Basing Vaccine Administration on Samples

One of the greatest ideas in biological and medical sciences is the development of vaccines. I stand in awe of the effectiveness of vaccines especially since the idea behind their development is for me rather simple though counter-intuitive.

In this story in Slate Magazine, Sydnet Spiesel makes the case for the administration of flu vaccines on a regular basis because new strains emerge predictably. As a result, the vaccines developed for the year before are not as effective subsequently.

While the logic behind the argument for vaccination of the most vulnerable is fairly solid, I am less convinced that universal vaccination is necessarily cost-effective. As piece argues, the benefits for vaccinations come from reduced mortality, reduced hospitalization and a reduction in deaths for the most vulnerable. However, noting that vaccinations for influenza provides herd immunity in the sense that the vaccinated are less likely to pass the disease or become ill, then it is perhaps less efficient to vaccinate all.

The critical factor then is to determine the proportion of a population that would need vaccination and ensure that the greatest number are protected. This would require knowledge of the demographic profile of the population and to concentrate the vaccines to those most vulnerable on the one hand and those who are the most efficient spreaders. I argue that this would require vaccination by sampling and determining the most appropriate moments for administering the vaccines to the distinct cohorts in the overall sample.