A cross-immunization model for the extinction of old influenza strains

Host and geographic barriers shape the competition, coexistence, and extinction patterns of influenza A (H1N1) viruses

The influenza virus mutates and spreads rapidly, making it suitable for studying evolutionary and ecological processes. The ecological factors and processes by which different lineages of influenza compete or coexist within hosts through time and across geographical space are poorly known. We hypothesized that competition would be stronger for influenza viruses infecting the same host compared to different hosts (the Host Barrier Hypothesis), and for those with a higher cross-region transmission intensity (the Geographic Barrier Hypothesis). Using available sequences of the influenza A (H1N1) virus in GenBank, we identified six lineages, twelve clades, and several replacement events. We found that human-hosted lineages had a higher cross-region transmission intensity than swine-hosted lineages. Co-occurrence probabilities of lineages infecting the same host were lower than those infecting different hosts, and human-hosted lineages had lower co-occurrence probabilities and genetic diversity than swine-hosted lineages. These results show that H1N1 lineages infecting the same host or with high cross-region transmission rates experienced stronger competition and extinction pressures than those infecting different hosts or with low cross-region transmission. Our study highlights how host and geographic barriers shape the competition, extinction, and coexistence patterns of H1N1 lineages and clades.

Superspreading of airborne pathogens in a heterogeneous world

Epidemics are regularly associated with reports of superspreading: single individuals infecting many others. How do we determine if such events are due to people inherently being biological superspreaders or simply due to random chance? We present an analytically solvable model for airborne diseases which reveal the spreading statistics of epidemics in socio-spatial heterogeneous spaces and provide a baseline to which data may be compared. In contrast to classical SIR models, we explicitly model social events where airborne pathogen transmission allows a single individual to infect many simultaneously, a key feature that generates distinctive output statistics. We find that diseases that have a short duration of high infectiousness can give extreme statistics such as 20% infecting more than 80%, depending on the socio-spatial heterogeneity. Quantifying this by a distribution over sizes of social gatherings, tracking data of social proximity for university students suggest that this can be a approximated by a power law. Finally, we study mitigation efforts applied to our model. We find that the effect of banning large gatherings works equally well for diseases with any duration of infectiousness, but depends strongly on socio-spatial heterogeneity.

Models of life: epigenetics, diversity and cycles

This review emphasizes aspects of biology that can be understood through repeated applications of simple causal rules. The selected topics include perspectives on gene regulation, phage lambda development, epigenetics, microbial ecology, as well as model approaches to diversity and to punctuated equilibrium in evolution. Two outstanding features are repeatedly described. One is the minimal number of rules to sustain specific states of complex systems for a long time. The other is the collapse of such states and the subsequent dynamical cycle of situations that restitute the system to a potentially new metastable state.