Mathematical modeling shows that local populations of the malaria parasite self-organize into a limited number of transient but distinct strains through competition for hosts in immunity space.

Some of the mutations that occur during influenza evolution can only be tolerated in conjunction with other mutations that increase the stability of a viral protein.

Understanding where future Ebola virus outbreaks may start and the changing nature of the populations living in these places is of critical importance in helping to prepare for future outbreaks.

Predicting the pandemic potential of influenza viruses from genetic sequence data could transform pandemic risk assessment but progress towards this goal will require the integration of experimental work, computational tools, and virus surveillance.

A study of tuberculosis cases in the Karonga district of Malawi reveals that the main lineages of M. tuberculosis differ in their transmission patterns and virulence.

Cryptic alleles affecting embryonic development are widespread in wild C. elegans populations.

Influenza transmission among ferrets correlates strongly with transmission among humans, so the ferret model for influenza transmission is a valid tool for pandemic potential in humans.

Deleterious mutations slow down flu's antigenic evolution, make it more punctuated in nature, and reduce the virus's genetic diversity.

A fine-grain map of residual transmission and importation in Swaziland shows where to target malaria elimination efforts.

A review of mathematical models applied to the West Africa Ebola epidemic suggests ways to improve the use of mathematical modeling in responding to public health emergencies.