The Rules of Contagion

campaign had looked like. In 2004, for example, anti gun violence
group The Brady Campaign had sent out e-mails asking people to
support new gun control measures. They encouraged recipients to
forward the e-mails to their friends; some of these friends then
forwarded the messages to their friends, and so on. For each e-mail
that was sent, on average around 2.4 people ended up seeing the
message. Based on this typical outbreak size, the reproduction
number of the campaign was about 0.58. A subsequent e-mail
campaign aimed to raise money for Hurricane Katrina relief efforts;
this time R was 0.77. However, there wasn’t always so much
transmission. Spare a thought for the marketing executives trying to
spread messages about cleaning products: Peretti and Watts found
that e-mails promoting Tide Coldwater detergent had an R of only
0.04 (i.e. the same as H7N9 bird flu). Whereas most of the Katrina e-
mails had spread between multiple people, over 99 per cent of the
Tide outbreaks stuttered to an end after only one transmission event.
[45]
Why do we care about measuring an infection if it won’t lead to a
large outbreak? For biological pathogens, a big concern is that these
infections will adapt to their new hosts. During a small outbreak,
viruses could pick up mutations that enable them to transmit more
easily. The more people that get infected, the more chances for such
adaptation. Before sparked a major outbreak in Hong Kong in
February 2003, there were a series of small clusters of infection in
Guangdong province, in southern China.[46] Between November
2002 and January 2003, seven outbreaks were reported in
Guangdong, with between one and nine cases in each. The average
outbreak size was five cases, suggesting that R may have been
around 0.8 during this period. But by the time of the Hong Kong
outbreak a couple of months later, had a far more troubling R of
more than 2.
There are several reasons the reproduction number of an infection
may increase. Recall that R depends on the four DOTS: duration of
infection, opportunities for transmission, transmission probability
during each opportunity, and average susceptibility. For biological
viruses, all of these features can influence transmission. Of the