Alun Lloyd

Healthcare-associated infections (HAI) are a significant source of preventable morbidity and mortality. Transmission models for HAI are a cornerstone method to both understand pathogen spread and evaluate control interventions. Models have been particularly helpful in addressing transmission-blocking interventions, for elucidating the connectivity among facilities, and their implications for controlling HAI. Mechanisms underlying antimicrobial resistance, such as co-selection, have received less attention in transmission models. In addition, key metrics������������������such as population-level fitness of resistant bacteria and the effect of resistant traits on fitness������������������are often unknown. This limits our understanding of the complex relationship between antimicrobial drug use and resistance, as well as the effectiveness of interventions aimed at changing drug selection pressure. The objective of this proposal is to develop models that more explicitly address resistance traits and modeling tools that support the identification of transmission sources and pathways for HAI. We will use the models to further identify HAI sources and evaluate and optimize interventions. In particular, we will address the following thematic areas: antimicrobial resistance (A), surveillance (A), genomics (B), and simulation of epidemiological studies (B). We have assembled an interdisciplinary group of researchers with expertise in infectious disease modeling, HAI hospital epidemiology and clinics, applied mathematics, and genomics located at North Carolina State University, Washington University (WU) and University of Tennessee. We plan to build on our previous and current collaborations among this team to: develop modeling approaches for addressing HAI transmission; extend phylodynamics methods; and model antimicrobial resistance dynamics. The CDC-Epi Center at WU and Barnes-Jewish Hospital in St. Louis, Missouri, will be the main source of data. Additionally, we will use nation-level publicly available data sources. We will carry out the following aims: 1) Develop improved approaches for inferring routes of acquisition of HAI and optimizing HAI surveillance and control: We will develop ward- and hospital- level network models that take into account the main routes of HAI acquisition and patient connectivity. We will apply optimization methods to identify environmental sampling protocols and cost-effective control strategies. 2) Phylodynamics to estimate fitness of antimicrobial resistance pathogens: We will apply and refine multi-type birth-death models to explore the fitness effects of a large number of antimicrobial-resistant traits on pathogen phylogenies, and speed the methods to quantify fitness for large numbers of strains, and 3) Multi-scale models for multidrug-resistant organisms: extended-spectrum beta-lactamase (ESBL)- producing Enterobacteriaceae as case study: We will develop both agent- and equation-based models that account for multi-scale dynamics of resistance transmission. This will greatly expand the models������������������ applications for evaluating interventions such as antimicrobial stewardship and rapid testing. Our models and tools will be made available to the broader community.

We will use long-term Ae. aegypti samples from Iquitos, Peru to assess patterns of spatial and temporal change in pyrethroid resistance genes and in genomic differentiation to improve our understanding of this mosquito������������������s population biology and response to human-induced selection. We will use this information and that from ongoing collections of Ae. aegypti to gain insight into the dynamics of pyrethroid resistance evolution and to improve the accuracy of components of a comprehensive and robust simulation model of Ae. aegypti/dengue dynamics. We will use the outcomes of this work to provide research, regulatory, and management communities with information needed to predict the dynamics of a variety of gene drive strategies as well as the spread of resistance to insecticides and gene drives in this arbovirus vector

This project will train undergraduate and graduate students, together with postdoctoral fellows, in creating mathematical models of biological systems and confronting them with biological data. Combining approaches from applied mathematics and statistics, trainees will learn a wide range of modeling and parameter estimation methodologies, producing cohorts of mathematical scientists that have received an interdisciplinary training and who are versed in cutting-edge modeling and statistical techniques.

Our goal is to develop safe, controllable, and effective gene drive technologies that can potentially be applied to eradicate invasive rodent populations on islands. We propose to achieve this by preventing the development of female progeny, thereby reducing population numbers and reproductive capacity. Invasive rodents directly and indirectly cause extinction and endangerment of species on islands globally and represent a major threat to biodiversity. Invasive rodents have these effects by directly preying on native species, out-competing them for resources, and destroying sensitive habitat. Pursuit of this goal is therefore closely aligned with the DARPA-relevant application of maintaining and protecting ecosystem biodiversity. Our proposed research under the Safe Genes program addresses Technical Areas 1 and 3 using three genetic model systems: Escherichia coli, fruit fly, and mouse. Project activities will be in three areas: genetics and reproduction; modeling and risk assessment; and ethics, engagement and communication. Impacts will include findings relevant to mitigating and reversing adverse gene drive effects and public and stakeholder engagement addressing broader concerns of international communities.

Dengue is the most important mosquito-borne viral disease affecting humans. In this project we will develop mathematical models to describe the transmission of dengue virus at the level of a city, paying particular attention to how the spread of the virus is affected by human movement within the city. We will work with researchers based in Iquitos, Peru, who are gathering data on the epidemiology of dengue in their city, the distribution of mosquitoes across the city, and on the patterns of human movement within their city. We shall develop individual-based models that draw upon these three sources of data to provide a mechanistic framework within which we can predict how infection will spread. These models will then be used to assess the likely effects of various control measures aimed at reducing or halting the spread of infection (for instance, spraying of insecticides that target adult mosquitoes, use of larvicides that target immature mosquitoes, or a putative human vaccine). The NC State component of this grant falls under one Project (Project 3: Drivers of Heterogeneities in Dengue Epidemiology, Transmission Dynamics and Control: PI Uriel Kitron, Emory University) of an overarching P01 proposal "Quantifying Heterogeneities in Dengue Virus Transmission Dynamics" (Program Director/PI: Thomas W. Scott, UC Davis).

This IGERT project will create a transformative graduate education program that trains students in technologies needed for manipulating pest genomes as well as methods needed to assess the environmental and social appropriateness of specific products of these manipulations. The concept of genetically manipulating a pest species to destroy or render it benign dates back to the 1940's, and there have been several major successes in using this approach. However, restricted tools of classical genetics limited the broader application of Genetic Pest Management. Recent advances in molecular genetics have provided much more precise techniques for manipulating the genomes of pests, and efforts are now underway for development and potential release of transgenic mosquitoes and transgenic agricultural pest species aimed at achieving Genetic Pest Management. The future of this pest management strategy will be determined by further technological advances, public attitudes to the novel technologies and products involved, and the creativity and wisdom of researchers and policy makers. Although esteemed scientific groups including the U.S. National Academy of Sciences have repeatedly emphasized that risk assessment for transgenic organisms should focus on the specific product and not the process, the legacy of genetically-engineered crop commercialization has made the logic behind this idea obscure to most people, including many scientists. For new applications of genetic engineering to be developed and judged appropriately, diverse social and cultural groups will need to more deeply examine the ramifications of each application. Broadly trained PhDs in biological and social sciences will facilitate this examination and help foster more sophisticated interactions among policy makers, academicians, and members of societies where Genetic Pest Management may be applied. Intellectual Merit of this IGERT derives from the fact that this could become the first graduate program in the world that is specifically training graduate students to understand, build, and assess impacts of transgenic organisms. All students will receive core transdisciplinary training that will encompass ethics, communication, economics, ecology, epidemiology, molecular biology, and population genetics. Each student will use expertise from at least two of these specialties in developing a dissertation. Our program is broad in integrating across diverse disciplines, but maintains the focus of students and faculty by specifically studying a small set of species that are targets for Genetic Pest Management. In each of the first years of the program, we will recruit graduate students in biological and social sciences. Each cohort of about six students, balanced across disciplines, will work together with faculty to choose a single target species as the focus of their dissertations. Focus on single species will challenge both student and faculty to work together, develop a common vocabulary, and understand how each other's disciplines operate. We are developing a set of core courses, which will provide all students with a basic toolkit for working in the field of Genetic Pest Management. Students specializing in the disciplines of a specific course will act as mentors to the other students taking the course. Broader Impacts of this IGERT fall into the following categories: 1) Improvement in the administration and extent of integrated graduate education at NCSU, 2) Impact on US integrated graduate education by evaluating a novel model of such integration, 3) Increased number of students from underrepresented groups that receive interdisciplinary education, 4) Improvement of methodologies for assessing and introducing new technologies, 5) Ph.D.s in biology and social sciences who have tools needed for future interdisciplinary, global work. 6) Education of local communities. Furthermore, most of the target pest species are of importance in poor nations, and we will use existing and newly developed partnerships to set up internships and dissertation projects in th

Improving Robustness of a Tactical Model of Aedes/Dengue dynamics SPECIFIC AIMS Overall goal: To provide the Aedes aegypti/dengue research, regulatory, and management communities with a robust modeling tool that can be used for examining and improving the efficacy and risk assessment of new programs that use current and novel tools for insect management and vaccine deployment. Goal will be achieved by 1) Expanding the spatial scale of the Aedes/dengue model to more fully examine predictions and uncertainty regarding population dynamics, genetics, and epidemiology 2) Conducting field experiments to improve estimation of biological parameters that contribute most to the uncertainty of the model predictions, and 3) Reassessment of uncertainty in a revised model that incorporates new estimates. 4) Testing of the final model based on comparison to spatial Aedes/dengue data from other areas, and Ae. aegypti perturbation and recovery experiments in Iquitos. Definition: A robust model is one that produces accurate predictions under diverse environmental conditions. Premise: 1) Dengue is the most important arboviral disease in the world, and there is currently substantial empirical research aimed at improving existing approaches and developing new tools for its suppression. 2) Robust, biologically-based mathematical models have been used to improve the efficacy of control measures for a number of diseases and pest species, and in assessing the utility and risks of novel management approaches. 3) Aedes/dengue interactions involve fewer species than in most other significant vector-borne human diseases, increasing the feasibility of developing robust biologically-based models for this system. The major innovative contributions expected from this work are: 1) First biologically detailed model of a mosquito population to be validated using spatial field data from multiple locations as well as population dynamic responses to field population perturbations. 2) First detailed model that captures endemic dynamics of dengue and can provide assessments of vaccine deployment strategies. 3) First spatial model of an insect disease vector that can assess the risks and benefits of transgenic and conventional strategies for suppressing disease through manipulation of the vector populations. 4) Novel approach for estimating proportion of infective bites and female reproductive patterns. 5) Field data on the intensity and pattern of intra-specific competition among Ae. aegypti larvae in natural conditions that can be used to test and re-parameterize larval component of our model. Objectives to be completed within plan of work: 1) Expand the spatial dimensions of our current Aedes/dengue model so that the human population in the model is large and mobile enough to allow examination of both epidemic and endemic dengue dynamics. 2) Complete uncertainty analysis on the current and the spatially expanded Aedes/dengue model. 3) Conduct field experiments on Ae. aegypti in Iquitos, Peru, to improve estimates of parameters that have been found to cause substantial model uncertainty (e.g., female fecundity and biting, larval competition). 4) Further develop and parameterize the epidemiological component of the spatially expanded model by collaborating with other research projects in Iquitos on ?Human Activity Space? and ?Dengue cohort analysis?. 5) Revise the Ae. aegypti and dengue components of model, retest uncertainty characteristics, validate the model against existing spatial/temporal Aedes/dengue population data from 3 countries, and adapt the model to specific study areas using Bayesian re-estimation of parameters. 6) Carry out large scale Ae. aegypti control operations in 30 by 30 house areas in Iquitos to test the predictive capability of the model under perturbed conditions.

The overriding goal of the Integrated Undergraduate Training in Mathematics and Life Sciences at North Carolina State University (NCSU) is to attract and train undergraduates in mathematics and life sciences for academic and nonacademic careers at the interface between mathematics, computational science, and life sciences. Galileo was perhaps the first to clearly state that the laws of nature are mathematical. Indeed and nearly 40 decades later, cutting edge research at the forefront of life sciences has become more dependent on mathematical, computational, and statistical methodologies. The proposed UBM program uses a multi-faceted approach to prepare next generation of mathematicians and scientists that will meet the holistic, multi-disciplinary research problems of the 21st century. More specifically, our proposed UBM has four primary objectives. It (1) provides a focused environment to involve undergraduate students in mathematics and life sciences in cutting edge cross-disciplinary research involving a broad spectrum of applications in life sciences. For many undergraduates, this will be their first research experience and one that will encourage them to pursue interdisciplinary graduate studies in mathematics and life sciences. It (2) develops and integrates a number of research training and professional development to ensure successful training of a new generation of mathematicians and scientists. These include the development of two new courses: an applied differential equations course in which the theory and analysis of ordinary differential equations are introduced in the context of relevant biological applications and a novel course in model verification and validation. The context-rich material curriculum will be supplemented with UBM research seminars and Professional Development Modules (PDM) that will be held weekly. Students will also be encouraged and assisted by faculty mentors to make professional contacts, participate in tours of mentor's laboratories, attend conferences, and become members in student chapters of professional/academic societies. It (3) provides a team environment for interdisciplinary and collaborative research. The proposed UBM program will train a cohort of 8 undergraduates per year, divided into two groups, with joint mentoring of each 4-student group (two mathematics majors and two life sciences majors) by a pair of faculty from mathematics and life science disciplines at NCSU as well as with our collaborators who are external to NCSU . The long-term objective is to institutionalize a paradigm for training mathematics and life science students for academic and nonacademic careers that involve collaborative, interdisciplinary, team research. It (4) enhances cooperation among faculty in mathematics and life science disciplines. Intellectual Merit and Education. There has been an outburst in the last ten to twenty years in quantitative analysis of biological systems that requires new approaches at how we educate undergraduates. The NCSU UBM team is truly interdisciplinary, with members in mathematics, biomathematics, statistics, biology, chemistry, veterinary medicine and medicine. This powerful combination of areas of expertise offers a truly unique cross-disciplinary educational experience for undergraduates in life sciences and mathematics. Indeed, the project will produce future scientists with both biological skills and mathematical insight and facility. In addition, both mathematics and life science disciplines can expect to gain by this collaborative effort. To faculty in mathematics, the stimulation of biological applications will enrich the discipline of mathematics as it provokes refinements and further mathematical developments. Life science faculty will benefit from the power of mathematical tools as they provide insight available in no other way. Broader Impact. The results of the proposed UBM program will provide a vehicle for systemic institutional change in introductory mathematics and science education. Since project leadership includes key members of existing

Rodent pests cause major economic losses and threaten food security and biodiversity worldwide. The problem is particularly acute on islands where most vertebrate extinctions occur. We propose to test an innovative approach based on genetic engineering. This would also support graduate training in the NCSU Genetic Engineering and Society Center.

The overall goal of this project is to develop a bioenergetics-based model of the effects of the environmental contaminant TCDD (dioxin) on energy homeostasis: specifically mitochondrial function, choline metabolism and development of fatty liver. An existing multi-organ computational model of energy homeostasis will be adapted and integrated with a physiologically-based pharmacokinetic (PBPK) model for describing quantitatively accurate target dosimetry of TCDD, thereby allowing investigation of the bioenergetic effects of exposure to TCDD on a number of biological processes. These processes include: (i) gene expression changes in lipid transport and metabolism in TCDD-elicited fatty liver (steatosis), (ii) development of steatosis following TCDD-induced perturbation of choline homeostasis, and (iii) reduction in the efficiency of ATP production as a result of interaction of ligand-activated aryl hydrocarbon receptor (AhR) with the ATP synthase complex. Model development and validation will be carried out iteratively in close collaboration with two laboratory research projects on bioenergetics and impairment of energy homeostasis by TCDD, based at Michigan State University (MSU).