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Climate risk is a consequence of climate hazards, exposure, and the vulnerability (IPCC 2014). Here, we assess future (2040–2049) climate risk for the entire contiguous US at the county level with a novel climate risk index integrating multiple hazards, exposures and vulnerabilities. Future, weather and climate hazards are characterized as frequency of heat wave, cold spells, dryer, and heavy precipitation events along with anomalies of temperature and precipitation using high resolution (4 km) downscaled climate projections. Exposure is characterized by projections of population, infrastructure, and built surfaces prone to multiple hazards including sea level rise and storm surges. Vulnerability is characterized by projections of demographic groups most sensitive to climate hazards. We found Florida, California, the central Gulf Coast, and North Atlantic at high climate risk in the future. However, the contributions to this risk vary regionally. Florida is projected to be equally hard hit by the three components of climate risk. The coastal counties in the Gulf states of Louisiana, Texas, Mississippi and Alabama are at high climate risk due to high exposure and hazard. High exposure and vulnerability drive high climate risk in California counties. This approach can guide planners in targeting counties at most risk and where adaptation strategies to reduce exposure or protect vulnerable populations might be best applied.

Climate change is one of the most challenging geophysical science and policy issues in modern times. The combined anthropogenic and natural forcing on the climate has profound impacts on the major spheres of the Earth system. Scholarly analysis has also revealed a cascading array of effects on the socioeconomic and political fabric. One of the more subtle effects of climate change is how it may affect certain sub-groups of people. Herein, we draw upon the literature to present the case for why African Americans are particularly vulnerable to climate change. While the focus is on one specific racial group, it is important to note that many of these findings may apply to an array of under-represented or underserved groups.

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This manuscript has been co-authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paidup, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/ downloads/doe-public-access-plan).

Accurately measuring water use by the economy is essential for developing reliable models of water resource availability. Indeed, these models rely on retrospective analyses that provide insights into shifting human population demands and adaptions to water shortages. However, accurate, methodologically consistent, empirically authentic, and spatiotemporally comprehensive historical datasets for water withdrawals are scarce. Herein, we present a reanalysis of annual resolution (1950–2016) historical data set on irrigation, electric power, and public supply water withdrawal within the conterminous United States (US) at the county‐level, and, for power plants, at the site‐level. To estimate electric power water use, we synthesized a historically comprehensive list of generators and historic patterns in generation across fuels, prime movers, and cooling technologies. Irrigation water use estimation required building a crop‐demand model that utilized historical information on irrigated acreage for crops and golf courses, stage‐specific crop water demand, and climate information. To estimate public water supply use, we developed a random forest model constructed from information on population, infrastructure, climate, and land cover. These estimates generally agree with total county and state water use information provided by the US Geological Survey (USGS) water use circular and estimates generated from independent studies for specific years. However, we also observed discrepancies between our estimates and USGS data that appear to be caused by inconsistencies in the methods used by the USGS's primary data sources at the state level over decades of data collection, highlighting the importance of reanalysis to yield spatiotemporally consistent and intercomparable estimates of water use.

Objectives: The purpose of this study was to assess microbial load and Methicillin Resistant Staphylococcus aureus from surfaces of public transport vehicle. Methods: The surfaces of public transport vehicle were sampled by swabbing. A total of 56 samples from 28 different vehicles operating in Kathmandu valley were collected and processed according to the standard methodology. The isolates were identified by culture, biochemical tests and subjected to antimicrobial susceptibility testing by modified Kirby-Bauer disk diffusion method following CLSI 2013 guidelines. Methicillin resistant species of Staphylococcus were detected by the virtue of cefoxitin resistance. Results: All 56 samples from the 28 different vehicles were found to have bacterial growth with average bacterial load of 2.47±1.22 x 105 CFU/cm2. The gas vehicles were found to be the most contaminated. Out of 56 samples, 35 (25.9%) were found to be S. aureus growth positive 11 (31.4%) of them being MRSA. Conclusion: The high flow of people with different health conditions in public transport makes the exchange of microorganism more significant. High bacterial load along with MRSA indicates the threats of transmission of infection among travellers. This is of a great public health concern as the mass population of different health condition is in direct exposure and is prone to get infected.

Background: Nasal sprays are used to deliver the medications locally to the nasal cavity. The majority of patients have been observed to perform nasal spray use techniques inadequately. This study was conducted to evaluate the impact of the intervention on nasal spray use technique. Methods: This was a prospective pre-and post-interventional study to evaluate the nasal spray use technique among the subjects with the help of nasal spray checklist. A standardized WHO nasal spray checklist was used on the study conducted in Manipal Teaching Hospital, Pokhara, Nepal from July to October 2019. Subjects were asked to demonstrate the technique and a scoring system was applied before and after the intervention by the researcher. The total score of the intervention technique ranges from 0 to 11. After evaluation of the technique at the first visit, subjects were provided with an informative leaflet having all the steps to be followed to use the spray and the technique was re-evaluated after 10 days. Results: A total of 81 subjects (51.9% male and 48.1% female) participated in the study. The average duration of nasal drug use was 15 days. The overall mean±SD score was 4.31 ±1.625 before intervention and 9.84±1.699 after intervention. After the intervention, the percentage of subjects using the nasal spray correctly increased by 50.27%. Wilcoxon signed rank test showed intervention on nasal spray use technique was effective (p=0.0001). Conclusion: The nasal spray use technique was poor among the subjects before the intervention. The intervention was substantially effective in improving the technique to use the nasal spray. Regular assessment and reinforcement of correct technique by health professionals will improve the proper use technique of nasal spray, hence increasing the effectiveness of the therapy.