Mann-Kendall Trend Test Research Articles

Could it be monkeypox? Use of an AI-based epidemic early warning system to monitor rash and fever illness

ObjectivesThe EPIWATCH artificial intelligence (AI) system scans open-source data using automated technology and can be used to detect early warnings of infectious disease outbreaks. In May 2022, a multicountry outbreak of Mpox in non-endemic countries was confirmed by the World Health Organization. This study aimed to identify signals of fever and rash-like illness using EPIWATCH and, if detected, determine if they represented potential Mpox outbreaks. Study designThe EPIWATCH AI system was used to detect global signals for syndromes of rash and fever that may have represented a missed diagnosis of Mpox from 1 month prior to the initial case confirmation in the United Kingdom (7 May 2022) to 2 months following. MethodsArticles were extracted from EPIWATCH and underwent review. A descriptive epidemiologic analysis was conducted to identify reports pertaining to each rash-like illness, locations of each outbreak and report publication dates for the entries from 2022, with 2021 as a control surveillance period. ResultsReports of rash-like illnesses in 2022 between 1 April and 11 July (n = 656 reports) were higher than in the same period in 2021 (n = 75 reports). The data showed an increase in reports from July 2021 to July 2022, and the Mann–Kendall trend test showed a significant upward trend (P = 0.015). The most frequently reported illness was hand-foot-and-mouth disease, and the country with the most reports was India. ConclusionsVast open-source data can be parsed using AI in systems such as EPIWATCH to assist in the early detection of disease outbreaks and monitor global trends.

Evaluating climate change impact on the hydrology of Kessie Watershed, Upper Blue Nile Basin, Ethiopia

Climate change affects ecosystems, agriculture, human health, forestry, and water resource availability. This study is mainly aimed at assessing the climate change effect on the water resources of the Kessie Watershed in the Upper Blue Nile Basin, Ethiopia. The updated Coupled Model Intercomparison Project Phase 6 (CMIP-6) data outputs were used. The three climate model outputs: ACESS_ESM1-5, FGOALS_g3, and GFDL_ESM4 with two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5) scenarios, were used. The climate model output rainfall and temperature data were downscaled to the station level through bias correction. The catchment hydrology was represented by the SWAT—Soil and Water Assessment Tool—through calibration and validation. Future temperatures and rainfall change were evaluated by the Mann–Kendall trend test and Sen’s slope estimator. Future climate change trend analysis and streamflow simulation were done on two time horizons: the 2050s (2041–2070) and the 2080s (2071–2100). The baseline streamflow data (1985–2014) were used as a reference. The global climate model projection data indicated mean annual precipitation and temperatures show a slight increase for the future in both scenarios for all climate model outputs. According to the SSP2-4.5 and SSP5-8.5 scenarios, respectively, mean annual precipitation is expected to increase by 5% and 4.89% in the 2050s and 10.13% and 6.8% in the 2080s based on ACCESS_ESM1-5; 4.7% and 3.8% in the 2050s and 4.3% and 4.84% in the 2080s based on FGOALS_g3; and 4.67% and 3.81% in the 2050s and 4.67% and 3.81% based on GFDL_ESM4 models data. Yearly average maximum temperature may increase by 3.62 °C and 1.87 °C in the 2050s and 3.31 °C and 2.99 °C in the 2080s based on ACCESS ESM1-5, 1.76 °C and 1.25 °C in the 2050s and 3.44 °C and 2.61 °C in the 2080s based on FGOALS-g3, and 2.15 °C and 3.83 °C in the 2050s and 1.37 °C and 2.66 °C in the 2080s based on GFDL-ESM4 model data. Similarly, the mean annual minimum temperature is also expected to increase by 2.73 °C and 1.90 °C in the 2050s and 5.63 °C and 4.52 °C in the 2080s based on ACCESS ESM1-5, 3.04 °C and 2.43 °C in the 2050s and 3.55 °C and 4.36 °C in the 2080s based on FGOALS-g3, and 2.31 °C and 3.29 °C in the 2050s, and 3.16 °C and 3.87 °C in the 2080s based on GFDL-ESM4 model data. The streamflow is also expected to increase. In the 2050s, simulated annual streamflow is expected to increase from 12.1 to 21.8% and 9.8 to 15.4% in SSP2-4.5 and SSP5-8.5, respectively, whereas in the 2080s, the change is expected to increase from 15.14 to 24.08% and 13.08 to 41% in SSP2-4.5 and SSP5-8.5, respectively. Future water resource potential of the case study watershed seems able to support irrigation and other projects.

Artificial intelligence for improving Nitrogen Dioxide forecasting of Abu Dhabi environment agency ground-based stations

Nitrogen Dioxide (NO_{2}) is a common air pollutant associated with several adverse health problems such as pediatric asthma, cardiovascular mortality,and respiratory mortality. Due to the urgent society’s need to reduce pollutant concentration, several scientific efforts have been allocated to understand pollutant patterns and predict pollutants’ future concentrations using machine learning and deep learning techniques. The latter techniques have recently gained much attention due it’s capability to tackle complex and challenging problems in computer vision, natural language processing, etc. In the NO_{2} context, there is still a research gap in adopting those advanced methods to predict the concentration of pollutants. This study fills in the gap by comparing the performance of several state-of-the-art artificial intelligence models that haven’t been adopted in this context yet. The models were trained using time series cross-validation on a rolling base and tested across different periods using NO_{2} data from 20 monitoring ground-based stations collected by Environment Agency- Abu Dhabi, United Arab Emirates. Using the seasonal Mann-Kendall trend test and Sen’s slope estimator, we further explored and investigated the pollutants trends across the different stations. This study is the first comprehensive study that reported the temporal characteristic of NO_{2} across seven environmental assessment points and compared the performance of the state-of-the-art deep learning models for predicting the pollutants’ future concentration. Our results reveal a difference in the pollutants concentrations level due to the geographic location of the different stations, with a statistically significant decrease in the NO_{2} annual trend for the majority of the stations. Overall, NO_{2} concentrations exhibit a similar daily and weekly pattern across the different stations, with an increase in the pollutants level during the early morning and the first working day. Comparing the state-of-the-art model performance transformer model demonstrate the superiority of ( MAE:0.04 (± 0.04),MSE:0.06 (± 0.04), RMSE:0.001 (± 0.01), R^{2}: 0.98 (± 0.05)), compared with LSTM (MAE:0.26 (± 0.19), MSE:0.31 (± 0.21), RMSE:0.14 (± 0.17), R^{2}: 0.56 (± 0.33)), InceptionTime (MAE: 0.19 (± 0.18), MSE: 0.22 (± 0.18), RMSE:0.08 (± 0.13), R^{2}:0.38 (± 1.35) ), ResNet (MAE:0.24 (± 0.16), MSE:0.28 (± 0.16), RMSE:0.11 (± 0.12), R^{2}:0.35 (± 1.19) ), XceptionTime (MAE:0.7 (± 0.55), MSE:0.79 (± 0.54), RMSE:0.91 (± 1.06), R^{2}: -4.83 (± 9.38) ), and MiniRocket (MAE:0.21 (± 0.07), MSE:0.26 (± 0.08), RMSE:0.07 (± 0.04), R^{2}: 0.65 (± 0.28) ) to tackle this challenge. The transformer model is a powerful model for improving the accurate forecast of the NO_{2} levels and could strengthen the current monitoring system to control and manage the air quality in the region.

Genetic counseling and testing for epithelial ovarian cancer in a diverse patient population.

e17563 Background: According to the current American Society of Clinical Oncology (ASCO) guidelines, “all women diagnosed with epithelial ovarian cancer should be offered germline genetic testing for BRCA1, BRCA2, and other ovarian cancer susceptibility genes, irrespective of their clinical features or family history”. Test results have implications for surveillance, familial testing, and treatment. We investigated how genetic counseling and testing rates at a New York City tertiary care center with a large minority population compared with national rates, and if any disparities existed. Methods: This is a retrospective cohort study of patients with newly diagnosed epithelial ovarian, fallopian tube, peritoneal cancer between January 2014 and June 2022. Data were obtained from pathology and chemotherapy databases at the NewYork-Presbyterian Brooklyn Methodist Hospital. Variables including age, race, ethnicity, BMI, insurance, language, family history of cancer, date of diagnosis, stage, and genetic counseling/testing status were manually extracted. Descriptive statistics were used to characterize the variables of interest. Chi-square/Fisher’s exact tests were used to examine the association between genetic counseling/testing and categorical variables. Wilcoxon rank-sum/t-tests were used for association between continuous factors. The Mann-Kendall trend test was used to assess year-to-year trends. Results: 144 patients were identified. Mean age at diagnosis was 63 years (SD:13). This diverse cohort included 51% white, 36% black, 3.5% Asian, 9% other/unknown; 9% were of Hispanic ethnicity and 26% were non-English speaking. 104 (72%) patients received genetic counseling and 99 (69%) received subsequent genetic testing. 95% of those that underwent genetic counseling underwent subsequent testing. The genetic counseling and testing rates were not influenced by race, ethnicity, language, insurance type, BMI, family history of cancer. It was associated with significant difference by cancer stage (p < 0.01). There was a significant upward trend of proportion of patients that received genetic counseling from 47% in 2015 to 100% in 2022 (p < 0.01). Most genetic counseling was performed by a gynecologic oncologist (93%) as opposed to a genetic counselor (6.7%). Overall, 12 (8.3%) patients were BRCA+. Conclusions: Genetic counseling and testing rates within this diverse study population proved to be at least twice as high as the national average of 10-30%, with an increasing year-to-year trend. There were no disparities observed, in contrast to previously published data. BRCA mutation detection was in line with established prevalence within ovarian cancer, indicating adequate screening. Concentrated efforts on behalf of oncologists ensures excellent access to testing.

Temperature Forecasting as a Means of Mitigating Climate Change and Its Effects: A Case Study of Mali

Temperature forecasts and trend analyzes were carried out for several locations in Mali as an important tool for warning of potentially threatening weather events such as severe heat waves, storms, droughts and floods, which could pose a great risk to humans and their environment. Five locations (Segou, Sikasso, Kayes, Gao and Taoudenni) across Mali (170 00’N – 40 00’W) were chosen for this research work. Satellite data of annual temperature obtained from the European Centre for Medium-Range Weather Forecast (ECMWF) database for 35 years (1985-2019) was used for this work. The Mann-Kendall trend test was carried out for various locations to observe and study the trend. Four Models including Auto Regressive and Integrated Moving Average (ARIMA), Exponential smoothening (ETS), TBATS (Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components) and the linear model were employed to forecast average temperature for 10 years for all the locations. The model that produces the best forecast at the 95% confidence level is expected to have the lowest Root Mean Square Error (RMSE) value. The results showed that no significant trends were recorded at the considered locations. The linear model produced the best forecast for Segou, Kayes and Taoudenni, while the TBATS model produced the best forecast for Gao and the ARIMA model produced the best forecast for Sikasso.

Lynch screening and genetic testing in endometrial cancer in a diverse population.

e17619 Background: Lynch syndrome (LS) accounts for most of the inherited endometrial cancers. Universal screening of endometrial tumors for defects in DNA mismatch repair (MMR) is recommended using immunohistochemistry (IHC) to identify which patients qualify for genetic counseling and testing. We report Lynch screening and genetic testing rates at a New York City tertiary care center with a large minority population, while investigating any potential disparities. Methods: This is a retrospective cohort study of patients with newly diagnosed endometrial cancer between January 2014 and June 2022. Data were obtained from pathology and chemotherapy databases at the NewYork-Presbyterian Brooklyn Methodist Hospital. Variables including age, race, ethnicity, BMI, insurance, language, family history of cancer, date of diagnosis, stage, MMR IHC, and genetic counseling/testing status were manually extracted. Descriptive statistics were used. Chi-square/Fisher’s exact tests were used to examine the association between genetic counseling/testing and categorical variables. Wilcoxon rank-sum/t-tests were used for continuous factors. The Mann-Kendall trend test was used to determine the significance of time trends. Results: 373 patients were identified. 45% identified as white, 42% black, 1.3% Asian, 12% other/unknown; 8.3% were of Hispanic ethnicity and 18% were non-English speaking. Mean age at diagnosis was 66 years (SD:10). 207 (55%) patients were screened using MMR IHC. 82 (40%) of these patients had MMR deficiencies on IHC. Of these, 63 (77%) received genetic counseling. 62 (98%) of those counseled subsequently underwent genetic testing, and ultimately 7 (11%) were diagnosed with LS. The overall rate of LS detected was 1.9% in the study population. The rate of MMR IHC testing has been increasing, reaching 95% in 2021 and 100% in 2022. It was associated with significant differences in mean age at diagnosis (p < 0.01) and insurance type (p = 0.04). 45% of patients that received MMR IHC had private insurance, compared to 34% of patients that did not. The rate was not influenced by race, language, BMI, family history of cancer, or stage. The proportion of patients that received genetic counseling and testing for endometrial cancer also showed a significant upwards trend over time (p < 0.01). Genetic counseling and testing rates were significantly different by ethnicity (p = 0.03), with only 3.0% of patients receiving genetic counseling/testing identifying as Hispanic. 98% of genetic counseling was performed by a gynecologic oncologist, as opposed to a genetic counselor. Conclusions: There were no disparities in access to initial IHC screening in this diverse patient population, however more work must be done to reach all ethnicities for genetic counseling and testing. The rate of LS detected was less than the known prevalence in endometrial cancer, possibly indicating demographic differences or gaps in screening.

An 8-year retrospective study of fixed prosthodontics clinical unit completions in a postgraduate prosthodontics program.

The range of aesthetic fixed prosthodontics materials utilizing digital manufacturing techniques has expanded in recent years ostensibly replacing traditional laboratory techniques and materials. This retrospective study conducted over eight consecutive years aimed to analyze the types of laboratory fabricated fixed prosthodontics clinical units completed in a postgraduate prosthodontics specialist training program and determine meaningful trends. The logbooks of eight postgraduate prosthodontics completions from 2014 to 2021 were reviewed and the different types of laboratory fabricated fixed prosthodontics units and total number of fixed prosthodontics units completed were recorded. The data was categorized and presented in tabulated and chart form using Microsoft Excel software (version 2016). Paired t-tests and Mann-Kendall trend tests were performed to analyze for statistical significance between the different restoration types across the program completions. Porcelain bonded to metal (PBM) crowns represented 42.05% of all fixed prosthodontics units completed over all study years followed by all-ceramic crowns (ACC) (18.14%) and full gold crowns (FGC) (10.70%). Jointly, PBM, ACC and FGC's encompassed 70.88% of all fixed prosthodontics units. Over the 8-year study period, there were observed trends of reduced use of PBM's, increased use of ACC's, statistically significant reduced use of FGC's (p = 0.035) and a statistically significant difference in the use of complete and partial coverage restorations (p < 0.001). PBM crowns were the dominant laboratory fabricated fixed prosthodontic clinical unit across postgraduate prosthodontics program completions. The trend in later years indicating ACC as the dominant crown type warrants further investigation.

Intra-gendered perceptions and adoption of climate-smart agriculture: Evidence from smallholder farmers in the Upper East Region of Ghana

Climate-smart agriculture (CSA) remains a key strategy for sustaining agricultural systems and achieving food security and nutrition. Despite this, uncertainty remains on how intra-gendered dynamics influence its adoption in dryland farming systems. This study implements both quantitative and qualitative approaches including household surveys, key informant interviews, and focus group discussions to explore how intra-gender dynamics shape the perceptions and adoption of climate-smart agriculture in three selected communities (Katanga, Dakio, and Zonno) in the Bolgatanga East District of the Upper East Region of Ghana. Specifically, the study answers the following research questions: (i) What is the degree of change in rainfall and temperature in the Bolgatanga East District? (ii) How does gender shape the perception of smallholder farmers on climate variability in the study communities? (iii) Which CSA interventions are employed by smallholder farming households in the study communities? (iv) Which socio-demographic factors influence intra-gendered perceptions and adoption of CSA in the study communities? Binary logistic regression was used to identify the factors influencing male and female farmers’ perceptions and adoption of climate-smart agriculture. Rainfall and temperature trends from 2010 to 2020 were analyzed using the Mann-Kendall trend test. We found that over the past ten years, smallholder farmers in the district have seen rising temperatures and erratic rainfall patterns. Less educated female smallholder farmers adopted CSA interventions relative to more educated female farmers. Married male smallholder farmers employed CSA interventions on their farms compared to single and divorced male farmers. The adoption of CSA was higher for female farmers with inherited farmland than for those with rented land. Our results indicate that the source of income and farming experience influence male smallholder farmers’ adoption of crop rotation and their decision to diversify crops on their farms. The farmland tenure system, farming experience, and income source of female farmers influence their choice to change planting dates. The study recommends the integration of intra-gendered dynamics in policy reforms to reduce the vulnerability of smallholder farmers with different socioeconomic characteristics to climate variability in Ghana.

Strengthening grassland carbon source and sink management to enhance its contribution to regional carbon neutrality

Grassland ecosystems are an important part of terrestrial ecosystems. It is of great significance to fully tap the potential of grassland carbon sinks to achieve the goal of carbon neutrality in the region and even worldwide. Previous studies have focused on analyzing the temporal and spatial distributions of grassland carbon sink capacity and lacked a systematic discussion of grassland carbon source/sink management. Taking three grasslands in the Inner Mongolia Autonomous Region of China as an example, this study characterized grassland carbon source/sink capacity through net ecosystem productivity (NEP), combined with a soil respiration model, Sen + MK (Mann-Kendall) trend test method and other methods, revealed the spatiotemporal distribution characteristics of NEP and carbon emissions (CEs) in the study area from 2000 to 2019, and used spatiotemporal and geographical weighted regression (GTWR) model to clarify the potential mechanism of grassland sink increase. Suggestions for grassland carbon source/sink management are also discussed. The study found that the CEs in the study area from 2000 to 2019 could be roughly divided into three stages: slow growth period (2000–2009), rapid growth period (2009–2011) and stable development period (2011–2019). Although grassland carbon sinks could not completely offset regional CEs, grassland ecosystems had a very large carbon sink potential, which could make important contributions to the realization of regional carbon neutrality goals. Grassland carbon sources/sinks were jointly affected by climate change and human activities, and the degree of impact varied from year to year, with the impact of human activities changing more significantly. On this basis, the study puts forward policy recommendations from four aspects: regional priority, dynamic monitoring and management, control of grazing intensity and implementation of ecological compensation, and it proposed a sustainable development pattern of “carbon trading-ecological compensation-grassland sink increase”. The research results have important practical guiding significance for the management of grassland sink increases and regional carbon neutral development strategies in Inner Mongolia under the background of climate change.

Trends in Ophthalmological Patents, 2005-2020.

Purpose: Technological development drives the optimization of therapeutics in ophthalmology, but quantifiable and systematic review of such innovation is lacking. To fill this gap, we characterize trends in ophthalmology-related patents in the United States from 2005 to 2020. Methods: Publicly available patent data from the US Patent and Trademark Office was analyzed with the R programming language. Ophthalmology-related patents were identified with a keyword search of their titles and claims text. Temporal trends were assessed with the Mann-Kendall trend test (α = 0.05, two-sided). Results: Of 4.5 million collected patents, some 21,000 (0.5%) were ophthalmology related. The number of annually granted ophthalmology patents increased over time (Mann-Kendall test: z = 4.91; P < 0.001), from 619 patents released in 2005 to 2,019 patents in 2020. Patent counts also increased over time for all ophthalmic subspecialties except oculoplastics, with steepest rises in retina (z = 4.91; P < 0.001) and cornea (z = 4.64; P < 0.001). The most cited patents were in biocompatible intraocular implants and implantable controlled-release drug delivery systems, which underscores particular advancement in therapeutic efficacy and safety in devices used in the treatment and management of common yet debilitating eye conditions. Conclusion: This exploratory analysis reveals hotspots for ophthalmology-related innovation in the United States that may predict current and future growth trends in device development and pharmacologic advancement in ophthalmology, paving the way for more diverse and effective treatment options for preserving vision.

Analysis of Hydrometeorological Trends and Drought Severity in Water-Demanding Mediterranean Islands under Climate Change Conditions

Global climate change has emerged as a problem in recent years, and its effects will likely continue to increase in the future. Several scientific studies conducted in the Mediterranean region have demonstrated relatively stationary trends for annual precipitation and significant upward trends for mean annual temperature. These trends present several implications, especially in the Greek islands that serve as major summer tourist destinations where the population is already unable to meet their water demands. The aim of this study is to investigate both long- and short-term variations in temperature and precipitation on three Greek islands in the Mediterranean Sea (Mykonos, Naxos, and Kos). The temperature and rainfall trends, as well as their magnitudes at yearly, seasonal, and monthly time steps, were determined using the non-parametric Mann–Kendall trend test. The Standardized Precipitation Index (SPI) was employed to identify the drought periods. According to the results, precipitation slightly increased (almost stationary) in the three islands, although this rise was not statistically significant. All three islands experienced a sharp and statistically significant increase in their mean annual air temperatures. The region may experience drought episodes as a result of the high temperature increase, which would drastically reduce the amount of water, available for use due to the increased evapotranspiration. For the Mediterranean region, the necessity for a drought management strategy to stop or diminish the severity of drought episodes and their effects has grown into a matter of great concern. It is crucial to take measures and conduct relevant research in order to create the conditions for adaptation and mitigation of climate change consequences and the increased appearance of drought phenomena.

Prediction of climate change impacts on availability of surface water resources in the semi-arid Tugwi Mukosi catchment of Zimbabwe

Climate change impact drivers includes increased rainfall variability, increased extreme events, and changes in the mean behaviour of hydro-meteorological variables such as air temperature, rainfall, and runoff. As such, this study assessed the potential impacts of climate change on surface water resources in a semi-arid Tugwi Mukosi catchment of Zimbabwe. The Mann-Kendall trend analysis, climate change downscaling and streamflow modelling were used as the primary methodology. The analysis of historical hydro-climatic data trends were performed using the Mann-Kendall trend test and Sen's slope method. Equally, observed daily rainfall was extended using bias-corrected CHIRPS satellite rainfall. Thus, a total of 9 Global Climate Models including (CCCma-CanESM2, Miroc Miroc 5, MOHCHadGEM2, MPI-M-MPI-ESM-LR, and NCCNorESM1-M) on the Sveriges Meteorologiska och Hydrologiska Institut (SMHI) Rosby Centre Atmosphere model version 4 (RCA4) RCM under the Representative Concentrated Pathways 4.5 and 8.5 were extracted and analysed for the 2030s (2021–2050) and 2060s (2051–2080) period. The results show significant (p<0.05) decreasing rainfall trends at the analysed stations, as well as significant decrease in rainfall for the 2030s and the 2060s under GCMs CCCma-CanESM 2 model. The Hydrologic Engineering Centre-Hydrological modeling System (HECHMS) (1997–1999) was calibrated and validated for the period 1981–2016. Calibration results on gauged catchment runoff and peak flows are satisfactory (Ngezi observed peak discharge and simulated peak discharge at 42.4 m3/s and 34.8 m3/s respectively, NSE 62.8%, Upper Muzhwi 30 m3/s and 19.5 m3/s, NSE 53.55%, Musogwezi 18.7 m3/,s and 16.5 m3/s, NSE 58.4%). The GCM-CanESM RCP 4.5 model showed a decrease in the runoff predicted of above 17% in both the 2030s and a significant decrease in the 2060s of 28.41% and 5% respectively. The combination of climate downscaling and water resources modelling is paramount to the management of water resources in a semi-arid area. Hydrological modelling and climate downscaling techniques gives important insights for water resources planning and development to support the water sector adaptation to climate change. The methodology applies to other data-scarce and semi-arid areas whose climate change impacts require further investigation.

Spatial–Temporal Evolution of the Coupling Coordination Degree between Water and Land Resources Matching and Cultivated Land Use Eco-Efficiency: A Case Study of the Major Grain-Producing Areas in the Middle and Lower Reaches of the Yangtze River

Improving the coupling coordination degree between water and land resources matching (WLRM) and cultivated land use eco-efficiency (CLUE) is crucial to ensuring national food security and constructing an ecological civilization. This study is based on the data of 71 prefecture-level cities in the major grain-producing areas in the middle and lower reaches of the Yangtze River from 2008 to 2020. The unit area water resource method, the slacks-based measurement (SBM)-undesirable, the Theil–Sen median analysis, the Mann–Kendall trend test, the coupling coordination degree model, and the spatial autocorrelation model are adopted to measure and analyze the WLRM, the CLUE, and the coupling and coordination level, and their spatial–temporal evolution characteristics quantitatively. Results show the following: (1) From 2008 to 2020, the average value of WLRM in the study areas is 18,200 m3/hm2, which is at a medium level, and the provinces show the characteristics of “high in the south and low in the north, with decreasing gradients”. (2) The annual average of CLUE is 0.777, which is in the medium level, and each province has the remarkable characteristics of “one high and four low”. (3) The coupling coordination degree of WLRM and CLUE is in the primary coordination level, which shows a significant positive correlation in space. In the local perspective, it shows the agglomeration characteristics of “high in the south and low in the north, nodule distribution”. In the future, the neighboring prefecture-level cities should actively build a synergistic mechanism for agricultural development, strengthen the reasonable use of water and land resources and pollution control techniques, drive the transformation of low–low aggregation areas to high–high aggregation areas, and improve the overall coordination of the study areas. This approach aims to promote the construction of ecological civilization and guarantee grain security and sustainable development of agriculture in China.

A changing landscape: Tracking and analysis of the international HDV epidemiology 1999-2020.

The international epidemiology of Hepatitis Delta Virus (HDV) is challenging to accurately estimate due to limited active surveillance for this rare infectious disease. Prior HDV epidemiological studies have relied on meta-analysis of aggregated and static datasets. These limitations restrict the capacity to actively detect low-level and/or geographically dispersed changes in the incidence of HDV diagnoses. This study was designed to provide a resource to track and analyze the international HDV epidemiology. Datasets analyzed collectively consisted of >700,000 HBV and >9,000 HDV reported cases ranging between 1999-2020. Datasets mined from government publications were identified for Argentina, Australia, Austria, Brazil, Bulgaria, Canada, Finland, Germany, Macao, Netherlands, New Zealand, Norway, Sweden, Taiwan, Thailand, United Kingdom, and United States. Time series analyses, including Mann-Kendall (MK) trend test, Bayesian Information Criterion (BIC), and hierarchal clustering, were performed to characterize trends in the HDV timelines. An aggregated prevalence of 2,560 HDV/HBV100,000 cases (95% CI 180-4940) or 2.56% HDV/HBV cases was identified, ranging from 0.26% in Canada to 20% in the United States. Structural breaks in the timeline of HDV incidence were identified in 2002, 2012, and 2017, with a significant increase occurring between 2013-2017. Significant increasing trends in reported HDV and HBV cases were observed in 47% and 24% of datasets, respectively. Analyses of the HDV incidence timeline identified four distinct temporal clusters, including Cluster I (Macao, Taiwan), Cluster II (Argentina, Brazil, Germany, Thailand), Cluster III (Bulgaria, Netherlands, New Zealand, United Kingdom, United States) and Cluster IV (Australia, Austria, Canada, Finland, Norway, Sweden). Tracking of HDV and HBV cases on an international scale is essential in defining the global impact of viral hepatitis. Significant disruptions of HDV and HBV epidemiology have been identified. Increased surveillance of HDV is warranted to further define the etiology of the recent breakpoints in the international HDV incidence.

Evaluation of Implementation and Effectiveness of China's Antibiotic Stewardship in the First Affiliated Hospital of Sun Yat-sen University.

Antibiotic stewardship has been prioritized by governments and health care organizations in recent years as antibiotic resistance is markedly increasing. A tertiary hospital in Guangzhou, China was chosen as a study example to undertake an implementation and effectiveness evaluation of China's antibiotic stewardship to improve and promote antimicrobial stewardship nationwide. The general surgery department of the study hospital was utilized to examine surgical site infection, and samples from across the hospital were used to identify bloodstream infection. Data was analyzed using descriptive analysis, the Mann-Kendall trend test, logit model and panel data model, and t-tests. In terms of prophylactic and therapeutic antibiotic rational use, respectively, we evaluated implementation conditions, the correlation between implementation and corresponding disease progress, and the cost-effectiveness of China's antibiotic stewardship. For perioperative prophylactic antibiotic use, antibiotic stewardship was found to have been well-implemented, cost-effective, and reduced the incidence of surgical site infection. However, concerning therapeutic use and antibiotic-resistant bacterial infection prophylaxis, the complexity of influencing factors and the contradiction between stewardship implementation and clinical demand needs to be further evaluated.

Towards understanding the environmental and climatic changes and its contribution to the spread of wildfires in Ghana using remote sensing tools and machine learning (Google Earth Engine)

ABSTRACT Data processing and climate characterisation to study its impact is becoming difficult due to insufficient and unavailable data, especially in developing countries. Understanding climate's impact on burnt areas in Ghana (Guinea-savannah (GSZ) and Forest-savannah Mosaic zones (FSZ)) leads us to opt for machine learning. Through Google Earth Engine (GEE), rainfall (PR), maximum temperature (Tmax), minimum temperature (Tmin), average temperature (Tmean), Palmer Drought Severity Index (PDSI), relative humidity (RH), wind speed (WS), soil moisture (SM), actual evapotranspiration (ETA) and reference evapotranspiration (ETR) have been acquired through CHIRPS (Climate Hazards group Infrared Precipitation with Stations), FLDAS dataset (Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System) and TerraClimate platform from 1991 to 2021. The objective is to analyse the link and the contribution of climatic and environmental parameters on wildfire spread in GSZ and FSZ in Ghana. Variables were analysed (area burnt and the number of active fires) through Spearman correlation and the cross-correlation function (CCF) (2001 to 2021). The tests (Mann-Kendall and Sens's slope trend test, Pettitt test and the Lee and Heghinian test) showed the overall decrease in rainfall and increase in temperature respectively (−0.1 mm; + 0.8°C) in GSZ and (−0.9 mm; + 0.3°C) in FSZ. In terms of impact, PR, ETR, FDI, Tmean, Tmax, Tmin, RH, ETA and SM contribute to fire spread. Through the codes developed, researchers and decision-makers could update them at different times easily to monitor climate variability and its impact on fires.

Investigation of Temperature Variations in Kozhikode District, Kerala

Kerala is situated on the Western Ghats' southern edge. Kerala has a topography that is asymmetrical. Its landform is characterized by steep slopes and rolling, quiet hills. Kerala has been experiencing temperature rise, irregular monsoons, and water scarcity for the past few years. The present study includes an investigation of temperature variations in the Kozhikode district, Kerala by examining the Maximum, Minimum, and Average Temperature in annual, seasonal, and monthly variations by time series of meteorological stations in the Kozhikode district. Gridded data of temperature prepared by the Indian Meteorological Department (IMD) and Centre for Water Resources Development and Management (CWRDM) for the Kozhikode region have been used in the study. The temperature data is collected from three meteorological stations in the Kozhikode district. The variation of temperature was analyzed by linear regression method. The statistical significance of the trend can be tested by a non-parametric test, such as the Mann-Kendall Trend Test.

Evaluation of General Circulation Models CMIP6 Performance and Future Climate Change over the Omo River Basin, Ethiopia

One of the world’s major issues is climate change, which has a significant impact on ecosystems, human beings, agricultural productivity, water resources, and environmental management. The General Circulation Models (GCMs), specially the recently released (coupled model intercomparison project six) CMIP6 are very indispensable to understand and support decision makers to identify adaptation strategies in response to future climate change in a basin. However, proper selection of skillful GCMs and future climate assessment is a prior task to climate impact studies. The objective of the study is an attempt to appraise the climate model’s performance and future climate scenarios of Shared Socioeconomic Pathways (SSPs) in the Omo River Basin. The performance evaluation of 20 GCMs of the CMIP6 was properly performed to reproduce the precipitation and the maximum temperature in the basin. Their performance has been carried out against the best selected mean monthly Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) precipitation and European Community Medium Water Range Weather Forecasts Version 5 (ECMWF-ERA5) maximum temperature. The GCMs of the CMIP6 were selected and ranked using the compromise programming method of multi-criteria decision making. The result shows that ensemble models and NorESM2-MM models have been designated to reproduce the precipitation and maximum temperature in the basin respectively. The Mann–Kendall trend test was executed to appraise the trend of selected CMIP6 models, and subsequently, downscaling and bias correction techniques were conducted. The projected seasonal precipitation of June, July, August, September (JJAS) and March, April, May (MAM) shows an increasing trend with 10.86, 17.66, 38.96 and 11.85, 22.1, and 40.7% under SSP2452031-2060, SSP5852031-2060, and SSP5852071-2100 scenarios respectively. Furthermore, increasing trends were detected in MAM by 12.8% and decreasing trends in JJAS were detected by 15.23% under SSP2452071-2100 scenario. The maximum temperature projection will be increased on average by 0.95, 1.78, 1.4, and 3.88 °C in JJAS and 1.53, 2.24, 1.56, and 3.89 °C in MAM under climate change scenarios of near-future SSP2452031-2060, SSP5852031-2060, far-future SSP2452071-2100, and SSP5852071-2100, respectively. Additionally, the basin has shown temporal-spatial climate fluctuation in terms of precipitation and maximum temperature.

Ley evolutiva de la relación entre el lago Dongting y las tres salidas del río Jingjiang en los últimos 60 años

The Three Gorges Reservoir has begun to play a comprehensive role in power generation, flood control, shipping and other aspects, since June 1, 2003. Using long time series runoff and sediment transport data, the evolution of the relationship of the Dongting Lake and the Three Outlets of the Jingjiang River after operation of the Three Gorges Project was analyzed using Back Propagation neural networks, Mann-Kendall trend test, and double cumulative curves. The results show that: (1) On interannual and interdecadal scales, the decrease in runoff from Dongting Lake is mainly caused by the sharp decrease in runoff from the Three Outlets. To some extent, the siltation of the Dongting Lake was alleviated because of the reduction of sediment transport coming from the Three Outlets. (2) By analyzing the consistency of runoff and sediment transport in and out of Dongting Lake, it was found that the influence of the hydraulic engineering in the Yangtze River on runoff and sediment entering and leaving Dongting Lake is asynchronous. The rate of decay of sediment into the Lake is much greater than the decay rate of sediment out of the Lake. (3) From the trend change of the dried-up days of the Three Outlets, the Three Outlets tend to be silted, and the Ouchi River and the Hudu River gradually decline. (4) From the sedimentation process line of Dongting Lake, cumulative sedimentation of Dongting Lake from 2003 to 2018 was -2829×104t, and the Dongting Lake changed from siltation state to erosion state. (5) A Back Propagation neural network model was used to simulate the runoff and sediment transport of Dongting Lake, and the results show that the simulation accuracy met the needs of Dongting Lake runoff and sediment transport prediction.

Identifying trends in SARS-CoV-2 RNA in wastewater to infer changing COVID-19 incidence: Effect of sampling frequency

SARS-CoV-2 RNA concentrations in wastewater solids and liquids are correlated with reported incident COVID-19 cases. Reporting of incident COVID-19 cases has changed dramatically with the availability of at-home antigen tests. Wastewater monitoring therefore represents an objective tool for continued monitoring of COVID-19 occurrence. One important use case for wastewater data is identifying when there are sustained changes or trends in SARS-CoV-2 RNA concentrations. Such information can be used to inform public health messaging, testing, and vaccine resources. However, there is limited research on best approaches for identifying trends in wastewater monitoring data. To fill this knowledge gap, we applied three trend analysis methods (relative strength index (RSI), percent change (PC), Mann-Kendall (MK) trend test) to daily measurements of SARS-CoV-2 RNA in wastewater solids from a wastewater treatment plant to characterize trends. Because daily measurements are not common for wastewater monitoring programs, we also conducted a downsampling analysis to determine the minimum sampling frequency necessary to capture the trends identified using the “gold standard” daily data. The PC and MK trend test appear to perform similarly and better than the RSI in terms of first detecting increasing and decreasing trends using a 14-day look-back period, so we only considered the PC and MK trend test methods in the downsampling analysis. Using an acceptable sensitivity and specificity cutoff of 0.5, we found that a minimum of 4 samples/week and 5 samples/week is necessary to detect trends identified by daily sampling using the PC and MK trend test method, respectively. If a higher sensitivity and specificity is needed, then more samples per week would be needed. Public health officials can adopt these trend analysis approaches and sampling frequency recommendations to wastewater monitoring programs aimed at providing information on how incident COVID-19 cases are changing in the contributing communities.