GENERAL: This lab and lab activity #6 are computer based explorations of statistical prediction of epidemics, a tool used by epidemiologists. This week’s exercise will be carried out using computer software developed by H. Eugene Stanley’s NSF funded "OGAF" project at Boston University. (Dr. Selinger, as a co-principle investigator, assisted in development of the software.) The model used is a percolation model, an epidemic controlled by spatial proximity.

OBJECTIVES: With this exercise, the building and testing of scientific models will be emphasized, including use of math skills such as graphing and analyzing data and simple statistical analysis. At the completion of this exercise, you should be able to identify the variables included in this epidemic scenario and learn how to predict epidemic size using a computer program; how to add variables which could affect the outcome; and how to apply this type of modeling to a human population.

INTRODUCTION: In this exercise, you will focus on a case where disease transfer is controlled simply by spatial proximity, with a static population, i.e., trees in an orchard. The scenario: A single tree in the middle of an apple orchard becomes infected with a pathogen that ruins its fruit (e.g., a fungal infection). The pathogen travels to all nearby trees within a distance of 10 meters. From there it travels to yet other trees adjacent to the newly infected ones, continuing until all trees in the local "cluster" have been infected. If the trees are dense enough, the local cluster is likely to include nearly the entire orchard.

EQUIPMENT AND PROCEDURE:

Further instructions and follow-up activities will be given to you at the time of the lab by Dr. Selinger and her assistants.

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