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McLeod, D. V.

Publications and source records attributed to McLeod, D. V..

3 recordsLinked to original sources

Mosaic vaccination: how distributing different vaccines across a population could improve epidemic control

Although vaccination has been remarkably effective against some pathogens, for others, rapid antigenic evolution results in vaccination conferring only weak and/or short-lived protection. Consequently, considerable effort has been invested in developing more evolutionarily robust vaccines, either by targeting highly conserved components of the pathogen (universal vaccines) or by including multiple immunological targets within a single vaccine (multi-epitope vaccines). An unexplored third possibility is to vaccinate individuals with one of a number of qualitatively different vaccines, creating a mosaic of individual immunity in the population. Here we explore whether a mosaic vaccination strategy can deliver superior epidemiological outcomes to conventional vaccination, in which all individuals receive the same vaccine. We suppose vaccine doses can be distributed between distinct vaccine targets (e.g., different surface proteins against which an immune response can be generated) and/or immunologically-distinct variants at these targets (e.g., strains); the pathogen can undergo antigenic evolution at both targets. Using simple mathematical models, we show that mosaic vaccination often outperforms conventional vaccination, leading to fewer infected individuals, improved vaccine efficacy, and lower individual risks over the course of the epidemic.

evolutionary biology

Epigenetic inheritance and the evolution of infectious diseases

Genes with identical DNA sequences may show differential expression because of epigenetic marks. These marks in pathogens are key to their virulence and are being evaluated as targets for medical treatment. Where epigenetic marks were created in response to past conditions (epigenetically inherited), they represent a form of memory, the impact of which has not been considered in the evolution of infectious diseases. We fill this gap by exploring the evolution of virulence in pathogens that inherit epigenetic information on the sex of their previous host. We show that memories of past hosts can also provide clues about the sex of present and future hosts when women and men differ in their immunity to infection and/or their interactions with the sexes. These biological and social differences between the sexes are pervasive in humans. We show that natural selection can favour the evolution of greater virulence in infections originating from one sex. Furthermore, natural selection can favour the evolution of greater virulence in infections across sexes (or within sexes). Our results explain certain patterns of virulence in diseases like measles, chickenpox and polio that have puzzled medical researchers for decades. In particular, they address why girls infected by boys (or boys infected by girls) are more likely to die from the infection than girls infected by girls (or boys infected by boys). We propose epigenetic therapies to treat infections by tampering with the memories of infecting pathogens. Counterintuitively, we predict that successful therapies should target pathogens genes that inhibit virulence, rather than those enhancing virulence. Our findings imply that pathogens can carry memories of past environments other than sex (e.g. those related to socioeconomic status) that may condition their virulence and could signify an important new direction in personalised medicine.

evolutionary biology

Understanding the evolution of multiple drug resistance in structured populations

The evolution of multidrug resistance (MDR) is a pressing public health concern. Yet many aspects, such as the role played by population structure, remain poorly understood. Here we argue that studying MDR evolution by focusing upon the dynamical equations for linkage disequilibrium (LD) can greatly simplify the calculations, generate more insight, and provide a unified framework for understanding the role of population structure. We demonstrate how a general epidemiological model of MDR evolution can be recast in terms of the LD equations. These equations reveal how the different forces generating and propagating LD operate in a dynamical setting at both the population and metapopulation levels. We then apply these insights to show how the LD perspective: (i) explains equilibrium patterns of MDR, (ii) provides a simple interpretative framework for transient evolutionary dynamics, and (iii) can be used to assess the consequences of different drug prescription strategies for MDR evolution.

evolutionary biology