A global data base of transmission trees

Infectious diseases propagate along networks of contacts of infected hosts. Increasingly, epidemiological investigations have used molecular analysis and case investigation to reconstruct these infection paths, which are then quantified as “transmission trees”. Findings from such studies have shown that features like contact structure, heterogeneity, and the presence of “super spreaders” may be crucial to the propagation and containment of epidemics. Presently, such research is primarily case-based and there is no global understanding of the ubiquity of such features across epidemics more generally. The goal of this project is to develop the first comprehensive data base of transmission trees. The student will compile data from the published literature into a common format. These data will be analyzed to look for patterns in transmission that may be generalized to other epidemics. The work will be performed using the scientific programming language R.

Host Lab: John Drake
Project type: Quantitative/Computer-based

Development of infectious disease research and teaching software

Using computer models to study infectious diseases can be challenging for students and researchers who are not trained as modelers. To make this process easier, we have developed several software packages, implemented in the popular R language, to help individuals learn about and analyze infectious disease models both at the individual and population level. The goal of this project is to further advance this software by implementing new features, making tutorials, testing existing features, etc. This will increase the usefulness and power of the software and will give future students and researchers better tools to learn about and analyze different infectious diseases. This project is quantitative. We will make use of the R language for all parts of this project. The project is offered by the Handel group:

Host Laboratory: Andreas Handel
Type of project: Quantitative/Computer-based

Data analysis to help inform norovirus vaccine design

Norovirus is a common cause of gastrointestinal disease. There is currently no vaccine, but several are under development. It is not clear how exactly a new norovirus vaccine should look like and to whom it should be mainly given (e.g. children or adults). Together with colleagues at Emory University, we are working on a project that analyzes different types of norovirus data to develop a comprehensive mathematical modeling framework to guide norovirus vaccine design and implementation. For this project, you will help with those analyses. The results of this analysis will allow us to better understand properties of norovirus infection and transmission and therefore will help inform the design and implementation of a future norovirus vaccine. This project is quantitative. We will make use of the R language for all analyses.

Host Laboratory: Andreas Handel
Type of project: Quantitative/Computer-based

Studying the relation between vaccine dose and outcomes

For every vaccine, the amount of the antigens of the pathogen one wants to vaccinate against is an important part. This amount that is currently not systematically determined but is instead based on sparse clinical data. We recently developed a framework that combines this data with mathematical models to better determine the vaccine dose that would lead to optimal outcomes. The goal of this project is to further advance this framework by combining data and computer models to determine what the impact of vaccine dose is on outcomes such as side effects and immune protection. This information will be useful for improved design of future vaccines. This project is quantitative. We will make use of the R language for all analyses.

Host Laboratory: Andreas Handel
Type of project: Quantitative/Computer-based

Exploring links between mosquitoes, the environment, and disease transmission

The Asian tiger mosquito, Aedes albopictus is one of the most highly invasive mosquito species seen to date.  The physiological and ecological plasticity of Ae. albopictus has led to its rapid global expansion.  Additionally, its ability to vector a wide-range of recently emerging arboviruses, such as dengue and Chikungunya, make it a significant public health threat.  The transmission of many mosquito-borne pathogens is strongly influenced by environmental temperature due to effects on the physiology of the insect vector and the pathogen.  Therefore, changes in local environmental conditions could significantly impact the distributions and dynamics of a range of mosquito-borne diseases.  Predicting the extent of possible changes in disease dynamics will require a detailed understanding of how a suite of mosquito-pathogen traits respond to variation in environmental temperature and other biotic factors. Projects can explore the following potential questions: 1) what are the microclimate conditions mosquitoes experience in the larval environment and relevant transmission settings?, 2) how does thermal variation influence mosquito life history traits relevant for transmission (e.g. larval development rates, larval survival, adult longevity)?, 3) can we use remotely sensed data to predict relevant mosquito microclimate?, or 4) what factors contribute to Ae. albopictus oviposition behavior and density-dependence in the larval environment. We are looking for two REU students that are interested in combining field work with computational approaches to carry out projects in the Athen’s system this summer mentored by Drs. Courtney Murdock (Infectious Diseases & Odum School of Ecology) and Craig Osenberg (Odum School of Ecology).

Host Laboratories: Courtney Murdock and Craig Osenberg
Type of Project: Combination of Empirical/Field-based, and Computational/Computer-based

Genomics of bacterial symbionts to determine nutritional roles in plant-sap feeding insects

Adelgids are sap-sucking insects that exhibit complex life cycles. Plant sap is a poor nutrient source for insects to feed upon, so many insects engage in obligate relationships with bacterial endosymbionts that play nutritional roles in synthesizing nutrients unavailable or in low quantity from the plant-sap diets of their hosts. However, the contributions of bacterial symbionts to adelgid nutrition is currently unknown on a family-wide scale. This project will involve working with a graduate student to characterize genomes from adelgid insects, including the use of high-performance computing to quality-check raw sequence data, followed by assembly and annotation of bacterial genomes. Comparison of the nutritional roles of bacterial symbionts between adelgid species may reveal that the symbionts are influenced by the complex lifestyles of the insects, an evolutionary process that has not been described to date but could be important in many organisms.

Host laboratory: Gaelen Burke
Type of project: Quantitative/Computer-based

Macro-ecology of predator-parasite interactions

Populations are under constant assault from a variety of natural enemies. Parasites increase mortality and decrease fecundity. Predators pick off animals and often influence prey behavior by their mere presence. Theoretical work has suggested that the removal of predators can have negative effects on prey populations by increasing the amount of parasitism. Empirical tests of this prediction have, however, revealed a more complex picture. Often behavioral changes can have effects on parasite transmission that may overwhelm the theoretical predictions.

In order to better understand the effect of predators on parasites we will test the effect of predator diversity and abundance on parasite prevalence in wild populations of large mammals. As an REU student you will collect information about the known predators of common ungulate species found in the Global Mammal Parasite Database and then collect range-maps for these predators to determine predation pressure on hosts at various points on their range. Depending on the interests of the student this work could include employing existing range-maps or using machine learning methods to construct new ones from recorded predator locations. During this process you will, through guided readings and discussions, develop testable hypotheses about the relationship between predators and parasites in these systems. After the necessary data have been collected you will conduct statistical analyses to test these hypotheses. In this project, you will learn to read and interpret scientific literature and to efficiently extract data following a protocol which we will develop. You will also get experience manipulating data and conducting statistical analyses in the R programming language with an opportunity to learn how to use machine-learning methods to model species distributions.

Host Lab: Vanessa Ezenwa, co-mentored by PhD Student Robert Richards
Type of Project: Quantitative/Computer-based

Display of stuffed mountain lions and their prey at the Denver Museum of Nature & Science in Denver, Colorado.

Temperature impacts on an insect-parasite interaction

For insects, environmental temperature can influence their physiology, survival, activity patterns, and large-scale distribution. Shifts in temperature will have pervasive effects, not just on individual insect species, but also on their interactions with other organisms, notably, their parasites. Given that insects are important pollinators and vectors of disease, it is vital that we explore how temperature impacts insect-parasite interactions. Monarch butterflies are parasitized by a protozoan parasite, Ophryocystis elektroscirrha (OE), that can have negative effects on the insect’s survival, reproduction, and flight ability. Their iconic migration exposes the butterflies to a range of environmental temperatures over the course of several generations, making the monarch-OE system quite suitable for investigating how temperature impacts host susceptibility and parasite virulence. This project, aimed at quantifying elements of host and parasite fitness at different temperatures, will include controlled lab experiments and the development of a mathematical model of infection. The student will participate in experimental data collection/analysis, model design, and model parameterization. This project is suitable for students with interests in infectious disease ecology and conservation hoping to integrate experimental and modeling techniques.

Host laboratory: Sonia Altizer & Richard Hall; co-mentored by Isabella Ragonese (PhD student)
Type of project: A combination of Quantitative (computer-based) and Empirical (lab-based)

Vive la resistance: the impact of antibiotic use in US livestock on emerging antibiotic resistance

Sydney Rentsch, a junior from Connecticut College, worked with Dr. JP Schmidt to examine the relationship between antibiotic use and resistance in US livestock.

Abstract:  The potential for livestock to spread antibiotic resistant pathogens to human populations is a cause for concern. This research focused on finding trends in data on US livestock antibiotic resistance, US livestock inventory and US livestock antibiotic consumption. Data was compiled from CDC, USDA and FDA reports and publicly available datasets. Data was analyzed in R and generalized additive models (GAMs) were used to test for increasing resistance as a function of time. We found that the tetracycline class of antibiotics had consistently high resistance over time. The antibiotic class lincosamides, had a sharp increase in resistance which was positively associated with the data from turkeys and chickens. Analyzes also found that poultry had the highest burden of antibiotic resistant pathogens. These results may lead future studies focused on antibiotic resistance in poultry and provide framework for future data analysis.


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Behavioral and environmental determinants of parasite transmission in a butterfly host

Chastity Ward, a senior from Fayetteville State University, worked on a project with Dr. Sonia Altizer, Dr. Richard Hall and Dr. Paola Barriga to examine how parasites of the Monarch butterfly are transmitted.

Abstract:  Many pathogens can be transmitted when infectious stages shed into the environment are later encountered by susceptible hosts. Environmental transmission is common among insect parasites, and also occurs for human diseases such as cholera and polio. Understanding how host behavior and environmental variables affect the shedding of infectious stages is crucial for predicting patterns of infection risk. Monarch butterflies Danaus plexippus are commonly infected by the protozoan Ophryocystis elektroscirrha (OE); this parasite is transmitted environmentally when infected adults deposit spores onto host plants (milkweed) that are consumed by monarch larvae. To quantify host contact with milkweeds as an estimate of parasite transmission, we set up outdoor flight cages with adult monarchs and milkweed plants. Cages varied in the number of adult monarchs and milkweed plants, and were assigned to one of two milkweed species. We used captive-raised monarchs from several genetic lineages, and marked the monarchs with unique number and color codes to track activity. We observed cages for replicate intervals over a week-long period, during which we noted observed monarch contacts with plants, and recorded monarch and plant identity, activity type, temperature, weather, and time of day. Our results showed strong heterogeneity in plant visitation rates among monarchs that was best explained by monarch sex (females had 4.7 times higher visitation rates than males, owing to frequent oviposition on milkweeds).  We also found wide variation among individual plants in the number of visits by monarchs. Milkweed species, plant flowering status and plant leaf number did not affect visitation rates, but plants in cages with a higher number of monarchs were visited more frequently. In sum, our findings provided evidence for individual monarch’s serving as superspreaders of infection, and for some milkweed plants serving as hotspots of infection. This study provides a starting point for estimating environmental parasite transmission in wild milkweed patches, and suggests that individual-level heterogeneity might be more important than environmental variation in driving parasite transmission in this system.


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