoV-2 reinfection rates. The meta-SEIRS model was constructed to predict the epidemic trend of COVID-19 from February to December 2023 in Sichuan province. Finally, according to the online questionnaire survey, the SARS-CoV-2 infection rate at the end of December 2022 in Sichuan province was 82.45%. The time-varying effective reproduction number in Sichuan province had two peaks from July to December 2022, with a maximum peak value of about 15. The prediction results based on the meta-SEIRS model showed that the highest peak of the second wave of COVID-19 in Sichuan province would be in late May 2023. The number of new infections per day at the peak would be up to 2.6 million. We constructed a meta-SEIRS model to predict the epidemic trend of COVID-19 in Sichuan province, which was consistent with the trend of SARS-CoV-2 positivity in China. Therefore, a meta-SEIRS model parameterized based on evidence-based data can be more relevant to the actual situation and thus more accurately predict future trends in the number of infections.

Novel identification of mixed infection of Lactococcus garvieae and Cryptocaryon irritans isolated from cultured Trachinotus ovatus in China.

Lactococcus garvieae has recently been identified and listed as one of the causative agents of hyperacute hemorrhagic sepsis in fish. In intensive recirculating aquaculture systems where there are high fish densities and minimal water changes, not only will it be conducive to the growth of bacteria, but Cryptocaryon irritans as a marine protozoan fish parasite is also prone to appear. This study reports the disease status of Trachinotus ovatus in an aquaculture area in Yangjiang City, Guangdong Province. Through the diagnosis of clinical symptoms of the diseased fish, identification of specific primers, 16s rRNA sequences phylogenetic tree analysis, physiological and biochemical identification, and observation of histopathological sections, the result of the experiment is that the mass death of T. ovatus is caused by a mixture of L. garvieae and C. irritants infections. Subsequently, regression infection experiments were performed to verify Koch's law. It was confirmed that the pathogen had strong virulence to T. ovatus. This is the first time that the co-infection of L. garvieae and C. irritans to T. ovatus was found in South China. The research results of this experiment have certain enlightenment significance for the epidemic trend of fish diseases in relevant sea areas.

High-Density Communities and Infectious Disease Vulnerability: A Built Environment Perspective for Sustainable Health Development

High-density communities have proliferated globally during rapid urbanization. They are characterized by a high population density and limited per capita public spaces, making them susceptible to infectious disease risks. The impact of infectious diseases in these communities, as evident during the COVID-19 pandemic, underscores their vulnerabilities. Yet, research on disease prevention in high-density areas remains limited. This study aims to investigate the relationship between the built environment and the transmission of infectious diseases in high-density urban communities, with a particular focus on the lessons learned during the COVID-19 pandemic. Utilizing Shenzhen city as a case study, this study collected data on the built environment and epidemic trends and involved a generalized linear regression analysis, aiming to understand the key built environment factors that affect epidemic spread in high-density areas. The results from the study revealed that high-density communities experience higher rates of infectious disease transmission compared to their medium- to low-density counterparts. The significant factors identified include land use mixture and walkability, with land use mixture showing the most substantial impact on infection rates. Through a combination of qualitative analysis and empirical research, we constructed a conceptual framework linking containment measures, non-pharmaceutical interventions, and the built environment. The findings emphasize the significance to focus on the health development of high-density communities and offer valuable insights for tailored urban planning and built environment design. These insights are crucial for promoting the healthy and sustainable transformation of existing high-density communities.

Using logistic function to predict epidemic trend of COVID-19 in China

As the novel coronavirus continues to spread and mutate, there has been growing concern over public health. Multiple measures have been enacted to mitigate the transmission of the disease, resulting in varying infection scenarios across different countries. To achieve timely and effective control of the epidemic, we note that predicting the future course of an epidemic plays an important role. The logistic function, a continuous-time demographic model, may be a suitable mathematical tool for estimating the trend of the epidemic. This paper aims to evaluate the accuracy of the logistic map in estimating the future trend of the COVID-19. We collect the most recent COVID-19 epidemiological data prior to January 30, 2023, and subsequently integrate figures into the curve fitting tool in MATLAB to generate an epidemic curve. By comparing the actual numbers and the predicted figures, the accuracy of logistic map can be properly assessed.

Trattare la bronchiolite con nCPAP nelle Pediatrie per “proteggere” le Terapie Intensive pediatriche?

Respiratory support with oxygen (O2 ) is the recognized mainstay of treatment in acute bronchiolitis. The methods of administration include - in addition to low flow O2 - also heated and humidified high flow O2 (HFNC) and CPAP, according to an increasing stratification of severity and respiratory effort. The transition from HFNC to CPAP requires, in most cases, the transfer of the child to an intensive care unit (PICU). The particular epidemic trend of bronchiolitis in the post-pandemic years and the concrete risk of care overload for PICUs led us to consider the use of nCPAP in the general paediatric ward as an alternative to transfer to intensive care, aiming to reduce the pressure on the PICU and the consequent discomfort and psychological load for children and their families. We describe our preliminary experience - which allowed us to avoid about 80% of transfers to PICU for bronchiolitis - discussing some clinical issues and possible organizational developments.