Reference Period Research Articles

Structure and Trends in Climate Parameters of Wine-Growing Regions in Slovenia

This study examined the structure and trends of climate parameters important for grape production from 1952 to 2022 in the wine-growing regions of Podravje, Posavje, and Primorska in Slovenia. Average and extreme temperature and precipitation data from six meteorological stations in three wine-growing regions were divided into annual and growing seasons. The results show that in the period 1991–2022, there was a warming in the growing season in all regions by 1.4–1.7 °C, except the southern part of Primorska (Koper station) 0.6 °C, compared to the reference period 1961–1990. The heat accumulation indices (GDDs and HI) increased significantly, which is mainly due to the increase in the maximum temperature in the growing season temperature (GST max) and the number of days with Tmax > 30 °C (NDT30). The NDT30 increased the most, by a factor of more than four. In the reference period (1961–1990), however, the trend in the number of hot days was even slightly negative. The mean seasonal temperature rose to around 17 °C in regions with a continental climate and to around 19 °C in the Mediterranean region, which could be reflected in the earlier ripening of the grapes. The trends show a decrease in total annual precipitation (AP) after 1991, but this was significant only at one inland location (Maribor), while the total precipitation during the growing season (GSP) decreased significantly at three locations (Maribor, Bilje, and Koper).

Runoff Prediction of Tunxi Basin under Projected Climate Changes Based on Lumped Hydrological Models with Various Model Parameter Optimization Strategies

Runoff is greatly influenced by changes in climate conditions. Predicting runoff and analyzing its variations under future climates are crucial for ensuring water security, managing water resources effectively, and promoting sustainable development within the catchment area. As the key step in runoff modeling, the calibration of hydrological model parameters plays an important role in models’ performance. Identifying an efficient and reliable optimization algorithm and objective function continues to be a significant challenge in applying hydrological models. This study selected new algorithms, including the strategic random search (SRS) and sparrow search algorithm (SSA) used in hydrology, gold rush optimizer (GRO) and snow ablation optimizer (SAO) not used in hydrology, and classical algorithms, i.e., shuffling complex evolution (SCE-UA) and particle swarm optimization (PSO), to calibrate the two-parameter monthly water balance model (TWBM), abcd, and HYMOD model under the four objective functions of the Kling–Gupta efficiency (KGE) variant based on knowable moments (KMoments) and considering the high and low flows (HiLo) for monthly runoff simulation and future runoff prediction in Tunxi basin, China. Furthermore, the identified algorithm and objective function scenario with the best performance were applied for runoff prediction under climate change projections. The results show that the abcd model has the best performance, followed by the HYMOD and TWBM models, and the rank of model stability is abcd > TWBM > HYMOD with the change of algorithms, objective functions, and contributing calibration years in the history period. The KMoments based on KGE can play a positive role in the model calibration, while the effect of adding the HiLo is unstable. The SRS algorithm exhibits a faster, more stable, and more efficient search than the others in hydrological model calibration. The runoff obtained from the optimal model showed a decrease in the future monthly runoff compared to the reference period under all SSP scenarios. In addition, the distribution of monthly runoff changed, with the monthly maximum runoff changing from June to May. Decreases in the monthly simulated runoff mainly occurred from February to July (10.9–56.1%). These findings may be helpful for the determination of model parameter calibration strategies, thus improving the accuracy and efficiency of hydrological modeling for runoff prediction.

Using syndromic surveillance to rapidly assess the impact of a June 2023 wildfire smoke event on respiratory-related emergency department visits, Massachusetts, United States

Abstract A statewide air quality advisory was issued in Massachusetts for 6–7 June 2023 due to smoke originating from wildfires in Canada. Of particular concern was fine particulate matter, which has an aerodynamic diameter of ⩽2.5 μm (PM2.5) and has been linked to adverse respiratory outcomes. The objective of this study was to rapidly assess the impact of this wildfire smoke event on respiratory-related emergency department (ED) visits among Massachusetts residents. For exposure, daily air quality index (AQI) data from the US Environmental Protection Agency were used. Massachusetts counties, where for each day from 6 to 8 June 2023, the daily AQI was ⩾101 (i.e. unhealthy air quality), were considered exposed. For each exposed period, two unexposed reference periods where AQI < 101 (i.e. ‘good’ or ‘moderate’ air quality) were identified within the two weeks prior to the exposed period, with the same days of the week and in the same county. Data from the Massachusetts Department of Public Health’s syndromic surveillance system were used to examine daily counts of ED visits for asthma, air-quality-related respiratory illness, and all causes by county of residence, age group, race, and Hispanic/Latino ethnicity. For each outcome, the numbers of ED visits were compared between the exposed and reference periods. Overall, there were no large increases in ED visits for any conditions examined during this wildfire smoke event. However, residents who were aged 18–64 years, Hispanic/Latino or White experienced small but not statistically significant increases in asthma-related ED visits. These potential differences in the effect on asthma-related ED visits by age and race/ethnicity may be relevant for analyses of future events. This study provides an example of how real-time, publicly available exposure data can be used in conjunction with outcome data from syndromic surveillance to rapidly examine the impact of wildfires and other acute environmental events on health.

The Key Role of Temporal Stratification for GCM Bias Correction in Climate Impact Assessments

AbstractCharacterizing climate change impacts on water resources typically relies on Global Climate Model (GCM) outputs that are bias‐corrected using observational data sets. In this process, two pivotal decisions are (a) the Bias Correction Method (BCM) and (b) how to handle the historically observed time series, which can be used as a continuous whole (i.e., without dividing it into sub‐periods), or partitioned into monthly, seasonal (e.g., 3 months), or any other temporal stratification (TS). Here, we examine how the interplay between the choice of BCM, TS, and the raw GCM seasonality may affect historical portrayals and projected changes. To this end, we use outputs from 29 GCMs belonging to the CMIP6 under the Shared Socioeconomic Pathway 5–8.5 scenario, using seven BCMs and three TSs (entire period, seasonal, and monthly). The results show that the effectiveness of BCMs in removing biases can vary depending on the TS and climate indices analyzed. Further, the choice of BCM and TS may yield different projected change signals and seasonality (especially for precipitation), even for climate models with low bias and a reasonable representation of precipitation seasonality during a reference period. Because some BCMs may be computationally expensive, we recommend using the linear scaling method as a diagnostics tool to assess how the choice of TS may affect the projected precipitation seasonality of a specific GCM. More generally, the results presented here unveil trade‐offs in how BCMs are applied, regardless of the climate regime, urging the hydroclimate community to carefully implement these techniques.

Linking local climate scenarios to global warming levels: applicability, prospects and uncertainties

Abstract Global warming levels (GWLs) are increasingly becoming a central concept in climate change studies. In recent years, their integrative quality for climate change impact analysis has been demonstrated, and methodological advancements have helped to compensate for some inherent shortfalls of the concept. However, their applicability at the regional level is debatable, and no study to date has examined the possibility of linking local climate scenarios to GWLs. For the case of Austria, we have evaluated the relation between global and local warming patterns, and whether version changes of global climate models could be incorporated into local climate scenarios by means of the GWL concept, without updating the actual data. We applied the time sampling approach, where GWLs are determined as periods when global mean temperature anomalies cross a certain threshold. GWL periods were sampled both from the global models in the background of the local climate scenarios (CMIP5), and from an equivalent ensemble of newer-generation climate models (CMIP6). Uncertainties resulting from sampling GWLs from different global climate model ensembles were examined, and prospects for local climate change impact assessments were discussed. Accounting for updated global climate model versions might be useful when the changes at certain GWLs are related to fixed reference periods, but temperature increments between GWLs remained relatively constant across model versions, even on the local level. The study bridges a significant gap to link regional and local climate projections to GWLs. Climate change impacts assessments that build on those datasets can benefit from the integrative character of GWLs, making studies comparable across multiple disciplines and model versions, and thus fostering a way to communicate local climate change impacts more comprehensible.

Acute Appendicitis After COVID-19 Vaccines in Italy: A Self-Controlled Case Series Study.

Cases of appendicitis were identified in the pivotal randomized clinical trial on BNT162b2 mRNA vaccine and reported from coronavirus disease 2019 (COVID-19) vaccine pharmacovigilance systems. Three cohort studies and two self-controlled case series (SCCS) studies evaluating the association between mRNA vaccines and appendicitis reported discordant results. To address this uncertainty, the present study examines in a large population, with a SCCS design, the association between mRNA (BNT162b2 and mRNA-1273) and, for the first time, viral vector (ChAdOx1-S and Ad26.COV2-S) COVID-19 vaccines and acute appendicitis. The SCCS study design was used to evaluate the association between COVID-19 vaccination and subsequent onset of acute appendicitis. The study was based on record linkage of health archives through TheShinISS application, a statistical tool that locally processes data from regional health care databases according to ad hoc, study-tailored and common data model. The study population included all vaccinated subjects ≥ 12 years old between 27 December 2020 and 30 September 2021. The acute appendicitis was identified through discharge diagnoses of hospital admissions or emergency department visits. Incident cases were defined as those who experienced a first event of acute appendicitis in the study period, excluding subjects with a diagnosis of appendicitis in the previous 5 years. Exposure was defined as the first or second dose of BNT162b2, mRNA-1273 and ChAdOx1-S and the single dose of Ad26.COV2-S. The risk interval was defined as 42 days from the first or second vaccination dose and divided into pre-specified risk subperiods; the reference period was the observation time outside the risk interval. Relative incidences (RI) and 95% confidence intervals (95% CI) were estimated with the SCCS method 'modified for event-dependent exposures', through unbiased estimating equations. The seasonal component was considered as a time-dependent covariate. In the 42-day risk interval 1285 incident cases of acute appendicitis occurred: 727 cases after the first dose and 558 cases after the second dose. In the main analysis, no increased risks of acute appendicitis were observed in subjects vaccinated with BNT162b, mRNA-1273, ChAdOx1-S and Ad26.COV2-S. The subgroup analyses by sex showed an increased risk in the 14-27 day risk interval, in males after the first dose of mRNA-1273 (RI of 1.71; 95% CI 1.08-2.70, p = 0.02) and in females after the single dose of Ad26.COV2-S (RI of 4.40; 95% CI 1.29-15.01, p = 0.02). There was no evidence of association of BNT162b, ChAdOx1-S, mRNA-1273 and Ad26.COV2-S with acute appendicitis in the general population. The results of the subgroup analyses by sex needs to be considered with caution. The multiplicity issue cannot be excluded being these hypotheses two of several hypotheses tested. In addition, relevant literature on the biological mechanism of the disease and evidence of similar effects with other vaccines or with the same vaccines are still lacking to provide strong support for a conclusion that there is an harmful effect in males and females with mRNA-1273 and Ad26.COV2-S.

Rainfall projections under different climate scenarios over the Kaduna River Basin, Nigeria

This research aimed to assess changes in mean and extreme rainfall within the Kaduna River Basin (KRB), specifically examining the implications of two Representative Concentration Pathways (RCPs)—4.5 and 8.5 scenarios. Employing a quantile mapping technique, this study corrected inherent biases in four Regional Climate Models, enabling the examination of mean precipitation and six indices capturing extreme precipitation events for the 2050s. These findings were compared against a historical reference period spanning from 1981 to 2010, considering the basin's upstream and downstream segments. Results revealed an average annual rainfall reduction under scenarios 4.5 (21.39%) and 8.5 (20.51%) across the basin. This decline exhibited a more pronounced impact on monthly rainfall during the wet season (April to October) compared to the dry season (November to March). Notably, a substantial decrement in wet indices, excluding consecutive wet days (CWD), was foreseen in both seasons for the upstream and downstream areas, signalling an impending drier climate. The anticipated rise in consecutive dry days (CDD) is poised to manifest prominently downstream attributed to global warming-induced climate change brought on by increased anthropogenic emissions of greenhouse gases. These findings accentuate a heterogeneous distribution of extreme rainfall, potentially leading to water scarcity issues throughout the KRB, especially impacting upstream users. Moreover, the projections hint at an increased risk of flash floods during intense wet periods. Consequently, this study advocates the implementation of targeted disaster risk management strategies within the KRB to address these foreseeable challenges.

Nutritional status, food security and other correlates among adult tuberculosis patients in a block of Murshidabad district, West Bengal.

Tuberculosis (TB) and malnutrition are epidemiologically interrelated two major public health problems in India. Food security also influences nutritional status. This aspect needs evaluation in diverse geographical areas. This study aimed to assess the level of food security, nutritional status and correlates among adult TB patients in a block of Murshidabad, West Bengal. This cross-sectional study was undertaken in the Nabagram block of Murshidabad district during April-July 2023. All adult (≥18 years) patients registered under the Tuberculosis Unit of the block during a reference period of 6 months (October 2022-March 2023) were considered study subjects. Eighty such eligible participants recruited randomly were interviewed with a pre-designed schedule for socio-demographic and programmatic characteristics. Household food security was measured using a validated U.S. Household Food Security Survey Module. Anthropometric measurements were taken, and nutritional status was determined based on body mass index. Statistical Package for the Social Sciences (SPSS) version 26 was used for analysis. Among 80 TB patients, 51% were underweight and 20% were severely underweight. The majority (90%) of them had high or marginal food security, and 10% had low or very low food security. On multivariable logistic regression, Hindu religion (adjusted odds ratio (AOR): 6.74, 95% confidence interval (CI): 2.12-29.39), presence of any chronic morbidity (AOR: 11.61, 95%CI: 2.71-49.78) and receipt of dietary counselling by a health worker (AOR: 7.25, 95%CI: 1.22-43.13) appeared as predictors of underweight. Underweight among TB patients is quite prevalent in the area, and few programmatic interventions are influencing factors. This underscores the importance of nutritional counselling services and the universal provision of Poshan benefits.

The impact of stagnation on the microbial quality of constructed water systems after COVID-19 shutdowns.

In response to COVID-19 pandemic, governments all over the world limited the movement of people and mandated temporary closure of different institutions. While, these measures helped to reduce the spread of COVID-19, stagnant water can cause water quality deterioration. Stagnation is considered in context with the proliferation of pathogenic and facultatively pathogenic bacteria which pose potential health risks to humans. The objective of this study was to document the hygienic microbiological status of different water systems after the first shutdowns (between 18th March 2020 and 18th May 2020) in Hungary in comparison with a reference period (between 3rd January 2020 to 17th March). During the reference period drinking waters were compliant > 95% of total samples to the parametric values. After the short period shutdowns, the ratio of tnon-compliant drinking water samples was 6.6%: mainly Pseudomonas aeruginosa (7%) and coliform bacteria (5%) resulted poor water quality. The microscopic analysis of drinking waters showed that after low water demand the values of non-compliant samples also increased due to the proliferation of Amoebozoa and other Protozoa species. The compliant pool waters' ratio was also high in the reference period (97-99%), while after the shutdowns more samples were positive in both pool operation type (fill-and-drain pools and pools with recirculation) due to the proliferation of P. aeruginosa (14%) and micrococci (12%). Legionella non-compliant samples in hot tap water did not show significant difference during both studied periods (15%) although after stagnation the Legionella CFU (colony forming unit) values of the samples increased markedly.

Use of fluoroquinolones and the risk of aortic and mitral regurgitation: A nationwide case-crossover study.

Recently, there have been conflicting results reporting an increased risk of AR or MR associated with oral fluoroquinolones (FQs).This study investigated whether the use of FQs increases the risk of mitral regurgitation (MR) or aortic regurgitation (AR). A retrospective cohort study was conducted by using the Taiwan National Health Insurance research database. A unidirectional case-crossover design without selecting controls from an external population was adopted in this study. A total of 26,650 adult patients with new onset of AR or MR between January 1, 2000, and December 31, 2012, were identified. The risk of outcomes was compared between the hazard period and one of the randomly selected referent periods of the same individuals. Before exclusion of pneumonia diagnosed within 2 months before the index date, patients who took FQs had a significantly greater risk of AR or MR (adjusted odds ratio [aOR] 1.51, 95% confidence interval [CI] 1.30-1.77), any AR (combined AR and MR) (aOR 1.50, 95% CI 1.10-2.04), and any MR (combined AR and MR) (aOR 1.37, 95% CI 1.16-1.62). After exclusion of pneumonia, FQs exposure remained significantly associated with a greater risk of MR (aOR 1.38, 95% CI 1.17-1.62) and any MR (aOR 1.25, 95% CI 1.05-1.48). The findings suggested that patients treated with FQs could be warned about the potential risk for MR even after considering the possibility of protopathic bias. Reducing unnecessary FQs prescriptions may be considered to reduce the risk of valvular heart disease.

Validation of a digital food frequency questionnaire for the Northern Sweden Diet Database

BackgroundDietary habits strongly influence health, with poor diets contributing to numerous deaths annually. Addressing this requires improved dietary habits and consistent monitoring thereof. In northern Sweden, a validated food frequency questionnaire (FFQ) has been used for decades, but trends show that its ability to accurately measure intake has diminished. With changing eating habits and food supply, updating the FFQ was crucial, leading to the development of FFQ2020. This study assessed FFQ2020’s relative validity using 24-hour recalls and evaluated its reproducibility.MethodsParticipants were recruited from one of the northern-Sweden population-based health screenings and by advertising. Food intake was registered in an electronic food frequency questionnaire (FFQ2020) (test instrument) and reference data were obtained by six repeated electronic 24-hour dietary recalls (24HDR). Intakes of single foods were aggregated into food groups and healthy diet index scores, and daily energy and nutrient intakes were estimated. Results from the two methods were described and tested in univariate analyses and correlation tests, Bland Altman plots, cross-classification validity, and intra-class correlation analyses.ResultsTotally, 628 adults were invited to participate in the study. Of these, 320 joined, and 244 completed at least four 24HDRs. The median intakes in food groups, as well as the mean index scores and estimated nutrient intakes, were largely similar between the FFQ2020 and 24HDR recordings. The correlation coefficients between the two assessments ranged from 0.253 to 0.693 for food groups, 0.520 to 0.614 for diet indices, and 0.340 to 0.629 for energy and nutrients. Intra-class correlation coefficients indicated at least good reproducibility for intakes of food groups, diet index scores, and nutrients. Generally, Bland-Altman plots did not reveal any gross systematic disagreement between the two methods for any of the assessments. However, there were single observations located outside the upper or lower 95% confidence interval (CI) limits for the difference between FFQ2020 and the 24HDR recordings.ConclusionIn concert, the results suggest that the relative validity and reproducibility of FFQ2020 are acceptable for trend analyses and group comparisons in large-scale studies but also that extended reference periods would improve the precision of less frequently consumed foods.

Regional Climate Change and Drought Dynamics in Tunceli, Turkey: Insights from Drought Indices

Global warming and climate change are causing temperatures to rise, which is having a negative impact on water resources. Climate change is a worldwide problem that affects and will continue to affect the frequency and intensity of natural disasters in many regions of the world. Tunceli region in Turkey, which until 10 years ago was known as an environmentally friendly city with abundant water resources and frequent rainfall, is experiencing a decrease in precipitation during the snowy winter season. This situation has made the investigation of climate change impacts an important issue in the region. Therefore, effective climate change adaptation strategies need to be developed. To determine these strategies, in this study, we assessed long-term drought conditions using multiple drought indices such as Standardized Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Normal Precipitation Index (PNI), and Aridity Index (AI). The SPI and RDI analyses were performed in annual reference periods on a time scale of 3, 6, 9, and 12 months using temperature, precipitation, and evaporation data. Consequently, the SPI and RDI results were compared, and both indices show similar behavior in dry, wet, and normal seasons. Nevertheless, RDI shows less variation between different time scales, which is an advantage over SPI and is probably due to the inclusion of potential evapotranspiration in RDI. The variations in PNI between humid and dry sub-humid categorizations throughout the years, combined with the AI results, indicate that the Tunceli region predominantly experiences a climate ranging from dry sub-humid to semi-arid. This study could help decision-makers take effective measures to become more resilient to climate change in temperate climate regions and take important steps toward sustainable water resources management.

Early Access for Medicines in ITALY: The Case of Ruxolitinib for Patients with Graft-Versus-Host Disease.

After European Medicines Agency (EMA) approval, national pricing and reimbursement procedures are necessary to guarantee access to drugs, based on the willingness to pay and the recognition of therapeutic value. These can result in delays in drug availability for patients, even for those with important unfmet needs for whom it may be necessary and ethical to ensure access. The objective of this study was to evaluate the use of ruxolitinib for patients with graft-versus-host disease (GvHD) after EMA approval at the University Hospital of Catania. We analysed data about the use of ruxolitinib in patients with GvHD, describing their basic characteristics, their outcomes and the cost of the treatment. In the reference period, 24 ruxolitinib treatments were started according to the Summary of Product Characteristic. The average treatment duration was 10 months. Twenty patients showed a response, maintained over time, with no adverse reactions. The total expenditure amounts to EUR 963,424. The use of ruxolitinib in a real population confirms its role in an important therapeutic need. The quantification of costs requires a reflection on the sustainability of early access to medicines authorised by the EMA for serious diseases and in the absence of therapeutic alternatives.

Projections on the Spatiotemporal Bioclimatic Change over the Phytogeographical Regions of Greece by the Emberger Index

Unquestionably, the rapidly changing climate and, therefore, alterations in the associated bioclimate, constitute an alarming reality with implications for daily practice and natural capital management. This research displays the present and projected bioclimate evolution over Greece’s phytogeographical regions. For this purpose, ultrahigh-resolution computation results on the spatial distribution of the Emberger index’s Q2 classes of bioclimatic characterization are analyzed and illustrated for the first time. The assessments are performed over the reference period (1970–2000) and two future time frames (2021–2040; 2041–2060) under the RCP4.5 and RCP8.5 emission scenarios. By 2060 and under the extreme RCP8.5, intense xerothermic trends are demonstrated owing to the resulting significant spatial evolution mainly of the Arid–Hot, Semi-Arid–Very Hot, Semi-Arid–Hot, and Semi-Arid–Temperate Q2 classes, respectively, over the phytogeographical regions of Kiklades (up to 29% occupation), Kriti and Karpathos (up to 30%), West Aegean Islands (up to 26%), North East (up to 56%), and North Central (up to 31%). The RCP8.5 long-term period exhibits the strongest impacts over approximately the right half of the Greek territory, with the bioclimate appearing more dry–thermal in the future. In conclusion, the Emberger index provides an in-depth view of the Greek area’s bioclimatic regime and the potential alterations due to climate change per phytogeographical region.

Evolution of Coastal Environments under Inundation Scenarios Using an Oceanographic Model and Remote Sensing Data

A new methodology to map Italian coastal areas at risk of flooding is presented. This approach relies on detailed projections of the future sea level from a high-resolution, three-dimensional model of the Mediterranean Sea circulation, on the best available digital terrain model of the Italian coasts, and on the most advanced satellite-derived data of ground motion, provided by the European Ground Motion Service of Copernicus. To obtain a reliable understanding of coastal evolution, future sea level projections and estimates of the future vertical ground motion based on the currently available data were combined and spread over the digital terrain model, using a GIS-based approach specifically developed for this work. The coastal plains of Piombino-Follonica and Marina di Campo (Tuscany Region), Alghero-Fertilia (Sardinia), and Rome and Latina-Sabaudia (Lazio Region) were selected as test cases for the new approach. These coastal stretches are important for the ecosystems and the economic activities they host and are relatively stable areas from a geological point of view. Flood maps were constructed for these areas, for the reference periods 2010–2040, 2040–2070, and 2040–2099. Where possible, the new maps were compared with previous results, highlighting differences that are mainly due to the more refined and resolved sea-level projection and to the detailed Copernicus ground motion data. Coastal flooding was simulated by using the “bathtub” approach without considering the morphodynamic processes induced by waves and currents during the inundation process. The inundation zone was represented by the water level raised on a coastal DTM, selecting all vulnerable areas that were below the predicted new water level. Consequent risk was related to the exposed asset.

Evaluating the cost and operational context for national human papillomavirus (HPV) vaccine delivery in three regions of Ethiopia.

Cervical cancer is the second leading cause of cancer deaths among women in Ethiopia. Human papillomavirus (HPV) vaccination is a primary prevention method for cervical cancer and was introduced in Ethiopia in 2018. We conducted a cross-sectional, mixed-methods study to understand the operational context for the HPV vaccination program and the associated costs in three regions of Ethiopia. Operations research provided insights on the frequency and intensity with which HPV vaccination program activities were done, focusing on activities conducted to vaccinate the cohort receiving its first dose in October 2019 and second dose in January 2021. Microcosting was used to estimate the costs to the health system for these activities. Data collection using structured questionnaires was done at 60 health facilities, 17 woredas, and 9 zones/sub-cities that were randomly selected from three purposively selected regions and the national level. Financial costs (monetary outlays) and economic costs (financial costs plus opportunity costs of resource use) were estimated in 2019 US$. Health facilities delivered an average of 411 HPV vaccine doses during the reference period, ranging from a mean of 86 to 606 across the three regions. Aggregated across all levels of the health system, the estimated financial cost per dose across the pooled sample was $2.23, and the economic cost per dose was $7.19, excluding the cost of vaccines and supplies. There were regional variations in these estimates, with mean financial cost per dose ranging from $1.17 to $7.18 and mean economic cost per dose ranging from $5.80 to $18.13 across the three regions. Regional variations exist in the service volume, frequency, and intensity of conducting HPV vaccination activities, as reflected in the estimated costs of delivery. Data generated from this study can be used to inform program planning and budgeting, taking into account regional variations, for effective utilization of resources.

No improvement in AUDIT-C screening and brief intervention rates among wait-list controls following support of Aboriginal Community Controlled Health Services: evidence from a cluster randomised trial

BackgroundWhile Aboriginal and Torres Strait Islander Australians are less likely to drink any alcohol than other Australians, those who drink are more likely to experience adverse alcohol-related health consequences. In a previous study, providing Aboriginal Community Controlled Health Services (ACCHSs) with training and support increased the odds of clients receiving AUDIT-C alcohol screening. A follow-up study found that these results were maintained for at least two years, but there was large variability in the effectiveness of the intervention between services. In this study, we use services that previously received support as a comparison group to test whether training and support can improve alcohol screening and brief intervention rates among wait-list control ACCHSs.MethodsDesign: Cluster randomised trial using routinely collected health data. Setting: Australia. Cases: Twenty-two ACCHSs that see at least 1000 clients a year and use Communicare as their practice management software. Intervention and comparator: After initiating support, we compare changes in screening and brief intervention between wait-list control services and services that had previously received support. Measurement: Records of AUDIT-C screening and brief intervention activity in routinely collected data.ResultsDuring the reference period we observed 357,257 instances where one of 74,568 clients attended services at least once during a two-monthly data extraction period. Following the start of support, the odds of screening (OR = 0.94 [95% CI 0.67, 1.32], p = 0.74, \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B{F}_{10}$$\\end{document}\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\approx$$\\end{document} 0.002) and brief intervention (OR = 1.43 [95% CI 0.69, 2.95], p = 0.34, \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B{F}_{10}$$\\end{document}\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\approx$$\\end{document} 0.002) did not improve for the wait-list control group, relative to comparison services.ConclusionsWe did not replicate the finding that support and training improves AUDIT-C screening rates with wait-list control data. The benefits of support are likely context dependent. Coincidental policy changes may have sensitised services to the effects of support in the earlier phase of the study. Then the COVID-19 pandemic may have made services less open to change in this latest phase. Future efforts could include practice software prompts to alcohol screening and brief intervention, which are less reliant on individual staff time or resources.Trial registrationRetrospectively registered on 2018-11-21: ACTRN12618001892202.

Climate change triggered planktonic cyanobacterial blooms in a regulated temperate river

Harmful algae blooms are a rare phenomenon in rivers but seem to increase with climate change and river regulation. To understand the controlling factors of cyanobacteria blooms that occurred between 2017 and 2020 over long stretches (> 250 km) of the regulated Moselle River in Western Europe, we measured physico-chemical and biological variables and compared those with a long-term dataset (1997–2016). Cyanobacteria (Microcystis) dominated the phytoplankton community in the late summers of 2017–2020 (cyano-period) with up to 110 µg Chlorophyll-a/L, but had not been observed in the river in the previous 20 years. From June to September, the average discharge in the Moselle was reduced to 69–76% and water temperature was 0.9–1.8 °C higher compared to the reference period. Nitrogen (N), phosphorus (P) and silica (Si) declined since 1997, albeit total nutrient concentrations remained above limiting conditions in the study period. Cyanobacterial blooms correlated best with low discharge, high water temperature and low nitrate. We conclude that the recent cyanobacteria blooms have been caused by dry and warm weather resulting in low flow conditions and warm water temperature in the regulated Moselle. Under current climate projections, the Moselle may serve as an example for the future of regulated temperate rivers.

Response and resilience to drought in northern forests revealed by Sentinel-2

ABSTRACT Enhancing forest drought resilience is important for preserving ecosystem services in the face of climate change, but operational management methods for boreal forests aiming to preserve ecosystem services under drought are still largely missing. This study explores the use of satellite remote sensing to monitor vegetation stress phases related to drought progression and to quantify both short- and long-term impacts on forest growth. Data from the Sentinel-2 satellite mission were used to calculate the response of vegetation indices across six forest types, using the time period from 2015 to 2017 as a reference dataset. The percentual difference between the drought year of 2018 and the reference period was used to represent disturbance intensity and the system’s capability to resist it. Additionally, the recovery time was taken into consideration. Breakpoint detection with daily temporal resolution was used to quantify the response time of each forest type in relation to the onset date of meteorological drought. Results indicate that Sentinel-2 data can be used to monitor vegetation stress associated with drought progression and estimate the characteristics of forest resilience. High temporal resolution observations should be prioritized over annual maximum vegetation index values to determine the intensity of disturbance. Consistent severe impacts were observed in areas with limited soil moisture availability. The recovery time of forests took up to 4 years. Drought exposure during consecutive years could be especially damaging for species requiring a longer recovery time than a single growing season. Sentinel-2-based monitoring approach could benefit decision-support systems for forest management aiming to enhance drought resilience.

Improving CMIP6 Atmospheric River Precipitation Estimation by Cycle‐Consistent Generative Adversarial Networks

AbstractGiven the important role of Atmospheric River precipitation (ARP) in the global hydrological cycle, accurate representation of ARP is significant. However, general circulation models (GCMs) demonstrate bias in simulating ARP. The target of this study is to quantify the performance of ARP intensity/frequency for CMIP6 simulations, and further to improve ARP estimation of CMIP6 using Cycle‐Consistent Generative Adversarial Networks (CycleGAN) with highlighting the more accurate ARP features under the global warming background. The findings of this study are as follows: (a) although ARP intensity/frequency in reserved‐optimal CMIP6 overall reproduces the observation, it is still underestimated at the stronger Atmospheric river (AR) scales, particularly for the AR highly active mid‐latitude regions. (b) The CycleGAN‐based bias correction approach markedly diminishes the bias of the CMIP6 simulations within most of the AR scales among both global and the four AR highly active regions. Moreover, the performance of the ARP in AR highly active regions is significant improvement, which is mainly due to the reduction of the bias at the strongest scale. (c) Relative to reference period (1986–2005), ARP intensity/frequency at the strongest scale increase notably under 3°C warming level, with an average value of 373.3% in intensity and 415.9% in frequency for global and the four key regions before correction, and the value is 451.9% and 492.5% after bias correction. The results illustrate that CycleGAN can effectively improve the ARP simulations of GCMs, and an early warning implies that future strong extreme ARP should potentially surpass the current expected.