ABSTRACT
Since their earliest days, humans have been struggling with infectious diseases. Caused by viruses, bacteria, protozoa, or even higher organisms like worms, these diseases depend critically on numerous intricate interactions between parasites and hosts, and while we have learned much about these interactions, many details are still obscure. It is evident that the combined host-parasite dynamics constitutes a complex system that involves components and processes at multiple scales of time, space, and biological organization. At one end of this hierarchy we know of individual molecules that play crucial roles for the survival of a parasite or for the response and survival of its host. At the other end, one realizes that the spread of infectious diseases by far exceeds specific locales and, due to today's easy travel of hosts carrying a multitude of organisms, can quickly reach global proportions. The community of mathematical modelers has been addressing specific aspects of infectious diseases for a long time. Most of these efforts have focused on one or two select scales of a multi-level disease and used quite different computational approaches. This restriction to a molecular, physiological, or epidemiological level was prudent, as it has produced solid pillars of a foundation from which it might eventually be possible to launch comprehensive, multi-scale modeling efforts that make full use of the recent advances in biology and, in particular, the various high-throughput methodologies accompanying the emerging -omics revolution. This special issue contains contributions from biologists and modelers, most of whom presented and discussed their work at the workshop From within Host Dynamics to the Epidemiology of Infectious Disease, which was held at the Mathematical Biosciences Institute at Ohio State University in April 2014. These contributions highlight some of the forays into a deeper understanding of the dynamics between parasites and their hosts, and the consequences of this dynamics for the spread and treatment of infectious diseases.
Subject(s)
Communicable Diseases/epidemiology , Host-Parasite Interactions , Models, Theoretical , HumansABSTRACT
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Subject(s)
Chromosomes, Human, X , Craniosynostoses/genetics , Ephrin-B1/genetics , Mutation , DNA/genetics , Female , Humans , Male , Polymerase Chain Reaction , Sequence Analysis, DNA , SyndromeABSTRACT
Explanatory style, a cognitive variable, reflects how people typically explain the causes of bad events involving themselves. Explanatory style emerged from the attributional reformulation of the learned helplessness and depression model as a way of explaining individual differences in response to uncontrollability. A central prediction of the reformulation is that people with habitual explanatory tendencies differ, and individuals with a pessimistic explanatory style will be more likely to exhibit depressive symptoms following bad events than individuals with an optimistic explanatory style. 116 upper-level undergraduates beginning a degree program at this university completed the Attributional Style Questionnaire. Scores were correlated with students' cumulative grade point averages and their total points earned in Consumer Behavior, the first course required in the Marketing major. Students with pessimistic explanatory style scores outperformed colleagues with optimistic explanatory style scores. Implications of these findings and possible explanations for why explanatory style did not correlate in the theoretically predicted way with academic achievement are considered.