ASU Scholarship Showcase

Background: Hemorrhagic fever with renal syndrome (HFRS), a rodent-borne infectious disease, is one of the most serious public health threats in China. Increasing our understanding of the spatial and temporal patterns of HFRS infections could guide local prevention and control strategies.

Methodology/Principal Findings: We employed statistical models to analyze HFRS case data together with environmental data from the Dongting Lake district during 2005–2010. Specifically, time-specific ecologic niche models (ENMs) were used to quantify and identify risk factors associated with HFRS transmission as well as forecast seasonal variation in risk across geographic areas. Results showed that the Maximum Entropy model provided the best predictive ability (AUC = 0.755). Time-specific Maximum Entropy models showed that the potential risk areas of HFRS significantly varied across seasons. High-risk areas were mainly found in the southeastern and southwestern areas of the Dongting Lake district. Our findings based on models focused on the spring and winter seasons showed particularly good performance. The potential risk areas were smaller in March, May and August compared with those identified for June, July and October to December. Both normalized difference vegetation index (NDVI) and land use types were found to be the dominant risk factors.

Conclusions/Significance: Our findings indicate that time-specific ENMs provide a useful tool to forecast the spatial and temporal risk of HFRS.

We conducted a 12-month-long experiment in a financial services company to study how the availability of treadmill workstations affects employees’ physical activity and work performance. We enlisted sedentary volunteers, half of whom received treadmill workstations during the first two months of the study and the rest in the seventh month of the study. Participants could operate the treadmills at speeds of 0–2 mph and could use a standard chair-desk arrangement at will. (a) Weekly online performance surveys were administered to participants and their supervisors, as well as to all other sedentary employees and their supervisors. Using within-person statistical analyses, we find that overall work performance, quality and quantity of performance, and interactions with coworkers improved as a result of adoption of treadmill workstations. (b) Participants were outfitted with accelerometers at the start of the study. We find that daily total physical activity increased as a result of the adoption of treadmill workstations.

Background:
Pandemic influenza is said to 'shift mortality' to younger age groups; but also to spare a subpopulation of the elderly population. Does one of these effects dominate? Might this have important ramifications?

Methods: We estimated age-specific excess mortality rates for all-years for which data were available in the 20th century for Australia, Canada, France, Japan, the UK, and the USA for people older than 44 years of age. We modeled variation with age, and standardized estimates to allow direct comparison across age groups and countries. Attack rate data for four pandemics were assembled.

Results: For nearly all seasons, an exponential model characterized mortality data extremely well. For seasons of emergence and a variable number of seasons following, however, a subpopulation above a threshold age invariably enjoyed reduced mortality. 'Immune escape', a stepwise increase in mortality among the oldest elderly, was observed a number of seasons after both the A(H2N2) and A(H3N2) pandemics. The number of seasons from emergence to escape varied by country. For the latter pandemic, mortality rates in four countries increased for younger age groups but only in the season following that of emergence. Adaptation to both emergent viruses was apparent as a progressive decrease in mortality rates, which, with two exceptions, was seen only in younger age groups. Pandemic attack rate variation with age was estimated to be similar across four pandemics with very different mortality impact.

Conclusions: In all influenza pandemics of the 20th century, emergent viruses resembled those that had circulated previously within the lifespan of then-living people. Such individuals were relatively immune to the emergent strain, but this immunity waned with mutation of the emergent virus. An immune subpopulation complicates and may invalidate vaccine trials. Pandemic influenza does not 'shift' mortality to younger age groups; rather, the mortality level is reset by the virulence of the emerging virus and is moderated by immunity of past experience. In this study, we found that after immune escape, older age groups showed no further mortality reduction, despite their being the principal target of conventional influenza vaccines. Vaccines incorporating variants of pandemic viruses seem to provide little benefit to those previously immune. If attack rates truly are similar across pandemics, it must be the case that immunity to the pandemic virus does not prevent infection, but only mitigates the consequences.

Traditionally, hazardous chemicals have been regulated in the U.S. on a one-by-one basis, an approach that is slow, expensive and can be inefficient, as illustrated by a decades-long succession of replacing one type of organohalogen flame retardants (OHFRs) with another one, without addressing the root cause of toxicity and associated public health threats posed. The present article expounds on the need for efficient monitoring strategies and pragmatic steps in reducing environmental pollution and adverse human health impacts. A promising approach is to combine specific bioassays with state-of-the-art chemical screening to identify chemicals and chemical mixtures sharing specific modes of action (MOAs) and pathways of toxicity (PoTs). This approach could be used to identify and regulate hazardous chemicals as classes or compound families, featuring similar biological end-points, such as endocrine disruption and mutagenicity. Opportunities and potential obstacles of implementing this approach are discussed.

Processed municipal sewage sludges (MSS) are an abundant, unwanted by-product of wastewater treatment, increasingly applied to agriculture and forestry for inexpensive disposal and soil conditioning. Due to their high organic carbon and lipid contents, MSS not only is rich in carbon and nutrients but also represents a “sink” for recalcitrant, hydrophobic, and potentially bioaccumulative compounds. Indeed, many organics sequestered and concentrated in MSS meet the US Environmental Protection Agency’s definition of being persistent, bioaccumulative, and toxic (PBT). In a strategic effort, our research team at the Biodesign Institute has created the National Sewage Sludge Repository (NSSR), a large repository of digested MSSs from 164 wastewater treatment plants from across the USA, as part of the Human Health Observatory (H2O) at Arizona State University (ASU). The NSSR likely represents the largest archive of digested MSS specimens in the USA. The present study summarizes key findings gleaned thus far from analysis of NSSR samples. For example, we evaluated the content of toxicants in MSS and computed estimates of nationwide inventories of mass produced chemicals that become sequestrated in sludge and later are released into the environment during sludge disposal on land. Ongoing efforts document co-occurrence of a variety of PBT compounds in both MSS and human samples, while also identifying a large number of potentially harmful MSS constituents for which human exposure data are still lacking. Finally, we summarize future opportunities and invite collaborative use of the NSSR by the research community. The H2O at ASU represents a new resource and research tool for environmental scientists and the larger research community. As illustrated in this work, this repository can serve to (i) identify and prioritize emerging contaminants, (ii) provide spatial and temporal trends of contaminants, (iii) inform and evaluate the effectiveness of environmental policy-making and regulations, and (iv) approximate, ongoing exposures and body burdens of mass-produced chemicals in human society.

Methicillin resistant Staphylococcus aureus (MRSA) is currently a major cause of skin and soft tissue infections (SSTI) in the United States. Seasonal variation of MRSA infections in hospital settings has been widely observed. However, systematic time-series analysis of incidence data is desirable to understand the seasonality of community acquired (CA)-MRSA infections at the population level. In this paper, using data on monthly SSTI incidence in children aged 0–19 years and enrolled in Medicaid in Maricopa County, Arizona, from January 2005 to December 2008, we carried out time-series and nonlinear regression analysis to determine the periodicity, trend, and peak timing in SSTI incidence in children at different age: 0-4 years, 5-9 years, 10-14 years, and 15-19 years. We also assessed the temporal correlation between SSTI incidence and meteorological variables including average temperature and humidity. Our analysis revealed a strong annual seasonal pattern of SSTI incidence with peak occurring in early September. This pattern was consistent across age groups. Moreover, SSTIs followed a significantly increasing trend over the 4-year study period with annual incidence increasing from 3.36% to 5.55% in our pediatric population of approximately 290,000. We also found a significant correlation between the temporal variation in SSTI incidence and mean temperature and specific humidity. Our findings could have potential implications on prevention and control efforts against CA-MRSA.

The large-scale use of antivirals during influenza pandemics poses a significant selection pressure for drug-resistant pathogens to emerge and spread in a population. This requires treatment strategies to minimize total infections as well as the emergence of resistance. Here we propose a mathematical model in which individuals infected with wild-type influenza, if treated, can develop de novo resistance and further spread the resistant pathogen. Our main purpose is to explore the impact of two important factors influencing treatment effectiveness: i) the relative transmissibility of the drug-resistant strain to wild-type, and ii) the frequency of de novo resistance. For the endemic scenario, we find a condition between these two parameters that indicates whether treatment regimes will be most beneficial at intermediate or more extreme values (e.g., the fraction of infected that are treated). Moreover, we present analytical expressions for effective treatment regimes and provide evidence of its applicability across a range of modeling scenarios: endemic behavior with deterministic homogeneous mixing, and single-epidemic behavior with deterministic homogeneous mixing and stochastic heterogeneous mixing. Therefore, our results provide insights for the control of drug-resistance in influenza across time scales.

The Middle Stone Age (MSA) is associated with early evidence for symbolic material culture and complex technological innovations. However, one of the most visible aspects of MSA technologies are unretouched triangular stone points that appear in the archaeological record as early as 500,000 years ago in Africa and persist throughout the MSA. How these tools were being used and discarded across a changing Pleistocene landscape can provide insight into how MSA populations prioritized technological and foraging decisions. Creating inferential links between experimental and archaeological tool use helps to establish prehistoric tool function, but is complicated by the overlaying of post-depositional damage onto behaviorally worn tools. Taphonomic damage patterning can provide insight into site formation history, but may preclude behavioral interpretations of tool function. Here, multiple experimental processes that form edge damage on unretouched lithic points from taphonomic and behavioral processes are presented. These provide experimental distributions of wear on tool edges from known processes that are then quantitatively compared to the archaeological patterning of stone point edge damage from three MSA lithic assemblages—Kathu Pan 1, Pinnacle Point Cave 13B, and Die Kelders Cave 1. By using a model-fitting approach, the results presented here provide evidence for variable MSA behavioral strategies of stone point utilization on the landscape consistent with armature tips at KP1, and cutting tools at PP13B and DK1, as well as damage contributions from post-depositional sources across assemblages. This study provides a method with which landscape-scale questions of early modern human tool-use and site-use can be addressed.

The known occurrence of pharmaceuticals in the built and natural water environment, including in drinking water supplies, continues to raise concerns over inadvertent exposures and associated potential health risks in humans and aquatic organisms. At the same time, the number and concentrations of new and existing pharmaceuticals in the water environment are destined to increase further in the future as a result of increased consumption of pharmaceuticals by a growing and aging population and ongoing measures to decrease per-capita water consumption. This review examines the occurrence and movement of pharmaceuticals in the built and natural water environment, with special emphasis on contamination of the drinking water supply, and opportunities for sustainable pollution control. We surveyed peer-reviewed publications dealing with quantitative measurements of pharmaceuticals in U.S. drinking water, surface water, groundwater, raw and treated wastewater as well as municipal biosolids. Pharmaceuticals have been observed to reenter the built water environment contained in raw drinking water, and they remain detectable in finished drinking water at concentrations in the ng/L to μg/L range. The greatest promises for minimizing pharmaceutical contamination include source control (for example, inputs from intentional flushing of medications for safe disposal, and sewer overflows), and improving efficiency of treatment facilities.