Ozone (O3) exposure is a recognised risk factor for respiratory and cardiovascular mortality, but its short-term effects on cancer remain largely unknown due to the absence of large-scale, multi-country evidence. Based on 9233,612 cancer deaths from 2000 to 2019 across 11,215 communities in Australia, Brazil, Canada, Chile, South Korea, Mexico, New Zealand and Thailand, this study provides the first comprehensive multi-country assessment of the associations between short-term O3 exposure and mortality from a wide range of cancer types, together with the contributions of major emission sources. Daily maximum 8-hour O3 concentrations were linked to residential locations and analysed using a space-time-stratified case-crossover design, with source-specific contributions from traffic, landscape fires and industrial emissions quantified. Each 10 μg/m3 increase in O3 (lag 0-1 days) was associated with a 0.84% (95% CI: 0.77-0.91%) increase in all-cancer mortality, with elevated risks observed for 24 cancer types except for nasopharyngeal, testicular cancer, and leukemia. Effect estimates varied by cancer type, ranging from a 0.42% increase for liver cancer to a 1.43% increase for thyroid cancer per 10 μg/m3 rise in O3 exposure. Short-term O3 exposure accounted for 6.37% (5.84-6.91%) of all cancer deaths, with the largest attributable fractions in Brazil (10.8%), Chile (6.3%) and Thailand (6.0%). Traffic emissions were the dominant contributor to O3-attributable cancer deaths overall, while landscape fire-related O3 contributed substantially in Australia and Brazil. These findings reveal a significant and previously under-recognised short-term impact of O3 exposure on cancer mortality and identify key emission sources driving this burden. The results provide important evidence for air-quality management and targeted cancer prevention strategies in diverse global regions.

Ambient fine particulate matter (PM2.5) is a major global threat to human health but its impacts on labour productivity remain poorly understood. Here we show that short-term exposure to PM2.5 was associated with substantial productivity losses related to premature deaths across 1,066 locations in seven countries between 2000 and 2019. Using mortality, air pollution and workforce participation data, we estimated that productivity-adjusted life-years (PALYs) lost owing to premature deaths increased by 2.70% (95% confidence interval 2.15–3.26%) for every 10-μg m−3 increase in PM2.5. Risks were higher among women, younger adults (15–44 years) and populations living in lower-middle-income areas. Overall, 5.0% (95% confidence interval 4.0–5.9%) of PALYs lost from premature deaths were attributable to PM2.5, corresponding to an annual economic cost of US$21.5 billion. Reducing PM2.5 concentrations below the World Health Organization air quality guideline could avoid 3.5% of PALY losses and US$16.7 billion in annual economic costs. These findings highlight the substantial labour and economic benefits of reducing air pollution. An estimated 5% of productivity-adjusted life-years (PALYs), representing US$21.5 billion, were attributed to premature deaths from PM2.5 air pollution in an analysis of seven countries between 2000 and 2019.

BACKGROUND:Lower-income countries have lower asthma prevalence. However, how differences in human development and inequality can explain changes in the prevalence of asthma and allergic diseases is not known. METHODS:The Global Asthma Network Phase I study reported prevalence of asthma and allergic diseases in children (6-7 years), adolescents (13-14 years), and their parents/guardians in 16, 25 and 17 countries. Gini inequality index (GinI) and human development index (HDI), together with mean annual relative humidity and temperature, and latitude, were used as potential explanatory factors of prevalence differences using meta-regression models, fitted values and heatmaps of prevalence. RESULTS:GinI and HDI explained some proportion of asthma prevalence variability, which was highest in children (up to ~70% for disease indicators such as current wheeze or symptoms of severe asthma) and lowest in adolescents (~22% for symptoms of severe asthma or asthma ever). Rhinoconjunctivitis prevalence variability was poorly explained by covariates (from ~53% for current rhinoconjunctivitis among children-an exception-to none). Eczema indicators were explained in a range from ~60% in children (current eczema symptoms and symptoms of severe eczema) to ~12% in adolescents (current eczema symptoms). Overall, heatmaps showed areas of higher prevalence in the intersection of high GinI and high HDI values. CONCLUSIONS:HDI and Gini explain part of the worldwide variability in the prevalence of asthma, rhinoconjunctivitis, and eczema. This explanatory power is highest for asthma and lowest for rhinoconjunctivitis. Lower-resourced communities in highly developed countries show the greatest hazard, particularly for asthma.

OBJECTIVES:To report patterns of asthma control, medications and healthcare utilisation in Australian adults with asthma in 2021, and assess changes since a similar survey in 2012. STUDY TYPE:Cross-sectional web-based survey (February-March 2021; n = 5427), compared with a similar 2012 survey (n = 2686). SETTING/PARTICIPANTS:Adults (≥ 18 years) with asthma, recruited from large web-based panels, with enrolment stratified by age group, gender and state/territory. MAIN OUTCOME MEASURES:Asthma control test (ACT), healthcare utilisation and medications. RESULTS:Median age was 46 years; 59% of participants reported female gender. Compared with 2012, fewer participants had well-controlled symptoms (ACT ≥ 20: 2021, 48.0%; 2012, 54.4%; p < 0.001), and more had very poorly controlled symptoms (ACT 5-15: 2021, 26.8%; 2012, 22.9%; p < 0.001). Urgent asthma healthcare had increased (2021, 37.9%; 2012, 28.6%; odds ratio 1.53 [95% confidence interval, 1.37-1.69]; p < 0.001). Inhaled corticosteroid (ICS) use in the previous year was similar (2021, 60.9%; 2012, 60.8%) but adherence was lower (p < 0.001). Fewer participants had good symptom control while taking little/no ICS (2021, 33.4%; 2012, 40.1%), and more had uncontrolled symptoms with little/no ICS (2021, 38.1%; 2012, 25.6%; p < 0.001); among the latter group, urgent healthcare utilisation had increased (2021, 63.5%; 2012, 41.2%; p < 0.001). In 2021, 28.7% reported using oral corticosteroids for asthma in the previous year; only 42.0% of ICS users recalled their inhaler technique having been checked in the past 12 months. Overuse of short-acting beta2-agonists was common: 56.3% adults obtained ≥ 3 inhalers in the previous year, and 10.5% obtained ≥ 12 inhalers. For symptom relief in the previous 4 weeks, only 13.3% adults reported using an anti-inflammatory reliever (ICS-formoterol). CONCLUSION:Our comparison of these two large nationally stratified sample surveys demonstrates significant worsening of key asthma indicators between 2012 and 2021, including worse symptom control and urgent healthcare use, but also indicates opportunities for improvement. The findings highlight an urgent need for system-wide implementation of the 2025 Australian asthma guidelines to reduce preventable morbidity. TRIAL REGISTRATION:ACTRN12620000977976p.

BACKGROUND:Existing rates of death and recurrent tuberculosis (TB) among people treated for rifampicin- or multidrug-resistant tuberculosis (RR/MDR-TB) are likely underestimates. We determined long-term disease outcomes among a cohort of people treated for RR/MDR-TB. METHODS:We conducted a prospective cohort study among patients treated by the National TB Program (NTP) in 10 provinces of Vietnam. Individuals with confirmed RR/MDR-TB starting World Health Organization-recommended regimens were followed up for ≥32 months. After this period, we surveyed the cohort to measure vital status and subsequent TB episodes. Family members completed verbal autopsies for deceased participants. We calculated rates of mortality and TB re-occurrence, and standardized mortality ratio (SMR) using participants' household contacts as a reference population. RESULTS:Between March 2016 and July 2020, 1755 patients were enrolled, of whom we assessed 1364 (77.7%) at final follow-up. Median follow-up time was 4.3 years. Successful treatment outcomes were reported for 1357/1755 (77.3%) individuals. From enrollment until end of follow-up, 289 participants died (16.5%; mortality rate, 42.6/1000 person-years); overall SMR was 5.6 and post-treatment SMR was 3.0. Tuberculosis was the probable or confirmed cause of death in 96 deceased participants. Many (71/165; 43.0%) deaths occurring on-treatment were not reported to the NTP. The rate of subsequent TB episodes among all participants, regardless of treatment outcome, was 10.3/1000 person-years. CONCLUSIONS:RR/MDR-TB survivors have high risks of mortality and re-occurring TB. Programmatic reports underestimate the true mortality rate both during and after treatment. Interventions are urgently needed to strengthen programmatic follow-up, improve treatment outcomes, and monitor for TB recurrence.

People with cancer may be susceptible to acute environmental stressors, including ambient fine particulate matter (PM2.5), but the contribution of traffic-related particles to short-term cancer mortality remains uncertain. We analysed daily cancer mortality records by cancer site from 2000 to 2019 across eight countries (Australia, Brazil, Canada, Chile, South Korea, Mexico, New Zealand and Thailand). A time-stratified case-crossover design was used to assess associations with all-source PM2.5 and traffic-sourced PM2.5 (TSPM2.5). The analysis included 9,223,612 cancer deaths. Every 10 μg m−3 increase in the 2-day moving average of all-source PM2.5 exposure (lag 0–1) was associated with a 0.77% increase in all-cancer mortality risk (95% confidence interval (CI) 0.64–0.89%). The corresponding increase in TSPM2.5 was associated with a 3.87% increase (95% CI 3.28–4.47%). Although TSPM2.5 represented only 14.72% of total PM2.5 concentrations, it accounted for 73.55% of PM2.5-attributable cancer deaths during the study period, equivalent to 1.21% (95% CI 1.03–1.39%) of total cancer mortality. Effect modification by age, sex or socioeconomic status was not statistically significant. Reducing TSPM2.5 exposure may help lower acute pollution-related mortality risks among people with cancer. Cancer is an important public health concern globally, but whether cancer patients face increased risks of mortality from traffic-contributed air pollution is unclear. The authors assess the contributions of traffic-sourced fine particulate matter pollution to cancer mortality across eight countries from 2000 to 2019.

Background: Chronic airways diseases impose substantial clinical and economic burdens in Vietnam. Established treatment algorithms for these conditions require differentiation between asthma and chronic obstructive pulmonary disease (COPD), which can impede timely treatment at the primary care level. The VCAPS4 trial evaluated a simplified anti-inflammatory reliever algorithm using a single inhaler (budesonide-formoterol 160/4.5 mcg) for adults presenting with undifferentiated chronic airways disease. Methods: We conducted a cost-effectiveness analysis of the VCAPS4 trial over 12 months compared to usual care from the Vietnamese health system perspective. A total of 3,095 participants were included (control: 1,421; intervention: 1,674). Health outcomes were expressed as exacerbations avoided and quality‑adjusted life‑years (QALYs), calculated using COPD‑specific cost and utility inputs to reflect the dominant pattern of disease severity in the trial population. Sensitivity (deterministic and probabilistic) and scenario analyses were performed. Findings: Compared with usual care, participants receiving the intervention experienced fewer exacerbations and gained an additional 0.019 QALYs (95% CI: 0.012 to 0.025) over 12 months. The intervention cost INT$210 per exacerbation avoided and was found to be cost saving when taking into the account costs of hospitalisations (INT$-2,342 per QALY). Cost savings were greatest among participants with variable or mixed airflow limitation. Results were robust across sensitivity and scenario analyses. Interpretation: A simplified single-inhaler approach using budesonide–formoterol was cost-effective for managing undifferentiated chronic airways disease in a resource‑limited primary care setting.

Recent studies report improved performance of ensemble models over machine learning (ML) models for air pollution estimation, although there is little evidence of their added value in settings with sparsely monitored data. We developed and compared three ML models, a supervised linear regression (SLR) model, and an ensemble model, for estimating annual average PM2.5, PM10, and NO2 in NSW, Australia, a relatively sparsely monitored, low pollution, and large geographic region. We assembled pollutant data from government and project monitors and data on 236 predictors including land use, population, traffic, and satellite observations. We used a three-stage DEML framework: (1) base-ML models (Random Forest (RF), XGBoost, GBM) and a SLR model; (2) meta-learner (RF, XGBoost, GBM, GLMNet); and (3) ensemble. We reserved 10% of data for hold-out validation and conducted 10-fold Cross validation (CV) using the training data sets. We evaluated the models using CV-R 2 and RMSE. DEML models resulted in the best fit for all pollutants; however, improvements over base ML models were modest, indicating the latter, with lower cost of implementation, are valuable for low pollution settings with heterogeneous monitoring density. Choice of CV methods substantially impacted model performance and should be considered, along with setting constraints, when choosing modeling methods.

Population-wide screening may accelerate the decline of tuberculosis (TB) incidence, but the optimal screening algorithm and duration must weigh resource considerations. We calibrated a deterministic transmission model to TB epidemiology in Viet Nam. We simulated three population-wide screening algorithms from 2025: sputum nucleic acid amplification tests (NAAT, Xpert MTB/RIF Ultra) only; chest radiography (CXR) followed by NAAT; and CXR-only without microbiological confirmation. We determined the annual screening rounds required to reduce pulmonary TB prevalence below 50 per 100,000 people. Cost-effectiveness was assessed using incremental cost-effectiveness ratios (ICERs), representing the additional costs (in US$) per disability-adjusted life year (DALY) averted compared to business-as-usual by 2050. Additionally, we evaluated the impact of NAAT cartridges costing US$1 each. NAAT-based algorithms required at least six rounds to reach the prevalence threshold, while CXR-only required three. NAAT-only achieved a prevalence reduction consistent with the ACT3 trial after three rounds. The CXR+NAAT algorithm averted 4.29m DALYs (95%UI:2.86-6.14) at US$225 (95%UI:85-520) per DALY averted compared with business-as-usual. The front-loaded investment of US$161m (95%UI:111-224) annually during the intervention resulted in average annual cost savings of US$12.7m (95%UI:6.7-21.4) up to 2050 compared to the business-as-usual counterfactual. Reducing the cost of NAAT to US$1 led to a 50% and 15% reduction in budget impact and a 63% and 26% reduction in the estimated ICER for the NAAT-only and CXR+NAAT algorithms, respectively. In Viet Nam, population-wide screening could achieve ambitious policy goals. Substantial front-loaded investment is immediately followed by persistent cost savings and could be further offset by more affordable NAATs.

Background: Individuals with Preserved Ratio Impaired Spirometry (PRISm), defined as FEV1/FVC ≥0.7 and FEV1 <80% predicted, are at higher risk of developing COPD. However, data for Australian adults are limited. We aimed to describe prevalence of PRISm and its relationship with clinical characteristics in Australia. Method: Data from the Burden of Lung Disease (BOLD) Australia study of randomly selected adults aged ≥40 years from six sites was classified into airflow limitation, PRISm, or normal spirometry groups. Demographic, clinical characteristics, and lung function were compared between groups. Results: Of the study sample ( n = 3518), 387 (11%) had PRISm, 549 (15.6%) had airflow limitation, and 2582 (73.4%) had normal spirometry. PRISm was more common in Indigenous Australian adults. Adults with PRISm had more frequent respiratory symptoms, more comorbidities, greater health burden and poorer quality of life than those with normal spirometry. Pre- and post-bronchodilator FEV1 and FVC were lower in adults with PRISm than those with airflow limitation. Adults with PRISm were less likely to use respiratory medicine than those with airflow limitation (OR = 0.56, 95% CI 0.38–0.81). Conclusions: PRISm was present in 11% of adults in this study and they had similar respiratory symptoms and health burden as adults with airflow limitation.

Background:Multidrug-resistant tuberculosis (TB) threatens global TB control, on account of poor treatment outcomes, high treatment toxicity and costs. Recent trials demonstrated the effectiveness of six-months of levofloxacin (6Lfx) to prevent TB disease among high-risk contacts. However, the cost-effectiveness of this strategy has not previously been evaluated. Methods:The VQUIN study was a double-blinded randomised control trial in Vietnam assessing the effectiveness of 6Lfx in household contacts of multidrug resistant/rifampicin resistant TB (MDR/RR-TB) to prevent progression to TB disease. Incorporating in-trial costs and effectiveness outcomes from the VQUIN trial, we developed a closed cohort, decision-analytic Markov model to assess the cost effectiveness of 6Lfx versus placebo in a cohort exposed to MDR/RR-TB in Vietnam. Findings:Over a 20-year time horizon, the provision of 6Lfx preventative therapy to household contacts of people infected with MDR/RR-TB was found to gain a total of 40.1 QALYs per 1000 population and save US$23,145 per 1000 population, indicating the strategy was cost saving. MDR/RR-TB cases averted over 20 years was 19.9 per 1000 population treated with 6Lfx, and the number of deaths averted was 3.2 per 1000 people treated. Interpretation:6Lfx therapy is a cost-saving strategy to reduce the incidence of active disease in household contacts of MDR/RR-TB in a resource-limited setting. Funding:National Health and Medical Research Council Project Grant (#1081443). GJF was supported by a NHMRC Leadership Fellowship (Level 1) (#2007920).

Transfer learning (TL) is a strategic solution to handle vast data volume requirements in deep learning (DL). It transfers knowledge learned from a large base dataset, as a pretrained model (PTM), to a new domain. In this study, we introduce an ensemble of classifiers trained on features extracted from some intermediate layers of a PTM for Tuberculosis (TB) detection task. We use different EfficientNet variants: EfficientNet-B0-EfficientNet-B3, as the PTM. Moreover, we introduce a rejection mechanism and implement post-hoc calibration methods to enhance the reliability and trustworthiness of the developed models. Additionally, we conduct analyses on domain-shift distribution, a topic rarely discussed in the context of TB detection. Through a fivefold cross-validation on two prominent chest X-ray datasets, the Montgomery County (MC) and Shenzhen (SZ), our ensemble approach achieved competitive results with accuracies of 94.89% (MC) and 92.75% (SZ). The incorporation of the devised rejection mechanism resulted in enhanced model accuracy, albeit with a coverage tradeoff. In domain-shift experiments, the proposed approach achieved an accuracy of 83.57% (63% coverage) when applying the MC-trained model on SZ, and an accuracy of 88.50% (82% coverage) when applying the SZ-trained model on MC.

Ground-level ozone (O3) is a significant public health concern. We developed maps of monthly average 1-h maximum O3 concentrations in New South Wales, Australia (2005-2018), a region with sparse monitoring. For the first time Bayesian Maximum Entropy (BME) blending was used within a Deep Ensemble Machine Learning (DEML) framework for air pollution predictions. The DEML combined geographical predictors in random forest (RF), extreme gradient boosting (XGBoost), and gradient boosted machine (GBM) models with three meta-models. BME blending incorporated observed O3 data into posterior predictions. We generated 2.5 km x 2.5 km resolution gridded surfaces. The DEML estimates achieved an R2 of 0.89 and RMSE of 2.3 ppb in the held-out test dataset at monitors. DEML grid cell predictions (R2: 0.84, RMSE: 3.03 ppb) were improved by BME blending (R2: 0.89, RMSE: 2.49 ppb). Mean bias reduced from -0.7 ppb to -0.4 ppb. This demonstrates high accuracy and precision in a sparsely monitored region.

Background Tuberculosis (TB) remains a significant health concern, contributing to the highest mortality among infectious diseases worldwide. However, none of the various TB diagnostic tools introduced is deemed sufficient on its own for the diagnostic pathway, so various artificial intelligence (AI)–based methods have been developed to address this issue. Objective We aimed to provide a comprehensive evaluation of AI-based algorithms for TB detection across various data modalities. Methods Following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) 2020 guidelines, we conducted a systematic review to synthesize current knowledge on this topic. Our search across 3 major databases (Scopus, PubMed, Association for Computing Machinery [ACM] Digital Library) yielded 1146 records, of which we included 152 (13.3%) studies in our analysis. QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies version 2) was performed for the risk-of-bias assessment of all included studies. Results Radiographic biomarkers (n=129, 84.9%) and deep learning (DL; n=122, 80.3%) approaches were predominantly used, with convolutional neural networks (CNNs) using Visual Geometry Group (VGG)-16 (n=37, 24.3%), ResNet-50 (n=33, 21.7%), and DenseNet-121 (n=19, 12.5%) architectures being the most common DL approach. The majority of studies focused on model development (n=143, 94.1%) and used a single modality approach (n=141, 92.8%). AI methods demonstrated good performance in all studies: mean accuracy=91.93% (SD 8.10%, 95% CI 90.52%-93.33%; median 93.59%, IQR 88.33%-98.32%), mean area under the curve (AUC)=93.48% (SD 7.51%, 95% CI 91.90%-95.06%; median 95.28%, IQR 91%-99%), mean sensitivity=92.77% (SD 7.48%, 95% CI 91.38%-94.15%; median 94.05% IQR 89%-98.87%), and mean specificity=92.39% (SD 9.4%, 95% CI 90.30%-94.49%; median 95.38%, IQR 89.42%-99.19%). AI performance across different biomarker types showed mean accuracies of 92.45% (SD 7.83%), 89.03% (SD 8.49%), and 84.21% (SD 0%); mean AUCs of 94.47% (SD 7.32%), 88.45% (SD 8.33%), and 88.61% (SD 5.9%); mean sensitivities of 93.8% (SD 6.27%), 88.41% (SD 10.24%), and 93% (SD 0%); and mean specificities of 94.2% (SD 6.63%), 85.89% (SD 14.66%), and 95% (SD 0%) for radiographic, molecular/biochemical, and physiological types, respectively. AI performance across various reference standards showed mean accuracies of 91.44% (SD 7.3%), 93.16% (SD 6.44%), and 88.98% (SD 9.77%); mean AUCs of 90.95% (SD 7.58%), 94.89% (SD 5.18%), and 92.61% (SD 6.01%); mean sensitivities of 91.76% (SD 7.02%), 93.73% (SD 6.67%), and 91.34% (SD 7.71%); and mean specificities of 86.56% (SD 12.8%), 93.69% (SD 8.45%), and 92.7% (SD 6.54%) for bacteriological, human reader, and combined reference standards, respectively. The transfer learning (TL) approach showed increasing popularity (n=89, 58.6%). Notably, only 1 (0.7%) study conducted domain-shift analysis for TB detection. Conclusions Findings from this review underscore the considerable promise of AI-based methods in the realm of TB detection. Future research endeavors should prioritize conducting domain-shift analyses to better simulate real-world scenarios in TB detection. Trial Registration PROSPERO CRD42023453611; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023453611

Background As climate change intensifies the frequency and severity of bushfires, exposure to bushfire smoke is emerging as a significant public health concern, associated with numerous adverse health outcomes, including exacerbation of chronic obstructive pulmonary disease, asthma, cardiovascular diseases, and respiratory infections. Objective This study examined policies related to the use of masks and respirators as protective measures against smoke exposure. Methods Policies and guidelines of health departments, emergency and fire services, and other relevant organisations of selected countries were reviewed. Guidelines were sourced from organizational websites, PubMed, and Google Scholar using specific keywords. Result There is variability in policies regarding mask and respirator use during bushfires. Health departments generally recommend using P2/ N95 respirators to protect the public from particulate exposure arising bushfire smoke, while emergency and fire services generally recommend surgical or cloth masks. Few guidelines provided detailed instructions on the proper use of respirators, including fit testing, or fit checking procedures. Most guidelines emphasised monitoring air quality and avoiding bushfire smoke, particularly for high-risk groups. There is no guidance provided on the length of time a mask should be used in any guideline. Conclusion The inconsistent recommendations from health organisations and countries regarding mask and respirator use during bushfires highlights the lack of high-quality evidence in this area. Health, emergency and fire services, and other relevant organisations should provide clear guidance around types of facemasks, the length of time a facemask should be used and on proper use of respirators use, including training and fit checking.

Mitigation measures against infectious aerosols are desperately needed. We aimed to: 1) compare germicidal ultraviolet radiation (GUV) at 254nm (254-GUVUpper-Room) and 222nm (222-GUVWhole-Room) with portable high efficiency particulate air (HEPA) filters to inactivate/remove airborne bacteriophage ϕX174, 2) measure the effect of air mixing on the effectiveness of 254-GUVUpper-Room, and 3) determine the relative susceptibility of ϕX174, SARS-CoV-2, and Influenza A(H3N2) to GUV (254nm, 222nm). A nebulizer generated ϕX174 laden aerosols in an occupied clinical room (sealed-low flow). Mitigation devices (3 commercial GUV devices, HEPA-470m3/hr-class H13 filter) were compared by counterbalanced experimental design with negative (no mitigation) control. Viral inactivation was determined by air sampling (SartoriusMD8 and Gilair5). Environmental physical properties (airflow, particle matter, GUV irradiance, temperature and humidity) were also characterized. The effect of improving air mixing on the efficacy of 254-GUVUpper-Room devices was systematically explored by adding fans. The relative susceptibility of SARS-CoV-2, Influenza A(H3N2) and ϕX174 were assessed by exposure to 254nm and 222nm wavelength radiation in a 82L chamber. 254-GUVUpper-Room with highest irradiance (Philips UV-C WL345W) resulted in highest calculated equivalent air changes per hour (eACH) of 8.18±0.74 (hr-1). This increased to 19.20±2.45 (hr-1) with the addition of 2 fans. HEPA filtration achieved 11.10±1.25 (hr-1). For 254nm GUV rank order (most-to-least) of susceptibility was SARS-CoV-2, ϕX174, Influenza A(H3N2), and for 222nm GUV SARS-CoV-2, Influenza A(H3N2), ϕX174. GUV effectively inactivates virus laden aerosol in poorly ventilated clinical environments. Efficacy is improved by increasing airflow. HEPA performance is superior to GUV under low flow conditions.

Background Tobacco remains the leading cause of preventable death globally. Vietnam's 2012 Law on Prevention and Control of Tobacco Harms establishes all healthcare facilities as smoke-free environments. We aimed to evaluate the implementation of these policies within health facilities across Vietnam. Methods A cross-sectional study was undertaken at 40 central, provincial, district and commune healthcare facilities in four provinces of Vietnam. The presence of tobacco sales, smoke-free signage, evidence of recent tobacco use and smoking behaviours by patients and staff were observed over a 1-week period at multiple locations within each facility. Adherence with national regulations was reported using descriptive statistics. Results 23 out of 40 facilities (57.5%) followed the requirements of the national smoke-free policy regarding tobacco sales, advertising and signage. Smoking was observed within health facility grounds at 26 (65%) facilities during the observation period. Indirect evidence of smoking was observed at 35 (88%) facilities. Sites where smoking was permitted (n=2) were more likely to have observed smoking behaviour (relative risk (RR) 2.16, 95% CI 1.83 to 2.56). Facilities where tobacco was sold (n=7) were more likely to have smoking behaviour observed at any of their sites (RR 1.53, 95% CI 0.93 to 2.51). Conclusions Implementation of current smoke-free hospital regulations remains incomplete, with widespread evidence of smoking observed at three levels of the Vietnamese healthcare facilities. Further interventions are required to establish the reputation of Vietnamese healthcare facilities as smoke-free environments.