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Urbanization is a worldwide phenomenon that modifies the environment. By affecting the reservoirs of pathogens and the body and immune conditions of hosts, urbanization alters the epidemiological dynamics and diversity of diseases. Cities could act as areas of pathogen dilution or amplification, depending on whether urban features have positive or negative effects on vectors and hosts. In this study, we focused on a host species and investigated the prevalence and diversity of avian malaria parasites (Plasmodium/Haemoproteus sp. and Leucocytozoon sp.) in great tits (Parus major) living across an urbanization gradient. In general, we observed high prevalence in adult birds (from 95% to 100%), yet lower prevalence in fledglings (from 0% to 38%). We found a slight tendency for increased Plasmodium sp. prevalence with increasing urbanization in adults. Urban nestlings had higher Plasmodium sp. infection rates than non-urban nestlings. We found evidence of higher diversity of parasites in the most natural urban park; however, parasite diversity was similar across other urbanization levels (e.g. from a little artificialized park to a highly anthropized industrial area). Parasite lineages were not habitat specific. Only one Plasmodium sp. lineage (YWT4) was associated with urban areas and some rare lineages (e.g., AFR065) were present only in a zoo area, perhaps because of the presence of African birds. This study suggests that urbanization can lead to a parasite amplification effect and can favor different avian malaria lineages.

Many human pathogens, including malaria, dengue, influenza, Streptococcus pneumoniae, and cytomegalovirus, coexist as multiple genetically distinct strains. Understanding how these multistrain pathogens evolve is of critical importance for forecasting epidemics and predicting the consequences of vaccination. One factor believed to play an important role is naturally acquired immunity. Consequently, a large body of research has sought to predict how acquired immunity molds the genomics of pathogen populations (i.e., what shapes pathogen strain structure). The diversity of existing models has resulted in conflicting evolutionary predictions and has sparked an ongoing debate about which predictions are most broadly applicable. Here, we adopt a multilocus population genetics perspective that unifies the predictions of existing models. We identify three key factors that determine the role of naturally acquired immunity in the evolution of pathogen strain structure: i) the strength and specificity of immune protections, ii) the dynamic immunological landscape, and iii) the number of loci coding for the antigens of the pathogen. Isolating and discussing these three factors clarifies the relationship among previous models of multistrain dynamics, and establishes a solid theoretical foundation for the study of the evolutionary epidemiology of multistrain pathogens. [ABSTRACT FROM AUTHOR]

Prokaryotic CRISPR-Cas adaptive immune systems insert spacers derived from viruses and other parasitic DNA elements into CRISPR loci to provide sequence-specific immunity. This frequently results in high within-population spacer diversity, but it is unclear if and why this is important. Here we show that, as a result of this spacer diversity, viruses can no longer evolve to overcome CRISPR-Cas by point mutation, which results in rapid virus extinction. This effect arises from synergy between spacer diversity and the high specificity of infection, which greatly increases overall population resistance. We propose that the resulting short-lived nature of CRISPR-dependent bacteria-virus coevolution has provided strong selection for the evolution of sophisticated virus-encoded anti-CRISPR mechanisms.

Worldwide inequalities in vaccine availability are expected to affect the spread and spatial distribution of infectious diseases. It is unclear, however, how spatial variation in vaccination coverage can affect the long-term evolution of pathogens. Here we use an analytical model and numerical simulations to analyse the influence of different imperfect vaccines on the potential evolution of pathogen virulence in a two-population model where vaccination coverage varies between populations. We focus on four vaccines, with different modes of action on the life cycle of a pathogen infecting two host populations coupled by migration. We show that, for vaccines that reduce infection risk or transmissibility, spatial heterogeneity has little effect on pathogen prevalence and host mortality, and no effect on the evolution of pathogen virulence. In contrast, vaccines that reduce pathogen virulence can select for more virulent pathogens and may lead to the coexistence of different pathogen strains, depending on the degree of spatial heterogeneity in the metapopulation. This heterogeneity is driven by two parameters: pathogen migration and the difference in the vaccination rate between the two populations. We show that vaccines that only reduce pathogen virulence select mainly for a single pathogen strategy in the long term, while vaccines that reduce both transmission and virulence can favor the coexistence of two pathogen genotypes. We discuss the implications and potential extensions of our analysis. [ABSTRACT FROM AUTHOR]

The experimental validation of theoretical predictions is a crucial step in demonstrating the predictive power of a model. While quantitative validations are common in infectious diseases epidemiology, experimental microbiology primarily focuses on the evaluation of a qualitative match between model predictions and experiments. In this study, we develop a method to deepen the quantitative validation process with a polymorphic viral population. We analyse the data from an experiment carried out to monitor the evolution of the temperate bacteriophage λ spreading in continuous cultures of Escherichia coli. This experimental work confirmed the influence of the epidemiological dynamics on the evolution of transmission and virulence of the virus. A variant with larger propensity to lyse bacterial cells was favoured in emerging epidemics (when the density of susceptible cells was large), but counter-selected when most cells were infected. Although this approach qualitatively validated an important theoretical prediction, no attempt was made to fit the model to the data nor to further develop the model to improve the goodness of fit. Here, we show how theoretical analysis—including calculations of the selection gradients—and model fitting can be used to estimate key parameters of the phage life cycle and yield new insights on the evolutionary epidemiology of the phage λ. First, we show that modelling explicitly the infected bacterial cells which will eventually be lysed improves the fit of the transient dynamics of the model to the data. Second, we carry out a theoretical analysis that yields useful approximations that capture at the onset and at the end of an epidemic the effects of epidemiological dynamics on selection and differentiation across distinct life stages of the virus. Finally, we estimate key phenotypic traits characterizing the two strains of the virus used in our experiment such as the rates of prophage reactivation or the probabilities of lysogenization. This study illustrates the synergy between experimental, theoretical, and statistical approaches; and especially how interpreting the temporal variation in the selection gradient and the differentiation across distinct life stages of a novel variant is a powerful tool to elucidate the evolutionary epidemiology of emerging infectious diseases. [ABSTRACT FROM AUTHOR]