  Despite being similar in structure, functioning, and size viral pathogens
enjoy very different mostly well-defined ways of life. They occupy their hosts
for a few days (influenza), for a few weeks (measles), or even lifelong (HCV),
which manifests in acute or chronic infections. The various transmission routes
(airborne, via direct contact, etc.), degrees of infectiousness (referring to
the load required for transmission), antigenic variation/immune escape and
virulence define further pathogenic lifestyles. To survive pathogens must
infect new hosts; the success determines their fitness. Infection happens with
a certain likelihood during contact of hosts, where contact can also be
mediated by vectors. Besides structural aspects of the host-contact network,
three parameters/concepts appear to be key: the contact rate and the
infectiousness during contact, which encode the mode of transmission, and third
the immunity of susceptible hosts. From here, what can be concluded about the
evolutionary strategies of viral pathogens? This is the biological question
addressed in this paper. The answer extends earlier results (Lange & Ferguson
2009, PLoS Comput Biol 5 (10): e1000536) and makes explicit connection to
another basic work on the evolution of pathogens (Grenfell et al. 2004, Science
303: 327-332). A mathematical framework is presented that models intra- and
inter-host dynamics in a minimalistic but unified fashion covering a broad
spectrum of viral pathogens, including those that cause flu-like infections,
childhood diseases, and sexually transmitted infections. These pathogens turn
out as local maxima of the fitness landscape. The models involve differential-
and integral equations, agent-based simulation, networks, and probability.
