The ability to distinguish separate types of disorder among patients who seem at first sight to have similar symptoms has been a powerful factor in the progress of medicine. It is for this reason that the attempt to distinguish different varieties of depressive illness is important. In Britain recent studies have been concerned with the presence (as rated by the examining physician) of various symptoms and signs which from clinical experience have been thought likely to distinguish a neurotic from a psychotic type of depression. The investigators agree on the presence of these two types but disagree on the nature of the distinction, one school holding that there are two largely distinct types of illness and the other that the types merely represent the opposite ends of a continuum. The holders of the latter view accept that there may well be distinct types of depressive illness, but maintain that, if so, they cannot be distinguished by present methods of clinical examination. The divergence of view has been attributed by Kendell (1968) to sampling differences and to the subjective bias of raters, and by Eysenck (1970) to disagreement on whether the two types of depressive illness are of a categorical nature (i.e. specific disease entities) or of a dimensional nature (i.e. each has a graded distribution in a population of depressed patients).

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Variation in host susceptibility results in flattening of the quantal response curve obtained in dilution counting experiments. This departure from the exponential curve obtained with uniform hosts is found primarily at the lower dilutions, where the infection rates are high. The test proposed by Moran, for the detection of host variability, may easily fail to detect quite appreciable heterogeneity with the numbers of observations that are likely to be available in practice. Examination of the response curves corresponding to various theoretical distributions of susceptibility suggests that detection of heterogeneity is unlikely unless the probability that a particle can initiate infection is distributed with a low mean and considerable positive skewness.The problem is related to that of estimating the standard deviation of a tolerance distribution from quantal response data. This suggests an alternative test, based on the Spearman-Kärber method, which, however, appears to be no better than Moran's test. Both methods provide estimates of the variability of the susceptibility distribution.

The Kermack & McKendrick theory of epidemics has been applied to data on deaths from influenza and influenzal pneumonia in Greater London in the years 1950-78. As a whole the theory gives a good description of the data, and the estimated values of the parameters can be plausibly related to the natural history of the disease. However, the possibility exists that the agreement is merely empirical, and field studies would be required to confirm its validity.