Annual Estimates Research Articles

Geospatial Assessment of Stormwater Harvesting Potential in Uganda’s Cattle Corridor

Freshwater scarcity remains a pressing global issue, exacerbated by inefficiencies in stormwater management during rainy seasons. Strategic stormwater harvesting offers a sustainable solution through runoff utilization for irrigation and livestock support. However, challenges such as limited farmer knowledge, difficult terrain, financial constraints, unpredictable weather, and scarce meteorological data hinder the accuracy of optimum stormwater harvesting sites. This study employs a GIS-based SCS-CN hydrological approach to address these issues, identifying suitable stormwater harvesting locations, estimating runoff volumes, and recommending site-specific storage structures. Using spatial datasets of daily rainfall (20 years), land use/land cover (LULC), digital elevation models (DEM), and soil data, the study evaluated 80 watersheds in Uganda’s cattle corridor. Annual runoff estimates within watersheds ranged from 62 million to 557 million m3, with 56 watersheds (70%) identified for multiple interventions such as farm ponds, check dams, and gully plugs. These structures are designed to enhance stormwater harvesting and utilization, improving water availability for livestock and crop production in a region characterized by water scarcity and erratic rainfall. The findings provide practical solutions for sustainable water management in drought-prone areas with limited meteorological data. This approach can be scaled to similar regions to enhance resilience in water-scarce landscapes. By offering actionable insights, this research supports farmers and water authorities in effectively allocating stormwater resources and implementing tailored harvesting strategies to bolster agriculture and livestock production in Uganda’s cattle corridor.

Long-term reconstructed vegetation index dataset in China from fused MODIS and Landsat data

The vegetation index is a key satellite-based variable used to monitor global vegetation distribution and growth. However, existing vegetation index datasets face limitations in achieving both high spatial and temporal resolution, restricting their application potential. This study revised a machine learning spatiotemporal fusion model (InENVI) to produce a high-resolution NDVI dataset with 8-day temporal and 30 m spatial resolution, covering China from 2001 to 2020. A total of 432,230 Landsat scenes were processed, enhancing data quality and accuracy. The dataset was validated using 255,000 samples across 6 geographical regions, showing strong performance in capturing spatiotemporal NDVI variations. Additionally, the dataset effectively addresses Scan Line Corrector-off stripes in Landsat 7 imagery. This dataset enables reliable annual NDVI estimates for China at a 30-m resolution and is available for reuse through an open data repository.

A Seasonal Fresh Tea Yield Estimation Method with Machine Learning Algorithms at Field Scale Integrating UAV RGB and Sentinel-2 Imagery

Traditional methods for estimating tea yield mainly rely on manual sampling surveys and empirical estimation, which are labor-intensive and time-consuming. Accurately estimating fresh tea production in different seasons has become a challenging task. It is possible to estimate the seasonal yield of tea at the field scale by using the spatial resolution of 10 m, 5-day revisit period and rich spectral information of Sentinel-2 imagery. This study integrated Sentinel-2 images and uncrewed aerial vehicle (UAV) RGB imagery to develop six regression models at the field scale, which were employed for the estimation of seasonal and annual fresh tea yields of the Yunlong Tea Cooperatives in Yixiang Town, Pu’er City, China. Firstly, we gathered fresh tea production data from 133 farmers in the cooperative over the past five years and obtained UAV RGB and Sentinel-2 imagery. Secondly, 23 spectral features were extracted from Sentinel-2 images. Based on the UAV images, the parcel of each farmer was positioned and three topographic features of slope, aspect, and elevation were extracted. Subsequently, these 26 features were screened using the random forest algorithm and Pearson correlation analysis. Thirdly, we applied six different regression algorithms to establish fresh tea yield models for each season and evaluated their estimation accuracy. The results showed that random forest regression models were the optimal choice for estimating spring and summer yields, with the spring model achieving an R2 value of 0.45, an RMSE of 40.38 kg/acre, and an rRMSE of 40.79%. Similarly, the summer model achieved an R2 value of 0.5, an RMSE of 78.46 kg/acre, and an rRMSE of 39.81%. For autumn and annual yield estimation, voting regression models demonstrated superior performance, with the autumn model achieving an R2 value of 0.42, an RMSE of 70.6 kg/acre, and an rRMSE of 39.77%, and the annual model attained an R2 value of 0.47, an RMSE of 168.7 kg/acre, and an rRMSE of 34.62%. This study provides a promising new method for estimating fresh tea yield in different seasons at the field scale.

P1253 Temporal Trend of Opioid Prescriptions Among Adults with Ulcerative Colitis: A Nationwide Cohort Study in Sweden 2008-2021

Abstract Background The rising opioid misuse and related mortality led the US government to declare opioid use as a public health emergency in 2017 [1]. Population-based studies on opioid use in Ulcerative Colitis (UC) are scarce [2]. The aim of this study was to describe the time trend of opioid use among adults with UC compared to the general population in Sweden. Methods We conducted a nationwide cohort study including individuals aged ≥18 years with a UC diagnosis, identified via two ICD-10 code K51 registrations in the National Patient Register. Each patient with UC was matched with up to 10 reference individuals without inflammatory bowel disease (IBD) by birth year, sex, calendar year, and place of residence. Observation started on January 1, 2008, at age 18, or the date when the UC diagnosis definition was fulfilled (whichever came last) and ended at emigration, death, or December 31, 2021 (whichever came first). Data on opioid dispensations were obtained from the Prescribed Drug Register. Opioid use per calendar year was defined as ≥1dispensed opioid prescription. We categorized codeine combinations, tramadol, and dextropropoxifen opioids as weak and oxycodone, morphine, hydromorphone, fentanyl, buprenorphine, tapentadol, and petidine as strong. Annual prevalence estimates of opioid use were calculated, and joinpoint analysis was performed to explore the trend and to estimate annual percent change (APC) of opioids. Results The cohort included 59,983 patients with UC (47.4% female) and 539,505 reference individuals. Cancer diagnoses within two years prior to the index date were observed in 1.1% of UC patients and 0.7% of reference individuals, while psychiatric disorders were identified in 3.8% and 3.6%, respectively. During the observation period, UC patients had a higher prevalence of opioid use compared to reference individuals. The Joinpoint analysis revealed three distinct periods (Figure 1): slightly increasing from 2008-2014, followed by decreasing trends during 2015-2018 (APC: -2.45) and 2019–2021 (APC: -5.20). As shown in Figure 2, the prevalence of any annual opioid use among UC patients declined from 15.5% in 2008 (compared to 9.5% for reference individuals) to 13.0% in 2021 (8.0% for reference individuals). Conversely, strong opioid use among UC patients increased from 3.0% to 9.0% over the study period, compared to a rise from 1.0% to 4.0% among reference individuals. Conclusion Opioid use among UC patients in Sweden showed a modestly decreasing trend since 2015 similar to that in the general population. The main limitation of this research was the inability to account for illegal opioid use, which is likely to underestimate the use of opioids among the reference group.

A Review on the Thermal Modeling Method for Molten Salt Receivers of Concentrating Solar Power Tower Plants

Concentrating solar power (CSP) tower plants using molten salt as the heat transfer fluid are currently the predominant technology used globally, and have experienced rapid development in recent years. The molten salt receiver, as the core piece of equipment for converting solar energy into thermal energy, directly determines the system efficiency, while its safety affects the plant’s operating hours. This paper reviews the details and operational status of commercial-scale CSP tower plants worldwide as of the end of 2023. It systematically summarizes the typical thermal models for mainstream tubular molten salt receivers by reviewing 37 models, including 11 three-dimensional (3D) numerical models, 8 two-dimensional (2D) semi-empirical models, and 18 one-dimensional (1D) semi-empirical models. By comparing and analyzing the key features of each model, the study concludes that detailed 3D numerical models are effective for monitoring overheating during operation, 2D semi-empirical models enable the rapid evaluation of receiver configurations, and 1D semi-empirical models support transient mass flow calculations and annual power generation estimations. Additionally, the paper outlines the current applications of receiver thermal models in system integration, particularly in combining CSP tower systems with other energy systems.

Tuberculosis healthcare service disruptions during the COVID-19 pandemic in Brazil, India and South Africa: A model-based analysis of country-level data.

Tuberculosis (TB) is the leading infectious disease cause of death worldwide. In recent years, stringent measures to contain the spread of SARS-CoV-2 have led to considerable disruptions of healthcare services for TB in many countries. The extent to which these measures have affected TB testing, treatment initiation and outcomes has not been comprehensively assessed. We aimed to estimate TB healthcare service disruptions occurring during the COVID-19 pandemic in Brazil, India, and South Africa. We obtained country-level TB programme and laboratory data and used autoregressive integrated moving average (ARIMA) time-series models to estimate healthcare service disruptions with respect to TB testing, treatment initiation, and treatment outcomes. We quantified disruptions as the percentage difference between TB indicator data observed during the COVID-19 pandemic compared with values for a hypothetical no-COVID scenario, predicted through forecasting of trends during a three-year pre-pandemic period. Annual estimates for 2020-2022 were derived from aggregated monthly data. We estimated that in 2020, the number of bacteriological tests conducted for TB diagnosis was 24.3% (95% uncertainty interval: 8.4%;36.6%) lower in Brazil, 27.8% (19.8;3 4.8%) lower in India, and 32.0% (28.9%;34.9%) lower in South Africa compared with values predicted for the no-COVID scenario. TB treatment initiations were 17.4% (13.9%;20.6%) lower than predicted in Brazil, 43.3% (39.8%;46.4%) in India, and 27.0% (15.2%;36.3%) in South Africa. Reductions in 2021 were less severe compared with 2020. The percentage deaths during TB treatment were 13.7% (8.1%; 19.7%) higher than predicted in Brazil, 1.7% (-8.9%;14.0%) in India and 21.8% (7.4%;39.2%) in South Africa. Our analysis suggests considerable disruptions of TB healthcare services occurred during the early phase of the COVID-19 pandemic in Brazil, India, and South Africa, with at least partial recovery in the following years. Sustained efforts to mitigate the detrimental impact of COVID-19 on TB healthcare services are needed.

The prevalence of HIV pre-exposure prophylaxis (HIV-PrEP) use and HIV-PrEP-to-need ratio in nine Canadian provinces, 2018-2021.

Measuring trends in HIV pre-exposure prophylaxis (HIV-PrEP) uptake is important to inform planning for prevention programs and policies. The HIV-PrEP-to-need ratio (PnR) is a construct used by public health organizations to explore disparities in the provision of HIV-PrEP across geographic areas and demographic categories (e.g., age, sex). This is a retrospective database review study using administrative pharmacy data, containing limited demographic information, from nine Canadian provinces. Annual estimates of persons taking HIV-PrEP and PnR were generated using data from the company IQVIA and the BC Centre for Excellence on HIV/AIDS. Data on new HIV diagnoses were obtained from the National HIV Surveillance System. The PnR was defined as the number of HIV-PrEP users divided by the number of new HIV diagnoses annually and is interpreted as the number of HIV-negative people using HIV-PrEP each year for every person newly diagnosed with HIV. In 2021, an estimated 23,644 individuals were prescribed HIV-PrEP, corresponding to an HIV-PrEP prevalence of 66.9 per 100,000 persons. This represents a 1.8-fold increase since 2018. The overall PnR was 16.8, meaning that for every person newly diagnosed with HIV, 17 HIV-negative individuals were taking HIV-PrEP. There were disparities between provinces (PnR range: 1.5/100,000-37.7/100,000) and between males and females (PnR 22.6 and 1.2, respectively). Females, individuals aged 0-19 years, and those in Manitoba, Saskatchewan and Prince Edward Island, had lower levels of HIV-PrEP use relative to epidemic need. In Canada, the use of HIV-PrEP increased from 2018 to 2021 and uptake varied by age, sex and province. HIV-PrEP-to-need ratio is a useful measure to assess uptake of HIV-PrEP as a prevention strategy and could be used to explore disparities in provision across provinces and available demographic categories. However, PnR could be improved with more information on key populations and other attributes, such as race/ethnicity, socioeconomic status and residence of city/rural area.

Annual biological variation and personalized reference intervals of 8 serum liver enzymes and 3 noninvasive tests in fatty liver patients.

The liver function tests and noninvasive tests (NITs) play important roles in the follow-up and monitoring of fatty liver disease (FLD). Our aim is to establish annual biological variation (BV) and personalized reference intervals (prRIs) of liver function tests for the first time in order to accurately assess the status and progress of FLD. 67 fatty liver patients who participated in regular physical examination once a year for six consecutive years, were enrolled. Based on these patients, we calculated annual BV and derived parameters, including reference change value (RCV), index of individuality (II), and total variation around the true homeostatic set point (TVset) which could further be used to derive prRI. We calculated the annual within-subject BV (CVI), within-person BV (CVP), RCV, II, TVset of 8 liver function tests and 3 NITs for fatty liver patients. CVI estimates of fatty liver patients for half of liver function tests were significantly lower than those of healthy people and these could lead to a lower RCV. IIs of all measurands were < 1.4 except for total bile acids (TBA). The mean of CVP is similar to the CVI; however, there is a significant heterogeneity in CVP among different subjects. Annual TVset estimates for 7 measurands were lower and prRI was also narrower in fatty liver patients than that of healthy people. Annual BV and their derived parameters based on fatty liver patients can provide an objective basis for the monitoring and follow-up of FLD, a global epidemic disease.

Economic Burden of Sickle Cell Disease in Saudi Arabia

ObjectiveThis study aimed to determine the direct and indirect costs of sickle cell disease (SCD) in Saudi Arabia. MethodsData were collected from 217 participants aged ≥18 years in the eastern region of Saudi Arabia, using a prevalence-based cost-of-illness approach. The Institute for Medical Technology Assessment Medical Consumption Questionnaire and Institute for Medical Technology Assessment Productivity Cost Questionnaire were used to assess costs. A multistage process was used, encompassing patient data collection over 3 months, cost calculation from clinic visits and drug prices, and extrapolation for annual estimates. ResultsThe study revealed substantial societal costs of SCD, with an average per-patient cost of SAR181 899 (US$48 506), covering healthcare and productivity losses. Healthcare costs, including hospitalization, informal care, and medication, averaged SAR80 306 (US$21 415). In addition, productivity costs, including unpaid work and presenteeism, averaged SAR101 594 (US$27 092). Obtaining higher levels of education, such as a diploma and BSc degree or higher, has been found to significantly decrease the costs associated with SCD (P = .016, P = .001). Furthermore, when comparing different employment statuses, students (B = −0.301, P = .058) were found to have marginally lower SCD costs, suggesting that their expenses were lower than those of individuals in other employment categories. The predictive model used in this study explained 11.2% of the variation in costs. ConclusionOur study highlights a significant economic burden of SCD in Saudi Arabia and highlights the need for targeted strategies to alleviate financial challenges and improve patient well-being.

Photo survey estimates of annual recruitment in eastern North American sea duck populations

AbstractSea duck (tribe mergini) populations have experienced significant declines in recent years, though underlying causes are poorly understood. Information on population demographic parameters may provide insight for wildlife managers seeking to maintain sustainable harvest. However, population monitoring capacity for sea ducks is limited relative to other waterfowl species because of their remote breeding distribution. The United States Fish and Wildlife Service organizes a Parts Collection Survey (PCS), which estimates recruitment in sea duck populations using age ratios (juveniles/adult), though estimates are biased because harvest vulnerability differs between age cohorts. We used a photo survey to calculate estimates of annual recruitment for long‐tailed duck (Clangula hyemalis), black scoter (Melanitta americana), surf scoter (M. perspicillata), and white‐winged scoter (M. deglandi; hereafter sea ducks) populations in eastern North America. Our team of surveyors collected photos of flighted sea ducks from shore and by boat in 11 states and 1 province from 15 October–15 December annually in 2019–2022. We classified photographed birds according to age and sex and calculated juvenile proportions of each species using a Bayesian binomial model. To compare photo survey estimates with PCS estimates, we used a paired t‐test organized by year. We found strong evidence that PCS estimates of juvenile proportions were greater than photo survey estimates for 3 sea duck species, indicating a consistent positive bias in PCS driven by harvest vulnerability. We also derived novel estimates of juvenile harvest vulnerability using the mean difference between within‐year estimates. Our work demonstrated the photo survey methodology produced annual recruitment estimates for 4 poorly monitored waterfowl populations with greater sample sizes and reduced systematic biases relative to existing methods; we recommend managers continue to adopt this approach in future years with additional consideration given for spatial representation and refinement of image classification procedures for long‐tailed duck estimates.

Toward spatio-temporal models to support national-scale forest carbon monitoring and reporting

Abstract National forest inventory (NFI) programs provide vital information on forest parameters’ status, trend, and change. Most NFI designs and estimation methods are tailored to estimate status over large areas but are not well suited to estimate trend and change, especially over small spatial areas and/or over short time periods (e.g. annual estimates). Fine-scale space-time indexed estimates are critical to a variety of environmental, ecological, and economic monitoring efforts. In the United States, for example, NFI data are used to estimate forest carbon status, trend, and change to support national, state, and local user group needs. Increasingly, these users seek finer spatial and temporal scale estimates to evaluate existing land use policies and management practices, and inform future activities. Here we propose a spatio-temporal Bayesian small area estimation modeling framework that delivers statistically valid estimates with complete uncertainty quantification for status, trend, and change. The framework accommodates a variety of space and time dependency structures, and we detail model configurations for different settings. The proposed framework is used to quantify forest carbon dynamics at an annual county-level across a 14 year period for the contiguous United States. Also, using an analysis of simulated data, we compare the proposed framework with traditional NFI estimators and offer computationally efficient algorithms, software, and data to reproduce results for benchmarking.

SEISMICITY of the TERRITORY of BELARUS in 2020

A review of seismicity in the territory of Belarus within 2020 based on the data of 17 digital stations is presented. 65 seismic events with Kd=5.3–8.5 were recorded in 2020. All the earthquakes are confined to the southern part of the monitored zone, the Soligorsk mining region included. A comparison of the parameters NΣ and ΣE for 2020 with the long-term average annual estimates showed that the level of the seismic energy released in 2020 remained rather low, while the number of events recorded in the period under consideration was higher than the background values. No any stable correlation between the energy released and the number of seismic events was observed during the long-term period of 1983–2020.

Epidemiological Analysis of Upper Extremity Amputations From Lawn Mower-Related Injuries.

Lawn mower-related injuries (LMIs) represent a complex spectrum of pathology with significant public health ramifications. The purpose of this study was to analyze the epidemiological factors associated with lawn mower upper extremity amputations. The National Electronic Injury Surveillance System (NEISS) database was queried from 2014 to 2023. National case estimates were established for upper extremity amputation events secondary to lawn mowers using diagnostic and injury-specific coding parameters. Documented cases from NEISS-participating hospitals were evaluated and injury data surrounding individual amputation events were analyzed. An estimated 17 509 upper extremity amputations occurred from 2014 to 2023 secondary to LMI in the United States. Annual case estimates and incidence rates remained relatively uniform across the 10-year study period. Most injuries were estimated to occur in 50- to 59-year-old patients. Case record review from pooled participating NEISS hospitals yielded 469 cases of upper extremity amputation directly associated with LMI from 2014 to 2023. Ninety-one percent of cases occurred in men, and most events involved the amputation of a finger (97%). Most cases of lawn mower-associated injury involved the amputation of the middle digit (41.6%) in isolation (64% of cases involved amputation of 1 digit). Despite advances in product safety and consumer education, the estimated frequency and incidence rate of upper extremity amputations secondary to LMI has remained largely unchanged over the past 10 years. When these events did occur, 40- to 60-year-old men were most often involved, most commonly leading to amputation of the third finger in isolation.

Hospitalization due to pneumococcal disease in the Unified Health System in Brazil: A retrospective analysis of administrative data

IntroductionCommunity-Acquired Pneumonia (CAP) caused by pneumococcus and Invasive Pneumococcal Disease (IPD) pose a substantial economic burden on health systems. The objective of the present study is to explore hospitalization costs of pneumococcal disease in the public health system in Brazil, the Unified Health System. MethodsRetrospective analysis of administrative data on hospitalized cases of pneumococcal disease from January 2019 to July 2023. Hospitalization cases recorded with ICD-10 codes of CAP due to S. pneumoniae and IPD were retrieved from DATASUS, the inpatient information system of the Unified Health System in Brazil. Costs were converted to US dollars by Using Purchasing Power Parity (USD-PPP). Absolute number of hospitalizations, costs of hospitalizations and healthcare resource utilization were presented descriptively. The annual cost estimate was calculated. Differences in costs by type of clinical presentation and age group were assessed. Factors associated with higher costs were explored by multiple linear regression models. ResultsA total of 22,498 hospitalization episodes were analyzed. Total cost of hospitalizations was USD-PPP 13,958,959 (BRL 34,659,578) with an annual mean estimate of USD-PPP 3,045,591 (BRL 7,562,090). Cost per hospitalization episode was significantly higher for meningitis, followed by septicemia, CAP and arthritis, with median values ranging from USD-PPP 190.93 to 615.14 (BRL 476.20 to 1529.02). (Kruskal-Wallis χ2 = 6473, df = 3, p-value < 0.0001). Costs were significantly higher among individuals aged 60-years and older. (Kruskal-Wallis test; χ2 = 773.53; df = 2, p-value < 0.0001). There were differences in age at hospitalization, length of stay, and ICU utilization among types of clinical presentations. ConclusionsOur findings reveal the economic burden associated with pneumococcal disease in the Unified Health System in Brazil. Hospitalization costs were higher for cases of meningitis and among individuals aged 60-years and above.

Nitrogen isotopes reveal high NOx emissions from arid agricultural soils in the Salton Sea Air Basin

Air quality management commonly aims to mitigate nitrogen oxide (NOx) emissions from combustion, reducing ozone (O3) and particulate matter (PM) pollution. Despite such ongoing efforts, regulations have recently proven ineffective in rural areas like the Salton Sea Air Basin of Southern California, which routinely violates O3 and PM air quality standards. With over $2 billion in annual agricultural sales and low population density, air quality in the region is likely influenced by the year-round farming activity. We conducted a source apportionment of NOx (an important precursor to both O3 and PM) using nitrogen stable isotopes of ambient NO2, which revealed a significant contribution from soil-emitted NOx to the regional budget. The soil source strength was estimated based on the mean δ15N-NOx from each emission category in the California Air Resources Board’s NOx inventory. Our annual average soil emission estimate for the air basin was 11.4 ± 4 tons/d, representing ~ 30% of the extant NOx inventory, 10× larger than the state’s inventory for soil emissions. Unconstrained environmental factors such as nutrient availability, soil moisture, and temperature have a first-order impact on soil NOx production in this agriculturally intensive region, with fertilization and irrigation practices likely driving most of the emissions variability. Without spatially and temporally accurate data on fertilizer application rates and irrigation schedules, it is difficult to determine the direct impacts that these variations have on our observations. Nevertheless, comparative analysis with previous studies indicates that soil NOx emissions in the Imperial Valley are likely underrepresented in current inventories, highlighting the need for more detailed and localized observational data to constrain the sizeable and variable emissions from these arid, agricultural soils.

Spatio-Temporal Changes in Erosion-Accumulation Processes on a Small Watershed in the Northern Part of the Central Russian Upland

First time comprehensive studies of soil erosion were carried out in a 42-hectare catchment area (near the Lomovets, Orel region) in the zone of Luvic Phaeozems with erosion resistance is significantly lower than that of Chernozems. Analysis of archival and historical cartographic materials showed that the duration of plowing of the catchment is 200 ± 10 years. The rates of soil erosion and accumulation over the entire plowing period, post Chernobyl period, last 50 ± 25 years and single erosion event (which occurred on May 31, 2022) were determined based on the use of field methods (soil-morphological, radiocesium, rain rills method, detailed survey using drone) and WaTEM/SEDEM erosion model calculation. The estimates of soil losses and accumulation indicate significant fluctuations in the rates of erosion-accumulative processes over the past 200 years, which are mainly due to the conditions of the formation of melt runoff, the repeatability and distribution of runoff-forming heavy rain within the warm season, the set of crops sown, the frequency and methods of tillage, changes in field boundaries. The average annual estimates of soil erosion for the agricultural period are higher than those for the post-Chernobyl period, since the rates of soil erosion have decreased in the last three decades. Estimates of soil losses using the WaTEM/SEDEM model are generally comparable with the results of determining soil losses based on the soil-morphological method, provided that the redistribution of sediment to the lower boundaries of arable land is taken into account. The spatial structure of a single erosive event turned out to be largely close to the spatial structure of the location of the areas of eroded and aggradational soils formed during the entire agricultural period.

Downscaling precipitation over High-mountain Asia using multi-fidelity Gaussian processes: improved estimates from ERA5

Abstract. The rivers of High-mountain Asia provide freshwater to around 1.9 billion people. However, precipitation, the main driver of river flow, is still poorly understood due to limited in situ measurements in this area. Existing tools to interpolate these measurements or downscale and bias-correct precipitation models have several limitations. To overcome these challenges, this paper uses a probabilistic machine learning approach called multi-fidelity Gaussian processes (MFGPs) to downscale the fifth ECMWF climate reanalysis (ERA5). The method is first validated by downscaling ERA5 precipitation data over data-rich Europe and then data-sparse upper Beas and Sutlej river basins in the Himalayas. We find that MFGPs are simpler to implement and more applicable to smaller datasets than other state-of-the-art machine learning methods. MFGPs are also able to quantify and narrow the uncertainty associated with the precipitation estimates, which is especially needed over ungauged areas and can be used to estimate the likelihood of extreme events that lead to floods or droughts. Over the upper Beas and Sutlej river basins, the precipitation estimates from the MFGP model are similar to or more accurate than available gridded precipitation products (APHRODITE, TRMM, CRU TS, and bias-corrected WRF). The MFGP model and APHRODITE annual mean precipitation estimates generally agree with each other for this region, with the MFGP model predicting slightly higher average precipitation and variance. However, more significant spatial deviations between the MFGP model and APHRODITE over this region appear during the summer monsoon. The MFGP model also presents a more effective resolution, generating more structure at finer spatial scales than ERA5 and APHRODITE. MFGP precipitation estimates for the upper Beas and Sutlej basins between 1980 and 2012 at a 0.0625° resolution (approx. 7 km) are jointly published with this paper.

Burden of Respiratory Syncytial Virus–Associated Hospitalizations in US Adults, October 2016 to September 2023

Respiratory syncytial virus (RSV) infection can cause severe illness in adults. However, there is considerable uncertainty in the burden of RSV-associated hospitalizations among adults prior to RSV vaccine introduction. To describe the demographic characteristics of adults hospitalized with laboratory-confirmed RSV and to estimate annual rates and numbers of RSV-associated hospitalizations, intensive care unit (ICU) admissions, and in-hospital deaths. This cross-sectional study used data from the RSV Hospitalization Surveillance Network (RSV-NET), a population-based surveillance platform that captures RSV-associated hospitalizations in 58 counties in 12 states, covering approximately 8% of the US population. The study period spanned 7 surveillance seasons from 2016-2017 through 2022-2023. Included cases from RSV-NET were nonpregnant hospitalized adults aged 18 years or older residing in the surveillance catchment area and with a positive RSV test result. Laboratory-confirmed RSV-associated hospitalization, defined as a positive RSV test result within 14 days before or during hospitalization. Hospitalization rates per 100 000 adult population, stratified by age group. After adjusting for test sensitivity and undertesting for RSV in adults hospitalized with acute respiratory illnesses, rates were extrapolated to the US population to estimate annual numbers of RSV-associated hospitalizations. Clinical outcome data were used to estimate RSV-associated ICU admissions and in-hospital deaths. From the 2016 to 2017 through the 2022 to 2023 RSV seasons, there were 16 575 RSV-associated hospitalizations in adults (median [IQR] age, 70 [58-81] years; 9641 females [58.2%]). Excluding the 2020 to 2021 and the 2021 to 2022 seasons, when the COVID-19 pandemic affected RSV circulation, hospitalization rates ranged from 48.9 (95% CI, 33.4-91.5) per 100 000 adults in 2016 to 2017 to 76.2 (95% CI, 55.2-122.7) per 100 000 adults in 2017 to 2018. Rates were lowest among adults aged 18 to 49 years (8.6 [95% CI, 5.7-16.8] per 100 000 adults in 2016-2017 to 13.1 [95% CI, 11.0-16.1] per 100 000 adults in 2022-2023) and highest among adults 75 years or older (244.7 [95% CI, 207.9-297.3] per 100 000 adults in 2022-2023 to 411.4 [95% CI, 292.1-695.4] per 100 000 adults in 2017-2018). Annual hospitalization estimates ranged from 123 000 (95% CI, 84 000-230 000) in 2016 to 2017 to 193 000 (95% CI, 140 000-311 000) in 2017 to 2018. Annual ICU admission estimates ranged from 24 400 (95% CI, 16 700-44 800) to 34 900 (95% CI, 25 500-55 600) for the same seasons. Estimated annual in-hospital deaths ranged from 4680 (95% CI, 3570-6820) in 2018 to 2019 to 8620 (95% CI, 6220-14 090) in 2017 to 2018. Adults 75 years or older accounted for 45.6% (range, 43.1%-48.8%) of all RSV-associated hospitalizations, 38.6% (range, 36.7%-41.0%) of all ICU admissions, and 58.7% (range, 51.9%-67.1%) of all in-hospital deaths. In this cross-sectional study of adults hospitalized with RSV before the 2023 introduction of RSV vaccines, RSV was associated with substantial burden of hospitalizations, ICU admissions, and in-hospital deaths in adults, with the highest rates occurring in adults 75 years or older. Increasing RSV vaccination of older adults has the potential to reduce associated hospitalizations and severe clinical outcomes.

Deepening Root Inputs: Potential Soil Carbon Accrual From Breeding for Deeper Rooted Maize.

Breeding annual crops for enhanced root depth and biomass is considered a promising intervention to accrue soil organic carbon (SOC) in croplands, with benefits for climate change mitigation and soil health. In annual crops, genetic technology (seed) is replaced every year as part of a farmer's fixed costs, making breeding solutions to climate change more scalable and affordable than management approaches. However, mechanistic understanding and quantitative estimates of SOC accrual potentials from crops with enhanced root phenotypes are lacking. Maize is the highest acreage and yielding crop in the US, characterized by relatively low root biomass confined to the topsoil, making it a suitable candidate for improvement that could be rapidly scaled. We ran a 2-year field experiment to quantify the formation and composition (i.e., particulate (POM), coarse and fine mineral-associated organic matter (chaOM and MAOM, respectively) of new SOC to a depth of 90 cm from the decomposition of isotopically labeled maize roots and exudates. Additionally, we used the process-based MEMS 2 model to simulate the SOC accrual potential of maize root ideotypes enhanced to either shift root production to deeper depths or increase root biomass allocation, assuming no change in overall productivity. In our field experiment, maize root decomposition preferentially formed POM, with doubled efficiency below 50 cm, while root exudates preferentially formed MAOM. Modeling showed that shifting root inputs to deeper layer or increasing allocation to roots resulted in a deterministic increase in SOC, ranging from 0.05 to 0.15 Mg C ha-1 per year, which are at the low end of the range of published SOC per hectare annual accrual estimates from adoption of a variety of crop management practices. Our analysis indicates that for maize, breeding for increasing root inputs as a strategy for SOC accrual has limited impact on a per-hectare basis, although given that globally maize is produced on hundreds of millions of hectares each year, there is potential for this technology and its effect to scale. For maize-soy system that dominates US acres, changes in the overall cropping system are needed for sizable greenhouse gas reductions and SOC accrual. This study demonstrated a modeling and experimental framework to quantify and forecast SOC changes created by changing crop root inputs.

Factors related to sepsis in critical care setting in Rwanda selected referral hospital

BACKGROUND Sepsis is described as potentially fatal organ failure induced by an unbalanced host response to infection. Annual estimates put the number of sepsis cases at over 19 million. The number of sepsis-related deaths is estimated to reach 5 million, with the vast majority happening in LMICs. However, such information is required to increase awareness of sepsis's global impact, especially in developing countries like Rwanda. The study aimed to evaluate the factors related to sepsis in a critical care setting in Rwanda's selected referral hospital. METHODOLOGY A cross-sectional study design with a quantitative approach was conducted and simple random sampling was used. Files of 191 study participants and a structured questionnaire were used in data collection, bivariate and multivariate logistic regression in SPSS version 21 was used in data analysis, and results were presented in tables. RESULTS The prevalence of sepsis was 40.3%. By plotting bivariate analysis the results showed that sepsis was significantly associated with the following variables; self-employed as an occupation with (OR=0.216, 95%CI:0.047-0.987) p 0.48 taking reference for unemployed; pneumonia with sepsis at (OR=1.993, 95%CI:0.657-6.043) p 0.023, systemic infection (OR=0.329, 95%CI:0.104-1.044) p 0.059; other procedure with (OR=4.735,95%CI:1.509- 14.855); procedure timeframe not mentioned with (OR=0.123,95%CI:0.027-0.553) p 0.032; hospitalized 15 days and more with OR=6.697 (95%CI:0.809-59.863) and p 0.032. CONCLUSION The prevalence of sepsis was 40.3% and factors related to sepsis include; occupation, having pneumonia, systemic infection, timeframe for carrying out the procedure, and patient being hospitalized for 15 days and more.