Frequency-dependent tolerance to aircraft disturbance drastically alters predicted impact on shorebirds.

Anthropogenic disturbance of wildlife is increasing globally. Generalizing impacts of disturbance to novel situations is challenging, as the tolerance of animals to human activities varies with disturbance frequency (e.g. due to habituation). Few studies have quantified frequency-dependent tolerance, let alone determined how it affects predictions of disturbance impacts when these are extrapolated over large areas. In a comparative study across a gradient of air traffic intensities, we show that birds nearly always fled (80%) if aircraft were rare, while birds rarely responded (7%) if traffic was frequent. When extrapolating site-specific responses to an entire region, accounting for frequency-dependent tolerance dramatically alters the predicted costs of disturbance: the disturbance map homogenizes with fewer hotspots. Quantifying frequency-dependent tolerance has proven challenging, but we propose that (i) ignoring it causes extrapolations of disturbance impacts from single sites to be unreliable, and (ii) it can reconcile published idiosyncratic species- or source-specific disturbance responses.

Global introductions and environmental impacts of freshwater megafish.

Freshwater megafish species, such as sturgeons, salmonids, carps, and catfishes, have a maximum reported weight ≥30 kg. Due to their charisma and economic value, they have been widely introduced outside of their native ranges. Here, we provide a comprehensive overview of the introduction of freshwater megafish and an assessment of their environmental impacts. Of the 134 extant freshwater megafish species, 46% have been introduced to new environments, and of these, 69% have established self-sustaining alien populations. These introductions affect 59% of the world's main basins, with the USA and western Europe being particular hotspots of megafish introductions. The common carp (Cyprinus carpio) is the most widely introduced species. Using the Environmental Impact Classification for Alien Taxa (EICAT and EICAT+) frameworks, we assessed the severity and type of negative and positive impacts posed by alien megafish on native species. Alien megafish caused negative impacts through nine different mechanisms, with predation being the most frequently reported mechanism, followed by herbivory and competition. Moreover, 58% of the alien megafish species with sufficient data to evaluate the severity of their impacts caused declining populations of native species, or worse, extirpations of native species populations. The positive environmental impacts of alien megafish were far less frequently documented. They include biotic interactions that benefit native species, and the provision of trophic resources or habitats. Widely introduced or extensively studied species are more likely to have documented severe impacts on native species. There is a clear trade-off between the economic benefits associated with megafish introductions and the severe adverse impacts they have on native biodiversity. Our study highlights the need for comprehensive risk assessments to evaluate the potential environmental impacts of megafish. More research and long-term monitoring schemes are required to inform management actions to protect biodiversity, particularly in the Global South.

Impact of the pandemic on surgical oncology in Piedmont, Italy: A retrospective observational study.

BACKGROUND AND METHODS: This retrospective observational study analyzes how the COVID-19 pandemic affected surgical oncology healthcare in a large sample from Piedmont, Northern Italy. Patients admitted for regular hospitalization were included (n = 99 651). Data from 2020 were compared to the averages from 2016 to 2019, stratified by tumor site, year, month, and admission method, using interrupted time series analysis post-March 2020. RESULTS: In 2020, oncological surgeries decreased by 12.3% (n = 17 923) compared to the 2016-2019 average (n = 20 432), notably dropping post-March (incidence rate ratio = 0.858; p < 0.001). The greatest reduction was observed for breast (-19.2%), colon (-18.2%), bladder (-17.5%), kidney (-14.2%), and prostate (-14%) surgeries. There was a huge reduction in nonemergency admissions (-13.6%), especially for colon (-23.8%), breast (-19.4%), and bladder (-18.7%). The proportion of hospitalizations with emergency access increased (p < 0.001). CONCLUSIONS: The COVID-19 pandemic led to a significant decrease in cancer surgeries in Piedmont in 2020, with an increase in the proportion of admissions through emergency access. DISCUSSION: The research provides valuable insights for comparing data with other regions and evaluating the effectiveness of efforts to recover lost surgical procedures. These findings can be useful to policymakers in developing coordinated measures and more efficient access strategies to healthcare services in any future emergency situations.

The potential impact fraction of population weight reduction scenarios on non-communicable diseases in Belgium: application of the g-computation approach.

BACKGROUND: Overweight is a major risk factor for non-communicable diseases (NCDs) in Europe, affecting almost 60% of all adults. Tackling obesity is therefore a key long-term health challenge and is vital to reduce premature mortality from NCDs. Methodological challenges remain however, to provide actionable evidence on the potential health benefits of population weight reduction interventions. This study aims to use a g-computation approach to assess the impact of hypothetical weight reduction scenarios on NCDs in Belgium in a multi-exposure context. METHODS: Belgian health interview survey data (2008/2013/2018, n = 27 536) were linked to environmental data at the residential address. A g-computation approach was used to evaluate the potential impact fraction (PIF) of population weight reduction scenarios on four NCDs: diabetes, hypertension, cardiovascular disease (CVD), and musculoskeletal (MSK) disease. Four scenarios were considered: 1) a distribution shift where, for each individual with overweight, a counterfactual weight was drawn from the distribution of individuals with a "normal" BMI 2) a one-unit reduction of the BMI of individuals with overweight, 3) a modification of the BMI of individuals with overweight based on a weight loss of 10%, 4) a reduction of the waist circumference (WC) to half of the height among all people with a WC:height ratio greater than 0.5. Regression models were adjusted for socio-demographic, lifestyle, and environmental factors. RESULTS: The first scenario resulted in preventing a proportion of cases ranging from 32.3% for diabetes to 6% for MSK diseases. The second scenario prevented a proportion of cases ranging from 4.5% for diabetes to 0.8% for MSK diseases. The third scenario prevented a proportion of cases, ranging from 13.6% for diabetes to 2.4% for MSK diseases and the fourth scenario prevented a proportion of cases ranging from 36.4% for diabetes to 7.1% for MSK diseases. CONCLUSION: Implementing weight reduction scenarios among individuals with excess weight could lead to a substantial and statistically significant decrease in the prevalence of diabetes, hypertension, cardiovascular disease (CVD), and musculoskeletal (MSK) diseases in Belgium. The g-computation approach to assess PIF of interventions represents a straightforward approach for drawing causal inferences from observational data while providing useful information for policy makers.

Heavy alcohol use and the HIV care continuum in Kenya: a population-based study.

Heavy alcohol use (HAU) can destabilize engagement along the HIV care continuum. Population-based studies assessing associations of HAU with HIV treatment outcomes are lacking, especially in sub-Saharan Africa. We leveraged data from the Kenya Population-based HIV Impact Assessment to identify associations of self-reported HAU, assessed using two items measuring the frequency and quantity of past-year alcohol consumption, with serum biomarkers for HIV serostatus unawareness, antiretroviral therapy (ART) non-use, and HIV viremia (≥1000 RNA copies/mL). Overall and sex-stratified survey-weighted logistic regression with jackknife variance estimation modeled adjusted odds ratios (adjOR) of HIV treatment indicators by HAU. Overall, 1491 persons living with HIV aged 15-64 years (68.4% female) were included. The prevalence of HAU was 8.9% (95% confidence interval [95%CI]: 6.8-11.0%) and was significantly more pronounced in males than females (19.6% vs. 4.0%, p < 0.001). In multivariable analysis, HAU was significantly (p < 0.001) associated with HIV serostatus unawareness (adjOR = 3.65, 95%CI: 2.14-6.23), ART non-use (adjOR = 3.81, 95%CI: 2.25-6.43), and HIV viremia (adjOR = 3.13, 95%CI: 1.85-5.32). Incorporating sex-specific alcohol use screening into HIV testing and treatment services in populations where HAU is prevalent could optimize clinical outcomes along the HIV care continuum.

The Global Environmental Impacts of China's Accession to the WTO: A 20-Year Review.

Robust empirical assessments of the long-term cumulative global effects of free trade and economic globalization on the environment are limited. This account fills this gap by constructing a dynamic computable general equilibrium model to estimate the environmental effects of a milestone in the recent history of trade liberalization: China's 20-year World Trade Organization (WTO) accession. The modeling shows that China's accession could have resulted in an increase in the global cumulative greenhouse gases (GHGs), sulfur dioxide (SO2), and nitrogen oxide (NOx) emissions by roughly 14,000 Mt CO2-eq, 64 Mt, and 46 Mt, respectively. The global production scale effect contributed to most of these estimated increases. The regional total output composition effect also caused higher emissions. Meanwhile, the sectoral output composition effect helped reduce total emissions to a limited extent. Fortunately, a package of emission abatement measures led to a decrease in emission factors and a drop in the global cumulative emissions of GHGs, SO2, and NOx. The findings suggest that to enjoy the free trade and economic globalization benefits and minimize the induced emission increases, it is vitally important to systemically reduce emissions across the entire economy and nurture a low-carbon trade regime.

Probabilistic Reference and 10% Effect Concentrations for Characterizing Inhalation Non-cancer and Developmental/Reproductive Effects for 2,160 Substances.

Chemicals assessment and management frameworks rely on regulatory toxicity values, which are based on points of departure (POD) identified following rigorous dose-response assessments. Yet, regulatory PODs and toxicity values for inhalation exposure (i.e., reference concentrations [RfCs]) are available for only ∼200 chemicals. To address this gap, we applied a workflow to determine surrogate inhalation route PODs and corresponding toxicity values, where regulatory assessments are lacking. We curated and selected inhalation in vivo data from the U.S. EPA's ToxValDB and adjusted reported effect values to chronic human equivalent benchmark concentrations (BMCh) following the WHO/IPCS framework. Using ToxValDB chemicals with existing PODs associated with regulatory toxicity values, we found that the 25th %-ile of a chemical's BMCh distribution (PODp25BMCh) could serve as a suitable surrogate for regulatory PODs (Q2 ≥ 0.76, RSE ≤ 0.82 log10 units). We applied this approach to derive PODp25BMCh for 2,095 substances with general non-cancer toxicity effects and 638 substances with reproductive/developmental toxicity effects, yielding a total coverage of 2,160 substances. From these PODp25BMCh, we derived probabilistic RfCs and human population effect concentrations. With this work, we have expanded the number of chemicals with toxicity values available, thereby enabling a much broader coverage for inhalation risk and impact assessment.

What Is the Impact of Accidentally Transporting Terrestrial Alien Species? A New Life Cycle Impact Assessment Model.

Alien species form one of the main threats to global biodiversity. Although Life Cycle Assessment attempts to holistically assess environmental impacts of products and services across value chains, ecological impacts of the introduction of alien species are so far not assessed in Life Cycle Impact Assessment. Here, we developed country-to-country-specific characterization factors, expressed as the time-integrated potentially disappeared fraction (PDF; regional and global) of native terrestrial species due to alien species introductions per unit of goods transported [kg] between two countries. The characterization factors were generated by analyzing global data on first records of alien species, native species distributions, and their threat status, as well as bilateral trade partnerships from 1870-2019. The resulting characterization factors vary over several orders of magnitude, indicating that impact greatly varies per transportation route and trading partner. We showcase the applicability and relevance of the characterization factors for transporting 1 metric ton of freight to France from China, South Africa, and Madagascar. The results suggest that the introduction of alien species can be more damaging for terrestrial biodiversity as climate change impacts during the international transport of commodities.

Two-Stage Machine Learning-Based Approach to Predict Points of Departure for Human Noncancer and Developmental/Reproductive Effects.

Chemical points of departure (PODs) for critical health effects are crucial for evaluating and managing human health risks and impacts from exposure. However, PODs are unavailable for most chemicals in commerce due to a lack of in vivo toxicity data. We therefore developed a two-stage machine learning (ML) framework to predict human-equivalent PODs for oral exposure to organic chemicals based on chemical structure. Utilizing ML-based predictions for structural/physical/chemical/toxicological properties from OPERA 2.9 as features (Stage 1), ML models using random forest regression were trained with human-equivalent PODs derived from in vivo data sets for general noncancer effects (n = 1,791) and reproductive/developmental effects (n = 2,228), with robust cross-validation for feature selection and estimating generalization errors (Stage 2). These two-stage models accurately predicted PODs for both effect categories with cross-validation-based root-mean-squared errors less than an order of magnitude. We then applied one or both models to 34,046 chemicals expected to be in the environment, revealing several thousand chemicals of moderate concern and several hundred chemicals of high concern for health effects at estimated median population exposure levels. Further application can expand by orders of magnitude the coverage of organic chemicals that can be evaluated for their human health risks and impacts.

Land Resources for Wind Energy Development Requires Regionalized Characterizations.

Estimates of the land area occupied by wind energy differ by orders of magnitude due to data scarcity and inconsistent methodology. We developed a method that combines machine learning-based imagery analysis and geographic information systems and examined the land area of 318 wind farms (15,871 turbines) in the U.S. portion of the Western Interconnection. We found that prior land use and human modification in the project area are critical for land-use efficiency and land transformation of wind projects. Projects developed in areas with little human modification have a land-use efficiency of 63.8 ± 8.9 W/m2 (mean ±95% confidence interval) and a land transformation of 0.24 ± 0.07 m2/MWh, while values for projects in areas with high human modification are 447 ± 49.4 W/m2 and 0.05 ± 0.01 m2/MWh, respectively. We show that land resources for wind can be quantified consistently with our replicable method, a method that obviates >99% of the workload using machine learning. To quantify the peripheral impact of a turbine, buffered geometry can be used as a proxy for measuring land resources and metrics when a large enough impact radius is assumed (e.g., >4 times the rotor diameter). Our analysis provides a necessary first step toward regionalized impact assessment and improved comparisons of energy alternatives.

A novel approach to deriving the fine-scale daily NO2 dataset during 2005-2020 in China: Improving spatial resolution and temporal coverage to advance exposure assessment.

Surface NO2 pollution can result in serious health consequences such as cardiovascular disease, asthma, and premature mortality. Due to the extensive spatial variation in surface NO2, the spatial resolution of a NO2 dataset has a significant impact on the exposure and health impact assessment. There is currently no long-term, high-resolution, and publicly available NO2 dataset for China. To fill this gap, this study generated a NO2 dataset named RBE-DS-NO2 for China during 2005-2020 at 1 km and daily resolution. We employed the robust back-extrapolation via a data augmentation approach (RBE-DA) to ensure the predictive accuracy in back-extrapolation before 2013, and utilized an improved spatial downscaling technique (DS) to refine the spatial resolution from 10 km to 1 km. Back-extrapolation validation based on 2005-2012 observations from sites in Taiwan province yielded an R2 of 0.72 and RMSE of 10.7 µg/m3, while cross-validation across China during 2013-2020 showed an R2 of 0.73 and RMSE of 9.6 µg/m3. RBE-DS-NO2 better captured spatiotemporal variation of surface NO2 in China compared to the existing publicly available datasets. Exposure assessment using RBE-DS-NO2 show that the population living in non-attainment areas (NO2 ≥ 30 µg/m3) grew from 376 million in 2005 to 612 million in 2012, then declined to 404 million by 2020. Unlike this national trend, exposure levels in several major cities (e.g., Shanghai and Chengdu) continued to increase during 2012-2020, driven by population growth and urban migration. Furthermore, this study revealed that low-resolution dataset (i.e., the 10 km intermediate dataset before the downscaling) overestimated NO2 levels, due to the limited specificity of the low-resolution model in simulating the relationship between NO2 and the predictor variables. Such limited specificity likely biased previous long-term NO2 exposure and health impact studies employing low-resolution datasets. The RBE-DS-NO2 dataset enables robust long-term assessments of NO2 exposure and health impacts in China.

Ambient PM2.5 exposure and rapid population aging: A double threat to public health in the Republic of Korea.

Particulate matter with an aerodynamic diameter of ≤2.5 µm (PM2.5) can infiltrate deep into the respiratory system, posing significant health risks. Notably, the health burden of PM2.5 is more pronounced among the older adult population. With an aging population, the public health burden attributable to PM2.5 could escalate even if the current PM2.5 level remains stable. This study evaluated the number of deaths attributable to long-term PM2.5 exposure in the Republic of Korea between 2020 and 2050 and identified the PM2.5 concentration required at least to maintain the current PM2.5 health burden. To calculate mortality for 2020-2050, we performed a health impact assessment using 3-year (2019-2021) average population-weighted PM2.5 concentrations, age-specific population and mortality rates. In 2020, 33,578 [95% confidence interval (CI) = 31,708-35,448] deaths were attributable to PM2.5 exposure. Projecting forward, if the 2019-2021 average PM2.5 level remains constant, mortality is projected to be 112,953 (95% CI = 109,963-115,943) in 2050, more than three times higher than in 2020. To maintain the same level of health burden in 2050 as in 2020, the PM2.5 concentration needs to be immediately reduced to 5.8 µg/m3. In an age-specific analysis, the proportion of older adults (ages 65+) to total mortality would increase from 83% (2020) to 96% (2050), indicating that the rising mortality is predominantly driven by the aging population. By region, the reduction of PM2.5 concentrations, which is required immediately in 2020 to have the health burden in 2050 equal to that in 2020, varied from 3.6 µg/m3 in Goheung-gun (25% reduction) to 20.8 µg/m3 in Heungdeok-gu (82% reduction). Our study emphasizes the critical need for air quality management to consider aging populations when establishing PM2.5 air quality standards, as well as their associated policies and regulations.

Urban green spaces and behavioral and cognitive development in children: A health impact assessment of the Barcelona "Eixos Verds" Plan (Green Axis Plan).

BACKGROUND: Urban environments lack natural features, while nature exposure in cities has been associated with health benefits, including children's neurodevelopment. Through extensive street greening, Barcelona's Eixos Verds (Green Axis) Plan enhances safety, environment, and climate resilience. We aimed to assess the Eixos Verds Plan's potential impact on children's behavioral and cognitive development due to the increased green space expected under the Eixos Verds implementation. METHODS: We performed a quantitative health impact assessment for Barcelona children at census-tract level (n = 1068). We assessed the Eixos Verds Plan's impact by comparing baseline green space distribution with the proposed plan, translating it into percentage green area (%GA) and Normalized Difference Vegetation Index (NDVI). By combining these exposure metrics with child-specific risk estimates and population data, we estimated potential improvements in children's behavioral and cognitive development due to full Eixos Verds implementation. RESULTS: With the full Eixos Verds implementation, citywide, %GA increased by 6.9% (IQR: 6.4%; range: 0-23.1%) and NDVI by 0.065 (IQR: 0.083; range: 0.000-0.194). Child behavioral and cognitive development outcomes are expected to improve compared to the baseline. Based on NDVI increases, children's Total Difficulties and Hyperactivity/Inattention scores, based on the Strengths and Difficulties Questionnaire (SDQ), are projected to decrease by 5% (95% CI: 0-15%) and 6% (95% CI: 0-17%). Working Memory and Superior Working Memory scores are expected to increase by 4% and 5%, respectively, based on the computerized n-back test, while the Inattentiveness score could be reduced by 1%, based on the computerized attentional test (ANT). INTERPRETATION: Urban greening as planning tool can improve behavioral and cognitive development in city children. Methods and results of our study are applicable to many cities worldwide, and similar results for children of real-life urban greening interventions can be expected.

Potential environmental and human health menace of spent graphite in lithium-ion batteries.

The growing demand for lithium-ion batteries for portable electronics and electric vehicles results in a booming lithium battery market, leading to a concomitant increase in spent graphite. This research investigated the potential impacts of spent graphite on environmental and human health using standardized toxicity extraction and Life Cycle Impact Assessment models. The spent graphite samples were classified as hazardous waste due to the average nickel content of 337.14 mg/L according to Chinese regulations. Besides, cadmium and fluorine were the other elements that exceeded the regulations threshold. Easily ignored aluminum and heavy metal cobalt are other harmful elements according to the results of Life Cycle Impact Assessments. All the metallic harmful elements mainly exist in a transferable state. Thermogravimetry infrared spectrometry coupled with mass spectrometry was employed to recognize the emitted gases and explore gas emission behavior. Inorganic gases of CO, H2S, SO2, SO3, oxynitride, HCl, and fluoride-containing gases were detected. Sulfur-containing gases released from spent graphite were contributed by the residual sulfuric acid after leaching. The correlation between the evolution of emitted gases and the heating schedule was established simultaneously. The research comprehensively illustrates the pollution of spent graphite and provides assistance for the design of green recycling schemes for spent graphite.

Designing energy-efficient buildings in urban centers through machine learning and enhanced clean water managements.

Rainwater Harvesting (RWH) is increasingly recognized as a vital sustainable practice in urban environments, aimed at enhancing water conservation and reducing energy consumption. This study introduces an innovative integration of nano-composite materials as Silver Nanoparticles (AgNPs) into RWH systems to elevate water treatment efficiency and assess the resulting environmental and energy-saving benefits. Utilizing a regression analysis approach with Support Vector Machines (SVM) and K-Nearest Neighbors (KNN), this study will reach the study objective. In this study, the inputs are building attributes, environmental parameters, sociodemographic factors, and the algorithms SVM and KNN. At the same time, the outputs are predicted energy consumption, visual comfort outcomes, ROC-AUC values, and Kappa Indices. The integration of AgNPs into RWH systems demonstrated substantial environmental and operational benefits, achieving a 57% reduction in microbial content and 20% reductions in both chemical usage and energy consumption. These improvements highlight the potential of AgNPs to enhance water safety and reduce the environmental impact of traditional water treatments, making them a viable alternative for sustainable water management. Additionally, the use of a hybrid SVM-KNN model effectively predicted building energy usage and visual comfort, with high accuracy and precision, underscoring its utility in optimizing urban building environments for sustainability and comfort.

Increase in sick leave episodes from short-term fine particulate matter exposure: A case-crossover study in Stockholm, Sweden.

Air pollution's short-term effects on a wide range of health outcomes have been studied extensively, primarily focused on vulnerable groups (e.g., children and the elderly). However, the air pollution effects on the adult working population through sick leave have received little attention. This study aims to 1) estimate the associations between particulate matter ≤2.5 µm3 (PM2.5) and sick leave episodes and 2) calculate the attributable number of sick leave days and the consequential productivity loss in the City of Stockholm, Sweden. Individual level daily sick leave data was obtained from Statistics Sweden for the years 2011-2019. Daily average concentrations of PM2.5 were obtained from the main urban background monitoring station in Stockholm. A case-crossover study design was applied to estimate the association between short-term PM2.5 and onset of sick leave episodes. Conditional logistic regression was used to estimate the relative increase in odds of onset per 10 µg/m3 of PM2.5, adjusting for temperature, season, and pollen. A human capital method was applied to estimate the PM2.5 attributable productivity loss. In total, 1.5 million (M) individual sick leave occurrences were studied. The measured daily mean PM2.5 concentration was 4.2 µg/m3 (IQR 3.7 µg/m3). The odds of a sick leave episode was estimated to increase by 8.5% (95% CI: 7.8-9.3) per 10 µg/m3 average exposure 2-4 days before. Sub-group analysis showed that private sector and individuals 15-24 years old had a lower increase in odds of sick leave episodes in relation to PM2.5 exposure. In Stockholm, 4% of the sick leave episodes were attributable to PM2.5 exposure, corresponding to €17 M per year in productivity loss. Our study suggests a positive association between PM2.5 and sick leave episodes in a low exposure area.

The hidden threat of heavy metal leaching in urban runoff: Investigating the long-term consequences of land use changes on human health risk exposure.

This study evaluated the potential effects of long-term land use and climate change on the quality of surface runoff and the health risks associated with it. The land use change projection 2030 was derived from the main changes in land use from 2009 to 2019, and rainfall data was obtained from the Long Ashton Research Station Weather Generator (LARS-WG) model. The Long-Term Hydrological Impact Assessment (L-THIA) model was then utilized to calculate the rate of runoff heavy metal (HM) pollutant loading from the urban catchment. It was found that areas with heavy development posed a significantly greater public health risk associated with runoff, with higher risks observed in high-development and traffic areas compared to industrial, residential, and commercial areas. Additionally, exposure to Lead (Pb), Mercury (Hg), and Arsenic (As) was found to contribute significantly to overall non-carcinogenic health risks for possible consumers of runoff. Carcinogenic risk values of As, Cadmium (Cd), and Pb were also observed to increase, particularly in high-development and traffic areas, by 2030. This investigation offers important insight into the health risks posed by metals present in surface runoff in urban catchment areas under different land use and climate change scenarios.

The impact of a regionally based translational cancer research collaborative in Australia using the FAIT methodology.

BACKGROUND: Translating research, achieving impact, and assessing impact are important aspirations for all research collaboratives but can prove challenging. The Hunter Cancer Research Alliance (HCRA) was funded from 2014 to 2021 to enhance capacity and productivity in cancer research in a regional centre in Australia. This study aimed to assess the impact and benefit of the HCRA to help inform future research investments of this type. METHOD: The Framework to Assess the Impact from Translational health research (FAIT) was selected as the preferred methodology. FAIT incorporates three validated methodologies for assessing impact: 1) Modified Payback; 2) Economic Analysis; and 3) Narrative overview and case studies. All three FAIT methods are underpinned by a Program Logic Model. Data were collected from HCRA and the University of Newcastle administrative records, directly from HCRA members, and website searches. RESULTS: In addition to advancing knowledge and providing capacity building support to members via grants, fellowships, scholarships, training, events and targeted translation support, key impacts of HCRA-member research teams included: (i) the establishment of a regional biobank that has distributed over 13,600 samples and became largely self-sustaining; (ii) conservatively leveraging $43.8 M (s.a.$20.5 M - $160.5 M) in funding and support from the initial $9.7 M investment; (iii) contributing to clinical practice guidelines and securing a patent for identification of stem cells for endometrial cell regeneration; (iv) shifting the treatment paradigm for all tumour types that rely on nerve cell innervation, (v) development and implementation of the world's first real-time patient treatment verification system (Watchdog); (vi) inventing the effective 'EAT' psychological intervention to improve nutrition and outcomes in people experiencing radiotherapy for head and neck cancer; (vi) developing effective interventions to reduce smoking rates among priority groups, currently being rolled out to disadvantaged populations in NSW; and (vii) establishing a Consumer Advisory Panel and Consumer Engagement Committee to increase consumer involvement in research. CONCLUSION: Using FAIT methodology, we have demonstrated the significant impact and downstream benefits that can be achieved by the provision of infrastructure-type funding to regional and rural research collaboratives to help address inequities in research activity and health outcomes and demonstrates a positive return on investment.

Acceptability of self-administered antigen test for COVID-19 in the Philippines.

OBJECTIVES: In response to the Omicron surge in early 2022, the HTA Philippines evaluated the acceptability of Filipinos in using self-administered antigen tests (SAAgTs) as part of COVID-19 HTAs in the Philippines. METHODS: Scoping review from literature databases was initially conducted to identify preset codes in the use of SAAgT. Preset codes were used to establish the questions for focus group discussions (FGDs). Semi-structured questionnaires were created through Delphi technique. FGDs with four stakeholder groups (i.e., nine healthcare workers [HCWs], seven representatives of at-risk groups, six economic frontliners, and seven representatives of micro-small-medium-sized enterprises) were conducted. RESULTS: Discomfort in being a target of stigma and being prescribed an "illness identity" when suspected or confirmed COVID-19-positive, along with lack of confidence to perform self-test, caused hesitancy in self-testing among participants. The need for subsidies for test kits from the government or employers was emphasized to increase its accessibility. Having a designated access point and reporting system for SAAgT was highlighted to avoid nepotism (padrino system attributed to debt of gratitude), inequitable distribution, and lapses in reporting. A participatory approach to education was perceived as crucial to reduce any misconceptions associated with the use of SAAgT. CONCLUSIONS: All FGD groups expressed favorable reviews on the implementation of SAAgT because it can potentially reduce the burden of health facility-administered tests. These findings were considered by the HTA Council in the recommendation of SAAgT as part of the overarching national strategies for the diagnosis and screening of COVID-19.

Health technology assessment and healthcare environmental sustainability: Prioritizing effort and maximizing impact.

The growing global focus on and sense of urgency toward improving healthcare environmental sustainability and moving to low-carbon and resilient healthcare systems is increasingly mirrored in discussions of the role of health technology assessment (HTA). This Perspective considers how HTA can most effectively contribute to these goals and where other policy tools may be more effective in driving sustainability, especially given the highly limited pool of resources available to conduct environmental assessments within HTA. It suggests that HTA might most productively focus on assessing those technologies that have intrinsic characteristics which may cause specific environmental harms or vulnerabilities, while the generic environmental impacts of most other products may be better addressed through other policy and regulatory mechanisms.