Hospitalizations For Respiratory Diseases Research Articles

Application of Environmental Cost Accounting to Reduce Emissions and Health Impact in the Greater ABC Region, Brazil

This work shows a proposal for reducing emissions, fuel costs, and respiratory disease hospitalizations using environmental cost accounting principles for the production of biodiesel production from waste frying oil (WFO). PM10, PM2.5, and O3 data from 2017 to 2022 were collected and correlated with the number of hospitalizations for respiratory diseases and their costs. WFO samples were collected locally from households and restaurants in the greater ABC region, Brazil, and biodiesel was produced using the samples. The results showed that throughout the studied period, one or more of the polluting gases showed a strong correlation with hospitalizations due to respiratory diseases, corroborating what has already been verified by other studies carried out by the WHO. WFO biodiesel was within the standard limits, and the total annual production was estimated to be 30,435 m3; moreover, the associated annual carbon credits would equal 67 tCO2, as well as a decrease of 30% in total pollutant emissions. Environmental cost accounting revealed that the annual number of respiratory disease hospitalizations could decrease by 3093 and the associated healthcare cost would decrease by USD 838 thousand per year; moreover, the sale of biodiesel and byproducts can generate an annual profit of USD 19 million. The biodiesel plant project had an NPV of USD 172.5 million, a payback of 1 month, and a return on investment of more than 170 times the initial financing. In addition, the reputation and the quality of life of the greater ABC region’s residents could improve.

Genetic and Clinical-epidemiologic Profile of hRSV in Pediatric Patients in Southern Brazil: A Four-year Hospital Surveillance Study.

Respiratory syncytial virus (hRSV) infections primarily cause acute respiratory illness and pediatric hospitalizations. We examined the hRSV molecular epidemiology in a pediatric cohort over a 4-year period and described the interrelationship with clinical data. A cross-sectional study was conducted from 2014 to 2017 on children with acute respiratory illness. Respiratory viruses were detected using a multiplex real-time polymerase chain reaction and molecular typing was performed by nucleotide sequencing. Three hundred fifty-three children with hRSV were included; 207 (36%) samples were submitted to partial G gene sequencing. A total of 58.3% (n = 120) were males, the median age was 2.3 months (interquartile range 1-4), and 36.4% (n = 75) of the children required intensive care unit assistance. Coinfection was detected in 27 (5.7%) children, mainly hRSV and rhinovirus (14.2%). A total of 95.6% of patients had no comorbidities, and prematurity (4.4%) was more frequent among those with comorbidities. hRSV-B was detected in 109 patients (53%) and hRSV-A in 98 patients (47%), with changes in incidence over the period. All the hRSV-A sequences were classified as ON1-like, with genetic lineage GA2.3.5 forming distinct clusters. hRSV-B sequences were identified as BA-like, comprising 3 genetic lineages, GB5.0.2, GB5.0.4a and GB5.0.5a, with variation over time, and a higher severity was associated with hRSV type B GB5.0.2 and GB5.0.4a lineages compared with the GB5.0.5a. Both hRSV subtypes showed similar severity and were not linked to comorbidities. Severe cases were more common in young patients and those infected with GB5.0.2 and GB5.0.4a genotypes. Understanding hRSV's molecular evolution is crucial for tracking new variants and assessing their impact on the effectiveness of emerging vaccines and monoclonal antibodies.

Short-term effects of air pollutants on hospitalization for childhood respiratory diseases in Suzhou City: a time-stratified case-crossover study

BackgroundShort-term exposure to air pollution has been demonstrated in previous studies to correlate with respiratory disease (RD) in children. Due to regional heterogeneity, our objective was to explore the correlation between short-term exposure to ambient air pollution and hospital admissions for respiratory ailments in children in Suzhou City from January 1, 2017, to December 31, 2022, alongside assessing the influence of the COVID-19 pandemic on this relationship.MethodsWe collected data on air pollutant levels and hospital admissions for childhood respiratory disease (RD) in Suzhou, China, from 2017 to 2022. We utilized a time-stratified case-crossover design along with a conditional logistic regression model to assess the short-term impacts of air pollutants on RD in children through stratified analysis and sensitivity analysis.ResultsA total of 13,408 children with respiratory diseases were included in the study. The findings revealed significant associations between hospitalization for respiratory diseases in children and exposure to PM2.5, PM10, SO2, NO2, and CO. The maximum effect values (95%CI, best lag days) for each 10 µg/m3 increase in the concentrations of PM2.5, PM10, SO2, and NO2 were as follows: 1.017 (1.003–1.031, lag0-2), 1.015 (1.004–1.026, lag0-2), 1.117 (1.001–1.247, lag0-1), and 1.036 (1.009–1.064, lag0-7). Additionally, the maximum effect value (95%CI, best lag days) for each 1 mg/m3 increase in CO concentration was found to be 1.267 1.017–1.579, lag0-7). Stratified analysis indicated that sex, season of admission, and stage of admission did not modify these correlations significantly; however, differential effects on various age groups and sexes were primarily observed among school-age and older children as well as boys.ConclusionsThe short-term exposure to PM2.5, PM10, SO2, NO2, and CO in Suzhou, China, exhibited a positive correlation with RD hospitalization. Prior to the COVID-19 pandemic, the adverse impacts of air pollutants on hospitalizations for childhood respiratory disease were mitigated compared to the period following the pandemic. Local governments should continue promoting decisions and measures for air pollution prevention and control to reduce further pollutant concentration, which is crucial for public health in reducing the burden of childhood respiratory diseases.

Hospitalisation patterns for respiratory diseases in Australia: an ecological study

ObjectivesThe objective of this study is to examine the hospitalisation profile for respiratory diseases in Australia between 1998 and 2019.DesignAn ecological study.SettingA population study that involved all private and public...

Yearly Assessment of Weather and Air Quality Impact on Respiratory Disease Hospitalizations: Faial Island (Azores) Study

Building upon our previous research conducted at weekly and monthly intervals, this study investigates the yearly dynamics of weather conditions and air quality on respiratory diseases, specifically tailored to Faial Island in the Azores. Expanding our analysis to a yearly basis allows for a more comprehensive understanding of long-term trends and seasonal variations in hospital admissions. Drawing upon extensive daily data spanning from 2008 to 2019, sourced from the Statistics Service of Hospital da Horta, the Meteorological Observatory Príncipe Alberto de Mónaco, and the Air Quality Monitoring Network of the Azores, we examined the differentiated relationships between yearly meteorological variables, such as temperature, dew point, and wind direction, and respiratory health outcomes. Additionally, we explored the persistent influence of air quality indicators, including suspended particulate matter with an aerodynamic diameter of 10 micrometers (µm) or less (PM10), sulfur dioxide (SO<sub>2)</sub>, nitrogen dioxide (NO<sub>2)</sub>, and ozone (O<sub>3</sub>), across different seasons and years. By incorporating yearly data into our analysis, this study aims to provide a comprehensive and nuanced understanding of the interplay between environmental factors and respiratory disease hospitalizations, thereby informing targeted interventions and public health strategies in insular regions. The principal component analysis (PCA) applied to the yearly data reveals interesting correlation patterns between meteorological variables and hospitalizations for respiratory diseases such as asthma, pneumonia, and rhinitis. Hospital admissions were found to increase during periods of lower temperatures and smaller temperature amplitudes, suggesting that prolonged cold conditions may exacerbate symptoms of these diseases. Additionally, atmospheric pollutant concentrations, such as suspended particles PM10, SO<sub>2</sub>, NO<sub>2</sub>, and O<sub>3</sub>, significantly varied across seasons, with a notable influence on the exacerbation of respiratory diseases. In insular regions like the Azores, these findings highlight the importance of targeted public health strategies to mitigate the impact of environmental factors on respiratory health.

Impact of Heat on Respiratory Hospitalizations among Older Adults in 120 Large US Urban Areas.

Extreme heat exposure is a well-known cause of mortality among older adults. However, the impacts of exposure on respiratory morbidity across US cities and population subgroups is not well understood. A nationwide study to determine the impact of high heat on respiratory disease hospitalizations among older adults (65+) living in the 120 largest US cities between 2000-2017. Daily rates of inpatient respiratory hospitalizations were examined with respect to variations in ZIP-code-level daily mean temperature and heat index. For each city, we estimated cumulative associations (lag-days 0-6) between warm-season heat (June-September) and cause-specific respiratory hospitalizations using time-stratified conditional quasi-Poisson regression with distributed lag non-linear models. We estimated nationwide associations using multivariate meta-regression and updated city-specific associations via best linear unbiased prediction. With stratified models, we explored effect modification by age, sex, and race (Black/white). Results were reported as percent change in hospitalizations at high temperatures (95th percentile) compared to median temperatures for each outcome, demographic group, and metropolitan area. We identified 3,275,033 respiratory hospitalizations among Medicare beneficiaries across 120 large US cites between 2000 and 2017. Nationwide, 7-day cumulative associations at high temperatures, resulted in a 1.2% (0.4%, 2.0%) increase in hospitalizations for primary diagnoses of all-cause respiratory disease, primarily driven by increases in respiratory tract infections [1.8% (0.6%, 3.0%)], and chronic respiratory diseases/respiratory failure [1.2% (0.0%, 2.4%)]. Stronger associations were observed when exposure was defined using the heat index instead of temperature. Across the 120 cities, we observed considerable geographic variation in the relative risk of heat-related respiratory hospitalizations, and we observed disproportionate burdens of heat-related respiratory hospitalizations among the oldest beneficiaries (85+ years), and among Black beneficiaries living in South Atlantic cities. During the 18-year study period, there were an estimated 11,710 excess respiratory hospitalizations due to heat exposure. Results suggest that high temperature and humidity contribute to exacerbation of respiratory tract infections and chronic lung diseases among older adults. Geographic variation in heat-related hospitalization rates suggests that contextual factors largely account for disproportionate burdens, and area-level influences should be further investigated in multi-city studies.

Cost-effectiveness of respiratory syncytial virus adjuvanted vaccine in Portuguese aged ≥ 60 years

Abstract Background Respiratory syncytial virus (RSV) infections are one of the leading causes of lower respiratory tract disease among adults aged ≥60 years in Europe. This study aims to assess the potential public health impact of the RSVPreF3 OA adjuvanted vaccine, the first approved preventive intervention for the older adult population in Portugal. Methods A monthly-cycle static Markov model was developed to assess RSVPreF3 OA adjuvanted vaccine impact on adults aged 60 years and older in Portugal. A single dose of RSVPreF3 OA adjuvanted vaccine was compared to no-vaccination over a three-year time-horizon. The model captures lower respiratory tract disease (LRTD) RSV cases, hospitalizations, deaths, and healthcare resource utilization. Data inputs were based on local published literature, supplemented by the best available data when local information was lacking. Results Based on preliminary analysis considering 75% vaccine coverage, model outputs estimate that RSVPreF3 OA adjuvanted vaccine can prevent 71,433 LRTD cases requiring medical attendance, 11,067 hospitalizations, 1,793 intensive care unit admissions and 1,003 deaths. The model estimates that 32 adults need to be vaccinated to avoid one RSV LRTD case, 207 adults need to be vaccinated to avoid one hospitalization and 2,283 adults need to be vaccinated to avoid one death. The incremental cost-effectiveness ratio was estimated at 9,541€, hence the RSVPreF3 OA adjuvanted vaccine is cost-effective compared to no vaccination. Conclusions The results demonstrate a strong preventive impact of the RSVPreF3 OA adjuvanted vaccine on health outcomes and healthcare resource utilization in adults ≥60 years, leading to a significant public health benefit. This result emphasizes the importance of preventing RSV to preserve the health and well-being of Portugal’s older adults. In addition, data from ongoing studies may enhance precision and extensive sensitivity analyses validate the robustness of the model’s input assumptions. Key messages • This study shows the robust evidence of RSVPreF3 OA adjuvanted vaccine to improve public health by preventing thousands of hospitalizations and deaths among ≥60 years, in Portugal. • Vaccinating adults aged ≥ 60 years with RSVPreF3 OA adjuvanted vaccine in Portugal is a cost-effective strategy.

Forecasting severe respiratory disease hospitalizations using machine learning algorithms

BackgroundForecasting models predicting trends in hospitalization rates have the potential to inform hospital management during seasonal epidemics of respiratory diseases and the associated surges caused by acute hospital admissions. Hospital bed requirements for elective surgery could be better planned if it were possible to foresee upcoming peaks in severe respiratory illness admissions. Forecasting models can also guide the use of intervention strategies to decrease the spread of respiratory pathogens and thus prevent local health system overload. In this study, we explore the capability of forecasting models to predict the number of hospital admissions in Auckland, New Zealand, within a three-week time horizon. Furthermore, we evaluate probabilistic forecasts and the impact on model performance when integrating laboratory data describing the circulation of respiratory viruses.MethodsThe dataset used for this exploration results from active hospital surveillance, in which the World Health Organization Severe Acute Respiratory Infection (SARI) case definition was consistently used. This research nurse-led surveillance has been implemented in two public hospitals in Auckland and provides a systematic laboratory testing of SARI patients for nine respiratory viruses, including influenza, respiratory syncytial virus, and rhinovirus. The forecasting strategies used comprise automatic machine learning, one of the most recent generative pre-trained transformers, and established artificial neural network algorithms capable of univariate and multivariate forecasting.ResultsWe found that machine learning models compute more accurate forecasts in comparison to naïve seasonal models. Furthermore, we analyzed the impact of reducing the temporal resolution of forecasts, which decreased the model error of point forecasts and made probabilistic forecasting more reliable. An additional analysis that used the laboratory data revealed strong season-to-season variations in the incidence of respiratory viruses and how this correlates with total hospitalization cases. These variations could explain why it was not possible to improve forecasts by integrating this data.ConclusionsActive SARI surveillance and consistent data collection over time enable these data to be used to predict hospital bed utilization. These findings show the potential of machine learning as support for informing systems for proactive hospital management.

Interim Effectiveness Estimates of 2024 Southern Hemisphere Influenza Vaccines in Preventing Influenza-Associated Hospitalization - REVELAC-i Network, Five South American Countries, March-July 2024.

To reduce influenza-associated morbidity and mortality, countries in South America recommend annual influenza vaccination for persons at high risk for severe influenza illness, including young children, persons with preexisting health conditions, and older adults. Interim estimates of influenza vaccine effectiveness (VE) from Southern Hemisphere countries can provide early information about the protective effects of vaccination and help guide Northern Hemisphere countries in advance of their season. Using data from a multicountry network, investigators estimated interim VE against influenza-associated severe acute respiratory illness (SARI) hospitalization using a test-negative case-control design. During March 13-July 19, 2024, Argentina, Brazil, Chile, Paraguay, and Uruguay identified 11,751 influenza-associated SARI cases; on average, 21.3% of patients were vaccinated against influenza, and the adjusted VE against hospitalization was 34.5%. The adjusted VE against the predominating subtype A(H3N2) was 36.5% and against A(H1N1)pdm09 was 37.1%. These interim VE estimates suggest that although the proportion of hospitalized patients who were vaccinated was modest, vaccination with the Southern Hemisphere influenza vaccine significantly lowered the risk for hospitalization. Northern Hemisphere countries should, therefore, anticipate the need for robust influenza vaccination campaigns and early antiviral treatment to achieve optimal protection against influenza-associated complications.

The hospitalisation risk of chronic circulatory and respiratory diseases associated with coal mining in the general population in Queensland, Australia

Queensland is the main coal mining state in Australia where populations in coal mining areas have been historically exposed to coal mining emissions. Although a higher risk of chronic circulatory and respiratory diseases has been associated with coal mining globally, few studies have investigated these associations in the Queensland general population. This study estimates the association of coal production with hospitalisations for chronic circulatory and respiratory diseases in Queensland considering spatial and temporal variations during 1997–2014.An ecological analysis used a Bayesian hierarchical spatiotemporal model to estimate the association of coal production with standardised rates of each, chronic circulatory and respiratory diseases, adjusting for sociodemographic factors and considering the spatial structure of Queensland's statistical areas (SA2) in the 18-year period. Two specifications; with and without a space-time interaction effect were compared using the integrated nested Laplace approximation -INLA approach. The posterior mean of the best fit model was used to map the spatial, temporal and spatiotemporal trends of risk.The analysis considered 2,831,121 hospitalisation records. Coal mining was associated with a 4 % (2.4—5.5) higher risk of hospitalisation for chronic respiratory diseases in the model with a space-time interaction effect which had the best fit. An emerging higher risk of either chronic circulatory and respiratory diseases was identified in eastern areas and some coal-mining areas in central and southeast Queensland. There were important disparities in the spatiotemporal trend of risk between coal -and non-coal mining areas for each, chronic circulatory and respiratory diseases.Coal mining is associated with an increased risk of chronic respiratory diseases in the Queensland general population. Bayesian spatiotemporal analyses are robust methods to identify environmental determinants of morbidity in exposed populations. This methodology helps identifying at-risk populations which can be useful to support decision-making in health. Future research is required to investigate the causality links between coal mining and these diseases.

PM2.5 and its components and respiratory disease healthcare encounters – Unanticipated increased exposure-response relationships in recent years after environmental policies

Prior studies reported excess rates (ERs) of cardiorespiratory events associated with short-term increases in PM2.5 concentrations, despite implementation of pollution-control policies. In 2017, Federal Tier 3 light-duty vehicle regulations began, and to-date there have been no assessments of population health effects of the policy. Using the NYS Statewide Planning and Research Cooperative System (SPARCS) database, we obtained hospitalizations and ED visits with a principal diagnosis of asthma or chronic obstructive pulmonary disease (COPD) for residents living within 15 miles of six urban PM2.5 monitoring sites in NYS (2014–2019). We used a time-stratified case-crossover design and conditional logistic regression (adjusting for ambient temperature, relative humidity, and weekday) to estimate associations between PM2.5, POC (primary organic carbon), SOC (secondary organic carbon), and rates of respiratory disease hospitalizations and emergency department (ED) visits from 2014 to 2019. We evaluated demographic disparities in these relative rates and compared changes in ERs before (2014–2016) and after Tier 3 implementation (2017–2019). Each interquartile range increase in PM2.5 was associated with increased ERs of asthma or COPD hospitalizations and ED visits in the previous 7 days (ERs ranged from 1.1%–3.1%). Interquartile range increases in POC were associated with increased rates of asthma ED visits (lag days 0–6: ER = 2.1%, 95% CI = 0.7%, 3.6%). Unexpectedly, the ERs of asthma admission and ED visits associated with PM2.5, POC, and SOC were higher during 2017–2019 (after Tier 3) than 2014–2016 (before Tier-3). Chronic obstructive pulmonary disease analyses showed similar patterns. Excess Rates were higher in children (<18 years; asthma) and seniors (≥65 years; COPD), and Black, Hispanic, and NYC residents. In summary, unanticipated increases in asthma and COPD ERs after Tier-3 implementation were observed, and demographic disparities in asthma/COPD and PM2.5, POC, and SOC associations were also observed. Future work should confirm findings and investigate triggering of respiratory events by source-specific PM.

Additive partial linear models with autoregressive symmetric errors and its application to the hospitalizations for respiratory diseases

Additive partial linear models with autoregressive symmetric errors and its application to the hospitalizations for respiratory diseases

A neuro-fuzzy model to predict respiratory disease hospitalizations arising from the effects of traffic-related air pollution in São Paulo

A neuro-fuzzy model to predict respiratory disease hospitalizations arising from the effects of traffic-related air pollution in São Paulo

Historical association between respiratory diseases hospitalizations and fire occurrence in the Pantanal wetland, Brazil

The occurrence of fires in the Pantanal wetland increases during drought conditions, resulting in higher aerosol emissions and deterioration of air quality. For the first time, a comprehensive assessment of the climatic effects on monthly Respiratory Disease Hospitalizations (RDH) was conducted in the Pantanal region. We investigated correlations among climatic variables and health indicators, focusing on three groups: RDH5 (<5 years old), RDH60 (≥60 years old), and RDH (total records) between 2003 and 2019 in all 17 municipalities of the region. We reported a 26–34% increase in RDH during drought years, as represented by the negative relationship between RDH and precipitation. Precipitation and humidity exert a primary control on fire occurrence and, hence, on respiratory illnesses in the Pantanal. Particulate material emissions are strongly related to increased fires and temperature across the region. Incidence rates among children and the elderly were four and three times higher, respectively, than general population, confirming the higher vulnerability of these groups. To effectively mitigate the risks and vulnerabilities associated with droughts, policies and action plans should prioritize vulnerable populations and implement targeted measures to reduce their exposure.

Nursing diagnoses and hospital readmission of patients with respiratory diseases: Findings from a case-control study.

The rate of readmission after hospitalisation for respiratory diseases has become a common and challenging clinical problem. Social and functional patient variables could help identify cases at high risk of readmission. The aim was to identify the nursing diagnoses that were associated with readmission after hospitalisation for respiratory disease in Spain. Case-control study within the cohort of patients admitted for respiratory disease during 2016-19 in a tertiary public hospital in Spain (n = 3781). Cases were patients who were readmitted within the first 30 days of discharge, and their controls were the remaining patients. All nursing diagnoses (n = 130) were collected from the electronic health record. They were then grouped into 29 informative diagnostic categories. Clinical confounder-adjusted odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated using logistic regression models. The readmission rate was 13.1%. The nursing diagnoses categories 'knowledge deficit' (OR: 1.61; 95%CI: 1.13-2.31), 'impaired skin integrity and risk of ulcer infection' (OR: 1.45; 95%CI: 1.06-1.97) and 'activity intolerance associated with fatigue' (OR: 1.56; 95%CI: 1.21-2.01) were associated with an increased risk of suffering an episode of hospital readmission rate at 30% after hospital discharge, and this was independent of sociodemographic background, care variables and comorbidity. The nursing diagnoses assigned as part of the care plan of patients during hospital admission may be useful for predicting readmissions.

Thermal stress and hospital admissions for cardiorespiratory disease in Brazil

The growing body of scientific literature underscores the intricate relationship between meteorological conditions and human health, particularly in the context of extreme temperatures. However, conventional temperature-centric approaches often fall short in capturing the complexity of thermal stress experienced by individuals. Temperature alone, as a metric, fails to encompass the entirety of the thermal stress individuals face, necessitating a more nuanced understanding. In response to this limitation, climatologists have devised thermal indices—composite measures meticulously crafted to reflect the intricate interplay of meteorological factors influencing human perception of temperature. Recognizing the inadequacy of simplistic temperature-focused methodologies, our study aims to address the multifaceted nature of thermal stress. In this study, we explored the association between thermal indices and hospital admissions for circulatory and respiratory diseases in Brazil. We used an extensive dataset spanning 11 years (2008–2018) from the Brazilian Ministry of Health, encompassing a total of 23,791,093 hospitalizations for circulatory and respiratory diseases. We considered four distinct thermal indices—Discomfort Index (DI), Net Effective Temperature (NET), Humidex (H), and Heat Index (HI). We used an extension of the two-stage design with a case time series to assess this relationship. In the first stage, we applied a distributed lag non-linear modeling framework to create a cross-basis function. We next applied quasi-Poisson regression models adjusted by time-varying confounders. In the second stage, we applied meta-analysis with random effects to estimate the national relative risk (RR). Our findings suggest robust variations among the thermal indices under examination. These variations underscore the intricate nature of associations between temperature and health, with each index capturing distinct aspects of thermal conditions. Our results indicate that extreme thermal conditions, both at the low and high ends, are associated with increased risks of hospital admissions. The diverse impact observed among different indices emphasizes the complex interplay between various meteorological factors and their specific physiological consequences. This underscores the necessity for a comprehensive comprehension of temperature metrics to guide precise public health interventions, recognizing the multifaceted nature of temperature-health relationships.

AIR POLLUTION BY FINE PARTICULATE MATERIAL ON HOSPITALIZATION FOR RESPIRATORY DISEASES IN THE ELDERLY

Objective: To analyze the effects of air pollution exposure on hospitalizations for respiratory diseases in the elderly. Methods: this was an ecological time series study in Cuiabá, Mato Grosso, during the years 2015 and 2016. Daily levels of fine particulate matter PM2.5 and carbon monoxide were estimated and made available by the National Institute for Space Research. Variables related to temperature, relative humidity and adjustments for temporal trend, seasonality and calendar effects were included in the stochastic model of the ARIMA class (integrated autoregressive moving averages). Results: During the period selected for data collection, there were 1556 hospitalizations for respiratory diseases in Cuiabá. It was verified with this study that the number of cases of respiratory hospitalizations in the elderly was higher between the months of May and September 2015, despite a smaller number of occurrences, in the same period of 2016. As for the monthly average number of hospitalizations of elderly people aged 60 or over, these ranged from 41 hospitalizations in December 2016 to 103 hospitalizations in May 2015. Conclusion: The present study found an association between an increase in PM2.5 and a greater number of hospitalizations of elderly people with 60 years or older due to respiratory diseases. These results are consistent with some other studies found in other investigations on the subject.

Sero-prevalence of Rickettsial Infection in the Coastal Area of Bangladesh

Background: Rickettsial infection is one of the most frequently occurring neglected diseases, which can be life-threatening if left untreated. Hence, it is important to know the burden of the disease for taking appropriate preventive and control measures. This paper focused on the seroprevalence of rickettsial infection among hospitalized patients residing in the coastal area of Teknaf, Cox’s Bazar, Bangladesh. Methods: We retrospectively analyzed the hospital records of Weil-Felix test-positive patients from January to December 2022 at Respiratory Disease Hospital, Teknaf. A rapid slide agglutination assay, colorimetric method, KOVA cell counting, flow cytometry method, and SPSS were used for data analysis. The necessary ethical approval was obtained from the Institutional Reviewer Board for using the hospital records. Results: A total of 91 (16.9%) Rickettsia-positive cases were found out of 538 suspected cases, of which half were male (49.5%). The most predominant age group was 5 to under 18 years of age (41.7%), followed by 18‒30 years of age (23.1%). Fever was the most prominent clinical symptom (97.7%), followed by cough (42.9%), muscle aches (29.7%), and headaches (27.5%). The blood count of the patients showed leukocytosis (53.2%), followed by neutrophilia (23.4%) and thrombocytosis (15.6%). Serum creatinine and C-reactive protein were elevated in 13% and 40% of cases, respectively. Urine analysis detected the presence of high pus cells (83.9%), followed by proteinuria (45.2%) and ketonuria (13.0%). Conclusion: In-depth confirmatory exploration and preventive measures are necessary to manage and mitigate the spread of infections at Teknaf.

From Forgotten Pathogen to Target for New Vaccines: What Clinicians Need to Know about Respiratory Syncytial Virus Infection in Older Adults.

Respiratory syncytial virus (RSV) is increasingly recognized as being implicated in acute illness in older adults, with a significant weight in hospitalizations for respiratory illness and death. By means of a best-evidence review, this paper aims to investigate whether RSV can be considered a forgotten pathogen in older patients, looking at trends in the literature volume and exploring possible epidemiological and clinical features underlying the focus given to it. We then present an assessment of its disease burden and present and future strategies for its reduction, particularly in light of the recent availability of new vaccines.

Health impact assessment of PM2.5 from uncovered coal trains in the San Francisco Bay Area: Implications for global exposures

Coal generates almost 40% of the world's electricity with 80 countries throughout the world using coal power. An inherent part of this generation is the rail transport of coal in uncovered cars, often up to a mile long. Existing studies document the subsequent increments of PM2.5 to the near-rail populations, which typically include a large number of economically disadvantaged residents and/or people of color. However, to date there is no assessment of the health implications of this stage in the use of coal. The present study quantifies such impacts on a region in the San Francisco Bay Area. The analysis shows important effects on mortality, hospitalization for cardiovascular and respiratory disease, asthma exacerbation, work loss, and days of restricted activity. Several of these outcomes exhibited a one to six percent increase over baseline. As such, it delineates the implications for the global effects of the transport of coal.