Teaching to the Test: De/Reconstructing the Argument

With the implementation of the Common Core Standards, the new Common Core test will start in Spring of 2015. This standardized test is given during the spring of a student’s junior year. Though the test is given junior year, the onus for making sure students are ready is also that of teachers working with freshmen and sophomores. Preparing students to be proficient in the skills necessary for college and potential careers is paramount; one way to ensure such preparation is creating exercises similar to that of the performance task on the sample test. The performance task focuses on assessing a student’s ability to comprehend multiple sources on one topic, support various claims with evidence from multiple sources, establish a counterargument, and compose an argumentative letter as a final product. The purpose of this project is to have students go through similar rhetorical moves as they will on the actual test. However, since the students are sophomores, the exercise will take place in small groups and at stations that divide up the tasks into more manageable chunks. Doing so will allow me to pinpoint students’ areas of weakness and modify the second exercise and my instruction accordingly to maximize learning and preparedness for constructing a solid argument

Statistical physics of vaccination

Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination–one of the most important preventive measures of modern times–is of great interest both theoretically and empirically. And in contrast to traditional approaches, recent research increasingly explores the pivotal implications of individual behavior and heterogeneous contact patterns in populations. Our report reviews the developmental arc of theoretical epidemiology with emphasis on vaccination, as it led from classical models assuming homogeneously mixing (mean-field) populations and ignoring human behavior, to recent models that account for behavioral feedback and/or population spatial/social structure. Many of the methods used originated in statistical physics, such as lattice and network models, and their associated analytical frameworks. Similarly, the feedback loop between vaccinating behavior and disease propagation forms a coupled nonlinear system with analogs in physics. We also review the new paradigm of digital epidemiology, wherein sources of digital data such as online social media are mined for high-resolution information on epidemiologically relevant individual behavior. Armed with the tools and concepts of statistical physics, and further assisted by new sources of digital data, models that capture nonlinear interactions between behavior and disease dynamics offer a novel way of modeling real-world phenomena, and can help improve health outcomes. We conclude the review by discussing open problems in the field and promising directions for future research

Population Estimation and Trappability of the European Badger (Meles meles): Implications for Tuberculosis Management.

peer-reviewedEstimates of population size and trappability inform vaccine efficacy modelling and are required for adaptive management during prolonged wildlife vaccination campaigns. We present an analysis of mark-recapture data from a badger vaccine (Bacille Calmette–Gue´ rin) study in Ireland. This study is the largest scale (755 km2) mark-recapture study ever undertaken with this species. The study area was divided into three approximately equal–sized zones, each with similar survey and capture effort. A mean badger population size of 671 (SD: 76) was estimated using a closed-subpopulation model (CSpM) based on data from capturing sessions of the entire area and was consistent with a separate multiplicative model. Minimum number alive estimates calculated from the same data were on average 49–51% smaller than the CSpM estimates, but these are considered severely negatively biased when trappability is low. Population densities derived from the CSpM estimates were 0.82–1.06 badgers km22, and broadly consistent with previous reports for an adjacent area. Mean trappability was estimated to be 34–35% per session across the population. By the fifth capture session, 79% of the adult badgers caught had been marked previously. Multivariable modelling suggested significant differences in badger trappability depending on zone, season and age-class. There were more putatively trap-wary badgers identified in the population than trap-happy badgers, but wariness was not related to individual’s sex, zone or season of capture. Live-trapping efficacy can vary significantly amongst sites, seasons, age, or personality, hence monitoring of trappability is recommended as part of an adaptive management regime during large–scale wildlife vaccination programs to counter biases and to improve efficiencies.Department of Agriculture, Food and the MarineTeagasc Walsh Fellowship Programm