Monthly Mean Research Articles

Advanced Forecasting of Drought Zones in Canada Using Deep Learning and CMIP6 Projections

This study addresses the critical issue of drought zoning in Canada using advanced deep learning techniques. Drought, exacerbated by climate change, significantly affects ecosystems, agriculture, and water resources. Canadian Drought Monitor (CDM) data provided by the Canadian government and ERA5-Land daily data were utilized to generate a comprehensive time series of mean monthly precipitation and air temperature for 199 sample locations in Canada from 1979 to 2023. These data were processed in the Google Earth Engine (GEE) environment and used to develop a Convolutional Neural Network (CNN) model to estimate CDM values, thereby filling gaps in historical drought data. The CanESM5 climate model, as assessed in the IPCC Sixth Assessment Report, was employed under four climate change scenarios to predict future drought conditions. Our CNN model forecasts CDM values up to 2100, enabling accurate drought zoning. The results reveal significant trends in temperature changes, indicating areas most vulnerable to future droughts, while precipitation shows a slow increasing trend. Our analysis indicates that under extreme climate scenarios, certain regions may experience a significant increase in the frequency and severity of droughts, necessitating proactive planning and mitigation strategies. These findings are critical for policymakers and stakeholders in designing effective drought management and adaptation programs.

Long Term Health Problems and Associated Factors among COVID-19 Recovered Patients

A cross-sectional, descriptive study was conducted among 181 individuals recovered from COVID-19 infection and had been missing infection (negative rt-PCR test) or signs-symptoms for minimum three months. The study aims determine newly developed health problems in patients, which was conducted at Post-COVID Unit of Anwer Khan Modern Medical College Hospital, Dhaka, Bangladesh, between July 2021 and June 2022. Through convenient sampling, data were collected by face-to-face interview and history of signs/ symptoms during the infection were recorded from reviewing prescription and interview as well by using a semi-structured questionnaire. The mean age of the participants was 39.56±6.92 years and male-female ratio was 1.45:1. The mean monthly family income of the participants was 36,022.09±4130.56 BDT which represents lower middle to middle class family in terms of Bangladesh context. During COVID-19 infection most of the (97%) respondents had fever, and 87%, 79% of the patients had sore throat and cough respectively as common symptoms; in addition, more than one-third (34%) had diarrhea. Several constitutional symptoms also recorded during their course of illness like headache (74%) and malaise (54%). More than one-third (34%) of the respondents required admission in hospital. During the course of infection, 41%, 26% and 31% participants were suffered from mild, moderate and severe form of COVID-19 illness. Most of the respondents developed long term health problems following COVID infection and post-viral fatigue was the most prevalent (85%) among the post COVID individuals and this long-term health problem-post viral fatigue was found to be associated with monthly income and it was statistically significant (p<0.05). Others long term health problems including shortness of breath (74%), loss of memory (38%), difficulty in concentration (41%), loss of hair (30%), fast beating or pounding heart (33%) were also noticed. Insomnia (56%), persistent cough (35%), loss of taste (32%) and change of bowel habit (28%) were other health problems revealed in this study. Association between loss of memory and gender (p<0.0001), diabetes mellitus and severity of COVID-19 (p<0.05), sore throat, cough and severity of COVID-19 (P<0.05) were also found significant. diabetes mellitus (35%), hypertension (34%) and bronchial asthma (24%) were observed to be most common comorbidities. Shortness of breath – one of the post-COVID consequence was found significantly associated with diabetes mellitus and bronchial asthma (p<0.05). Our study found that persistence of various signs and symptoms from COVID-19 infection and newly yield complications in individual who recovered from COVID-19 infection are collectively comprise long term health problems of post-COVID patients. This long-term health problem of post-COVID people is a major public health concern. Fatigue, dyspnea, difficulty to concentrate, memory loss, persistent cough, fast beating or pounding heart, loss of smell, loss of taste, insomnia are the most common long term health problems in COVID-19 recovered people. Long-term follow up may be recommended to understand future consequences of COVID-19 patients and well-being for the post-COVID people. CBMJ 2024 July: vol. 13 no. 02 P: 158-168

Spatial-temporal analysis of climate and socioeconomic conditions on cholera incidence in Mozambique from 2000 to 2018: an ecological longitudinal retrospective study

ObjectivesThis study aims to assess both socioeconomic and climatic factors of cholera morbidity in Mozambique considering both spatial and temporal dimensions.DesignAn ecological longitudinal retrospective study using monthly provincial cholera cases...

Phleum pratense-pollen adaptive variations and pollen microbiome investigation under different climatic regions and prospects of allergenicity.

Phleum pratense is an allergenic grass that pollinates in spring in Pakistan. Databases Allergenonline.org and Allergen.org record ten P. pratense allergens and their isoforms. Phl P 1, Phlp 5, and Phl p 11 are major P. pratense-pollen allergens with demonstrated basophil activity and skin test reactivity. Little is known about P. pratense pollen adaptive variations in different climatic regions and pollen-associated microbial diversity. In this study, we collected P. pratense-pollen and soils in the spring season 2022. Samples were collected from three climatic regions in Pakistan (R1, R2 and R3) with differences in mean monthly air temperature, mean monthly precipitation and elevation. The morphology of pollen was observed by light microscopy, scanning electron microscopy (SEM), biochemical fingerprint analysis, and composition of pollen were investigated by fourier-transform infrared spectroscopy (FTIR). The pollen-associated bacterial populations were identified through a Biolog GEN III microplate system. The pollen water-soluble proteins were isolated and stabilized in phosphate buffer saline (PBS) and tested for allergenicity responses through dot blots and western blots analysis. The morphology study found difference in pollen biochemical composition. Biolog identified Brevibacterium epidermidis and Pantoea agglomerans from P. pratense pollen. Protein extract quantification and sodium dodecyl sulfate-poly acrylamide gel electrophoresis (SDS-PAGE) gel found decreased protein expression in R1 region pollen compared to R2 and R3 region pollen. Allergenicity studies found differential expression of beta-expansin and profilin allergens in pollen obtained from the three regions. Beta-expansin and profilin were suppressed in R1 pollen and expressed in compared to R2 and R3 pollen. This is the first study to identify B. epidermidis and P. agglomerans growth on P. pratense pollen. Variable allergen expression in P. pratense pollen has also been observed in different regions. Soil pH, an increase in mean monthly temperature and a decrease in mean monthly precipitation correlated with pollen biochemical composition, and reduced beta-expansin and profilin expression involved in pollen growth and development. The findings of this research are unique, which enhances basic knowledge and understanding of P. pratense-pollen associated microbiota and climate change impacts on the pollen allergen expression.

Trend analysis of precipitation and drought characteristics over Churu district of northeast Rajasthan, India

ABSTRACT Drought is one of the most destructive natural disasters, becoming more extreme and less predictable due to climate change. Drought directly affects a region's water resources, leading to inadequate water availability and harming crops, animals, and humans. The objective of the present study is to assess the long-term trends of precipitation and drought characteristics for the Churu district of northeast Rajasthan, India. For this purpose, mean monthly precipitation data are collected through the India-WRIS from 1901 to 2022. The trend analysis uses statistical methods (M-K test & amp; SS estimator), and the results are compared with a graphical method (innovative trend analysis). Drought events are found using precipitation-based drought indices, i.e., standardized precipitation index, Z-score index, and percentage of normal precipitation index. Interestingly, the results of the statistical method are well matched with the results of the graphical method. The study concludes that during the annual precipitation a rising trend is observed, which can help to mitigate the severity of drought. Also, it is found that moderately dry droughts occur most frequently compared with other drought events. This study will help policy-makers and local administrators to take necessary action to mitigate the severity of drought.

Real-world comparison of health care costs of venetoclax-obinutuzumab vs Bruton's tyrosine kinase inhibitor use among US Medicare beneficiaries with chronic lymphocytic leukemia in the frontline setting.

Bruton's tyrosine kinase inhibitors (BTKis) and the BCL-2 inhibitor venetoclax in combination with obinutuzumab (VEN-O) are both recommended as frontline therapy in chronic lymphocytic leukemia (CLL). However, VEN-O is a 12-month fixed-duration therapy generating durable remissions whereas BTKis are continuous treat-to-progression treatments. To examine costs before and after the fixed-duration treatment period for VEN-O relative to that observed for BTKis in a national sample of older US adults with CLL in the frontline setting. This retrospective analysis used Medicare Parts A, B, and D claims from 2016 to 2021. Fee-for-service Medicare beneficiaries aged 66 years or older initiating frontline CLL treatment with VEN-O or a BTKi treatment between June 1, 2019, and June 30, 2020 (index date = first prescription fill date), were included in the sample. Mean cost measures were captured for both groups over 2 fixed time periods calculated from the index date: Month 0 to 12 (proxy for VEN-O on-treatment period) and Month 13 to 18 (proxy for VEN-O off-treatment period). A difference-in-difference approach was used. Multivariate generalized linear models estimated changes in adjusted mean monthly costs during Month 0 to 12 vs Month 13 to 18, for the VEN-O group relative to the BTKi group. The final sample contained 193 beneficiaries treated with VEN-O and 1,577 beneficiaries treated with BTKis. Risk-adjusted all-cause monthly total costs were similar for VEN-O patients ($13,887) and BTKi patients ($14,492) between Month 0 and 12. Moreover, during Month 13 to 18, the mean monthly all-cause total costs declined by 67% for VEN-O ($13,887 to $4,462) but only by 10% for BTKi ($14,492 to $13,051). Hence, the relative reduction in costs across the 2 periods was significantly larger for VEN-O (-$9,425) vs BTKi (-$1,441) patients (ie, difference in difference = -$7,984; P < 0.001). Similar patterns were observed for CLL-related costs, with the substantially larger reductions in CLL-related total monthly costs (-$9,880 VEN-O vs -$1,753 BTKi; P < 0.001) for the VEN-O group primarily driven by the larger reduction in CLL-related monthly prescription costs (-$9,437 VEN-O vs -$2,020 BTKi; P < 0.001). This real-world study of older adults with CLL found a large reduction in monthly Medicare costs in the 6 months after completion of the fixed-duration treatment period of VEN-O, largely driven by the reduction in CLL-related prescription drug costs. A similar decline in costs was not observed among those treated with BTKis. Our study highlights the substantial economic benefits of fixed-duration VEN-O relative to treat-to-progression therapies like BTKis in the first-line CLL setting.

Assessing the Potential Impacts of Climate Change on Drought in Uzbekistan: Findings from RCP and SSP Scenarios

Future climate change and its impact on drought is critical for Uzbekistan, located in Central Asia, the world’s largest arid zone. This study examines the evolving intensity of climate change and drought events using multi-model ensembles (MMEs) derived from the Coupled Model Intercomparison Project Phase 5 and 6 (CMIP5 and CMIP6) simulated under the Representative Concentration Pathway and Shared Socioeconomic Pathway (RCP and SSP) scenarios. The projections show different rates of increase in temperature and precipitation under the RCPs and SSPs. Projected temperature increases are expected to reach up to 2–2.5 °C under SSP1-2.6, SSP2-4.5, and SSP3-7.0, by mid-century. By 2080–2099, an increase is projected of 2–3 °C in monthly mean temperatures throughout the year (SSP1-2.6), and a more pronounced increase in summer up to 3–4 °C (SSP2-4.5) and 4–6 °C (SSP3-7.0), with a marked contrast in conditions between the mountainous and desert regions of Uzbekistan. Regional changes in precipitation over the study periods show relatively little variability, except for FD, where notable trends are found. Under SSP1-2.6 and SSP2-4.5, the increase in precipitation is relatively modest, whereas the changes in SSP3-7.0 are more substantial, with some regions experiencing variations of up to 10–20 mm per period. The Standardized Precipitation Evapotranspiration Index (SPEI), calculated based on the projected temperature and precipitation, provides an estimate of future drought trends. Our results show increasing aridity under all scenarios by mid-century, with longer-term projections indicating stabilization around different SPEI values by 2100: RCP2.6 and SSP1-1.9 stabilize around −1.0; RCP4.5, RCP6.0, SSP2-4.5, and SSP3-7.0 stabilize around −1.5; while RCP8.5 and SSP5-8.5 scenarios project values of −2 or less by 2100. Notable differences in the SPEI index are found between lowland and foothill regions. In view of Uzbekistan’s heavy reliance on agriculture and irrigation, which are the sectors that are expected to be mostly affected by climate change, our study provides a scientific basis for informed policy decision-making. This includes various aspects such as planning and management water resources, as well as the broader socioeconomic development of the country.

On a relation between shrinking of sea ice coverage and climate warming in the marine Arctic

Arctic amplification (AA) of the climate warming is understood as the excess of the surface air temperature rise in the Arctic over the same process in the non-Arctic latitudes, and it is a fundamental characteristic of the climate during periods of warming. The positive feedback between albedo and shrinking of the sea ice coverage has been identified as the first possible cause of AA. The article presents quantitative estimates of the relationship between the summer decrease and autumn-winter restoration of the ice coverage with the rise of the surface air temperature in the marine Arctic based on data of observations. The mean monthly values of the temperature in the marine Arctic and the mean monthly values of areas covered by the sea ice in the Arctic Ocean and the Arctic seas for the period 1989–2020 were used. It has been found that the observed warming and the decrease of the ice coverage are accompanied by a growth of inter-monthly changes in the coverage and the same in the air temperature. Negative trends in increments of the ice coverage in May–July is indicative of a long-term growth in inter-monthly shrinkage of the ice coverage due to increasing melting, while negative trends in increments of the temperature in the same months is suggestive of a slowdown in the temperature rise from month to month, presumably due to the increasing heat consumption for the snow and ice melting and the water heating. The positive correlation confirms the relation between growing negative inter-monthly differences in the ice coverage and decreasing positive differences in the air temperature during these months. Based on that we determined a sensitivity of the inter-monthly increments of the temperature to the increments of the ice coverage, which was used to estimate the weakening of the positive air temperature trend in May–July over the Arctic Ocean and over the seas of the Northern Sea Route (NSR). Estimating of the relationship between month-to-month changes in temperature and ice coverage in the autumn-winter months meet difficulties due to the strong influence of external heat influx. Only in November and January a slowdown in the air temperature drop from October to November and from December to January had been revealed, with a positive trend in the ice coverage increments.

A Randomized Trial of the Impact of Ferric Citrate on Erythropoietin and Intravenous Iron Use in Patients Receiving Dialysis

Introduction: Ferric citrate (FC) is an FDA-approved iron-based phosphate binder for adults with dialysis-dependent chronic kidney disease. This study investigated the impact of FC as the primary phosphate-lowering therapy on utilization of erythropoiesis-stimulating agents (ESAs) and intravenous (IV) iron. Methods: In this randomized, open-label, active-controlled, multicenter study (NCT04922645), patients on dialysis and receiving ESAs were randomized to receive FC or remain on standard of care (SOC) phosphate-lowering therapy for up to 6 months. Primary endpoints were the difference in change from baseline to efficacy evaluation period (EEP) in mean monthly ESA and IV iron doses. Secondary endpoints included treatment differences in hemoglobin, phosphate, TSAT, and ferritin levels. Results: Two hundred nine patients were randomized to FC and had a day 1 dosing visit (n = 103) or SOC (n = 106). The two groups had similar baseline laboratory characteristics; however, atherosclerotic CV disease, peripheral vascular disease, and congestive heart failure were more common in the SOC group. The mean treatment difference in ESA monthly dose was −30.8 μg (FC vs. SOC; p = 0.02). An absolute though non-statistically significant change in mean monthly IV iron dose of −37.2 mg (p = 0.17) was observed with FC. Mean hemoglobin, TSAT, and ferritin all increased from baseline to the EEP with FC versus SOC. Serious adverse events occurred in 28% of patients receiving FC versus 37% in those receiving SOC. Conclusions: In patients receiving dialysis, treatment with FC as compared to remaining on SOC phosphate binders resulted in reductions in mean monthly ESA and IV iron dose.

Impact of El Niño, Indian Ocean dipole, and Madden–Julian oscillation on land surface temperature in Kuching City Sarawak, during the periods of 1997/1998 and 2015/2016: a pilot study

ABSTRACT The severe El Niño events of 1997/1998 and 2015/2016 caused significant disruptions in Southeast Asia, particularly in Borneo, resulting in hazardous haze and acute water shortages. This study examines the influence of El Niño, the Indian Ocean Dipole (IOD), and the Madden–Julian oscillation (MJO) on regional climate, using time-series data from February 1993 to December 2020. Data from El Niño, IOD, and MJO indices were integrated with Landsat 5 and 8 land surface temperature records, allowing for a detailed analysis of their combined effects on regional temperature and precipitation patterns. Time-series trend decomposition and the generalized linear mixed model approach identified the Oceanic Niño Index (ONI) as a significant driver of temperature increases and dry spell occurrences during the peak El Niño years. On the other hand, ONI correlated strongly with mean monthly temperatures, underscoring its dominant influence. In addition, the IOD was found to significantly affect regional temperatures with a regression coefficient of 0.38867 (p = 0.0455), indicating its significant but less pronounced impact compared with ONI. These findings clarify the dynamics between key climate indices and their impact on regional climate extremes, offering critical insights for improving climate resilience and adaptation in tropical regions.

Temporal Variation in and Influence of Environmental Variables on a Lepidopteran Community in a Mediterranean Mid-Mountain Area

The temporal variation in a community of nocturnal and diurnal Lepidoptera was studied in a Mediterranean mid-mountain area of the SW Iberian Peninsula between 2017 and 2019. Monthly samplings that allowed for the identification of 3528 specimens, belonging to 373 species from 40 different families, also provided data on the temporal and seasonal variation in richness and the abundance (dominated by Geometridae and Noctuidae), diet type (mainly oligophagous), voltinism (mostly univoltine) and biogeography of the community, primarily Mediterranean in scope. Richness, abundance and diversity were also found to be highly positively correlated with temperature and solar radiation, and less negatively correlated with precipitation and humidity. Canonical correspondence analyses (CCAs) also indicate that temperature and radiation are the climatic variables with the greatest influence on species occurrence over the different months of the year. The CCAs gave a cumulative variance value of 84.79% when using the monthly mean values of temperature, solar radiation and minimum relative humidity, and 86.4% if only monovoltine species were considered. Guidelines to maintain diversity in the environment of the study area are provided. It is possible that the area may function as a refuge area for Lepidoptera in the face of climate change and deforestation that are occurring in the geographical environment.

Evidence for seasonal shift in the reproduction of Aldabra giant tortoises (Aldabrachelys gigantea) in managed care in the Northern hemisphere compared to the natural habitat in the Southern hemisphere.

Ex situ breeding constitutes an important tool for species conservation; however, many reptile species are not managed sustainably under human care due to poor fecundity in ex situ settings. In this study, we tested whether the translocation of a seasonally reproducing species to a different environment results in decoupling of extrinsic signals and intrinsic conditions. The endocrinological patterns of plasma steroid sex hormones, follicular development, and mating behaviour of two female and two male sexually mature Aldabra tortoises (Aldabrachelys gigantea) in a zoological institution in the Northern hemisphere was aligned with enclosure climate data (mean monthly daylight duration, temperature, and precipitation) and compared with respective hormone patterns of wild individuals and climate conditions in the native habitat on the Aldabra Atoll in the Southern hemisphere. Whereas occurrence of mating behaviour was not considered a limiting factor, lack of ovulation and subsequent follicular atresia was the main reason for the lack of reproductive output. While it was impossible to elucidate the triggering factors of ovulation and the multifactorial complexity of reproduction was not fully addressed, this study indicates suboptimal temperature conditions and relative temporal shifts of interacting external triggers (temperature and photoperiod) in the zoo setting.

An Assessment of Changes in the Thermal Environment during the COVID-19 Lockdown: Case Studies from the Greenland and Norwegian Seas

The COVID-19 lockdown had a significant impact on human activities, reducing anthropogenic heat and CO2 emissions. To effectively assess the impact of the lockdown on the thermal environment, we used the sliding paired t-test, which we improved from the traditional sliding t-test by introducing the paired t-test for sliding statistical tests, to test the abrupt change in the thermal environment. Furthermore, an additive decomposition model and wavelet analysis method were used to analyze the characteristics of trend and irregular change, coherence, and phase difference of the time series data with respect to the thermal environment. We chose the Greenland Sea and the Norwegian Sea, regions highly sensitive to changes in climate and ocean circulation, as case studies and used remote sensing data of the sea surface temperature (SST) and the atmospheric CO2 concentration data obtained from the Goddard Earth Sciences Data and Information Services Center from January 2015 to December 2021 for the analysis. The results show that although the annual spatial mean SST in 2020 is lower than the mean of all 7 years in most areas of the two seas, there is no evidence of a significant mutation in the decrease in the SST during the lockdown in 2020 compared with the temperatures before, according to the sliding paired t-test. The analysis of the irregular components of the monthly mean SST decomposed by an additive decomposition model also does not show the anomalously low SST during the lockdown in 2020. In addition, the lockdown had almost no impact on the increasing trend of CO2 concentration. The wavelet analysis also shows that there is no obvious anomaly in coherence or phase difference between the periodic variation of the SST and the CO2 concentrations in 2020 compared with other years. These results suggest that the direct effect of the COVID-19 lockdown on the thermal environment of the study area could be negligible.

Assessing drought in Turkish basins through satellite observations

AbstractDrought occurs when there is a sustained decrease in rainfall over an extended period, impacting the socio‐cultural and environmental aspects of humans and other living beings. The geographic distribution and timing of droughts play a crucial role in drought management and mitigation strategies. Identifying and predicting the onset of droughts in specific regions, especially in watershed areas, is a primary concern in the field of hydrology. This study focuses on how the spatiotemporal patterns of drought are developing in Turkish Basins using detailed data on Terrestrial Water Storage (TWS), precipitation, and temperature at the pixel level. GRACE (Gravity Recovery and Climate Experiment), PERSIANN (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks), and WorldClim (World Climate) data sets are employed to assess long‐term changes of drought on a basin‐scale. Spatial analyses are conducted in a Geographic Information System (GIS) environment for the derivation of basinal monthly mean, minimum, and maximum statistics of TWS, precipitation, and temperature anomalies within Turkish Basins. Time series analyses are implemented to investigate the temporal evolution of droughts in these basins, for the basinal monthly mean, minimum, and maximum statistics obtained. The Mann–Kendall trend test and Pettitt change point detection tests are used to assess the statistical significance of the calculated trends and to expose the existence of any change point therein, respectively. The findings of the study indicate that Turkiye faces a significant risk of drought development in nearly all its basins, particularly after 2016. The GRACE dataset provides realistic insights into the temporal behaviour of hydrological droughts. PERSIANN is effective in identifying years with extreme meteorological conditions, and the standardized precipitation index (SPI) shows similar effectiveness, while they are ineffective in exposing significant trends due to the nature of the precipitation data. WorldClim data proves insufficient for modelling the temporal behaviour of droughts in these basins.

Comparison of Two Financial Incentives to Encourage the Use of Adalimumab Biosimilars: Results of a French Experiment Close to Clinicians.

In 2018, the French government introduced two mutually exclusive financial incentives to increase etanercept and insulin glargine biosimilar use. The general case redirects 20% of the price difference between the reference product and its biosimilars to hospitals for every biosimilar dispensed in community pharmacies from hospital prescriptions. The experimental case redirects 30% to prescribing clinical units after hospital selection. Adalimumab was added to these incentives in 2019, after its first biosimilar was launched. This retrospective observational study aimed to compare both general and experimental incentives after 19 months to assess the impact of directly incentivizing clinical units for adalimumab biosimilars. The monthly number of adalimumab boxes dispensed in community pharmacies was linked to the corresponding hospital's prescription using IQVIA Xponent data from November 2017 to October 2020. The monthly mean rate of adalimumab biosimilars was compared between incentive groups and subgroups depending on hospitals' prior experience with the etanercept experimental case. General case hospitals had a significantly lower mean biosimilar uptake (16.7% vs 23.2%, p = 0.029) than those included in the experimental case. Twenty-three of the 40 hospitals in the experimental case and ten out of the 91 hospitals studied in the general case had already taken part in the etanercept experiment. Biosimilar uptake was higher, but not statistically significant, for hospitals with prior experience in the adalimumab general case group (p = 0.086). This study confirmed that incentivizing close to physicians was more effective in increasing the biosimilar rate. It also suggested that previous incentive experience positively influenced biosimilar penetration.

Timesavers: Clinical Decision Support and Automation of MRSA and VRE Deisolation

Background: Most healthcare facilities in the US apply contact precautions (CP) for patients with methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant enterococci (VRE) infection and/or colonization. Most individuals with MRSA or VRE colonization will clear over time; however, frontline clinicians rarely evaluate for discontinuation of CP, resulting in increased burden on infection preventionists (IPs). Automation of time- and test-based evaluation using clinical decision support systems (CDSS) embedded in electronic health records (EHR) may increase evaluation and discontinuation of CP when appropriate, while preserving IP resources. Methods: This quality improvement initiative was implemented at Mass General Brigham (MGB), an integrated healthcare system, where patients with MRSA or VRE infection/colonization are identified in the EHR with a corresponding “infection status” and CP applied. Following MGB policy (Figure 1), CDSS features included: 1) automated time-based resolution from 2/15/2023-11/13/2023 and 2) automated ordering of screening assays for patients eligible for test-based evaluation from 6/20/2023-11/14/2023 (Figure 2). Counts of CP discontinuation and automated ordering were performed. IPs at one MGB facility performing manual review of patients self-recorded the time spent evaluating for CP discontinuation. Using these time reports, the average time to complete these tasks and the projected time savings were calculated over the implementation period. Results: Four IPs recorded the time to review patients for CP discontinuation, including reviewing recent antimicrobial administration, microbiology results, ordering screening test(s), and contacting the primary team. Twenty-five patient encounters were timed with a mean of 4.7 minutes documented per encounter. Over a 9-month period after initiation of the automated time-based resolution, the monthly mean number of patients with CP for MRSA and VRE which were automatically discontinued was 247 and 100, respectively. Projected IP time savings over the same 9-month period for MRSA and VRE were 174.1 and 70.5 hours, respectively. Over a 5-month period after initiation of automated ordering of MRSA polymerase chain reaction (PCR)/culture, as well as VRE culture for test-based evaluation, the monthly mean number of MRSA culture, MRSA PCR, and VRE culture automatically ordered for patients on CP for MRSA and VRE were 176, 24, and 145, respectively. Projected IP time savings over the same 5-month period for MRSA and VRE were 78.3 and 56.8 hours, respectively.Conclusion: Healthcare systems that enhance their EHR with CDSS to automate CP evaluations may improve frontline clinician workflow, patient flow and bed capacity, while optimizing use of IP resources.

Combating Disparities in a Pandemic: Increasing Dissemination of Coronavirus Disease 2019 Resources in Spanish.

Disparities exist in access to coronavirus disease 2019 (COVID-19)-related health information. We aimed to close a gap in online traffic between English and Spanish COVID-19-related health information on our institution's publicly-facing website by 50% within ten months. We used A3 improvement methodology. Outcome measures were the mean monthly difference between English and Spanish COVID-19 online traffic vis-a-vis (1) total webpage views and (2) unique webpage visits. Process measures were stratification of outcome measures by language. Plan-Do-Study-Act cycles included: Recurring advertisements on a local Spanish television station disseminating up-to-date COVID-19 information, including our institution's Spanish COVID-19 online resources, incorporation of QR codes into clinic discharge paperwork linking to institutional Spanish COVID-19 resources, and leveraging social media to expand reach. Control charts assessed impact over time. There were 1,226,196 total webpage views (369,983 Spanish; 856,213 English) and 1,065,536 unique webpage visits (350,518 Spanish; 715,018 English). Both outcome measures displayed sustained, special cause improvement from a mean monthly difference of 25,397 to 11,321 webpage views (55.4% reduction, June 2021) and 25,066 to 7080 unique webpage visits (71.8% reduction, February 2021) corresponding to special cause improvements in process measures. Improvements were not temporally associated with an intervention but coincided with emergency use approval of the COVID-19 vaccine for children aged 12-15 years (May 2021). Although our interventions did not directly show improvements in our measures, we noted increased page views of Spanish COVID-19-related health information on our institution's publicly-facing website in times of high demand for linguistically appropriate services, including pediatric vaccine roll-out.

Characteristics of Gaseous Elemental Mercury in a Suburban Area of Shanghai, China.

To clarify gaseous elemental mercury (GEM) in suburban megacities in the Yangtze River Delta region, China, we observed GEM concentrations from December 2019 to November 2020 in Wujing town, a suburban area of Shanghai. The annual mean GEM concentration was 1.44 ± 0.88 ng m-3. Compared with the historical monitoring data of GEM in Shanghai over the past 10 years, the concentration of GEM showed a decreasing trend. The monthly mean concentrations of GEM showed clear seasonal variation, with higher values in the spring and winter. In spring and winter, typical Hg pollution events were observed, which could be mostly associated with increased local anthropogenic activity and temperature inversion. The results of the correlation analysis of the daily mean GEM concentrations with the AQI and backward trajectory calculations indicate that mercury pollution at monitoring sites can be affected by local, regional and interregional influences.

A Statistical Study of the Day‐To‐Day Variability of Diurnal and Semidiurnal Tides in the Ionospheric Dynamo Region From MIGHTI/ICON Observations

AbstractThe statistics of day‐to‐day tidal variability within 35‐day running mean windows is obtained from Michelson Interferometer for Global High‐Resolution Thermospheric Imaging (MIGHTI)/Ionospheric Connection Explorer (ICON) observations in the 90–107 km height region for the year 2020. Temperature standard deviations for 18 diurnal and semidiurnal tidal components, and for four quasi‐stationary planetary waves are presented, as function of latitude, altitude, and day‐of‐year. Our results show that the day‐to‐day variability (DTDV) can be as large as 70% of the monthly mean amplitudes, thus providing a significant source of variability for the ionospheric E‐region dynamo and hence for the F‐region plasma. We further validate our results with COSMIC‐2 ionospheric observations and present an approach to extend the MIGHTI/ICON results to all latitudes using Hough Mode Extension fitting, to produce global tidal fields and their statistical DTDV that are suitable as lower boundary conditions for nudging and ensemble modeling of TIE‐GCM. In the future, this will likely help to establish a data‐driven perspective of space weather variability caused by the tidal weather of the lower atmosphere.

Empirical Model of Equatorial ElectroJet (EEJ) Using Long‐Term Observations From the Indian Sector

AbstractThe Equatorial Electrojet (EEJ) is one of the important near‐earth space weather phenomena which exhibits significant diurnal, seasonal and solar activity variations. This paper investigates the EEJ variations at diurnal, seasonal and solar cycle time scales from the Indian sector and portrays a new empirical EEJ field model developed using the observations spanning over nearly two solar cycles. The Method of Naturally Orthogonal Components (MNOC), also known as Principal Component Analysis (PCA), was employed to extract the dominant patterns of principal diurnal, semi‐diurnal, and ter‐diurnal components contributing to the EEJ variation. The amplitudes of these diurnal, semi‐diurnal, and ter‐diurnal components in EEJ are found to vary significantly with the season and solar activity. The seasonal and solar activity dependencies of these principal components are modeled using suitable bimodal distribution functions. Finally, the empirical model for EEJ field was built by combining the principal components with their corresponding modeled amplitudes. This model accurately reproduces the diurnal, seasonal and solar activity variations of EEJ. The modeled monthly mean variations of EEJ field at ground exhibit excellent correlation of 0.96 with the observations with the root mean square error &lt;5 nT. It also successfully captures the seasonal and solar activity variations of Counter Electrojet (CEJ). Finally, this model named “Indian Equatorial Electrojet (IEEJ) Model” is made publicly available for interested scientific users (https://iigm.res.in/system/files/IEEJ_model.html).