the sense that their genetic sequence gradually changes over time.
Occasionally this evolution will lead to a difference we care about –
like the flu virus changing its appearance – but often it will just
happen in the background without having a noticeable effect on an
outbreak.
The rate of evolution can affect our ability to analyse outbreaks,
though. Phylogenetic analysis is more effective when looking at
pathogens that evolve fairly quickly, like and flu. This is because
the genetic sequence will change as pathogens spread from one
person to another, making it possible to estimate the likely path of
infection. In contrast, viruses like measles evolve slowly, which
means there won’t be much variation from one person to another.[11]
As a result, working out how the cases are related is a bit like trying
to piece together a human family tree in a country where everyone
has the same surname.
As well as biological limitations to phylogenetic methods, there
are also practical ones. In the early stages of the West Africa Ebola
epidemic, Pardis Sabeti, a geneticist with the Broad Institute in
Boston, analysed sequence data from ninety-nine viruses from
Sierra Leone. Phylogenetic trees showed that the infection had
spread from Guinea to Sierra Leone in May 2014, possibly after a
funeral. Given the seriousness of the outbreak, Sabeti and her
colleagues quickly added the new genetic sequences to a public
database. This initial burst of research was then followed by a period
of relative silence. Although several other teams had been collecting
virus samples, nobody else released any new genetic sequences
between 2 August and 9 November 2014. During this same period,
there were over 10,000 Ebola cases reported in West Africa, with the
epidemic reaching its peak in October.[12]
There are a couple of possible reasons for the delay in releasing
sequences. The cynical explanation is that new data are valuable
academic currency. Research papers using genetic sequences to
study outbreaks are likely to get published in coveted scientific
journals, which creates an incentive for researchers to sit on
potentially important data. However, based on my interactions with