WATER RESOURCES, HEALTH, AND THE SUSTAINABILITY OF INTERVENTIONS TO ACHIEVE WATER AND SANITATION TARGETS OF THE MILLENNIUM DEVELOPMENT GOALS IN A CHANGING WORLD

This dissertation addresses sustainability of rapid provision of safe water and sanitation required to meet the Millennium Development Goals. Review of health-related literature and global statistics demonstrates engineers\u27 role in achieving the MDGs. This review is followed by analyses relating to social, environmental, and health aspects of meeting MDG targets. Analysis of national indicators showed that inadequate investment, poor or nonexistent policies and governance are challenges to global sanitation coverage in addition to lack of financial resources and gender disparity. Although water availability was not found to be a challenge globally, geospatial analysis demonstrated that water availability is a potentially significant barrier for up to 46 million people living in urban areas and relying on already degraded water resources for environmental income. A daily water balance model incorporating the National Resources Conservation Services curve number method in Bolivian watersheds showed that local water stress is linked to climate change because of reduced recharge. Agricultural expansion in the region slightly exacerbates recharge reductions. Although runoff changes will range from -17% to 14%, recharge rates will decrease under all climate scenarios evaluated (-14% to -27%). Increasing sewer coverage may place stress on the readily accessible natural springs, but increased demand can be sustained if other sources of water supply are developed. This analysis provides a method for hydrological analysis in data scarce regions. Data required for the model were either obtained from publicly available data products or by conducting field work using low-cost methods feasible for local participants. Lastly, a methodology was developed to evaluate public health impacts of increased household water access resulting from domestic rainwater harvesting, incorporating knowledge of water requirements of sanitation and hygiene technologies. In 37 West African cities, domestic rainwater harvesting has the potential to reduce diarrheal disease burden by 9%, if implemented alone with 400 L storage. If implemented in conjunction with point of use treatment, this reduction could increase to 16%. The methodology will contribute to cost-effectiveness evaluations of interventions as well as evaluations of potential disease burden resulting from reduced water supply, such as reductions observed in the Bolivian communities

Regionalization of Hydrologic Response in the Great Lakes Basin: Considerations of Temporal Scales of Analysis

Methods for predicting streamflow in areas with limited or nonexistent measures of hydrologic response commonly rely on regionalization techniques, where knowledge pertaining to gauged watersheds is transferred to ungauged watersheds. Hydrologic response indices have frequently been employed in contemporary regionalization research related to predictions in ungauged basins. In this study, we developed regionalization models using multiple linear regression and regression tree analysis to derive relationships between hydrologic response and watershed physical characteristics for 163 watersheds in the Great Lakes basin. These models provide an empirical means for simulating runoff in ungauged basins at a monthly time step without implementation of a rainfall-runoff model. For the dependent variable in these regression models, we used monthly runoff ratio as the indicator of hydrologic response and defined it at two temporal scales: (1) treating all monthly runoff ratios as individual observations and (2) using the mean of these monthly runoff ratios for each watershed as a representative observation. Application of the models to 62 validation watersheds throughout the Great Lakes basin indicated that model simulations were far more sensitive to the temporal characterization of hydrologic response than to the type of regression technique employed, and that models conditioned on individual monthly runoff ratios (rather than long term mean values) performed better. This finding is important in light of the increased usage of hydrologic response indices in recent regionalization studies. Models using individual observations for the dependent variable generally simulated monthly runoff with reasonable skill in the validation watersheds (median Nash-Sutcliffe efficiency = 0.53, median R2 = 0.66, median absolute value of deviation of runoff volume = 13%). These results suggest the viability of empirical 3 approaches to simulate runoff in ungauged basins. This finding is significant given the many regions of the world with sparse gaging networks and limited resources for gathering the field data required to calibrate rainfall-runoff models

Drivers of understory plant communities in Sierra Nevada mixed conifer forests with pyrodiversity

Background: Fire suppression in western North America increased and homogenized overstory cover in conifer forests, which likely affected understory plant communities. We sought to characterize understory plant communities and their drivers using plot-based observations from two contemporary reference sites in the Sierra Nevada, USA. These sites had long-established natural fire programs, which have resulted in restored natural fire regimes. In this study, we investigated how pyrodiversity—the diversity of fire size, severity, season, and frequency—and other environment factors influenced species composition and cover of forest understory plant communities. Results: Understory plant communities were influenced by a combination of environmental, plot-scale recent fire history, and plot-neighborhood pyrodiversity within 50 m. Canopy cover was inversely proportional to understory plant cover, Simpson’s diversity, and evenness. Species richness was strongly influenced by the interaction of plot-based fire experience and plot-neighborhood pyrodiversity within 50 m. Conclusions: Pyrodiversity appears to contribute both directly and indirectly to diverse understory plant communities in Sierra Nevada mixed conifer forests. The indirect influence is mediated through variability in tree canopy cover, which is partially related to variation in fire severity, while direct influence is an interaction between local and neighborhood fire activity

Prenatal exposure to multiple metallic and metalloid trace elements and the risk of bacterial sepsis in extremely low gestational age newborns: A prospective cohort study

Background Prenatal exposures to metallic and metalloid trace elements have been linked to altered immune function in animal studies, but few epidemiologic studies have investigated immunological effects in humans. We evaluated the risk of bacterial sepsis (an extreme immune response to bacterial infection) in relation to prenatal metal/metalloid exposures, individually and jointly, within a US-based cohort of infants born extremely preterm. Methods We analyzed data from 269 participants in the US-based ELGAN cohort, which enrolled infants delivered at <28 weeks' gestation (2002–2004). Concentrations of 8 trace elements—including 4 non-essential and 4 essential—were measured using inductively coupled plasma tandem mass spectrometry in umbilical cord tissue, reflecting in utero fetal exposures. The infants were followed from birth to postnatal day 28 with bacterial blood culture results reported weekly to detect sepsis. Discrete-time hazard and quantile g-computation models were fit to estimate associations for individual trace elements and their mixtures with sepsis incidence. Results Approximately 30% of the extremely preterm infants developed sepsis during the follow-up period (median follow-up: 2 weeks). After adjustment for potential confounders, no trace element was individually associated with sepsis risk. However, there was some evidence of a non-monotonic relationship for cadmium, with hazard ratios (HRs) for the second, third, and fourth (highest) quartiles being 1.13 (95% CI: 0.51–2.54), 1.94 (95% CI: 0.87–4.32), and 1.88 (95% CI: 0.90–3.93), respectively. The HRs for a quartile increase in concentrations of all 8 elements, all 4 non-essential elements, and all 4 essential elements were 0.92 (95% CI: 0.68–1.25), 1.19 (95% CI: 0.92–1.55), and 0.77 (95% CI: 0.57–1.06). Cadmium had the greatest positive contribution whereas arsenic, copper, and selenium had the greatest negative contributions to the mixture associations. Conclusions We found some evidence that greater prenatal exposure to cadmium was associated with an increased the risk of bacterial sepsis in extremely preterm infants. However, this risk was counteracted by a combination of arsenic, copper, and selenium. Future studies are needed to confirm these findings and to evaluate the potential for nutritional interventions to prevent sepsis in high-risk infants

Development of the InTelligence And Machine LEarning (TAME) Toolkit for Introductory Data Science, Chemical-Biological Analyses, Predictive Modeling, and Database Mining for Environmental Health Research

Research in environmental health is becoming increasingly reliant upon data science and computational methods that can more efficiently extract information from complex datasets. Data science and computational methods can be leveraged to better identify relationships between exposures to stressors in the environment and human disease outcomes, representing critical information needed to protect and improve global public health. Still, there remains a critical gap surrounding the training of researchers on these in silico methods. We aimed to address this gap by developing the inTelligence And Machine lEarning (TAME) Toolkit, promoting trainee-driven data generation, management, and analysis methods to “TAME” data in environmental health studies. Training modules were developed to provide applications-driven examples of data organization and analysis methods that can be used to address environmental health questions. Target audiences for these modules include students, post-baccalaureate and post-doctorate trainees, and professionals that are interested in expanding their skillset to include recent advances in data analysis methods relevant to environmental health, toxicology, exposure science, epidemiology, and bioinformatics/cheminformatics. Modules were developed by study coauthors using annotated script and were organized into three chapters within a GitHub Bookdown site. The first chapter of modules focuses on introductory data science, which includes the following topics: setting up R/RStudio and coding in the R environment; data organization basics; finding and visualizing data trends; high-dimensional data visualizations; and Findability, Accessibility, Interoperability, and Reusability (FAIR) data management practices. The second chapter of modules incorporates chemical-biological analyses and predictive modeling, spanning the following methods: dose-response modeling; machine learning and predictive modeling; mixtures analyses; -omics analyses; toxicokinetic modeling; and read-across toxicity predictions. The last chapter of modules was organized to provide examples on environmental health database mining and integration, including chemical exposure, health outcome, and environmental justice indicators. Training modules and associated data are publicly available online (https://uncsrp.github.io/Data-Analysis-Training-Modules/). Together, this resource provides unique opportunities to obtain introductory-level training on current data analysis methods applicable to 21st century science and environmental health

Geologic predictors of drinking water well contamination in North Carolina

More than 200 million people worldwide, including 11 million in the US, are estimated to consume water containing arsenic (As) concentrations that exceed World Health Organization and US EPA standards. In most cases, the As found in drinking water wells results from interactions between groundwater and geologic materials (geogenic contamination). To that end, we used the NCWELL database, which contains chemical information for 117,960 private drinking wells across North Carolina, to determine the spatial distribution of wells containing As contaminated water within geologic units. Specific geologic units had large percentages (up to 1 in 3) of wells with water exceeding the EPA As maximum contaminant level (MCL, 10 μg/L), both revealing significant variation within areas that have been previously associated with As contamination and identifying as yet unidentified problematic geologic units. For the 19 geologic units that have >5% of wells that contain water with As concentrations in exceedance of 10 μg/L, 12 (63%) are lithogenically related to the Albemarle arc, remnants of an ancient volcanic island, indicating the importance of volcanogenic materials, as well as recycled (eroded and deposited) and metamorphosed volcanogenic material. Within geologic units, wells that have As concentrations exceeding 10 μg/L tended to have pH values greater than wells with As concentrations less than 10 μg/L, emphasizing the importance of the extent of interaction between groundwater and geologic materials. Using census information with the geologic-based exceedance percentages revealed the importance of regional geology on estimates of population at risk compared to estimates based on county boundaries. Results illustrate that relating As contamination to geologic units not only helps explain sources of geogenic contamination but sharpens the identification of communities at risk for exposure and further illuminates problematic areas through geologic interpretation

Great Lakes Runoff Intercomparison Project Phase 3: Lake Erie (GRIP-E)

Hydrologic model intercomparison studies help to evaluate the agility of models to simulate variables such as streamflow, evaporation, and soil moisture. This study is the third in a sequence of the Great Lakes Runoff Intercomparison Projects. The densely populated Lake Erie watershed studied here is an important international lake that has experienced recent flooding and shoreline erosion alongside excessive nutrient loads that have contributed to lake eutrophication. Understanding the sources and pathways of flows is critical to solve the complex issues facing this watershed. Seventeen hydrologic and land-surface models of different complexity are set up over this domain using the same meteorological forcings, and their simulated streamflows at 46 calibration and seven independent validation stations are compared. Results show that: (1) the good performance of Machine Learning models during calibration decreases significantly in validation due to the limited amount of training data; (2) models calibrated at individual stations perform equally well in validation; and (3) most distributed models calibrated over the entire domain have problems in simulating urban areas but outperform the other models in validation

Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK.

BACKGROUND: A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. METHODS: This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. FINDINGS: Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0-75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4-97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; pinteraction=0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8-80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3-4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. INTERPRETATION: ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials. FUNDING: UK Research and Innovation, National Institutes for Health Research (NIHR), Coalition for Epidemic Preparedness Innovations, Bill & Melinda Gates Foundation, Lemann Foundation, Rede D'Or, Brava and Telles Foundation, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midland's NIHR Clinical Research Network, and AstraZeneca

Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK

Background A safe and efficacious vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), if deployed with high coverage, could contribute to the control of the COVID-19 pandemic. We evaluated the safety and efficacy of the ChAdOx1 nCoV-19 vaccine in a pooled interim analysis of four trials. Methods This analysis includes data from four ongoing blinded, randomised, controlled trials done across the UK, Brazil, and South Africa. Participants aged 18 years and older were randomly assigned (1:1) to ChAdOx1 nCoV-19 vaccine or control (meningococcal group A, C, W, and Y conjugate vaccine or saline). Participants in the ChAdOx1 nCoV-19 group received two doses containing 5 × 1010 viral particles (standard dose; SD/SD cohort); a subset in the UK trial received a half dose as their first dose (low dose) and a standard dose as their second dose (LD/SD cohort). The primary efficacy analysis included symptomatic COVID-19 in seronegative participants with a nucleic acid amplification test-positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to treatment received, with data cutoff on Nov 4, 2020. Vaccine efficacy was calculated as 1 - relative risk derived from a robust Poisson regression model adjusted for age. Studies are registered at ISRCTN89951424 and ClinicalTrials.gov, NCT04324606, NCT04400838, and NCT04444674. Findings Between April 23 and Nov 4, 2020, 23 848 participants were enrolled and 11 636 participants (7548 in the UK, 4088 in Brazil) were included in the interim primary efficacy analysis. In participants who received two standard doses, vaccine efficacy was 62·1% (95% CI 41·0–75·7; 27 [0·6%] of 4440 in the ChAdOx1 nCoV-19 group vs71 [1·6%] of 4455 in the control group) and in participants who received a low dose followed by a standard dose, efficacy was 90·0% (67·4–97·0; three [0·2%] of 1367 vs 30 [2·2%] of 1374; pinteraction=0·010). Overall vaccine efficacy across both groups was 70·4% (95·8% CI 54·8–80·6; 30 [0·5%] of 5807 vs 101 [1·7%] of 5829). From 21 days after the first dose, there were ten cases hospitalised for COVID-19, all in the control arm; two were classified as severe COVID-19, including one death. There were 74 341 person-months of safety follow-up (median 3·4 months, IQR 1·3–4·8): 175 severe adverse events occurred in 168 participants, 84 events in the ChAdOx1 nCoV-19 group and 91 in the control group. Three events were classified as possibly related to a vaccine: one in the ChAdOx1 nCoV-19 group, one in the control group, and one in a participant who remains masked to group allocation. Interpretation ChAdOx1 nCoV-19 has an acceptable safety profile and has been found to be efficacious against symptomatic COVID-19 in this interim analysis of ongoing clinical trials