# Glossary

## Basic and useful concepts for the reading of this website

**Bayesian** theory calls for the use of the posterior predictive distribution to do predictive inference, i.e., to predict the distribution of a new, unobserved data point. That is, instead of a fixed point as a prediction, a distribution over possible points is returned. In the Bayesian view, a probability is assigned to a hypothesis.

**Complex systems **are networks made of a number of components that interact with each other, typically in a nonlinear fashion. Complex systems may arise and evolve through self-organization, such that they are neither completely regular nor com- pletely random, permitting the development of emergent behavior at macroscopic scales.

**Deterministic model** is a mathematical representation of a system in which relationships are fixed (i.e. no parameters characterized by probability distribution), so for fixed starting values it will always produce the same result.

**Differentiation** is the process of finding the *derivative* of a curve. And the word “derivative” is just the fancy calculus term for the curve’s *slope* or *steepness*. And because the slope of a curve is equivalent to a simple rate (like miles per hour or profit per item), the derivative is a rate as well as a slope.

**Emergence (of complex systems) **is a nontrivial relationship between the properties of a system at different scales (microscopic and macroscopic) over scale. Macroscopic properties are called emergent when it is hard to explain them simply from microscopic properties.

**Enzootic** refers to an infectious disease that is present in a host population at all times, but having low incidence within the population.

**Epizootic** refers to an infectious disease outbreak in a population that affects a large number of animals simultaneously but does not persist.

**Frequentist inference** is a type of statistical inference that draws conclusions from sample data by emphasizing the frequency or proportion of the data.In the frequentist view, a hypothesis is tested without being assigned a probability.

The **Goodness of fit** of a statistical model describes how well your description of the world fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question.

**Hypotheses** (plural is important) – descriptions of how the world might work; they can often be translated into quantitative predictions via models. A **hypothesis** is an unproved theory, proposition, supposition, etc., tentatively accepted to explain certain facts or to provide a basis for further investigation.

An **infectious disease **refers to the change in the state of health of a host organism as a result of invasion of the body by pathogenic organisms. Note that the disease is the manifestation of theinfection in a host organism, but infection can occurwithout causing disease.

**Model **is a simplified representation of a system. It can be conceptual, verbal, diagrammatic, physical, or formal (mathematical).

**Mechanistic models** assume that a complex system can be understood by examining the functioning of each of its parts and how they are coupled together. Mechanistic models usually have a tangible, physical appearance, as the components of the system are real, solid and visible.

**Parameter vs. Variable**: The first is a fixed number, the second changing in time.

A **parasite** is an organism that lives in (endoparasites) or on (ectoparasites) the living tissue of a host organism; the biological interaction between host and parasite is called parasitism. Microparasites, which include viruses and bacteria, reproduce within their hosts. Macroparasites, which include multicellular endo- and ectoparasites, generally spend some portion of the life cycle away from the primary host.

A **pathogen** is any disease-producing microorganism or material (e.g prions are infectious proteins, but are not technically organisms).

A **reservoir host** is an animal species that maintains a parasite life cycle and functions as the source of the infection for humans or other species.

**Self-organization** **(of complex systems) **is a dynamical process by which a system spontaneously forms nontrivial macroscopic structures and/or behaviors (order) over time.

**Stochastic model** has some of the parameters uncertain and these are thus characterized by probability distribution. For fixed starting values they will produce many different results depending on the actual values the random variable takes. The random variation is usually based on fluctuations observed in historical data for a selected period using standard time series techniques.

**Vectorial capacity** is a term that takes into account the efficiency of the vector in transmitting the pathogen, the lifespan of the infectious hosts, andthe degree of contact between the host and vector.

**Theory** is a systematic statement of principles involved, or a formulation of apparent relationships or underlying principles of certain observed phenomena which has been verified to some degree.

A **zoonosis** is an infection or disease that can be shared between humans and wildlife.