  US public health authorities claim imposing quarantines on healthcare workers
returning from West Africa is incorrect according to science. Their positions
rely upon a set of studies and experience about outbreaks and transmission
mechanisms in Africa as well as assumptions about what those studies imply
about outbreaks in the US. According to this view the probability of a single
infection is low and that of a major outbreak is non-existent. In a series of
brief reports we will provide insight into why properties of networks of
contagion that are not considered in traditional statistics suggest that risks
are higher than those assumptions suggest. We begin with the difference between
thin and fat tailed distributions applied to the number of infected individuals
that can arise from a single one. Traditional epidemiological models consider
the contagion process as described by $R_0$, the average number of new infected
individuals arising from a single case. However, in a complex interdependent
society it is possible for the actual number due to a single individual to
dramatically differ from the average number, with severe consequences for the
ability to contain an outbreak when it is just beginning. Our analysis raises
doubts about the scientific validity of policy recommendations of public health
authorities. We also point out that existing CDC public health policies and
actions are inconsistent with their claims.
