Measures of population differentiation, such as F_ST, are traditionally derived from the partition of diversity within and between populations. However, the emergence of population clusters from multilocus analysis is a function of genetic structure (departures from panmixia) rather than of diversity. If the populations are close to panmixia, slight differences between the mean pairwise distance within and between populations (low F_ST) can manifest as strong separation between the populations, thus population clusters are often evident even when the vast majority of diversity is partitioned within populations rather than between them. For any given F_ST value, clusters can be tighter (more panmictic) or looser (more stratified), and in this respect higher F_ST does not always imply stronger differentiation. In this study we propose a measure for the partition of structure, denoted E_ST, which is more consistent with results from clustering schemes. Crucially, our measure is based on a statistic of the data that is a good measure of internal structure, mimicking the information extracted by unsupervised clustering or dimensionality reduction schemes. To assess the utility of our metric, we ranked various human (HGDP) population pairs based on F_ST and E_ST and found substantial differences in ranking order. E_ST ranking seems more consistent with population clustering and classification and possibly with geographic distance between populations. Thus, E_ST may at times outperform F_ST in identifying evolutionary significant differentiation.

The conventional account of Jenner’s cowpox vaccine attributes a series of enabling properties to pre-laboratory inoculation: harvesting, preserving and transmitting infectious material; attenuating disease first through variolation and again through cowpox substitution; and a visible ‘take’ validating the procedure. Applying Occam’s razor, this review considers simpler alternative explanations. A recurring pattern is revealed in which early assumptions became established premises that were insufficiently challenged even as scientific standards advanced. Thus, the take alone did not establish poxvirus transmission, and variolation’s 0.5–2% versus 20–30% mortality comparison improperly contrasted healthy recipients with patients already ill with smallpox. Jennerian vaccination inherited and compounded these limitations and was not demonstrably superior to contemporary refined variolation. The major/minor division did not independently explain the decline in smallpox burden, and the attributed 300-million twentieth-century death toll could not be substantiated from contemporary population-level mortality records. Most importantly, eradication coincided with a diagnostic discontinuity: 1978 marked both the first year without recognised naturally acquired cases and the first year in which laboratory confirmation became a de facto requirement for validating suspected smallpox outbreaks. These findings challenge the traditional interpretation of smallpox and its eradication.

Measures of population differentiation, such as F _ST , are traditionally derived from the partition of diversity within and between populations. However, the emergence of population clusters from multilocus analysis is a function of genetic structure (departures from panmixia) rather than of diversity. If the populations are close to panmixia, slight differences between the mean pairwise distance within and between populations (low F _ST ) can manifest as strong separation between the populations, thus population clusters are often evident even when the vast majority of diversity is partitioned within populations rather than between them. For any given F _ST value, clusters can be tighter (more panmictic) or looser (more stratified), and in this respect higher F _ST does not always imply stronger differentiation. In this study we propose a measure for the partition of structure, denoted E _ST , which is more consistent with results from clustering schemes. Crucially, our measure is based on a statistic of the data that is a good measure of internal structure, mimicking the information extracted by unsupervised clustering or dimensionality reduction schemes. To assess the utility of our metric, we ranked various human (HGDP) population pairs based on F _ST and E _ST and found substantial differences in ranking order. In some cases examined, most notably among isolated Amazonian tribes, E _ST ranking seems more consistent with demographic, phylogeographic and linguistic measures of classification compared to F _ST . Thus, E _ST may at times outperform F _ST in identifying evolutionary significant differentiation.