Primary Health Care Interventions for Potentially Preventable Ear, Nose, and Throat Conditions in Rural and Remote Areas: A Systematic Review.

Background:Primary and secondary level preventive primary health care programs providing early detection and timely management of ear, nose, and throat (ENT) conditions in rural and remote regions are fundamental to preventing downstream impacts on health, social, and educational outcomes. However, the range and quality of evidence is yet to be reviewed. Objectives: The study objectives were to identify and synthesize the evidence of primary health care interventions for detection and management of ENT conditions in rural and remote areas, and evaluate the quality of the research and effectiveness of interventions. Methods: A systematic literature search of 6 databases (February 2023). The review was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement, and the quality appraisal of studies was evaluated using the Mixed Methods Appraisal Tool (initial screening questions: Are there clear research questions? Do the collected data allow to address the research questions?). Results: Ten studies met the inclusion criteria. The results describe interventions for detection and management of respiratory tract infections, otitis media, and ear disease in primary health care settings. No studies met the inclusion criteria for tonsillitis. The role of community-based programs and allied health workers in the detection and management of ENT conditions was found to be effective in rural and remote regions. Only 2 of the studies met the screening criteria for quality appraisal. Conclusions: The study findings may inform future programs and policy development to address detection and management of ENT conditions in rural and remote primary care settings, and supports the need for further research on innovative models of care targeting potentially preventable hospitalizations through primary and secondary level prevention.

The α-crystallin Chaperones Undergo a Quasi-ordered Co-aggregation Process in Response to Saturating Client Interaction.

Small heat shock proteins (sHSPs) are ATP-independent chaperones vital to cellular proteostasis, preventing protein aggregation events linked to various human diseases including cataract. The α-crystallins, αA-crystallin (αAc) and αB-crystallin (αBc), represent archetypal sHSPs that exhibit complex polydispersed oligomeric assemblies and rapid subunit exchange dynamics. Yet, our understanding of how this plasticity contributes to chaperone function remains poorly understood. Using biochemical and biophysical analyses combined with single-particle electron microscopy (EM), we examined structural changes in αAc, αBc and native heteromeric lens α-crystallins (αLc) in their apo-states and at varying degree of chaperone saturation leading to co-aggregation, using lysozyme and insulin as model clients. Quantitative single-particle analysis unveiled a continuous spectrum of oligomeric states formed during the co-aggregation process, marked by significant client-triggered expansion and quasi-ordered elongation of the sHSP oligomeric scaffold, whereby the native cage-like sHSP assembly displays a directional growth to accommodate saturating conditions of client sequestration. These structural modifications culminated in an apparent amorphous collapse of chaperone-client complexes, resulting in the creation of co-aggregates capable of scattering visible light. Intriguingly, these co-aggregates maintain internal morphological features of highly elongated sHSP oligomers with striking resemblance to polymeric α-crystallin species isolated from aged lens tissue. This mechanism appears consistent across αAc, αBc and αLc, albeit with varying degrees of susceptibility to client-induced co-aggregation. Importantly, our findings suggest that client-induced co-aggregation follows a distinctive mechanistic and quasi-ordered trajectory, distinct from a purely amorphous process. These insights reshape our understanding of the physiological and pathophysiological co-aggregation processes of α-crystallins, carrying potential implications for a pathway toward cataract formation.

'SurgTalk': The Educational Outcomes Associated With Development of a Surgical Podcast for Undergraduate Medical Students.

OBJECTIVE: Educational podcast series are becoming increasingly popular as free open access medical education (FOAMed) resources, however, the educational benefit associated with their use is unclear. The aim of this study was to assess the educational outcomes associated with the implementation of a surgical podcast series for undergraduate medical students. METHODS: Two conversational case-based podcast episodes were recorded covering 2 common surgical presentations. Final-year medical students were recruited prospectively in January 2023 and underwent a baseline multiple choice question (MCQ) test covering the material within the podcast episodes. Participants were then provided with the episode files through encrypted Google Drive links. Two weeks following baseline assessment, students repeated the initial MCQ test and completed a postpodcast reaction survey. Data were analyzed using a paired t-test, multivariable regression analyses, and simple descriptive statistics. RESULTS: Fifty students were enrolled in the study. All participants undertook the baseline assessment. About 98% completed the postpodcast MCQ, while 94% completed the postpodcast reaction survey. All participants who undertook the reaction survey (n = 47) found the podcast helpful in explaining surgical concepts, 92% of participants found the podcast enjoyable to listen to. The most commonly reported activity undertaken while listening was "commuting/driving" (n = 24, 48%). The mean baseline MCQ score was 44.6%. The mean postpodcast MCQ score was 65.51%. There was a mean absolute increase in test score of 20.2% from baseline which was statistically significant (95%CI 14.67-25.6, p < 0.001). CONCLUSION: Implementation of this podcast series was associated with a statistically significant improvement in mean test score from baseline, reflecting knowledge acquisition. There was a positive user reaction and students were able to listen while performing other activities. Further evaluation of the educational outcomes associated with podcast use, particularly the effects on knowledge retention and clinical competence, is required.

The α-crystallin chaperones undergo a quasi-ordered co-aggregation process in response to saturating client interaction.

Small heat shock proteins (sHSPs) are ATP-independent chaperones vital to cellular proteostasis, preventing protein aggregation events linked to various human diseases including cataract. The α-crystallins, αA-crystallin (αAc) and αB-crystallin (αBc), represent archetypal sHSPs that exhibit complex polydispersed oligomeric assemblies and rapid subunit exchange dynamics. Yet, our understanding of how this plasticity contributes to chaperone function remains poorly understood. This study investigates structural changes in αAc and αBc during client sequestration under varying degree of chaperone saturation. Using biochemical and biophysical analyses combined with single-particle electron microscopy (EM), we examined αAc and αBc in their apo-states and at various stages of client-induced co-aggregation, using lysozyme as a model client. Quantitative single-particle analysis unveiled a continuous spectrum of oligomeric states formed during the co-aggregation process, marked by significant client-triggered expansion and quasi-ordered elongation of the sHSP scaffold. These structural modifications culminated in an apparent amorphous collapse of chaperone-client complexes, resulting in the creation of co-aggregates capable of scattering visible light. Intriguingly, these co-aggregates maintain internal morphological features of highly elongated sHSP scaffolding with striking resemblance to polymeric α-crystallin species isolated from aged lens tissue. This mechanism appears consistent across both αAc and αBc, albeit with varying degrees of susceptibility to client-induced co-aggregation. Importantly, our findings suggest that client-induced co-aggregation follows a distinctive mechanistic and quasi-ordered trajectory, distinct from a purely amorphous process. These insights reshape our understanding of the physiological and pathophysiological co-aggregation processes of sHSPs, carrying potential implications for a pathway toward cataract formation.

A five year descriptive analysis of potentially preventable hospitalisations for Ear, Nose, and Throat conditions in regional Victoria, Australia, from 2015 to 2020.

BACKGROUND: Potentially preventable hospitalisations of ear, nose, and throat conditions in the Murray Primary Health Network region have been found to be higher than the state average of Victoria, Australia. This study aimed to examine the association between selected patient-level characteristics and the likelihood of residing in a Murray PHN postcode with higher than expected numbers of potentially preventable ENT hospitalisations. METHODS: Unit record hospital separation data were obtained from the Victorian Admitted Episodes Dataset. Postcodes were classified as having higher than expected numbers of potentially preventable hospitalisations across three subgroups of ENT using indirect standardisation techniques. Differences between patients from 'higher than expected' postcodes and 'other' postcodes with respect to the distribution of demographic and other patient characteristics were determined using chi-squared tests for each ENT subgroup. The results were confirmed by logistic regression analyses using resident of a postcode with higher than expected hospitalisations as the outcome variable. RESULTS: Of the 169 postcodes located in the catchment area, 15 were identified as having higher than expected numbers of upper respiratory tract infection hospitalisations, 14 were identified for acute tonsillitis, and 12 were identified for otitis media. Patients from postcodes with 'higher than expected' hospitalisations for these conditions were more likely than others to be aged between 0 and 9 years, Indigenous, or from a culturally and linguistically diverse background. CONCLUSION: Further investigation of the identified postcodes is warranted to determine access to and utilisation of primary healthcare services in the management of PPH ENT conditions in the region.

Treatment of Alcohol Use Problems Among Rural Populations: a Review of Barriers and Considerations for Increasing Access to Quality Care.

Purpose of Review: Individuals living in rural areas face unique challenges when accessing services for alcohol-related problems and are at increased risk of experiencing alcohol-related harms. We outline research on rural-urban treatment gaps in alcohol use treatment, identify common barriers to treatment, and provide recommendations for how to address the difficulties faced by this population. Recent Findings: Globally, individuals living in rural and remote areas are less likely to receive care for alcohol-related concerns compared to those residing in urban areas. Rural areas suffer from insufficient access to specialty providers, and rural residents are likely to experience greater stigma regarding seeking treatment for alcohol-related concerns. Summary: Given rural-urban disparities in access to treatment for alcohol use concerns, treatment efforts should incorporate stakeholders across the medical system. Telehealth options are particularly promising for increasing access to care. Adaptations should emphasize existing strengths among rural populations, such as strong religious beliefs and close community ties.

Effects of Fluids on the Sublingual Microcirculation in Sepsis.

Sepsis is one of the most common and deadly syndromes faced in Intensive Care settings globally. Recent advances in bedside imaging have defined the changes in the microcirculation in sepsis. One of the most advocated interventions for sepsis is fluid therapy. Whether or not fluid bolus affects the microcirculation in sepsis has not been fully addressed in the literature. This systematic review of the evidence aims to collate studies examining the microcirculatory outcomes after a fluid bolus in patients with sepsis. We will assimilate the evidence for using handheld intra vital microscopes to guide fluid resuscitation and the effect of fluid bolus on the sublingual microcirculation in patients with sepsis and septic shock. We conducted a systematic search of Embase, CENTRAL and Medline (PubMed) using combinations of the terms "microcirculation" AND "fluid" OR "fluid resuscitation" OR "fluid bolus" AND "sepsis" OR "septic shock". We found 3376 potentially relevant studies. Fifteen studies published between 2007 and 2021 fulfilled eligibility criteria to be included in analysis. The total number of participants was 813; we included six randomized controlled trials and nine non-randomized, prospective observational studies. Ninety percent used Sidestream Dark Field microscopy to examine the microcirculation and 50% used Hydroxyethyl Starch as their resuscitation fluid. There were no clear effects of fluid on the microcirculation parameters. There was too much heterogeneity between studies and methodology to perform meta-analysis. Studies identified heterogeneity of affect in the sepsis population, which could mean that current clinical classifications were not able to identify different microcirculation characteristics. Use of microcirculation as a clinical endpoint in sepsis could help to define sepsis phenotypes. More research into the effects of different resuscitation fluids on the microcirculation is needed.

Zoster meningitis in an immunocompetent young patient post first dose of BNT162b2 mRNA COVID-19 vaccine, a case report.

Recently published observational data suggests an increased risk of herpes zoster infection post-vaccination with the BNT162b2 mRNA vaccine. We describe the case of VZV meningitis post BNT162b2 mRNA vaccination in a young immunocompetent patient. A 39-year-old patient with no medical history presented with a vesicular rash, headache, nausea and fever, days after receiving BNT162b2 mRNA vaccination. CSF analysis revealed a pleocytosis, and VZV DNA was confirmed by PCR testing. The patient received intravenous aciclovir with resolution of symptoms within 48 h. He was discharged after 14 days of treatment. Case reports of herpes zoster reactivation post vaccination and details of subsequent successful vaccination course completion have allowed us to recommend the patient receive his second dose of the BNT162b2 mRNA vaccine. At the time of writing, however, the patient has declined to receive further vaccination due to fears of an adverse event. To the best of our knowledge, this is the first reported case in a young patient of herpes zoster meningitis following COVID-19 mRNA vaccination. The sharing of clinical experiences and reporting of suspected side effects, particularly for vaccines that employ novel technology, increases knowledge of the safety profile of these vaccines and allows clinicians to better aid patients make informed decisions with regard to commencing and completing vaccination.

Beyond BASICS: A scoping review of novel intervention content to enhance the efficacy of brief alcohol interventions for emerging adults.

OBJECTIVE: Brief motivational interventions (BMIs) that include personalized drinking feedback delivered in a motivational interviewing (MI) style have demonstrated reductions in drinking across numerous clinical trials with emerging adults (EAs) ages 18-25. However, effect sizes for these BMIs are generally small to moderate and drinking reductions are often not maintained beyond short-term follow-ups. Additionally, EAs may be more interested in approaches that highlight wellness, mood enhancement, or goal pursuit rather than programs focused exclusively on reducing alcohol-related risk. Thus, there is a need to evaluate novel intervention content as an alternative or supplement to BMIs in this high-risk population. METHOD: This scoping review examined studies of novel intervention elements to reduce alcohol consumption among EAs. Eligible studies were published in peer-reviewed journals in English from January 2015 to September 2021 and evaluated novel brief interventions, operationalized as one to five sessions focused on alcohol-related outcomes with key content beyond what has typically been included in alcohol BMIs. Results were categorized as additions to BMIs or stand-alone interventions and were synthesized within these categories by theoretical approach. RESULTS: Although standard in-person BMIs have the greatest empirical support, there are a variety of alternative intervention approaches that might enhance health and wellness and that can be feasibly integrated with BMIs or offered as an appealing "gateway" to increase help-seeking among EAs who drink alcohol. CONCLUSIONS: More research is needed to empirically evaluate both the relative efficacy of supplements and stand-alone alternatives to BMI among higher risk EAs and their potential for widespread dissemination. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Audiologists' perspective on the treatment of ear-related ear, nose, and throat conditions in rural Victoria.

OBJECTIVES: To understand the experience of audiologists in managing and treating ear-related ear, nose and throat conditions in rural areas, and to identify the compounding factors that influence patient outcomes and potential targets for intervention. DESIGN: A focus group was conducted using a qualitative descriptive approach. Responses were audio-recorded, transcribed and thematically analysed. SETTING: The focus group was conducted in the rural town of Mildura in the state of Victoria, Australia. PARTICIPANTS: A sample of 19 audiologists from Victoria participated, of which 14 were rurally based and 5 were metropolitan-based. The length of participants' professional experience ranged from 1 to 43 years. RESULTS: Long wait lists, and a lack of locally based ear, nose and throat surgeons were identified as barriers to the treatment of ear-related ear, nose and throat conditions. Open communication between health services and efficient care for time-sensitive conditions were seen as outcomes of good practice. Hand hygiene, nose-blowing, reducing tobacco smoke exposure and promoting the use of noise protective equipment were the 4 community health campaigns mentioned to support ear care for those residing in rural areas. Additional themes of ear conditions, treatment, management and primary health care were identified. CONCLUSION: Improving referral pathways for the treatment of ear-related ear, nose and throat conditions, and providing education about ear, nose and throat assessment and treatment in primary health care settings could increase appropriate referrals, improve patient outcomes and reduce wait periods for treatment.

Satellite Monitoring for Air Quality and Health.

Data from satellite instruments provide estimates of gas and particle levels relevant to human health, even pollutants invisible to the human eye. However, the successful interpretation of satellite data requires an understanding of how satellites relate to other data sources, as well as factors affecting their application to health challenges. Drawing from the expertise and experience of the 2016-2020 NASA HAQAST (Health and Air Quality Applied Sciences Team), we present a review of satellite data for air quality and health applications. We include a discussion of satellite data for epidemiological studies and health impact assessments, as well as the use of satellite data to evaluate air quality trends, support air quality regulation, characterize smoke from wildfires, and quantify emission sources. The primary advantage of satellite data compared to in situ measurements, e.g., from air quality monitoring stations, is their spatial coverage. Satellite data can reveal where pollution levels are highest around the world, how levels have changed over daily to decadal periods, and where pollutants are transported from urban to global scales. To date, air quality and health applications have primarily utilized satellite observations and satellite-derived products relevant to near-surface particulate matter <2.5 µm in diameter (PM2.5) and nitrogen dioxide (NO2). Health and air quality communities have grown increasingly engaged in the use of satellite data, and this trend is expected to continue. From health researchers to air quality managers, and from global applications to community impacts, satellite data are transforming the way air pollution exposure is evaluated.

Statistical downscaling with spatial misalignment: Application to wildland fire PM2.5 concentration forecasting.

Fine particulate matter, PM2.5, has been documented to have adverse health effects and wildland fires are a major contributor to PM2.5 air pollution in the US. Forecasters use numerical models to predict PM2.5 concentrations to warn the public of impending health risk. Statistical methods are needed to calibrate the numerical model forecast using monitor data to reduce bias and quantify uncertainty. Typical model calibration techniques do not allow for errors due to misalignment of geographic locations. We propose a spatiotemporal downscaling methodology that uses image registration techniques to identify the spatial misalignment and accounts for and corrects the bias produced by such warping. Our model is fitted in a Bayesian framework to provide uncertainty quantification of the misalignment and other sources of error. We apply this method to different simulated data sets and show enhanced performance of the method in presence of spatial misalignment. Finally, we apply the method to a large fire in Washington state and show that the proposed method provides more realistic uncertainty quantification than standard methods.

Application and evaluation of a low-cost PM sensor and data fusion with CMAQ simulations to quantify the impacts of prescribed burning on air quality in Southwestern Georgia, USA.

Prescribed burning (PB) is a prominent source of PM2.5 in the southeastern US and exposure to PB smoke is a health risk. As demand for burning increases and stricter controls are implemented for other anthropogenic sources, PB emissions tend to be responsible for an increasing fraction of PM2.5 concentrations. Here, to quantify the effect of PB on air quality, low-cost sensors are used to measure PM2.5 concentrations in Southwestern Georgia. The feasibility of using low-cost sensors as a supplemental measurement tool is evaluated by comparing them with reference instruments. A chemical transport model, CMAQ, is also used to simulate the contribution of PB to PM2.5 concentrations. Simulated PM2.5 concentrations are compared to observations from both low-cost sensors and reference monitors. Finally, a data fusion method is applied to generate hourly spatiotemporal exposure fields by fusing PM2.5 concentrations from the CMAQ model and all observations. The results show that the severe impact of PB on local air quality and public health may be missed due to the dearth of regulatory monitoring sites. In Southwestern Georgia PM2.5 concentrations are highly non-homogeneous and the spatial variation is not captured even with a 4-km horizontal resolution in model simulations. Low-cost PM sensors can improve the detection of PB impacts and provide useful spatial and temporal information for integration with air quality models. R2 of regression with observations increases from an average of 0.09 to 0.40 when data fusion is applied to model simulation withholding the observations at the evaluation site. Adding observations from low-cost sensors reduces the underestimation of nighttime PM2.5 concentrations and reproduces the peaks that are missed by the simulations. In the future, observations from a dense network of low-cost sensors could be fused with the model simulated PM2.5 fields to provide better estimates of hourly exposures to smoke from PB.Implications: Prescribed burning emissions are a major cause of elevated PM2.5 concentrations, posing a risk to human health. However, their impact cannot be quantified properly due to a dearth of regulatory monitoring sites in certain regions of the United States such as Southwestern Georgia. Low-cost PM sensors can be used as a supplemental measurement tool and provide useful spatial and temporal information for integration with air quality model simulations. In the future, data from a dense network of low-cost sensors could be fused with model simulated PM2.5 fields to provide improved estimates of hourly exposures to smoke from prescribed burning.

A multi-analysis approach for estimating regional health impacts from the 2017 Northern California wildfires.

Smoke impacts from large wildfires are mounting, and the projection is for more such events in the future as the one experienced October 2017 in Northern California, and subsequently in 2018 and 2020. Further, the evidence is growing about the health impacts from these events which are also difficult to simulate. Therefore, we simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling with WRF-CMAQ, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses. To demonstrate these analyses, we estimated the health impacts from smoke impacts during wildfires in October 8-20, 2017, in Northern California, when over 7 million people were exposed to Unhealthy to Very Unhealthy air quality conditions. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ system. Interestingly, this approach did not necessarily improve overall results, however it was key to simulating the initial 12-hr explosive fire activity and smoke impacts. To improve these results, we applied one data fusion and three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across all cases, the best Pearson correlation was 0.5. Overall, WRF-CMAQ simulations were biased high and the geostatistical methods were biased low. Finally, we applied the optimized PM2.5 exposure estimate in an exposure-response function. Estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% CI: 0, 196) with 47% attributable to wildland fire smoke.Implications: Large wildfires in the United States and in particular California are becoming increasingly common. Associated with these large wildfires are air quality and health impact to millions of people from the smoke. We simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses from the October 2017 Northern California wildfires. Temporary monitors deployed for the wildfires provided an important model evaluation dataset. Total estimated regional mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to the wildland fire smoke. This illustrates the profound effect that even a 12-day exposure to wildland fire smoke can have on human health.

Estimating Wildfire Smoke Concentrations during the October 2017 California Fires through BME Space/Time Data Fusion of Observed, Modeled, and Satellite-Derived PM2.5.

Exposure to wildfire smoke causes adverse health outcomes, suggesting the importance of accurately estimating smoke concentrations. Geostatistical methods can combine observed, modeled, and satellite-derived concentrations to produce accurate estimates. Here, we estimate daily average ground-level PM2.5 concentrations at a 1 km resolution during the October 2017 California wildfires, using the Constant Air Quality Model Performance (CAMP) and Bayesian Maximum Entropy (BME) methods to bias-correct and fuse three concentration datasets: permanent and temporary monitoring stations, a chemical transport model (CTM), and satellite-derived estimates. Four BME space/time kriging and data fusion methods were evaluated. All BME methods produce more accurate estimates than the standalone CTM and satellite products. Adding temporary station data increases the R2 by 36%. The data fusion of observations with the CAMP-corrected CTM and satellite-derived concentrations provides the best estimate (R2 = 0.713) in fire-impacted regions, emphasizing the importance of combining multiple datasets. We estimate that approximately 65,000 people were exposed to very unhealthy air (daily average PM2.5 ≥ 150.5 µg/m3).

Wildfire and prescribed burning impacts on air quality in the United States.

Air quality impacts from wildfires have been dramatic in recent years, with millions of people exposed to elevated and sometimes hazardous fine particulate matter (PM 2.5 ) concentrations for extended periods. Fires emit particulate matter (PM) and gaseous compounds that can negatively impact human health and reduce visibility. While the overall trend in U.S. air quality has been improving for decades, largely due to implementation of the Clean Air Act, seasonal wildfires threaten to undo this in some regions of the United States. Our understanding of the health effects of smoke is growing with regard to respiratory and cardiovascular consequences and mortality. The costs of these health outcomes can exceed the billions already spent on wildfire suppression. In this critical review, we examine each of the processes that influence wildland fires and the effects of fires, including the natural role of wildland fire, forest management, ignitions, emissions, transport, chemistry, and human health impacts. We highlight key data gaps and examine the complexity and scope and scale of fire occurrence, estimated emissions, and resulting effects on regional air quality across the United States. The goal is to clarify which areas are well understood and which need more study. We conclude with a set of recommendations for future research. IMPLICATIONS: In the recent decade the area of wildfires in the United States has increased dramatically and the resulting smoke has exposed millions of people to unhealthy air quality. In this critical review we examine the key factors and impacts from fires including natural role of wildland fire, forest management, ignitions, emissions, transport, chemistry and human health.

Methods, availability, and applications of PM2.5 exposure estimates derived from ground measurements, satellite, and atmospheric models.

Fine particulate matter (PM2.5) is a well-established risk factor for public health. To support both health risk assessment and epidemiological studies, data are needed on spatial and temporal patterns of PM2.5 exposures. This review article surveys publicly available exposure datasets for surface PM2.5 mass concentrations over the contiguous U.S., summarizes their applications and limitations, and provides suggestions on future research needs. The complex landscape of satellite instruments, model capabilities, monitor networks, and data synthesis methods offers opportunities for research development, but would benefit from guidance for new users. Guidance is provided to access publicly available PM2.5 datasets, to explain and compare different approaches for dataset generation, and to identify sources of uncertainties associated with various types of datasets. Three main sources used to create PM2.5 exposure data are ground-based measurements (especially regulatory monitoring), satellite retrievals (especially aerosol optical depth, AOD), and atmospheric chemistry models. We find inconsistencies among several publicly available PM2.5 estimates, highlighting uncertainties in the exposure datasets that are often overlooked in health effects analyses. Major differences among PM2.5 estimates emerge from the choice of data (ground-based, satellite, and/or model), the spatiotemporal resolutions, and the algorithms used to fuse data sources.Implications: Fine particulate matter (PM2.5) has large impacts on human morbidity and mortality. Even though the methods for generating the PM2.5 exposure estimates have been significantly improved in recent years, there is a lack of review articles that document PM2.5 exposure datasets that are publicly available and easily accessible by the health and air quality communities. In this article, we discuss the main methods that generate PM2.5 data, compare several publicly available datasets, and show the applications of various data fusion approaches. Guidance to access and critique these datasets are provided for stakeholders in public health sectors.

Machine Learning-Based Integration of High-Resolution Wildfire Smoke Simulations and Observations for Regional Health Impact Assessment.

Large wildfires are an increasing threat to the western U.S. In the 2017 fire season, extensive wildfires occurred across the Pacific Northwest (PNW). To evaluate public health impacts of wildfire smoke, we integrated numerical simulations and observations for regional fire events during August-September of 2017. A one-way coupled Weather Research and Forecasting and Community Multiscale Air Quality modeling system was used to simulate fire smoke transport and dispersion. To reduce modeling bias in fine particulate matter (PM2.5) and to optimize smoke exposure estimates, we integrated modeling results with the high-resolution Multi-Angle Implementation of Atmospheric Correction satellite aerosol optical depth and the U.S. Environmental Protection Agency AirNow ground-level monitoring PM2.5 concentrations. Three machine learning-based data fusion algorithms were applied: An ordinary multi-linear regression method, a generalized boosting method, and a random forest (RF) method. 10-Fold cross-validation found improved surface PM2.5 estimation after data integration and bias correction, especially with the RF method. Lastly, to assess transient health effects of fire smoke, we applied the optimized high-resolution PM2.5 exposure estimate in a short-term exposure-response function. Total estimated regional mortality attributable to PM2.5 exposure during the smoke episode was 183 (95% confidence interval: 0, 432), with 85% of the PM2.5 pollution and 95% of the consequent multiple-cause mortality contributed by fire emissions. This application demonstrates both the profound health impacts of fire smoke over the PNW and the need for a high-performance fire smoke forecasting and reanalysis system to reduce public health risks of smoke hazards in fire-prone regions.

Introducing early-phase medical students to clinical paediatrics using simulation and a flipped-classroom.

AIM: Both simulation and the flipped-classroom improve learning outcomes in medical education, with evidence emerging that they are effective in combination ('flipped-simulation'). Previous studies evaluating simulation in paediatrics have assessed efficacy for senior students. This study aimed to assess whether using flipped-simulation in early-phase medical student education would show similar benefits. METHODS: A flipped-simulation session was introduced into the earliest phase of the University of New South Wales Sydney's undergraduate medical program. A pre-test-post-test study design was used to assess short-term knowledge gains with an eight-item quiz administered before and after students attended the session. A retrospective cohort design was used to assess long-term knowledge retention, with student scores from a 10-item quiz administered at the second-phase paediatric course orientation, compared between a group that completed the flipped-simulation course and a group that attended an alternative play-based session. Additional survey data regarding student satisfaction were gathered. RESULTS: Students demonstrated short-term knowledge gains: mean test scores improved from the pre-test to post-test (3.4 ± 1.5 vs. 6.0 ± 1.3, P < 0.001). Students attending the flipped-simulation course retained knowledge more effectively in the longer term: mean test scores of students who completed the flipped-simulation session were significantly higher than those who attended the alternative play-based session (4.4 ± 1.9 vs. 3.4 ± 1.8, P < 0.001). Survey data demonstrated high student confidence in practical skills. CONCLUSION: Combining simulation and the flipped-classroom is effective for early-phase medical students, with improved knowledge over the short and long term, and high student satisfaction.