Showing papers by "Pejman Rohani published in 2006"
TL;DR: Examples from human and wildlife disease systems are reviewed to illustrate the challenges inherent in understanding the mechanisms and impacts of seasonal environmental drivers, and to highlight general insights that are relevant to other ecological interactions.
Abstract: Seasonal variations in temperature, rainfall and resource availability are ubiquitous and can exert strong pressures on population dynamics. Infectious diseases provide some of the best-studied examples of the role of seasonality in shaping population fluctuations. In this paper, we review examples from human and wildlife disease systems to illustrate the challenges inherent in understanding the mechanisms and impacts of seasonal environmental drivers. Empirical evidence points to several biologically distinct mechanisms by which seasonality can impact host-pathogen interactions, including seasonal changes in host social behaviour and contact rates, variation in encounters with infective stages in the environment, annual pulses of host births and deaths and changes in host immune defences. Mathematical models and field observations show that the strength and mechanisms of seasonality can alter the spread and persistence of infectious diseases, and that population-level responses can range from simple annual cycles to more complex multiyear fluctuations. From an applied perspective, understanding the timing and causes of seasonality offers important insights into how parasite-host systems operate, how and when parasite control measures should be applied, and how disease risks will respond to anthropogenic climate change and altered patterns of seasonality. Finally, by focusing on well-studied examples of infectious diseases, we hope to highlight general insights that are relevant to other ecological interactions.
1,304 citations
TL;DR: To generate epidemics with the characteristic signatures observed in data, it is found that a combination of seasonal variation in vector demography and a short-lived period of cross-immunity is sufficient.
Abstract: The management of infectious diseases is an increasingly important public health issue, the effective implementation of which is often complicated by difficulties in teasing apart the relative roles of extrinsic and intrinsic factors influencing transmission. Dengue, a vector-borne strain polymorphic disease, is one such infection where transmission dynamics are affected by environmental variables as well as immune-mediated serotype interactions. To understand how alternative hypotheses concerning dengue infection and transmission may explain observed multiannual cycles in disease incidence, we adopt a theoretical approach that combines both ecological and immunological mechanisms. We demonstrate that, contrary to perceived wisdom, patterns generated solely by antibody-dependent enhancement or heterogeneity in virus virulence are not consistent with serotype-specific notification data in important ways. Furthermore, to generate epidemics with the characteristic signatures observed in data, we find that a combination of seasonal variation in vector demography and, crucially, a short-lived period of cross-immunity is sufficient. We then show how understanding the persistence and eradication of dengue serotypes critically depends on the alternative assumed mechanisms.
337 citations
TL;DR: It is shown that the interaction between density dependent effects and harvesting can substantially increase both disease prevalence and the absolute number of infectious individuals, which clearly increases the risk of cross-species disease transmission into domestic and livestock populations.
Abstract: Theoretical studies of wildlife population dynamics have proved insightful for sustainable management, where the principal aim is to maximize short-term yield, without risking population extinction. Surprisingly, infectious diseases have not been accounted for in harvest models, which is a major oversight because the consequences of parasites for host population dynamics are well-established. Here, we present a simple general model for a host species subject to density dependent reproduction and seasonal demography. We assume this host species is subject to infection by a strongly immunizing, directly transmitted pathogen. In this context, we show that the interaction between density dependent effects and harvesting can substantially increase both disease prevalence and the absolute number of infectious individuals. This effect clearly increases the risk of cross-species disease transmission into domestic and livestock populations. In addition, if the disease is associated with a risk of mortality, then the synergistic interaction between hunting and disease-induced death can increase the probability of host population extinction.
113 citations
TL;DR: In this article, the authors use extensive numerical simulations to demonstrate that the periodic nature of pulse vaccination strategies can make disease dynamics resonate and emphasize the importance of carefully taking into account the dynamical properties of the disease when designing a pulse vaccination strategy.
105 citations
07 Aug 2006
TL;DR: The reader is introduced to the most important notions of epidemic modeling based on the presentation of the classic models as well as the very basic SIR epidemiological model.
Abstract: witnessed the rapid emergence and development of a substantial theory of epidemics. In 1927, Kermack and McKendrick [41] derived the celebrated threshold theorem, which is one of the key results in epidemiology. It predicts – depending on the transmission potential of the infection – the critical fraction of susceptibles in the population that must be exceeded if an epidemic is to occur. This was followed by the classic work of Bartlett [9], who examined models and data to expose the factors that determine disease persistence in large populations. Arguably, the first landmark book on mathematical modeling of epidemiological systems was published by Bailey [8] which led in part to the recognition of the importance of modeling in public health decision making [7]. Given the diversity of infectious diseases studied since the middle of the 1950s, an impressive variety of epidemiological models have been developed.A comprehensive review of them would be both beyond the scope of the present chapter and of limited interest. Instead, here we introduce the reader to the most important notions of epidemic modeling based on the presentation of the classic models. After presenting general notions of mathematical modeling (Section 22.2) and the nature of epidemiological data available to the modeler (Section 22.3), we detail the very basic SIR epidemiological model (Section 22.5).We explain
83 citations
TL;DR: A seasonally-forced mathematical model provides the threshold condition for disease control in terms of four major parameters: coverage of the primary vaccine; efficacy of the vaccine; waning rate; and the rate of booster administration, and shows that if the vaccine provides only temporary immunity, then the infection typically cannot be eradicated by a single vaccination episode.
Abstract: Despite the effectiveness of vaccines in dramatically decreasing the number of new infectious cases and severity of illnesses, imperfect vaccines may not completely prevent infection. This is because the immunity afforded by these vaccines is not complete and may wane with time, leading to resurgence and epidemic outbreaks notwithstanding high levels of primary vaccination. To prevent an endemic spread of disease, and achieve eradication, several countries have introduced booster vaccination programs. The question of whether this strategy could eventually provide the conditions for global eradication is addressed here by developing a seasonally-forced mathematical model. The analysis of the model provides the threshold condition for disease control in terms of four major parameters: coverage of the primary vaccine; efficacy of the vaccine; waning rate; and the rate of booster administration. The results show that if the vaccine provides only temporary immunity, then the infection typically cannot be eradicated by a single vaccination episode. Furthermore, having a booster program does not necessarily guarantee the control of a disease, though the level of epidemicity may be reduced. In addition, these findings strongly suggest that the high coverage of primary vaccination remains crucial to the success of a booster strategy. Simulations using estimated parameters for measles illustrate model predictions.
58 citations
TL;DR: A seasonally forced two-disease age-structured model using empirically derived age-specific force of infection (ASFOI) for numerous infections of childhood concludes that age structure is an important factor that should be taken into account in order to explore the underlying mechanisms of disease interference.
Abstract: Recent studies have demonstrated that ecological interference among some childhood diseases may have important dynamic consequences. An interesting question is, when would we expect the interference effect to be pronounced? To address the issue, here we develop a seasonally forced two-disease age-structured model, using empirically derived age-specific force of infection (ASFOI) for numerous infections of childhood. Our comparative numerical analysis shows that when the ASFOIs for the two diseases largely overlap, the dynamics predicted by the two-disease model are generally different from those predicted by the analogous single-disease model, suggesting strong fingerprints of disease interference. When the ASFOIs overlap less, on the other hand, both diseases behave as predicted by the single-disease model, suggesting weak interference. We conclude that age structure is an important factor that should be taken into account in order to explore the underlying mechanisms of disease interference.
17 citations
TL;DR: A simulation model to explore the influence of aggregation on coexistence in communities of species competing for patchy ephemeral resources shows that, in the absence of any intraspecific aggregation, variation between species in the way that resource heterogeneity affects survival increases the likelihood of species coexistence.
Abstract: It is well established that intraspecific aggregation has the potential to promote coexistence in communities of species competing for patchy ephemeral resources. We developed a simulation model to explore the influence of aggregation on coexistence in such communities when an important assumption of previous studies - that interspecific interactions have only negative effects on the species involved - is relaxed. The model describes a community of competing insect larvae in which an interaction that is equivalent to intraguild predation (IGP) can occur, and is unusual in that it considers species exploiting very small resource patches (carrying capacity = 1). Model simulations show that, in the absence of any intraspecific aggregation, variation between species in the way that resource heterogeneity affects survival increases the likelihood of species coexistence. Simulations also show that intraspecific aggregation of the dominant competitor's eggs across resource patches can promote coexistence by reducing the importance of interspecific competition relative to that of intraspecific competition. Crucially, however, this effect is altered if one competitor indulges in IGP. In general, coexistence is only possible when the species that is capable of IGP is less effective at exploiting the shared resource than its competitor. Because it reduces the relative importance of interspecific interactions, intraspecific aggregation of the eggs of a species that is the victim of IGP actually reduces the likelihood of coexistence in parts of parameter space in which the persistence of the other species is dependent on its ability to exploit its competitor. Since resource heterogeneity, intraspecific aggregation and IGP are all common phenomena, these findings shed light on mechanisms that are likely to influence diversity in communities exploiting patchy resources.
4 citations
07 Aug 2006
TL;DR: Genetics and Evolution of Infectious Diseases,’’ UMR CNRS/IRD 2724, Institute of Research for the Development (IRD), BP 64501 34394 Montpellier Cedex 5, France.
Abstract: H Broutin,1 N Mantilla-Beniers,2 and P Rohani3 1Unit of Research 165 “Genetics and Evolution of Infectious Diseases,’’ UMR CNRS/IRD 2724, Institute of Research for the Development (IRD), BP 64501 34394 Montpellier Cedex 5, France 2Department of Zoology, University of Cambridge, Downing Street, Cambridge, CB2 3EJ, United Kingdom and Instituto Gulbenkian de Ciencia,Apartado 14, 2781-901 Oeiras, Portuga 3Institute of Ecology, University of Georgia,Athens, GA 30602, USA
2 citations