Chains of infection: A description of the course of an infection among a set of individuals. The
susceptibles infected by direct contact with the introductory cases are said to make up the
first generation of cases; the susceptibles infected by direct contact with the first generation
are said to make up the second generation and so on. The enumeration of the number of cases
in each generation is called an epidemic chain. Thus the sequence 1–2–1–0 denotes a chain
consisting of one introductory case, two first generation cases, one second generation case
and no cases in later generations. [Occupational and Environmental Medicine, 2004, 61,
96–102.]
Ch a l mers,Tho mas Cl a rk ( 1917^1995) : Born in Forest Hills, New York, Chalmers graduated
from Columbia University College of Physicians and Surgeons in 1943. After entering
private practice he became concerned over the lack of knowledge on the efficacy of accepted
medical therapies, and eventually became a leading advocate for
clinical trials
, and later for
meta-analysis
setting up a meta-analysis consultancy company at the age of 75. In a
distinguished research and teaching career, Chalmers was President and Dean of the
Mount Sinai Medical Center and School of Medicine in New York City from 1973 to
1983. He died on 27 December 1995, in Hanover, New Hampshire.
Champernowne, David Gawen (1912^2000): Born in Oxford, Champernowne studied
mathematics at King’s College, Cambridge, later switching to economics, and gaining first
class honours in both. Before World War II he worked at the London School of Economics
and then at Cambridge where he demonstrated that the evolution of an income and wealth
distribution could be represented by a Markovian model of income mobility. During the war
he worked at the Ministry of Aircraft Production, and at the end of the war became Director
of the Oxford Institute of Statistics. In 1948 he was made Professor of Statistics at Oxford,
and carried out work on the application of
Bayesian analysis
to
autoregressive series
.In
1958 Champernowne moved to Cambridge and continued research into the theory of capital
and the measurement of economic inequality. He died on 22 August 2000.
Chance events: According to Cicero these are events that occurred or will occur in ways that are
uncertain-events that may happen, may not happen, or may happen in some other way.
Cicero’s characterization of such events is close to one dictionary definition of chance
namely, ‘the incalculable element in existence that renders events unpredictable’. But for
Leucippus (circa 450 B.C.) the operation of chance was associated with some hidden cause
and such a view was held widely in the middle ages where chance had no place in the
universe, rather all events were though of as predetermined by God or by extrinsic causes
determined by God. But in the 20
th
century the deterministic view of the universe was
overthrown by the successful development of quantum mechanics with its central tenet
being that it is impossible to predict exactly the outcome of an atomic (or molecular) system
and where this uncertainty is not due to measurement error or experimental clumsiness but is
a fundamental aspect of the basic physical laws themselves. [Chance Rules, 2nd edition,
2008, B. S. Everitt, Springer, New York.]
Change point problems: Problems with chronologically ordered data collected over a period of
time during which there is known (or suspected) to have been a change in the underlying
data generation process. Interest then lies in, retrospectively, making inferences about the
time or position in the sequence that the change occurred. A famous example is the
Lindisfarne scribes data in which a count is made of the occurrences of a particular type
of pronoun ending observed in 13 chronologically ordered medieval manuscripts believed to
be the work of more than one author. A plot of the data (see Fig. 29) shows strong evidence
of a change point. A simple example of a possible model for such a problem is the following;
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