Hospital Admissions For Respiratory Diseases Research Articles

Association between PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} and respiratory diseases admission in peninsula Malaysia during haze

Numerous studies have been conducted in other countries on the health effects of exposure to particulate matter with a diameter of 10 microns or less PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document}, but little research has been conducted in Malaysia, particularly during the haze season. This study intends to investigate how exposure of PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} influenced hospital admissions for respiratory diseases during the haze period in peninsula Malaysia and it was further stratified by age group, gender and respiratory diseases categories. The study includes data from all patients with respiratory diseases in 92 government hospitals, as well as PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} concentration and meteorological data from 92 monitoring stations in Peninsula Malaysia starting from 1st January 2000 to 31st December 2019. A quasi-poison time series regression with distributed lag nonlinear model (DLNM) was employed in this study to examine the relationship between exposure of PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} and hospital admissions for respiratory diseases during the haze period. Haze period for this study has been defined from June to September each year. According to the findings of this study, PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} was positively associated with hospitalisation of respiratory disease within 30 lag days under various lag patterns, with lag 25 showing the strongest association (RR = 1.001742, CI 1.001029,1.002456). Using median as a reference, it was discovered that females were more likely than males to be hospitalized for PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} exposure. Working age group will be the most affected by the increase in PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} exposure with a significant cumulative RR from lag 010 to lag 030. The study found that PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} had a significant influence on respiratory hospitalisation in peninsula Malaysia, particularly for lung diseases caused by external agents(CD5). Therefore, it is important to implement effective intervention measures to control PM10\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PM_{10}$$\\end{document} and reduce the burden of respiratory disease admissions.

Impact of the coronavirus disease 2019 pandemic on hospital admissions for idiopathic pulmonary fibrosis: a nationwide population-based study

BackgroundPrevious studies have consistently reported a decrease in hospital admissions for respiratory diseases during the coronavirus disease 2019 (COVID-19) pandemic. However, the impact of the pandemic on idiopathic pulmonary fibrosis (IPF) admissions remains unknown.MethodsThis study used data from the Korean National Health Insurance Service database. IPF was defined based on the International Classification of Diseases 10th Revision (ICD-10) and rare intractable disease (RID) codes. The rate of IPF admissions was calculated by dividing the number of IPF admissions by the prevalence of IPF. The rate of IPF admissions during the COVID-19 pandemic (2020–2021) was compared with the mean rate of admissions during the prepandemic period (2017–2019) and presented as the rate ratio (RR). A sensitivity analysis was conducted on patients treated with systemic corticosteroids during IPF admission.ResultsIn patients with IPF defined based on the ICD-10 (analysis 1), the RRs significantly decreased from March in 2020 to December 2021, except for June and September in 2020. Similarly, in patients with IPF defined based on the ICD-10 and RID (analysis 2), the RRs significantly decreased from March 2020 to December 2021, except for June and September 2020. In the sensitivity analysis of analysis 1, the RR significantly decreased in 2020 (0.93; 95%CI: 0.88–0.99; P = 0.029), whereas the RR in 2021 was not significantly different. The RRs in the sensitivity analysis of analysis 2 significantly decreased to 0.85 (0.79–0.92; P < 0.001) in 2020 and 0.82 (0.76–0.88; P < 0.001) in 2021. In the subgroup analysis, the rates of IPF admissions significantly decreased in 2020 and 2021 across both sexes, patients aged ≥ 60 years, and all household income groups.ConclusionsThe rate of IPF admissions significantly decreased during the COVID-19 pandemic. This result indicates that preventive measures against COVID-19 may effectively mitigate IPF exacerbation. Therefore, it is assumed that there is a close relationship between respiratory viral infections and IPF exacerbations.

Predicting hospital admissions for upper respiratory tract complaints: An artificial neural network approach integrating air pollution and meteorological factors.

This study uses artificial neural networks (ANNs) to examine the intricate relationship between air pollutants, meteorological factors, and respiratory disorders. The study investigates the correlation between hospital admissions for respiratory diseases and the levels of PM10 and SO2 pollutants, as well as local meteorological conditions, using data from 2017 to 2019. The objective of this study is to clarify the impact of air pollution on the well-being of the general population, specifically focusing on respiratory ailments. An ANN called a multilayer perceptron (MLP) was used. The network was trained using the Levenberg-Marquardt (LM) backpropagation algorithm. The data revealed a substantial increase in hospital admissions for upper respiratory tract diseases, amounting to a total of 11,746 cases. There were clear seasonal fluctuations, with fall having the highest number of cases of bronchitis (N = 181), sinusitis (N = 83), and upper respiratory infections (N = 194). The study also found demographic differences, with females and people aged 18 to 65years having greater admission rates. The performance of the ANN model, measured using R2 values, demonstrated a high level of predictive accuracy. Specifically, the R2 value was 0.91675 during training, 0.99182 during testing, and 0.95287 for validating the prediction of asthma. The comparative analysis revealed that the ANN-MLP model provided the most optimal result. The results emphasize the effectiveness of ANNs in representing the complex relationships between air quality, climatic conditions, and respiratory health. The results offer crucial insights for formulating focused healthcare policies and treatments to alleviate the detrimental impact of air pollution and meteorological factors.

Amazon Wildfires and Respiratory Health: Impacts during the Forest Fire Season from 2009 to 2019.

The Brazilian Amazon, a vital tropical region, faces escalating threats from human activities, agriculture, and climate change. This study aims to assess the relationship between forest fire occurrences, meteorological factors, and hospitalizations due to respiratory diseases in the Legal Amazon region from 2009 to 2019. Employing simultaneous equation models with official data, we examined the association between deforestation-induced fires and respiratory health issues. Over the studied period, the Legal Amazon region recorded a staggering 1,438,322 wildfires, with 1,218,606 (85%) occurring during August-December, known as the forest fire season. During the forest fire season, a substantial portion (566,707) of the total 1,532,228 hospital admissions for respiratory diseases were recorded in individuals aged 0-14 years and 60 years and above. A model consisting of two sets of simultaneous equations was constructed. This model illustrates the seasonal fluctuations in meteorological conditions driving human activities associated with increased forest fires. It also represents how air quality variations impact the occurrence of respiratory diseases during forest fires. This modeling approach unveiled that drier conditions, elevated temperatures, and reduced precipitation exacerbate fire incidents, impacting hospital admissions for respiratory diseases at a rate as high as 22 hospital admissions per 1000 forest fire events during the forest fire season in the Legal Amazon, 2009-2019. This research highlights the urgent need for environmental and health policies to mitigate the effects of Amazon rainforest wildfires, stressing the interplay of deforestation, climate change, and human-induced fires on respiratory health.

Ambient temperature and seasonal variation in inpatient mortality from respiratory diseases: a retrospective observational study.

The seasonal fluctuation in mortality and hospital admissions from respiratory diseases, with a winter peak and a summer trough, is widely recognized in extratropical countries. However, little is known about the seasonality of inpatient mortality and the role of ambient temperature remains uncertain. We aimed to analyse the association between ambient temperature and in-hospital mortality from respiratory diseases in the provinces of Madrid and Barcelona, Spain. We used data on daily hospitalisations, weather (ie, temperature and relative humidity) and air pollutants (ie, PM2.5, PM10, NO2and O3) for the Spanish provinces of Madrid and Barcelona during 2006-2019. We applied a daily time-series quasi-Poisson regression in combination with distributed lag non-linear models (DLNM) to assess, on the one hand, the seasonal variation in fatal hospitalisations and the contribution of ambient temperature, and on the other hand, the day-to-day association between temperature and fatal hospital admissions. The analyses were stratified by sex, age and primary diagnostic of hospitalisation. The study analysed 1710012 emergency hospital admissions for respiratory diseases (mean [SD] age, 60.4 [31.0] years; 44.2% women), from which 103845 resulted in in-hospital death (81.4 [12.3] years; 45.1%). We found a strong seasonal fluctuation in in-hospital mortality from respiratory diseases. While hospital admissions were higher during the cold season, the maximum incidence of inpatient mortality was during the summer and was strongly related to high temperatures. When analysing the day-to-day association between temperature and in-hospital mortality, we only found an effect for high temperatures. The relative risk (RR) of fatal hospitalisation at the 99th percentile of the distribution of daily temperatures vs the minimum mortality temperature (MMT) was 1.395 (95% eCI: 1.211-1.606) in Madrid and 1.612 (1.379-1.885) in Barcelona. In terms of attributable burden, summer temperatures (June-September) were responsible for 16.2% (8.8-23.3) and 22.3% (15.4-29.2) of overall fatal hospitalisations from respiratory diseases in Madrid and Barcelona, respectively. Women were more vulnerable to heat than men, whereas the results by diagnostic of admission showed heat effects for acute bronchitis and bronchiolitis, pneumonia and respiratory failure. Unless effective adaptation measures are taken in hospital facilities, climate warming could exacerbate the burden of inpatient mortality from respiratory diseases during the warm season. European Research Council Consolidator Grant EARLY-ADAPT, European Research Council Proof-of-Concept Grants HHS-EWS and FORECAST-AIR.

Effect of ambient air pollution on hospital admission for respiratory diseases in Hanoi children during 2007–2019

Air pollution poses a threat to children's respiratory health. This study aims to quantify the association between short-term air pollution exposure and respiratory hospital admissions among children in Hanoi, Vietnam, and estimate the population-attributable burden using local data. A case-crossover analysis was conducted based on the individual records where each case is their own control. The health data was obtained from 13 hospitals in Hanoi and air pollution data was collected from four monitoring stations from 2007 to 2019. We used conditional logistic regression to estimate Percentage Change (PC) and 95% Confidence Interval (CI) in odd of hospital admissions per 10 μg/m3 increase in daily average particulate matter (e.g. PM1, PM2.5, PM10), Sulfur Dioxide (SO2), Nitrogen Dioxide (NO2), 8-h maximum Ozone and per 1000 μg/m3 increase in daily mean of Carbon Monoxide (CO). We also calculated the number and fraction of admissions attributed to air pollution in Hanoi by using the coefficient at lag 0. A 10 μg/m3 increase in the concentration of PM10, PM2.5, PM1, SO2, NO2, O3 8-h maximum and 1000 μg/m3 increase in CO concentration was associated with 0.6%, 1.2%, 1.4%, 0.8%, 1.6%, 0.3%, and 1.7% increase in odd of admission for all respiratory diseases among children under 16 years at lag 0–2. All PM metrics and NO2 are associated with childhood admission for pneumonia and bronchitis. Admissions due to asthma and upper respiratory diseases are related to increments in NO2 and CO. For attributable cases, PM2.5 concentrations in Hanoi exceeding the World Health Organization Air Quality Guidelines accounted for 1619 respiratory hospital admissions in Hanoi children in 2019. Our findings show that air pollution has a detrimental impact on the respiratory health of Hanoi children and there will be important health benefits from improved air quality management planning to reduce air pollution in Vietnam.

Prepayment meters strongly associated with multiple types of deprivation and emergency respiratory hospital admissions: an observational, cross-sectional study

BackgroundPrepayment meters (PPMs) require energy to be paid in advance. Action groups and media contend that PPMs are concentrated in the most vulnerable groups, prone to run out of credit...

Double trouble: The interaction of PM2.5 and O3 on respiratory hospital admissions

The co-occurrence of fine particulate matter (PM2.5) and ozone (O3) pollution during the warm season has become a growing public health concern. The interaction between PM2.5 and O3 and its contribution to disease burden associated with co-pollution has not been thoroughly examined. We collected data on hospital admissions for respiratory diseases from a city-wide hospital discharge database in Beijing between 2013 and 2019. City-wide 24-h mean PM2.5 and daily maximum 8-h mean O3 were averaged from 35 monitoring stations across Beijing. Conditional Poisson regression was employed to estimate the interaction between warm-season PM2.5 and O3 on respiratory admissions. A model incorporating a tensor product term was used to fit the non-linear interaction and estimate the number of respiratory admissions attributable to PM2.5 and O3 pollution. From January 18, 2013 to December 31, 2019, 1,191,308 respiratory admissions were recorded. We observed multiplicative interactions between warm-season PM2.5 and O3 on upper respiratory infections (P = 0.004), pneumonia (P = 0.002), chronic obstructive pulmonary disease (P = 0.041), and total respiratory disease (P < 0.001). PM2.5-O3 co-pollution during warm season exhibited a super-additive effect on respiratory admissions, with a relative excess risk due to interaction of 1.65% (95%CI: 0.46%–2.84%). There was a non-linear pattern of the synergistic effect between PM2.5 and O3 on respiratory admissions. Based on the World Health Organization global air quality guidelines, 12,421 respiratory admissions would be reduced if both daily PM2.5 and O3 concentrations had not exceeded the target (PM2.5 15 μg/m3, O3 100 μg/m3). The number of respiratory admissions attributable to either PM2.5 or O3 pollution decreased by 48.7% from 2013 to 2019. Prioritizing O3 control during the warm season is a cost-effective strategy for Beijing. These findings underscore the significance of concurrently addressing both PM2.5 pollution and O3 pollution during the warm season to alleviate the burden of respiratory diseases.

Implementation of Internet of Things (IoT) Technology in Air Pollution Monitoring in Jakarta: Quantitative Analysis of the Influence of Air Quality Change and Its Impact on Public Health in Jakarta

Air pollution is a pressing global issue, particularly in urban areas where rapid industrialization and urbanization have led to deteriorating air quality. Jakarta, as one of the world's most populous megacities, faces significant challenges in managing air pollution and safeguarding public health. This research paper explores the implementation of Internet of Things (IoT) technology for air pollution monitoring in Jakarta and quantitatively assesses the influence of air quality changes on public health outcomes. The study involves the deployment of IoT sensors to collect real-time data on key air pollutants, including particulate matter (PM2.5, PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3). Statistical analyses, including regression and correlation analyses, reveal strong associations between air quality variables and health indicators. Findings indicate that elevated levels of PM2.5 and NO2 are linked to increased hospital admissions for respiratory diseases, and CO levels are associated with hypertension and cardiovascular diseases. The study also explores public perception through surveys and questionnaires, highlighting a high level of awareness and support for government initiatives to improve air quality. The results emphasize the need for informed policy decisions, including stricter emission standards and public awareness campaigns, to combat air pollution and protect public health in Jakarta.

Effect of Ambient Temperature on Hospital Admissions for Respiratory Disease in Suburban Rural Villages of a Semi-Arid Region in Northwest China.

This study evaluated the effects of extreme temperatures on hospital admissions for respiratory diseases (RDs) in a semi-arid region in the Northwest of China. Distributed lag nonlinear model was constructed, and stratified analysis by gender and age was performed. The exposure-response curve between temperature and RD hospital admissions was almost W-shaped. Either extremely cold temperatures or moderately cold temperatures presented a short-term acute harmful effect, and the relative risks were higher among males (1.976, 95% confidence interval [CI]: 1.773-2.203; 1.242, 95% CI: 1.203-1.282) and the elderly (2.363, 95% CI: 1.724-3.240; 1.267, 95% CI: 1.154-1.390). Both extreme and moderately hot temperatures had higher risks among females (2.040, 95% CI: 1.815-2.292; 1.328, 95% CI: 1.276-1.381). The relationship between air temperature and RD hospital admissions was nonlinear. Vulnerable populations varied according to extreme temperature conditions.

Short-term effects of air pollution on respiratory hospitalizations in Ha Nam, during 2018-2020

Objectives: Air pollution has adverse effects on the respiratory system. Ha Nam is one of the most polluted provinces in Vietnam. This study aims at assessing the short-term association between air pollution and respiratory diseases among Ha Nam inhabitants during 2018-2020. Method: This ecological study used data from Ha Nam Provincial General Hospital and Obstetric-Paediatric Hospital for health information, and data from Center for Interdisciplinary Integrated Technology Field Monitoring (FIMO) for PM2.5 and temperature data. Time-series analysis was applied to estimate the risk of admissions due to respiratory diseases and daily ambient PM2.5 concentrations. Results: The majority of respiratory-related admissions were upper respiratory infections (47.3%) and pneumonia (40.8%). Number of male admissions were higher than that of female for most respiratory diseases, except chronic obstructive pulmonary disease (COPD). The strongest association between PM2.5 concentrations and hospital admissions for respiratory diseases in Ha Nam was observed in lag 2. Conclusion: The study found positive associations between PM2.5 concentration and hospital admissions. Further investigation with a large admissions are need to certained findings. estimate the number of admissions attributed to air pollution in Ha Nam. Keywords: PM2.5, respiratory diseases, hospital admissions.

Cold-induced adaptive thermogenesis is impaired by exposure of Asian sand dust in mice

Desertification and desert sandstorms caused by the worsening global warming pose increasing risks to human health. In particular, Asian sand dust (ASD) exposure has been related to an increase in mortality and hospital admissions for respiratory diseases. In this study, we investigated the effects of ASD on metabolic tissues in comparison to diesel particulate matter (DPM) that is known to cause adverse health effects. We found that larger lipid droplets were accumulated in the brown adipose tissues (BAT) of ASD-administered but not DPM-administered mice. Thermogenic gene expression was decreased in these mice as well. When ASD-administered mice were exposed to the cold, they failed to maintain their body temperature, suggesting that the ASD administration had led to impairments in cold-induced adaptive thermogenesis. However, impaired thermogenesis was not observed in DPM-administered mice. Furthermore, mice fed a high-fat diet that were chronically administered ASD demonstrated unexplained weight loss, indicating that chronic administration of ASD could be lethal in obese mice. We further identified that ASD-induced lung inflammation was not exacerbated in uncoupling protein 1 knockout mice, whose thermogenic capacity is impaired. Collectively, ASD exposure can impair cold-induced adaptive thermogenic responses in mice and increase the risk of mortality in obese mice.

Case-crossover study for the association between increased hospital admissions for respiratory diseases and the increase in atmospheric PM2.5 and PM2.5-bound trace elements in Pretoria, South Africa

ABSTRACT Outdoor PM2.5 was sampled in Pretoria, 18 April 2017 to 28 February 2020. A case-crossover epidemiology study was associated for increased PM2.5 and trace elements with increased hospital admissions for respiratory disorders (J00-J99). The results included a significant increase in hospital admissions, with total PM2.5 of 2.7% (95% CI: 0.6, 4.9) per 10 µg·m−3 increase. For the trace elements, Ca of 4.0% (95% CI: 1.4%−6.8%), Cl of 0.7% (95% CI: 0.0%−1.4%), Fe of 3.3% (95% CI: 0.5%−6.1%), K of 1.8% (95% CI: 0.2–3.5) and Si of 1.3% (95% CI: 0.1%−2.5%). When controlling for PM2.5, only Ca of 3.2% (95% CI: 0.3, 6.1) and within the 0–14 age group by 5.2% (95% CI: 1.5, 9.1). Controlling for a co-pollutant that is highly correlated with PM2.5 does reduce overestimation, but further studies should include deposition rates and parallel sampling analysis.

Development and application of photocatalytic coating for roadside NOx mitigation in Hong Kong

A facile chemical method for the development of photocatalytic coating products was proposed based on practical application perspective for the Hong Kong roadside nitrogen oxides (NOx) mitigation. TiO2-based photocatalytic coating PC-C film with crystallized size of around 5–6 nm was synthesized with the peptization of H2O2. The PC-C coating possesses a super-hydrophilicity surface and is proven to have a NOx degradation rate of 46.8% with an optimum pH level of 7. In addition, the PC-C coating presents a promising photocatalytic NOx degradation compared with other commercially available coating products and P25 when applied on two building materials of poly-methyl methacrylate (PMMA) and concrete surface. A weather resistance simulation and a 180-day on-site field trial were carried out the attenuation effects of photocatalytic coating applied in outdoor exposure. Based on epidemiological estimation and field investigation, hospital admissions for respiratory diseases (HARD) and mortality cases (MC) could be reduced with the application of PC-C coating along the street canyon. This work demonstrates the feasibility of air pollution control measures for the local roadside NOx using photocatalytic technology, offering promising health benefits with environmental remediation.

Evaluation of the relationship between thermal comfort conditions and respiratory diseases in Amasya City, Turkey.

Studies examining the relationship between thermal comfort conditions-the state of feeling insulated against atmospheric factors in the environment-and diseases have been very limited. In Turkey, which is in the transition zone of air masses in middle latitudes, thermal comfort conditions change frequently due to sudden weather changes. This study was conducted to examine the relationship between thermal comfort conditions and respiratory diseases in Amasya, an exemplary Turkish city in the Black Sea Region of Turkey. To determine the thermal comfort conditions in the study between 2017 and 2019, the PET (physiologically equivalent temperature) index obtained from the RayMan model was used for data including hourly air temperature (°C), relative humidity (%), wind velocity (m/s), and cloud cover (octa). Daily air temperature data were also obtained. The relationship between PET values and air temperature and respiratory disease hospital admissions was analyzed by Pearson correlation analysis and linear regression analysis. The results revealed a very high negative correlation between both thermal comfort conditions (PET) and air temperature and respiratory diseases (p < 0.000). The results show that with an increase of 1 °C in thermal comfort conditions (PET), hospital admissions due to respiratory diseases will decrease by approximately 64 to 67 patients. It is predicted that the number of patients will decrease by approximately 89 to 94 with an increase of 1 °C in air temperature. These findings can be informative and serve as guidance for decision-makers in efforts to protect public health, for preventive medicine studies, and for studies on the effects of climate change on human health.

Effects of Heatwaves on Hospital Admissions for Cardiovascular and Respiratory Diseases, in Southern Vietnam, 2010-2018: Time Series Analysis.

This study investigated the associations between heatwaves and daily hospital admissions for cardiovascular and respiratory diseases in two provinces in Viet Nam known to be vulnerable to droughts during 2010-2018. This study applied a time series analysis with data extracted from the electronic database of provincial hospitals and meteorological stations from the corresponding province. To eliminate over-dispersion, this time series analysis used Quasi-Poisson regression. The models were controlled for the day of the week, holiday, time trend, and relative humidity. Heatwaves were defined as the maximum temperature exceeding P90th over the period from 2010 to 2018 during at least three consecutive days. Data from 31,191 hospital admissions for respiratory diseases and 29,056 hospitalizations for cardiovascular diseases were investigated in the two provinces. Associations between hospital admissions for respiratory diseases and heatwaves in Ninh Thuan were observed at lag 2, with excess risk (ER = 8.31%, 95% confidence interval: 0.64-16.55%). However, heatwaves were negatively associated with cardiovascular diseases in Ca Mau, which was determined amongst the elderly (age above 60), ER = -7.28%, 95%CI: -13.97--0.08%. Heatwaves can be a risk factor for hospital admission due to respiratory diseases in Vietnam. Further studies need to be conducted to assert the link between heat waves and cardiovascular diseases.

Efficacy of nirsevimab against respiratory syncytial virus lower respiratory tract infections in preterm and term infants, and pharmacokinetic extrapolation to infants with congenital heart disease and chronic lung disease: a pooled analysis of randomised controlled trials

In a phase 2b trial and the phase 3 MELODY trial, nirsevimab, an extended half-life, monoclonal antibody against respiratory syncytial virus (RSV), protected healthy infants born preterm or at full term against medically attended RSV lower respiratory tract infection (LRTI). In the MEDLEY phase 2-3 trial in infants at higher risk for severe RSV infection, nirsevimab showed a similar safety profile to that of palivizumab. The aim of the current analysis was to assess the efficacy of nirsevimab using a weight-banded dosing regimen in infants born between 29 weeks gestational age and full term. Infants enrolled in the phase 2b and MELODY trials were randomised (2:1) to receive a single intramuscular injection of nirsevimab (infants weighing <5 kg received 50 mg; those weighing ≥5 kg received 100 mg) or placebo before the RSV season. Infants in MEDLEY were randomised (2:1) to receive one dose of nirsevimab (infants weighing <5 kg received 50 mg; those weighing ≥5 kg received 100 mg) followed by four monthly placebo doses, or five once-a-month intramuscular doses of palivizumab. We report a prespecified pooled efficacy analysis assessing the weight-banded dosing regimen proposed on the basis of the phase 2b and MELODY trials, in addition to extrapolated efficacy in infants with chronic lung disease, congenital heart disease, or extreme preterm birth (<29 weeks' gestational age) based on pharmacokinetic data from the phase 2-3 MEDLEY safety trial. For the pooled efficacy analysis, the primary endpoint was incidence of medically attended RSV LRTI through 150 days post-dose. The secondary efficacy endpoint was number of admissions to hospital for medically attended RSV LRTI. The incidence of very severe RSV LRTI was an exploratory endpoint, defined as cases of hospital admission for medically attended RSV LRTI that required supplemental oxygen or intravenous fluids. We also did a prespecified exploratory analysis of medically attended LRTI of any cause (in the investigator's judgement) and hospital admission for respiratory illness of any cause (defined as any upper respiratory tract infection or LRTI leading to hospital admission). Post hoc exploratory analyses of outpatient visits and antibiotic use were also done. Nirsevimab serum concentrations in MEDLEY were assessed using population pharmacokinetic methods and the pooled data from the phase 2b and MELODY trials. An exposure target was defined on the basis of an exposure-response analysis. To successfully demonstrate extrapolation, more than 80% of infants in MEDLEY had to achieve serum nirsevimab exposures at or above the predicted efficacious target. Overall, 2350 infants (1564 in the nirsevimab group and 786 in the placebo group) in the phase 2b and MELODY trials were included in the pooled analysis. Nirsevimab showed efficacy versus placebo with respect to the primary endpoint of medically attended RSV LRTI (19 [1%] nirsevimab recipients vs 51 [6%] placebo recipients; relative risk reduction [RRR] 79·5% [95% CI 65·9-87·7]). Consistent efficacy was shown for additional endpoints of RSV LRTI hospital admission (nine [1%] nirsevimab recipients vs 21 [3%] placebo recipients; 77·3% [50·3-89·7]) and very severe RSV (five [<1%] vs 18 [2%]; 86·0% [62·5-94·8]). Nirsevimab recipients had fewer hospital admissions for any-cause respiratory illness (RRR 43·8% [18·8-61·1]), any-cause medically attended LRTI (35·4% [21·5-46·9]), LRTI outpatient visits (41·9% [25·7-54·6]), and antibiotic prescriptions (23·6% [3·8-39·3]). Among infants with chronic lung disease, congenital heart disease, or extreme preterm birth in MEDLEY, nirsevimab serum exposures were similar to those found in the pooled data; exposures were above the target in more than 80% of the overall MEDLEY trial population (94%), including infants with chronic lung disease (94%) or congenital heart disease (80%) and those born extremely preterm (94%). A single dose of nirsevimab protected healthy infants born at term or preterm from medically attended RSV LRTI, associated hospital admission, and severe RSV. Pharmacokinetic data support efficacy extrapolation to infants with chronic lung disease, congenital heart disease, or extreme prematurity. Together, these data suggest that nirsevimab has the potential to change the landscape of infant RSV disease by reducing a major cause of infant morbidity and the consequent burden on caregivers, clinicians, and health-care providers. AstraZeneca and Sanofi.

Trend of Admissions Due to Chronic Lower Respiratory Diseases: An Ecological Study.

Objective: This study aimed to examine the trend of hospital admissions related to chronic lower respiratory diseases in England and Wales between 1999 and 2020. Method: This ecological analysis used data that were made accessible to the public and were taken from the Patient Episode Database for Wales (PEDW) and the Hospital Episode Statistics (HES) databases in England for the time span between April 1999 and April 2020. The patients were grouped into four age groups: under 15, 15−59, 60−74, and 75 years and above. Results: In 2020, there were 432,193 chronic lower respiratory disease hospital admissions, which increased from 239,606 in 1999. The hospital admission rate increased by 57.5% (from 459.54 (95% CI 457.71−461.38) in 1999 to 723.70 (95% CI 721.55−725.85) in 2020 per 100,000 people, p < 0.5). The majority of hospital admissions for chronic lower respiratory diseases were found to be directly linked to age (more prevalent in the 75+ age group). Moreover, female hospital admission rates for chronic lower respiratory diseases grew by 85.2% between 1999 and 2020, increasing from 445.45 (95% CI 442.92−447.97) to 824.96 (95% CI 821.73−828.19) per 100,000 people. Conclusion: The rate of hospital admissions due to chronic lower respiratory diseases has sharply increased during the past two decades. COPD was the most common cause for chronic lower respiratory disease admissions. Ageing was also found to be a factor in increased hospital admissions. Future studies are warranted to identify other risk factors of hospital admissions due to chronic lower respiratory diseases and specifically COPD.

Investigating the Relationship between Climate and Hospital Admissions for Respiratory Diseases before and during the COVID-19 Pandemic in Brazil

This study aimed to analyze meteorological variables versus hospital admissions for respiratory diseases for the age groups of children under five and the elderly (over 65 years of age) in different climate regions of Brazil, for the years 2018 and 2020, i.e., before and after the outbreak of the COVID-19 pandemic. The aim of the study was, on one hand, to evaluate the influence of weather variables on respiratory disease in humans, and on the other hand, take into account two years with differing dynamics due to a worldwide pandemic that significantly changed people’s lifestyles. The human biometeorological index (Universal Thermal Climate Index, UTCI) was used as representative of the integral association of meteorological variables. UTCI data were obtained from the ERA5-HEAT reanalysis database, which provides hourly grid data with a spatial resolution of 0.25° × 0.25°. The Brazilian cities Manaus, Brasilia and Porto Alegre, which represent different climatic contexts in the country, were used in the analysis. The method compared temperature and climate reanalysis data to hospital admission data for respiratory diseases, obtained from the Brazilian Unified Health System database (DATASUS), according to the International Classification of Diseases, Tenth Edition (ICD-10). Correlation analysis was performed between variables (hospital admissions versus climate-related data) in order to identify associations between them, also accounting for different time-lag effects. We analyzed seasonal influences on the obtained correlations, correlation strength and direct or inverse relationships. Results showed that the pandemic interfered in the association between morbidity due to respiratory illnesses and climate-related variables.

Temperature modifies the association between air pollution and respiratory disease hospital admissions in an industrial area of South Africa: The Vaal Triangle Air Pollution Priority Area

Background: Epidemiological studies reported independent effects of air pollution and temperature on health, yet these twoexposures are often treated as separate risk factors. Few studies investigated temperature effect modification on the health effects ofair pollution in Africa and none examined the effects of black carbon on respiratory disease (RD) hospitalisations. The aim of this studywas to determine whether the association between RD hospitalisations and air pollution in the Vaal Triangle Air Pollution Priority Areawas modified by apparent temperature (Tapp) during January 2013 to February 2020. Methods: RD admission data (ICD10 J00-J99) were obtained from two hospitals located in Vanderbijlpark and Vereeniging. AmbientPM10, PM2.5, BC, NO2, SO2 and O3, temperature and relative humidity data were obtained from six monitoring stations. A case-crossover epidemiological study design was applied. Lag0-1 was investigated, i.e. the average air pollutant level on the day and the day before hospitalisation. Models were adjusted for public holidays and Tapp. Effect modification was investigated by stratifying days into low, moderate and high Tapp days. Susceptibility by age and sex was investigated. Results: Of the 43 386 hospital admissions, 50.9% (n=22 092) were women and 51.4% (n=22 304) were 0-14-year olds. Air pollutantsexceeded the daily WHO air quality guidelines generally on more than 50% of the days. In general, moderate Tapp worsened the effects of PM2.5, PM10, SO2 and BC, whilst the effects of NO2 and O3 were most pronounced on days with high Tapp. The elderly and females were more vulnerable to air pollution, especially on days with moderate Tapp. Conclusions: These results indicate that the risk of RD hospitalisation due to ambient air pollution exposure is different on low,moderate and high Tapp days in Vanderbijlpark and Vereeniging.