Prediction Accuracy of SNP Epistasis Models Generated by Multifactor Dimensionality Reduction and Stepwise Penalized Logistic Regression

Conventional statistical modeling techniques, used to detect high-order interactions between SNPs, lead to issues with high-dimensionality due to the number of interactions which need to be evaluated using sparse data. Statisticians have developed novel methods Multifactor Dimensionality Reduction (MDR), Generalized Multifactor Dimensionality Reduction (GMDR), and stepwise Penalized Logistic Regression (stepPLR) to analyze SNP epistasis associated with the development of or outcomes for genetic disease. Due to inconsistencies in published results regarding the performance of these three methods, this thesis used data from the very large GenIMS study to compare the prediction accuracies of 90-day mortality in SNP epistasis models. Comparisons were made using prediction accuracy, sensitivity, specificity, model consistency, chi-square tests, sign tests, and biological plausibility. Testing accuracies were generally higher for GMDR compared to MDR, and stepPLR yielded substandard performance since the models predicted that all subjects were alive at ninety days. Stepwise PLR, however, determined that IL-1A SNPs IL1A_M889, rs1894399, rs1878319, and rs2856837 were each significant predictors of 90-day mortality when adjusting for the other SNPs in the model. In addition, the model included a borderline significant, second-order interaction between rs28556838 and rs3783520 associated with 90-day mortality in a cohort of patients hospitalized with community-acquired pneumonia (CAP). The public health importance of this thesis is that the relative risk for CAP may be higher for a set of SNPs across different genes. The ability to predict which patients will experience a poor outcome may lead to more effective prevention strategies or treatments at earlier stages. Furthermore, identification of significant SNP interactions can also expand the scientific knowledge about biological mechanisms affecting disease outcomes. Altogether, the GMDR method yielded higher prediction accuracies than MDR, and MDR performed better than stepPLR when establishing SNP epistasis models associated with 90-day mortality in the GenIMS cohort

Struggling While Managing Chronic Illness

Although research documenting the struggling response to chronic illness would assist nurses in understanding their patients and potentially in the assessment and support of struggling patients, such research is only in the infancy stage. The purpose of this research study was to address the rarity of literature describing and defining the concept of families struggling while managing chronic illness. Using Strauss and Corbin\u27s paradigm model and grounded theory methodology, the researcher analyzed interviews with nine rural families managing chronic illness. The analysis revealed that families managing chronic illness struggled with everyday living, to obtain a diagnosis, with spiritual beliefs, and with cognitive and existential thoughts, encompassing mind, body and spirit struggles. Struggling occurred within and between individuals and groups. A thought process, more specifically, an awareness, interpretation, deciphering of meaning, or perception was a strong component of the struggling experience. The core phenomenon identified was struggling, which was preceded by the causal conditions perceiving uncertainty and/or vulnerability and ascribing negative meaning to illness management. Struggling occurred within the context of managing chronic illness. Intervening conditions for struggling were ineffective adapting and adapting. Action/ interaction strategies for struggling were denying, emphasizing loss, fostering independence, strengthening relationships, and turning to faith. Consequences of the action/interaction strategies were stagnating and reintegrating. In light of this study\u27s findings, struggling while managing chronic illness is defined as the perception of a difficult process (e.g., a battle, conflict, strenuous effort, or task) while managing chronic illness. The perception of great difficulty is often preceded by perception of vulnerability or uncertainty and/or ascribing negative meaning to chronic illness management. The difficult process can occur within the body, mind, or spirit of a person or group of persons. The understanding of struggling as a perception makes it relatable to other literature exploring perceptions, representations, and ascribed meanings of not only illness experiences, but also other experiences, such as pain and treatments. Nurses can help those managing chronic illness identify its associated perceptions and representations, which in some cases is struggling

Changing Trends in the Undergraduate Fraternity/Sorority Experience: An Evaluative and Analytical Literature Review

Fraternal organizations in American institutions of higher education have a significant influence on student life and campus culture. Historically, research has shown that fraternities and sororities provide environments that support negative and often illegal activities that can be detrimental to individuals and communities at large. However, recent research has identified new trends that suggest this may be changing. This article identifies these trends and implications

The value of monitoring wildlife roadkill

The number of wildlife-vehicle collisions has an obvious value in estimating the direct effects of roads on wildlife, i.e. mortality due to vehicle collisions. Given the nature of the data—species identification and location—there is, however, much wider ecological knowledge that can be gained by monitoring wildlife roadkill. Here, we review the added value and opportunities provided by these data, through a series of case studies where such data have been instrumental in contributing to the advancement of knowledge in species distributions, population dynamics, and animal behaviour, as well as informing us about health of the species and of the environment. We propose that consistently, systematically, and extensively monitoring roadkill facilitates five critical areas of ecological study: (1) monitoring of roadkill numbers, (2) monitoring of population trends, (3) mapping of native and invasive species distributions, (4) animal behaviour, and (5) monitoring of contaminants and disease. The collection of such data also offers a valuable opportunity for members of the public to be directly involved in scientific data collection and research (citizen science). Through continuing to monitor wildlife roadkill, we can expand our knowledge across a wide range of ecological research areas, as well as facilitating investigations that aim to reduce both the direct and indirect effects of roads on wildlife populations

Estimating the impact of city-wide Aedes aegypti population control: An observational study in Iquitos, Peru.

During the last 50 years, the geographic range of the mosquito Aedes aegypti has increased dramatically, in parallel with a sharp increase in the disease burden from the viruses it transmits, including Zika, chikungunya, and dengue. There is a growing consensus that vector control is essential to prevent Aedes-borne diseases, even as effective vaccines become available. What remains unclear is how effective vector control is across broad operational scales because the data and the analytical tools necessary to isolate the effect of vector-oriented interventions have not been available. We developed a statistical framework to model Ae. aegypti abundance over space and time and applied it to explore the impact of citywide vector control conducted by the Ministry of Health (MoH) in Iquitos, Peru, over a 12-year period. Citywide interventions involved multiple rounds of intradomicile insecticide space spray over large portions of urban Iquitos (up to 40% of all residences) in response to dengue outbreaks. Our model captured significant levels of spatial, temporal, and spatio-temporal variation in Ae. aegypti abundance within and between years and across the city. We estimated the shape of the relationship between the coverage of neighborhood-level vector control and reductions in female Ae. aegypti abundance; i.e., the dose-response curve. The dose-response curve, with its associated uncertainties, can be used to gauge the necessary spraying effort required to achieve a desired effect and is a critical tool currently absent from vector control programs. We found that with complete neighborhood coverage MoH intra-domicile space spray would decrease Ae. aegypti abundance on average by 67% in the treated neighborhood. Our framework can be directly translated to other interventions in other locations with geolocated mosquito abundance data. Results from our analysis can be used to inform future vector-control applications in Ae. aegypti endemic areas globally

Body size data collected non-invasively from drone images indicate a morphologically distinct Chilean blue whale (Blaenoptera musculus) taxon

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Leslie, M. S., Perkins-Taylor, C. M., Durban, J. W., Moore, M. J., Miller, C. A., Chanarat, P., Bahamonde, P., Chiang, G., & Apprill, A. Body size data collected non-invasively from drone images indicate a morphologically distinct Chilean blue whale (Blaenoptera musculus) taxon. Endangered Species Research, 43, (2020): 291-304, https://doi.org/10.3354/esr01066.The blue whale Balaenoptera musculus (Linnaeus, 1758) was the target of intense commercial whaling in the 20th century, and current populations remain drastically below pre-whaling abundances. Reducing uncertainty in subspecific taxonomy would enable targeted conservation strategies for the recovery of unique intraspecific diversity. Currently, there are 2 named blue whale subspecies in the temperate to polar Southern Hemisphere: the Antarctic blue whale B. m. intermedia and the pygmy blue whale B. m. brevicauda. These subspecies have distinct morphologies, genetics, and acoustics. In 2019, the Society for Marine Mammalogy’s Committee on Taxonomy agreed that evidence supports a third (and presently unnamed) subspecies of Southern Hemisphere blue whale subspecies, the Chilean blue whale. Whaling data indicate that the Chilean blue whale is intermediate in body length between pygmy and Antarctic blue whales. We collected body size data from blue whales in the Gulfo Corcovado, Chile, during the austral summers of 2015 and 2017 using aerial photogrammetry from a remotely controlled drone to test the hypothesis that the Chilean blue whale is morphologically distinct from other Southern Hemisphere blue whale subspecies. We found the Chilean whale to be morphologically intermediate in both overall body length and relative tail length, thereby joining other diverse data in supporting the Chilean blue whale as a unique subspecific taxon. Additional photogrammetry studies of Antarctic, pygmy, and Chilean blue whales will help examine unique morphological variation within this species of conservation concern. To our knowledge, this is the first non-invasive small drone study to test a hypothesis for systematic biology.We are thankful to Foundation MERI (Melimoyu Ecosystem Research Institute) for logistical and funding support. Cruise support in 2017 was provided by the Dalio Foundation (now ‘OceanX’)

Calling in sick: Impacts of fever on intra-urban human mobility

© 2016 The Author(s) Published by the Royal Society. All rights reserved. Pathogens inflict a wide variety of disease manifestations on their hosts, yet the impacts of disease on the behaviour of infected hosts are rarely studied empirically and are seldom accounted for in mathematical models of transmission dynamics. We explored the potential impacts of one of the most common disease manifestations, fever, on a key determinant of pathogen transmission, host mobility, in residents of the Amazonian city of Iquitos, Peru. We did so by comparing two groups of febrile individuals (dengue-positive and dengue-negative) with an afebrile control group. A retrospective, semi-structured interview allowed us to quantify multiple aspects of mobility during the two-week period preceding each interview. We fitted nested models of each aspect of mobility to data from interviews and compared models using likelihood ratio tests to determine whether there were statistically distinguishable differences in mobility attributable to fever or its aetiology. Compared with afebrile individuals, febrile study participants spent more time at home, visited fewer locations, and, in some cases, visited locations closer to home and spent less time at certain types of locations. These multifaceted impacts are consistent with the possibility that disease-mediated changes in host mobility generate dynamic and complex changes in host contact network structure

Dengue illness impacts daily human mobility patterns in Iquitos, Peru

Background Human mobility plays a central role in shaping pathogen transmission by generating spatial and/or individual variability in potential pathogen-transmitting contacts. Recent research has shown that symptomatic infection can influence human mobility and pathogen transmission dynamics. Better understanding the complex relationship between symptom severity, infectiousness, and human mobility requires quantification of movement patterns throughout infectiousness. For dengue virus (DENV), human infectiousness peaks 0–2 days after symptom onset, making it paramount to understand human movement patterns from the beginning of illness. Methodology and principal findings Through community-based febrile surveillance and RT-PCR assays, we identified a cohort of DENV+ residents of the city of Iquitos, Peru (n = 63). Using retrospective interviews, we measured the movements of these individuals when healthy and during each day of symptomatic illness. The most dramatic changes in mobility occurred during the first three days after symptom onset; individuals visited significantly fewer locations (Wilcoxon test, p = 0.017) and spent significantly more time at home (Wilcoxon test, p = 0.005), compared to when healthy. By 7–9 days after symptom onset, mobility measures had returned to healthy levels. Throughout an individual’s symptomatic period, the day of illness and their subjective sense of well-being were the most significant predictors for the number of locations and houses they visited. Conclusions/Significance Our study is one of the first to collect and analyze human mobility data at a daily scale during symptomatic infection. Accounting for the observed changes in human mobility throughout illness will improve understanding of the impact of disease on DENV transmission dynamics and the interpretation of public health-based surveillance data

Disease-driven Reduction in Human Mobility Influences Human-Mosquito Contacts and Dengue Transmission Dynamics

Heterogeneous exposure to mosquitoes determines an individual’s contribution to vector-borne pathogen transmission. Particularly for dengue virus (DENV), there is a major difficulty in quantifying human-vector contacts due to the unknown coupled effect of key heterogeneities. To test the hypothesis that the reduction of human out-of-home mobility due to dengue illness will significantly influence population-level dynamics and the structure of DENV transmission chains, we extended an existing modeling framework to include social structure, disease-driven mobility reductions, and heterogeneous transmissibility from different infectious groups. Compared to a baseline model, naïve to human pre-symptomatic infectiousness and disease-driven mobility changes, a model including both parameters predicted an increase of 37% in the probability of a DENV outbreak occurring; a model including mobility change alone predicted a 15.5% increase compared to the baseline model. At the individual level, models including mobility change led to a reduction of the importance of out-of-home onward transmission (R, the fraction of secondary cases predicted to be generated by an individual) by symptomatic individuals (up to -62%) at the expense of an increase in the relevance of their home (up to +40%). An individual’s positive contribution to R could be predicted by a GAM including a non-linear interaction between an individual’s biting suitability and the number of mosquitoes in their home (\u3e10 mosquitoes and 0.6 individual attractiveness significantly increased R). We conclude that the complex fabric of social relationships and differential behavioral response to dengue illness cause the fraction of symptomatic DENV infections to concentrate transmission in specific locations, whereas asymptomatic carriers (including individuals in their pre-symptomatic period) move the virus throughout the landscape. Our findings point to the difficulty of focusing vector control interventions reactively on the home of symptomatic individuals, as this approach will fail to contain virus propagation by visitors to their house and asymptomatic carriers