Effects of COVID-19 lockdown and unlock on health of Bhutan-India-Bangladesh trans-boundary rivers.

The COVID-19 pandemic significantly destructs the rhythm of global modern human civilization but worldwide lockdown radically recovers the health of the total environment. The Himalayan trans-boundary rivers provide huge provisional, regulatory and cultural ecosystem services to millions of people throughout the year but in the recent years the water quality is being deteriorated due to multiple reasons. In the last decade, India-Bangladesh political relationship has been slightly broken down due to water sharing and environmental flow of rivers.The COVID-19 lockdown offered a great scope to execute the comparative study among pre, lockdown and unlock phase. The research attempts to investigate the spatiotemporal water quality of trans-boundary rivers through WAWQI and irrigation water quality indices such as Sodium absorption ratio, Soluble sodium percentage, Potential salinity, Magnesium hazard and Kelly's index considering eighteen water quality parameters (pH, EC, TDS, TSS, Ca²âº, Mg²âº, Na²âº, K⁺, F-, Cl-, NO3-, SO4²-, PO43-, DO, T, TUR, COD and BOD). The result shows the strong positive correlation between EC and TDS during three phases. Significant reduction of BOD, COD and TUR has been noticed almost 70% stations during lockdown compared with prelockdown while augmentation of DO has been recorded around 40% stations. WQI of most of the stations shows around 80% improvement of water quality during lockdown period. Moreover, worst kind of WQI was found in the Mathabhanga-Churni river followed by Mahananda. During lockdown, the striking results show that SAR and MH were significantly amplified in most of the stations due to agricultural run-off.

Private well water testing promotion in pediatric preventive care: A randomized intervention study.

Over 43 million U.S. residents rely on private unregulated wells for their drinking water, raising public health concerns, particularly in regions like northern New England where widespread groundwater arsenic contamination is now recognized. Children are particularly vulnerable to adverse health effects from arsenic exposure. Despite AAP Guidelines, approaches to engage pediatric clinicians in promoting private well testing have not been previously described. We sought to determine the most effective practice approaches to achieve successful well water testing in routine pediatric care. 12 primary care clinics were block randomized to one of four study arms. Two intervention variables were assessed: (1) test results access (parent only vs. parent and clinic) and (2) follow up approaches (yes/no). Parents of children under 12 months using a private well were eligible. Prepaid water tests were provided. Primary outcome was parental water test completion. Eleven clinics successfully implemented processes identifying well users. 240 testing kits were dispensed. Completion rates averaged 29% (range 10 to 61%). The study arm with both clinic results access and staff follow up system was 2.3 times more likely to achieve test completion than other arms (95% CI 1.12-4.86, p = .03). Kit distribution by clinicians versus nursing staff, irrespective of study arm, had 2.4 times greater completion (95% CI 1.13-5.11, p = .02). Systematic drinking water source screening can be improved in pediatric care. Higher testing completion was found in practices randomized to reminders and structured follow up versus single visit discussion, but clinician involvement was the most predictive factor.

Short Communication: HIV-DRLink: A Tool for Reporting Linked HIV-1 Drug Resistance Mutations in Large Single-Genome Data Sets Using the Stanford HIV Database.

The prevalence of HIV-1 drug resistance is increasing worldwide and monitoring its emergence is important for the successful management of populations receiving combination antiretroviral therapy. It is likely that pre-existing drug resistance mutations linked on the same viral genomes are predictive of treatment failure. Because of the large number of sequences generated by ultrasensitive single-genome sequencing (uSGS) and other similar next-generation sequencing methods, it is difficult to assess each sequence individually for linked drug resistance mutations. Several software/programs exist to report the frequencies of individual mutations in large data sets, but they provide no information on linkage of resistance mutations. In this study, we report the HIV-DRLink program, a research tool that provides resistance mutation frequencies as well as their genetic linkage by parsing and summarizing the Sierra output from the Stanford HIV Database. The HIV-DRLink program should only be used on data sets generated by methods that eliminate artifacts due to polymerase chain reaction recombination, for example, standard single-genome sequencing or uSGS. HIV-DRLink is exclusively a research tool and is not intended to inform clinical decisions.

Impacts of land surface model and land use data on WRF model simulations of rainfall and temperature over Lake Tana Basin, Ethiopia.

The Weather Research and Forecasting (WRF) model is one of the regional climate models for dynamically downscaling climate variables at finer spatial and temporal scales. The objective of this study was to evaluate the performance of WRF model for simulating temperature and rainfall over Lake Tana basin in Ethiopia. The WRF model was configured for six experimental setups using three land surface models (LSMs): Noah, RUC and TD; and two land use datasets: USGS and updated New Land Use (NLU). The performances of WRF configurations were assessed by comparing simulated and observed data from March to August 2015. The result showed that temperature and rainfall simulations were sensitive to LSM and land use data choice. The combination of NLU with RUC and TD produced very small cold bias (0.27 °C) and warm bias (0.20 °C) for 2m maximum temperature (Tmax) and 2m minimum temperature (Tmin), respectively. WRF model with RUC and NLU captured well the observed spatial and temporal variability of Tmax, while TD and NLU for Tmin. Moreover, rainfall simulation was better with NLU; especially NLU and Noah configuration produced the smallest mean bias (2.39 mm/day) and root mean square error (6.6 mm/day). All the WRF experiments overestimated light and heavy rainfall events. Overall, findings showed that the application of updated land use data substantially improved the WRF model performance in simulating temperature and rainfall. The study would provide valuable support for identifying suitable LSM and land use data that can accurately predict the climate variables in the Blue Nile basin.

Map Archive Mining: Visual-Analytical Approaches to Explore Large Historical Map Collections.

Historical maps are unique sources of retrospective geographical information. Recently, several map archives containing map series covering large spatial and temporal extents have been systematically scanned and made available to the public. The geographical information contained in such data archives makes it possible to extend geospatial analysis retrospectively beyond the era of digital cartography. However, given the large data volumes of such archives (e.g., more than 200,000 map sheets in the United States Geological Survey topographic map archive) and the low graphical quality of older, manually-produced map sheets, the process to extract geographical information from these map archives needs to be automated to the highest degree possible. To understand the potential challenges (e.g., salient map characteristics and data quality variations) in automating large-scale information extraction tasks for map archives, it is useful to efficiently assess spatio-temporal coverage, approximate map content, and spatial accuracy of georeferenced map sheets at different map scales. Such preliminary analytical steps are often neglected or ignored in the map processing literature but represent critical phases that lay the foundation for any subsequent computational processes including recognition. Exemplified for the United States Geological Survey topographic map and the Sanborn fire insurance map archives, we demonstrate how such preliminary analyses can be systematically conducted using traditional analytical and cartographic techniques, as well as visual-analytical data mining tools originating from machine learning and data science.

Association between trace elements in the environment and stroke risk: The reasons for geographic and racial differences in stroke (REGARDS) study.

The disparities in stroke mortality between blacks and whites, as well as the increased stroke mortality in the "stroke belt" have long been noted. The reasons for these disparities have yet to be fully explained. The association between trace element status and cardiovascular diseases, including stroke, has been suggested as a possible contributor to the disparities in stroke mortality but has not been fully explored. The purpose of this study is to investigate distributions of four trace elements (arsenic, mercury, magnesium, and selenium) in the environment in relation to stroke risk. The study population (N=27,770) is drawn from the Reasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort. Environmental distribution of each trace element was determined using data from the United States Geological Survey (USGS) and was categorized in quartiles. A proportional hazards model, adjusted for demographic data and stroke risk factors, was used to examine the association of interest. The results showed that higher selenium levels in the environment were associated with increased stroke risk, and the hazard ratio for the 4th quartile compared to the 1st quartile was 1.33 (95% CI: 1.09, 1.62). However, there was no statistically significant relationship between environmental arsenic, mercury or magnesium and the risk of stroke. Because of dietary and non-dietary exposure as well as bioavailability, further research using biomarkers is warranted to examine the association between these trace elements and the risk of stroke.

Predicting Posttraumatic Stress Symptom Prevalence and Local Distribution after an Earthquake with Scarce Data.

BACKGROUND: After a major earthquake, the assignment of scarce mental health emergency personnel to different geographic areas is crucial to the effective management of the crisis. The scarce information that is available in the aftermath of a disaster may be valuable in helping predict where are the populations that are in most need. OBJECTIVE: The objectives of this study were to derive algorithms to predict posttraumatic stress (PTS) symptom prevalence and local distribution after an earthquake and to test whether there are algorithms that require few input data and are still reasonably predictive. METHODS: A rich database of PTS symptoms, informed after Chile's 2010 earthquake and tsunami, was used. Several model specifications for the mean and centiles of the distribution of PTS symptoms, together with posttraumatic stress disorder (PTSD) prevalence, were estimated via linear and quantile regressions. The models varied in the set of covariates included. RESULTS: Adjusted R2 for the most liberal specifications (in terms of numbers of covariates included) ranged from 0.62 to 0.74, depending on the outcome. When only including peak ground acceleration (PGA), poverty rate, and household damage in linear and quadratic form, predictive capacity was still good (adjusted R2 from 0.59 to 0.67 were obtained). CONCLUSIONS: Information about local poverty, household damage, and PGA can be used as an aid to predict PTS symptom prevalence and local distribution after an earthquake. This can be of help to improve the assignment of mental health personnel to the affected localities. Dussaillant F , Apablaza M . Predicting posttraumatic stress symptom prevalence and local distribution after an earthquake with scarce data. Prehosp Disaster Med. 2017;32(4):357-367.

Minimally invasive treatments for perforator vein insufficiency.

Incompetent superficial veins are the most common cause of lower extremity superficial venous reflux and varicose veins; however, incompetent or insufficient perforator veins are the most common cause of recurrent varicose veins after treatment, often unrecognized. Perforator vein insufficiency can result in pain, skin changes, and skin ulcers, and often merit intervention. Minimally invasive treatments have replaced traditional surgical treatments for incompetent perforator veins. Current minimally invasive treatment options include ultrasound guided sclerotherapy (USGS) and endovascular thermal ablation (EVTA) with either laser or radiofrequency energy sources. Advantages and disadvantages of each modality and knowledge on these treatments are required to adequately address perforator venous disease.

Disaster Metrics: Evaluation of de Boer's Disaster Severity Scale (DSS) Applied to Earthquakes.

INTRODUCTION: Quantitative measurement of the medical severity following multiple-casualty events (MCEs) is an important goal in disaster medicine. In 1990, de Boer proposed a 13-point, 7-parameter scale called the Disaster Severity Scale (DSS). Parameters include cause, duration, radius, number of casualties, nature of injuries, rescue time, and effect on surrounding community. Hypothesis This study aimed to examine the reliability and dimensionality (number of salient themes) of de Boer's DSS scale through its application to 144 discrete earthquake events. METHODS: A search for earthquake events was conducted via National Oceanic and Atmospheric Administration (NOAA) and US Geological Survey (USGS) databases. Two experts in the field of disaster medicine independently reviewed and assigned scores for parameters that had no data readily available (nature of injuries, rescue time, and effect on surrounding community), and differences were reconciled via consensus. Principle Component Analysis was performed using SPSS Statistics for Windows Version 22.0 (IBM Corp; Armonk, New York USA) to evaluate the reliability and dimensionality of the DSS. RESULTS: A total of 144 individual earthquakes from 2003 through 2013 were identified and scored. Of 13 points possible, the mean score was 6.04, the mode = 5, minimum = 4, maximum = 11, and standard deviation = 2.23. Three parameters in the DSS had zero variance (ie, the parameter received the same score in all 144 earthquakes). Because of the zero contribution to variance, these three parameters (cause, duration, and radius) were removed to run the statistical analysis. Cronbach's alpha score, a coefficient of internal consistency, for the remaining four parameters was found to be robust at 0.89. Principle Component Analysis showed uni-dimensional characteristics with only one component having an eigenvalue greater than one at 3.17. The 4-parameter DSS, however, suffered from restriction of scoring range on both parameter and scale levels. CONCLUSION: Jan de Boer's DSS in its 7-parameter format fails to hold statistically in a dataset of 144 earthquakes subjected to analysis. A modified 4-parameter scale was found to quantitatively assess medical severity more directly, but remains flawed due to range restriction on both individual parameter and scale levels. Further research is needed in the field of disaster metrics to develop a scale that is reliable in its complete set of parameters, capable of better fine discrimination, and uni-dimensional in measurement of the medical severity of MCEs.

USGS48 Puerto Rico precipitation - a new isotopic reference material for δ2H and δ18O measurements of water.

A new secondary isotopic reference material has been prepared from Puerto Rico precipitation, which was filtered, homogenised, loaded into glass ampoules, sealed with a torch, autoclaved to eliminate biological activity, and calibrated by dual-inlet isotope-ratio mass spectrometry. This isotopic reference material, designated as USGS48, is intended to be one of two isotopic reference waters for daily normalisation of stable hydrogen (δ(2)H) and stable oxygen (δ(18)O) isotopic analysis of water with a mass spectrometer or a laser absorption spectrometer. The δ(2)H and δ(18)O values of this reference water are-2.0±0.4 and-2.224±0.012 ‰, respectively, relative to Vienna Standard Mean Ocean Water on scales normalised such that the δ(2)H and δ(18)O values of Standard Light Antarctic Precipitation reference water are-428 and-55.5 ‰, respectively. Each uncertainty is an estimated expanded uncertainty (U=2u(c)) about the reference value that provides an interval that has about a 95 % probability of encompassing the true value. This isotopic reference water is available by the case of 144 glass ampoules containing 5 mL of water in each ampoule.

Environmental risk analysis of hazardous material rail transportation.

An important aspect of railroad environmental risk management involves tank car transportation of hazardous materials. This paper describes a quantitative, environmental risk analysis of rail transportation of a group of light, non-aqueous-phase liquid (LNAPL) chemicals commonly transported by rail in North America. The Hazardous Materials Transportation Environmental Consequence Model (HMTECM) was used in conjunction with a geographic information system (GIS) analysis of environmental characteristics to develop probabilistic estimates of exposure to different spill scenarios along the North American rail network. The risk analysis incorporated the estimated clean-up cost developed using the HMTECM, route-specific probability distributions of soil type and depth to groundwater, annual traffic volume, railcar accident rate, and tank car safety features, to estimate the nationwide annual risk of transporting each product. The annual risk per car-mile (car-km) and per ton-mile (ton-km) was also calculated to enable comparison between chemicals and to provide information on the risk cost associated with shipments of these products. The analysis and the methodology provide a quantitative approach that will enable more effective management of the environmental risk of transporting hazardous materials.

Temporal evolution of depth-stratified groundwater salinity in municipal wells in the major aquifers in Texas, USA.

We assessed spatial distribution of total dissolved solids (TDS) in shallow (<50 m), intermediate (50-150 m), and deep (>150 m) municipal (domestic and public supply) wells in nine major aquifers in Texas for the 1960s-1970s and 1990s-2000s periods using geochemical data obtained from the Texas Water Development Board. For both time periods, the highest median groundwater TDS concentrations in shallow wells were found in the Ogallala and Pecos Valley aquifers and that in the deep wells were found in the Trinity aquifer. In the Ogallala, Pecos Valley, Seymour and Gulf Coast aquifers, >60% of observations from shallow wells exceeded the secondary maximum contaminant level (SMCL) for TDS (500 mg L(-1)) in both time periods. In the Trinity aquifer, 72% of deep water quality observations exceeded the SMCL in the 1990s-2000s as compared to 64% observations in the 1960s-1970s. In the Ogallala, Edwards-Trinity (plateau), and Edwards (Balcones Fault Zone) aquifers, extent of salinization decreased significantly (p<0.05) with well depth, indicating surficial salinity sources. Geochemical ratios revealed strong adverse effects of chloride (Cl(-)) and sulfate (SO4(2-)) on groundwater salinization throughout the state. Persistent salinity hotspots were identified in west (southern Ogallala, north-west Edwards-Trinity (plateau) and Pecos Valley aquifers), north central (Trinity-downdip aquifer) and south (southern Gulf Coast aquifer) Texas. In west Texas, mixed cation SO4-Cl facies led to groundwater salinization, as compared to Na-Cl facies in the southern Gulf Coast, and Ca-Na-HCO3 and Na-HCO3 facies transitioning to Na-Cl facies in the Trinity-downdip regions. Groundwater mixing ensuing from cross-formational flow, seepage from saline plumes and playas, evaporative enrichment, and irrigation return flow had led to progressive groundwater salinization in west Texas, as compared to ion-exchange processes in the north-central Texas, and seawater intrusion coupled with salt dissolution and irrigation return flow in the southern Gulf Coast regions.