Ben Adams

Cross-protective immunity can account for the alternating epidemic pattern of dengue virus serotypes circulating in Bangkok

Dengue virus, the causative agent of dengue fever and its more serious manifestation dengue hemorrhagic fever, is widespread throughout tropical and subtropical regions. The virus exists as four distinct serotypes, all of which have cocirculated in Bangkok for several decades with epidemic outbreaks occurring every 8–10 years. We analyze time-series data of monthly infection incidence, revealing a distinctive pattern with epidemics of serotypes 1, 2, and 3 occurring at approximately the same time and an isolated epidemic of serotype 4 occurring in the intervening years. Phylogenetic analysis of virus samples collected over the same period shows that clade replacement events are linked to the epidemic cycle and indicates that there is an interserotypic immune reaction. Using an epidemic model with stochastic seasonal forcing showing 8- to 10-year epidemic oscillations, we demonstrate that moderate cross-protective immunity gives rise to persistent out-of-phase oscillations similar to those observed in the data, but that strong or weak cross-protection or cross-enhancement only produces in-phase patterns. This behavior suggests that the epidemic pattern observed in Bangkok is the result of cross-protective immunity and may be significantly altered by changes in the interserotypic immune reaction.

Characterizing social cascades in flickr

Online social networking sites like MySpace and Flickr have become a popular way to share and disseminate content. Their massive popularity has led to the viral marketing of content, products, and political campaigns on the sites themselves. Despite the excitement, the precise mechanisms by which information is exchanged over these networks are not well understood. In this paper, we investigate social cascades, or how information disseminates through social links in online social networks. Using real traces of 1,000 popular photos and a social network collected from Flickr, and a theoretical framework borrowed from epidemiology, we show that social cascades are an important factor in the dissemination of content. Our work provides an important first step in understanding how information disseminates in social networks.

Man Bites Mosquito: Understanding the Contribution of Human Movement to Vector-Borne Disease Dynamics

In metropolitan areas people travel frequently and extensively but often in highly structured commuting patterns. We investigate the role of this type of human movement in the epidemiology of vector-borne pathogens such as dengue. Analysis is based on a metapopulation model where mobile humans connect static mosquito subpopulations. We find that, due to frequency dependent biting, infection incidence in the human and mosquito populations is almost independent of the duration of contact. If the mosquito population is not uniformly distributed between patches the transmission potential of the pathogen at the metapopulation level, as summarized by the basic reproductive number, is determined by the size of the largest subpopulation and reduced by stronger connectivity. Global extinction of the pathogen is less likely when increased human movement enhances the rescue effect but, in contrast to classical theory, it is not minimized at an intermediate level of connectivity. We conclude that hubs and reservoirs of infection can be places people visit frequently but briefly and the relative importance of human and mosquito populations in maintaining the pathogen depends on the distribution of the mosquito population and the variability in human travel patterns. These results offer an insight in to the paradoxical observation of resurgent urban vector-borne disease despite increased investment in vector control and suggest that successful public health intervention may require a dual approach. Prospective studies can be used to identify areas with large mosquito populations that are also visited by a large fraction of the human population. Retrospective studies can be used to map recent movements of infected people, pinpointing the mosquito subpopulation from which they acquired the infection and others to which they may have transmitted it.

How important is vertical transmission in mosquitoes for the persistence of dengue? Insights from a mathematical model.

In many regions dengue incidence fluctuates seasonally with few if any infections reported in unfavourable periods. It has been hypothesized that vertical transmission within the mosquito population allows the virus to persist at these times. A review of the literature shows that vertical infection efficiencies are 1-4%. Using a mathematical model we argue that at these infection rates vertical transmission is not an important factor for long term virus persistence. In endemic situations, increases in reproductive number, half-life and persistence times of the disease only become significant when vertical infection efficiency exceeds 20-30%. In epidemic situations vertical infection accelerates the course of the outbreak and may actually reduce persistence time. These results stem from the fact that the mosquito life-cycle is relatively rapid and vertically acquired infections are multiplicatively diluted with every generation. When the efficiency of vertical infection is as low as reported from empirical studies, the virus is rapidly lost unless there is regular amplification in the human population. Processes such as asymptomatic human dengue cases are therefore more likely to be important in persistence than transmission within the vector population. The empirical data are not, however, unequivocal and we identify several areas of research that would further clarify the role of vertical transmission in the epidemiology of dengue.

The Role of Genomics in Tracking the Evolution of Influenza A Virus

Influenza A virus causes annual epidemics and occasional pandemics of short-term respiratory infections associated with considerable morbidity and mortality. The pandemics occur when new human-transmissible viruses that have the major surface protein of influenza A viruses from other host species are introduced into the human population. Between such rare events, the evolution of influenza is shaped by antigenic drift: the accumulation of mutations that result in changes in exposed regions of the viral surface proteins. Antigenic drift makes the virus less susceptible to immediate neutralization by the immune system in individuals who have had a previous influenza infection or vaccination. A biannual reevaluation of the vaccine composition is essential to maintain its effectiveness due to this immune escape. The study of influenza genomes is key to this endeavor, increasing our understanding of antigenic drift and enhancing the accuracy of vaccine strain selection. Recent large-scale genome sequencing and antigenic typing has considerably improved our understanding of influenza evolution: epidemics around the globe are seeded from a reservoir in East-Southeast Asia with year-round prevalence of influenza viruses; antigenically similar strains predominate in epidemics worldwide for several years before being replaced by a new antigenic cluster of strains. Future in-depth studies of the influenza reservoir, along with large-scale data mining of genomic resources and the integration of epidemiological, genomic, and antigenic data, should enhance our understanding of antigenic drift and improve the detection and control of antigenically novel emerging strains.

Coexistence conditions for strains of influenza with immune cross-reaction

The accumulation of cross-immunity in the host population is an important factor driving the antigenic evolution of viruses such as influenza A. Mathematical models have shown that the strength of temporary non-specific cross-immunity and the basic reproductive number are both key determinants for evolutionary branching of the antigenic phenotype. Here we develop deterministic and stochastic versions of one such model. We examine how the time of emergence or introduction of a novel strain affects co-existence with existing strains and hence the initial establishment of a new evolutionary branch. We also clarify the roles of cross-immunity and the basic reproductive number in this process. We show that the basic reproductive number is important because it affects the frequency of infection, which influences the long term immune profile of the host population. The time at which a new strain appears relative to the epidemic peak of an existing strain is important because it determines the environment the emergent mutant experiences in terms of the short term immune profile of the host population. Strains are more likely to coexist, and hence to establish a new clade in the viral phylogeny, when there is a significant time overlap between their epidemics. It follows that the majority of antigenic drift in influenza is expected to occur in the earlier part of each transmission season and this is likely to be a key surveillance period for detecting emerging antigenic novelty.

One-dimensional daisyworld: spatial interactions and pattern formation.

The zero-dimensional daisyworld model of Watson and Lovelock (1983) demonstrates that life can unconsciously regulate a global environment. Here that model is extended to one dimension, incorporating a distribution of incoming solar radiation and diffusion of heat consistent with a spherical planet. Global regulatory properties of the original model are retained. The daisy populations are initially restricted to hospitable regions of the surface but exert both global and local feedback to increase this habitable area, eventually colonizing the whole surface. The introduction of heat diffusion destabilizes the coexistence equilibrium of the two daisy types. In response, a striped pattern consisting of blocks of all black or all white daisies emerges. There are two mechanisms behind this pattern formation. Both are connected to the stability of the system and an overview of the mathematics involved is presented. Numerical experiments show that this pattern is globally determined. Perturbations in one region have an impact over the whole surface but the regulatory properties of the system are not compromised by transient perturbations. The relevance of these results to the Earth and the wider climate modelling field is discussed.

Disrupting seasonality to control disease outbreaks:the case of koi herpes virus

Common carp accounts for a substantial proportion of global freshwater aquaculture production. Koi herpes virus (KHV), a highly virulent disease affecting carp that emerged in the late 1990s, is a serious threat to this industry. After a fish is infected with KHV, there is a temperature dependent delay before it becomes infectious, and a further delay before mortality. Consequently, KHV epidemiology is driven by seasonal changes in water temperature. Also, it has been proposed that outbreaks could be controlled by responsive management of water temperature in aquaculture setups. We use a mathematical model to analyse the effect of seasonal temperature cycles on KHV epidemiology, and the impact of attempting to control outbreaks by disrupting this cycle. We show that, although disease progression is fast in summer and slow in winter, total mortality over a 2-year period is similar for outbreaks that start in either season. However, for outbreaks that start in late autumn, mortality may be low and immunity high. A single bout of water temperature management can be an effective outbreak control strategy if it is started as soon as dead fish are detected and maintained for a long time. It can also be effective if the frequency of infectious fish is used as an indicator for the beginning of treatment. In this case, however, there is a risk that starting the treatment too soon will increase mortality relative to the case when no treatment is used. This counterproductive effect can be avoided if multiple bouts of temperature management are used. We conclude that disrupting normal seasonal patterns in water temperature can be an effective strategy for controlling koi herpes virus. Exploiting the seasonal patterns, possibly in combination with temperature management, can also induce widespread immunity to KHV in a cohort of fish. However, employing these methods successfully requires careful assessment to ensure that the treatment is started, and finished, at the correct time.

Antigenic distance and cross-immunity, invasibility and coexistence of pathogen strains in an epidemiological model with discrete antigenic space.

In models of pathogen interaction and evolution discrete genotypes in the form of bit strings may be mapped to points in a discrete phenotype space based on similarity in antigenic structure. Cross-immunity between strains, that is the reduction in susceptibility to strain A conferred to a host by infection with strain B, can then be defined for pairs of points in the antigenic space by a specified function. Analysis of an SIR type model shows that, if two strains are at equilibrium, the shape of the cross-immunity function has a strong influence on the invasion and coexistence of a third strain and, consequently, the expected evolutionary pathway. A function that is constant except for discontinuities at the end points is expected to result in the accumulation of diversity until a pair of discordant strains occurs that can, depending on parameter values, exclude all other strains. For a function of the form f(h)=h(q), where h is the antigenic distance between two strains, invasion and coexistence is always possible if q<or=1 and little antigenic structure is expected in the pathogen population. However, if q>1 invasion and coexistence may be impossible, depending on parameter values, and the pathogen population is expected to show significant antigenic structuring. In addition to illuminating the role of cross-immunity in pathogen evolution, this analysis indicates that the choice of cross-immunity function, the representation of immunity acquired from multiple previous infections and the number of elements used to characterize the antigenic space must be carefully considered in the development and interpretation of more sophisticated models of pathogen dynamics and evolution.

Spatial pattern formation in a model of vegetation-climate feedback

We consider a spatial version of Watson and Lovelocks tutorial model of vegetation-climate feedbacks (Watson A J and Lovelock J E 1983 Biological homeostasis of the global environment: the parable of daisyworld Tellus B 35 284–9). Two simple plant types compete on a hypothetical planet, stabilizing the global temperature via an albedo feedback. Numerical solutions show an alternating pattern of the two plant types. A stability analysis shows that there are two mechanisms involved in the pattern formation. A Turing-like process causes the uniform equilibrium state to be unstable to non-constant perturbations and the solution tends towards a striped pattern. This solution is then modified by a mechanism which restricts stripe length and results in subdivision. By calculating the associated temperature function we show how the maximum stripe length can be determined and the stability of different patterns assessed.