Epidemiological landscape models reproduce cyclic insect outbreaks

Forest insect outbreaks can have large impacts on ecosystems and understanding the underlying ecological processes is critical for their management. Current process-based modeling approaches of insect outbreaks are often based on population processes operating at small spatial scales (i.e. within individual forest stands). As such, they are difficult to parameterize and offer limited applicability when modeling and predicting outbreaks at the landscape level where management actions take place. In this paper, we propose a new process-based landscape model of forest insect outbreaks that is based on stand defoliation, the Forest-Infected-Recovering-Forest (FIRF) model. We explore both spatially-implicit (mean field equations with global dispersal) and spatially-explicit (cellular automata with limited dispersal between neighboring stands) versions of this model to assess the role of dispersal in the landscape dynamics of outbreaks. We show that density-dependent dispersal is necessary to generate cyclic outbreaks in the spatially-implicit version of the model. The spatially-explicit FIRF model with local and stochastic dispersal displays cyclic outbreaks at the landscape scale and patchy outbreaks in space, even without density-dependence. Our simple, process-based FIRF model reproduces large scale outbreaks and can provide an innovative approach to model and manage forest pests at the landscape scale.     

Meningitis,pathogenicity near criticality: the epidemiology of meningococcal disease as a model for accidental pathogens

We formulate and analyse a model for infectious diseases transmitted by asymptomatic carriers finding, that if harmless and pathogenic strains of the infected agent compete, frequent outbreaks of the pathogenic strains can occur. A counterintuitively high number of clustered outbreaks at low pathogenicity in our model compares well with observations in diseases with severe and often fatal results for the host, as for example in meningitis. These clustered outbreaks can be described by the typical scaling behaviour around criticality. The epidemic model is a susceptible-infected-recovered system (SIR) for the harmless infective agent, acting as a background to a mutant strain Y which occasionally creates severely affected hosts X. The full system of SIRYX is described in the master equation framework, confirming limiting assumptions about a reduced YX-system with the SIR-system in stationarity. In this limiting case we can analytically show convergence to power law scaling typical for critical states, as well as the divergence of the variance of outbreaks near criticality. These large fluctuations of outbreaks of accidental pathogens as mutants of otherwise harmless commensal organisms is the challenging new feature of our model for future epidemiology of diseases like meningococcal disease.     

A neuroeconomic theory of rational addiction and nonlinear time-perception

Neuroeconomic conditions for "rational addiction" (Becker & Murphy 1988) have been unknown. This paper derived the conditions for "rational addiction" by utilizing a nonlinear time-perception theory of "hyperbolic" discounting, which is mathematically equivalent to the q-exponential intertemporal choice model based on Tsallis' statistics. It is shown that (i) Arrow-Pratt measure for temporal cognition corresponds to the degree of irrationality (i.e., Prelec's "decreasing impatience" parameter of temporal discounting) and (ii) rationality in addicts is controlled by a nondimensionalization parameter of the logarithmic time-perception function. Furthermore, the present theory illustrates the possibility that addictive drugs increase impulsivity via dopaminergic neuroadaptation without increasing irrationality. Future directions in the application of the model to studies in neuroeconomics are discussed.     

Recurrent and synchronous insect pest outbreaks in forests

A minimal model for the interactions of trees, insects, and their enemies suggests a simple formula for splitting all forests where insect outbreaks can occur into two categories: where outbreaks are periodic and endogenously generated and where outbreaks are triggered by exogenous factors and are, in general, recurrent but aperiodic. The formula is in full agreement with all field studies in which various phenomena triggering insect outbreaks have been identified. The observed consequences of introductions and removals of insects are also well predicted by the minimal model. But, even more surprisingly, the model allows a simple and explicit condition for the synchronization of outbreaks in spatially extended forests to be derived analytically. This condition is, in general, satisfied when the insect is a so-called pest, that is, when the outbreaks are extreme. The model also predicts the possibility of traveling waves of insect outbreaks.     

How parasitism affects critical patch-size in a host-parasitoid model: application to the forest tent caterpillar

Habitat structure has broad impacts on many biological systems. In particular, habitat fragmentation can increase the probability of species extinction and on the other hand it can lead to population outbreaks in response to a decline in natural enemies. An extreme consequence of fragmentation is the isolation of small regions of suitable habitat surrounded by a large region of hostile matrix. This scenario can be interpreted as a critical patch-size problem, well studied in a continuous time framework, but relatively new to discrete time models. In this paper we present an integrodifference host-parasitoid model, discrete in time and continuous in space, to study how the critical habitat-size necessary for parasitoid survival changes in response to parasitoid life history traits, such as emergence time. We show that early emerging parasitoids may be able to persist in smaller habitats than late emerging species. The model predicts that these early emerging parasitoids lead to more severe host outbreaks. We hypothesise that promoting efficient late emerging parasitoids may be key in reducing outbreak severity, an approach requiring large continuous regions of suitable habitat. We parameterise the model for the host species of the forest tent caterpillar Malacosoma disstria Hbn., a pest insect for which fragmented landscape increases the severity of outbreaks. This host is known to have several parasitoids, due to paucity of data and as a first step in the modelling we consider a single generic parasitoid. The model findings are related to observations of the forest tent caterpillar offering insight into this host-parasitoid response to habitat structure.     

Thermodynamic extremal principles in evolution

Summary An evolutionary ecosystem may be described in terms of a quasi autocatalytic model, i.e. in terms of a sequence of different autocatalytic systems. Such a sequence can exhibit considerable evolutionary change (for example, adjustment of various rate constants) even if the dissipation function remains essentially the same. Under these conditions the dissipation is always a monotonically increasing function of the concentration of catalyst (biomass) and certain rate constants (the catalytic capacity). Biomass and catalytic capacity are complementary in the sense that the quasi autocatalytic system always assumes a steady state by varying these quantities in the opposite direction (all other conditions remaining constant). This means that evolutionary systems cannot exhibit orthogenetic increases in both rate of operation and biomass, at least within any given evolutionary epoch. This has implications for the importance of spatial heterogeneity in stabilizing the behavior of evolutionary systems.     

Disease,population viability,and recovery of endangered Sierra Nevada bighorn sheep

Sierra Nevada bighorn sheep (Ovis canadensis sierrae) experienced a severe population decline after European settlement from which they have never recovered; this subspecies was listed as endangered under the United States Endangered Species Act (ESA) in 1999. Recovery of a listed species is accomplished via federally mandated recovery plans with specific population goals. Our main objective was to evaluate the potential impact of disease on the probability of meeting specific population size and persistence goals, as outlined in the Sierra Nevada bighorn sheep recovery plan. We also sought to heuristically evaluate the efficacy of management strategies aimed at reducing disease risk to or impact on modeled bighorn populations. To do this, we constructed a stochastic population projection model incorporating disease dynamics for 3 populations (Langley, Mono, Wheeler) based on data collected from 1980 to 2007. We modeled the dynamics of female bighorns in 4 age classes (lamb, yearling, adult, senescent) under 2 disease scenarios: 5% lower survival across the latter 3 age classes and persistent 65% lower lamb survival (i.e., mild) or 65% reduced survival across all age classes followed by persistent 65% lower lamb survival (i.e., severe). We simulated management strategies designed to mitigate disease risk: reducing the probability of a disease outbreak (to represent a strategy like domestic sheep grazing management) and reducing mortality rate (to represent a strategy that improved survival in the face of introduced disease). Results from our projection model indicated that management strategies need to be population specific. The population with the highest growth rate ( ; Langley; = 1.13) was more robust to the effects of disease. By contrast, the population with the lowest growth rate (Mono; = 1.00) would require management intervention beyond disease management alone, and the population with a moderate growth rate (Wheeler; = 1.07) would require management sufficient to prevent severe disease outbreaks. Because severe outbreaks increased adult mortality, disease can directly reduce the probability of meeting recovery plan goals. Although mild disease outbreaks had minimal direct effects on the populations, they reduced recruitment and the number of individuals available for translocation to other populations, which can indirectly reduce the probability of meeting overall, range-wide minimum population size goals. Based on simulation results, we recommend reducing the probability of outbreak by continuing efforts to manage high-risk (i.e., spatially close) allotments through restricted grazing regimes and stray management to ensure recovery for Wheeler and Mono. Managing bighorn and domestic sheep for geographic separation until Sierra Nevada bighorn sheep achieve recovery objectives would enhance the likelihood of population recovery. © 2011 The Wildlife Society.     

An IDEA for Short Term Outbreak Projection: Nearcasting Using the Basic Reproduction Number

Background

Communicable disease outbreaks of novel or existing pathogens threaten human health around the globe. It would be desirable to rapidly characterize such outbreaks and develop accurate projections of their duration and cumulative size even when limited preliminary data are available. Here we develop a mathematical model to aid public health authorities in tracking the expansion and contraction of outbreaks with explicit representation of factors (other than population immunity) that may slow epidemic growth.

Methodology

The Incidence Decay and Exponential Adjustment (IDEA) model is a parsimonious function that uses the basic reproduction number R₀, along with a discounting factor to project the growth of outbreaks using only basic epidemiological information (e.g., daily incidence counts).

Principal Findings

Compared to simulated data, IDEA provides highly accurate estimates of total size and duration for a given outbreak when R₀ is low or moderate, and also identifies turning points or new waves. When tested with an outbreak of pandemic influenza A (H1N1), the model generates estimated incidence at the i+1^th serial interval using data from the i^th serial interval within an average of 20% of actual incidence.

Conclusions and Significance

This model for communicable disease outbreaks provides rapid assessments of outbreak growth and public health interventions. Further evaluation in the context of real-world outbreaks will establish the utility of IDEA as a tool for front-line epidemiologists.     

Mental impairment in Martin-Bell syndrome is probably determined by interaction of several genes: simple explanation of phenotypic differences between unaffected and affected males with the same X chromosome

Summary A family with Martin-Bell syndrome (MBS) is described with transmission of this X-linked trait by a normal male who manifested the fragile site at Xq27. This family shows features apparently typical for all families with a normal male transmitter. The daughters of this male are mentally normal and their fragile site is difficult or impossible to detect but detection of the heterozygous genotype is much easier among the granddaughters. This can be explained by a model assuming that mental deficiency in patients with MBS is determined by several genes, i.e. the X-linked MBS-gene as major gene undergoing X-inactivation and interacting with at least one modifying gene. The model assuming one autosomal modifier segregating independently from the MBS-gene is tested using the results of segregation analysis performed by Sherman et al. (1984, 1985). No significant differences have been found between the predictions of this model and the findings of the segregation analysis. Nearly all of the segregation data are exactly predicted by the model. Possible differences are discussed either to be due to biased data or to require slight modification of the model to get a better fit of the data. The apparent phenotypic differences between a normal carrier grand-father and his affected grandsons as well as between his daughters and his heterozygous granddaughters are also simply explained on the basis of this model. Several modifier loci may exist each of them related to one of the various phenotypic effects of the X-linked major gene (MBS-gene) leading typic effects of the X-linked major gene (MBS-gene) leading to a syndrome that does not include any obligate feature.     

Mechanical-Statistical Modeling in Ecology: From Outbreak Detections to Pest Dynamics

Knowledge about large-scale and long-term dynamics of (natural) populations is required to assess the efficiency of control strategies, the potential for long-term persistence, and the adaptability to global changes such as habitat fragmentation and global warming. For most natural populations, such as pest populations, large-scale and long-term surveys cannot be carried out at a high resolution. For instance, for population dynamics characterized by irregular abundance explosions, i.e., outbreaks, it is common to report detected outbreaks rather than measuring the population density at every location and time event. Here, we propose a mechanical-statistical model for analyzing such outbreak occurrence data and making inference about population dynamics. This spatio-temporal model contains the main mechanisms of the dynamics and describes the observation process. This construction enables us to account for the discrepancy between the phenomenon scale and the sampling scale. We propose the Bayesian method to estimate model parameters, pest densities and hidden factors, i.e., variables involved in the dynamics but not observed. The model was specified and used to learn about the dynamics of the European pine sawfly (Neodiprion sertifer Geoffr., an insect causing major defoliation of pines in northern Europe) based on Finnish sawfly data covering the years 1961–1990. In this application, a dynamical Beverton–Holt model including a hidden regime variable was incorporated into the model to deal with large variations in the population densities. Our results gave support to the idea that pine sawfly dynamics should be studied as metapopulations with alternative equilibria. The results confirmed the importance of extreme minimum winter temperatures for the occurrence of European pine sawfly outbreaks. The strong positive connection between the ratio of lake area over total area and outbreaks was quantified for the first time.     

Introduction to the food safety concerns of verotoxin-producing Escherichia coli

Verotoxin-producing Escherichia coli (VTEC) have emerged in the past two decades as food-borne pathogens that can cause major outbreaks of human illnesses worldwide. The number of outbreaks has increased in recent years due to changes in food production and processing systems, eating habits, microbial adaptation, and methods of VTEC transmission. The human illnesses range from mild diarrhea to hemolytic uremic syndrome (HUS) that can lead to death. The VTEC outbreaks have been attributed to O157:H7 and non-O157:H7 serotypes of E. coli. These E. coli serotypes include motile (e.g., O26:H11 and O104:H21) and nonmotile (e.g., O111:H-, O145:H-, and O157:H-) strains. In the United States, E. coli O157:H7 has been the major cause of VTEC outbreaks. Worldwide, however, non-O157:H7 VTEC (e.g., members of the O26, O103, O111, O118, O145, and O166 serogroups) have caused approximately 30% of the HUS cases in the past decade. Because large numbers of the VTEC outbreaks have been attributed to consumption of ruminant products (e.g., ground beef), cattle and sheep are considered reservoirs of these food-borne pathogens. Because of the food safety concern of VTEC, a global perspective on this problem is addressed (Exp Biol Med Vol. 228, No. 4). The first objective was to evaluate the known non-O157:H7 VTEC strains and the limitations associated with their detection and characterization. The second objective was to identify the VTEC serotypes associated with outbreaks of human illnesses and to provide critical evaluation of their virulence. The third objective was to determine the rumen effect on survival of E. coli O157:H7 as a VTEC model. The fourth objective was to explore the role of intimins in promoting attaching and effacing lesions in humans. Finally, the ability of VTEC to cause persistent infections in cattle was evaluated.     

Clearance of fear memory from the hippocampus through neurogenesis by omega-3 fatty acids: a novel preventive strategy for posttraumatic stress disorder?

Not only has accidental injury been shown to account for a significant health burden on all populations, regardless of age, sex and geographic region, but patients with accidental injury frequently present with the psychiatric condition of posttraumatic stress disorder (PTSD). Prevention of accident-related PTSD thus represents a potentially important goal. Physicians in the field of psychosomatic medicine and critical care medicine have the opportunity to see injured patients in the immediate aftermath of an accident. This article first briefly reviews the prevalence and associated factors of accident-related PTSD, then focuses on a conceptual model of fear memory and proposes a new, rationally hypothesized translational preventive intervention for PTSD through promoting hippocampal neurogenesis by omega-3 fatty acid supplementation. The results of an open-label pilot trial of injured patients admitted to the intensive care unit suggest that omega-3 fatty acid supplementation immediately after accidental injury can reduce subsequent PTSD symptoms.     

Population outbreaks in a discrete world

We present and analyze a simple three-patch host-parasitoid model where population growth is discrete. The model gives solutions that are qualitatively similar to the stable large-amplitude patterns in space found in reaction-diffusion theory. In the context of host-parasitoid interactions, the large-amplitude portions of the solution can be thought of as spatially localized host population outbreaks. Here, we show that the biological requirements for localized population outbreaks in a discrete world are identical to those found in reaction- diffusion theory. Furthermore, the model conveniently allows investigation into the robustness of these population outbreaks under the influence of density-dependent dispersal behavior. We find that localized population outbreaks in space can still occur with modest amounts of pursuit and aggregative behavior by parasitoids. We end by showing that evidence from a real host-parasitoid system is consistent with the predictions of the model.     

Recruitment in networks of pulmonary capillaries.

To improve our understanding of the pressure-flow characteristics of pulmonary capillaries, we analyzed by means of computer stimulation a theoretical model composed of 50 interconnected nonlinear elements. Each element required a critical pressure across it before flow occurred and there was a subsequent linear pressure-flow region whose slope, or resistance, could be related to the transmural pressure of the element ("distensibility"). The critical pressures and resistances of each element of the network were randomly chosen from distributions. We found that recruitment (i.e., onset of flow) occurred over a large range of network upstream or "arterial" pressures, and that relatively high arterial pressures were required before all elements had no distensibility. Intermittent and reverse flow were commonly seen in some elements as the arterial pressure was raised in steps. These flow reversals were particularly common when the critical pressures and resistances of the elements were inversely related. The critical pressures required for such behavior in the capillary segments of the pulmonary microcirculation were calculated to be extremely small, of the order of 0.02 cmH2O. Pressures of this magnitude might result from sticking of red cells to capillary walls or to each other. The properties of such a network may explain the patchiness of flow in the pulmonary microcirculation and the large range of arterial pressures over which recruitment is observed to occur.     

Human evolution in Polynesia

The number of eastern Polynesian females required to found the Maori population of Aotearoa (New Zealand) has been recalculated. Our estimates use computer simulations that incorporate realistic sigmoid population growth models and include previously published and new mitochondrial DNA (mtDNA) 3' hypervariable region 1 sequences from M?ori (N = 109) and other eastern Polynesian (N = 125) volunteers. Approximately 190 (170-230) women are estimated to have been present in the founding waka (canoes). This new figure is more than double the previous estimate (Murray-McIntosh et al. 1998). Our claim for a large Maori founding population fits well with M?ori oral history and has additional support from M?ori paleodemography studies based on fertility estimates (Brewis et al. 1990; Pool 1991). An increasing body of data, including our own, supports the concept of planned multiple settlement voyages to Aotearoa by Polynesian navigators, leading us to suggest that theories for an "accidental discovery" of Aotearoa can now be completely disregarded. Four rare and novel M?ori mtDNA haplotypes have been identified in the present study, but we are unable to assign the immediate origin of M?ori to an exact Pacific island "homeland" because these haplotypes are not currently known elsewhere in Polynesia. We also discuss briefly the ultimate origin of all Polynesians (including M?ori) in a wider context. In general, we support the emerging consensus for Pacific origins most closely encapsulated by the "slow boat" model (Oppenheimer and Richards 2001a). Previously "competing" models for the settlement of Oceania are seen as extremes in a continuum of possibilities with the slow boat representing an "intermediate" model. We suggest that a complete account is now close, incorporating data from all relevant interdisciplinary fields to provide a "synthetic total evidence theory."     

Modelling whole-plant allocation in relation to carbon and nitrogen supply: Coordination versus optimization: Opinion

One of the few integrating theories related to allocation is the hypothesis of optimization. While optimization theory has great heuristic appeal and has been used to describe a range of physiological and ecological phenomena, it has major limitations. Optimization is necessarily based on a definite time integral and an optimal control strategy must be specific to the same patterns exhibited by the driving variables over this same period of time. Optimization tends to employ the use of oversimplifications in order to facilitate analytical solutions to the optimal control strategy, i.e. the mechanism governing the response of plants, which is the critical issue of interest. It is difficult to define objective criteria that can account for the natural variability in plants and testing the quantitative predictions of optimality models is also difficult. Thus, we suggest that optimization theory is too limited for practical use in modelling whole plant allocation. In this paper, we introduce the use of coordination theory as a practical alternative. We develop a simple plant growth allocation model using both coordination and optimization approaches and show that coordination theory is easily applied, produces results that are quantitatively similar to optimization, and overcomes the inherent limitations of optimization theory.     

A comparative analysis of metacommunity types in the freshwater realm

Most metacommunity studies have taken a direct mechanistic approach, aiming to model the effects of local and regional processes on local communities within a metacommunity. An alternative approach is to focus on emergent patterns at the metacommunity level through applying the elements of metacommunity structure (EMS; Oikos, 97, 2002, 237) analysis. The EMS approach has very rarely been applied in the context of a comparative analysis of metacommunity types of main microbial, plant, and animal groups. Furthermore, to our knowledge, no study has associated metacommunity types with their potential ecological correlates in the freshwater realm. We assembled data for 45 freshwater metacommunities, incorporating biologically highly disparate organismal groups (i.e., bacteria, algae, macrophytes, invertebrates, and fish). We first examined ecological correlates (e.g., matrix properties, beta diversity, and average characteristics of a metacommunity, including body size, trophic group, ecosystem type, life form, and dispersal mode) of the three elements of metacommunity structure (i.e., coherence, turnover, and boundary clumping). Second, based on those three elements, we determined which metacommunity types prevailed in freshwater systems and which ecological correlates best discriminated among the observed metacommunity types. We found that the three elements of metacommunity structure were not strongly related to the ecological correlates, except that turnover was positively related to beta diversity. We observed six metacommunity types. The most common were Clementsian and quasi‐nested metacommunity types, whereas Random, quasi‐Clementsian, Gleasonian, and quasi‐Gleasonian types were less common. These six metacommunity types were best discriminated by beta diversity and the first axis of metacommunity ecological traits, ranging from metacommunities of producer organisms occurring in streams to those of large predatory organisms occurring in lakes. Our results showed that focusing on the emergent properties of multiple metacommunities provides information additional to that obtained in studies examining variation in local community structure within a metacommunity.     

Using Modelling to Disentangle the Relative Contributions of Zoonotic and Anthroponotic Transmission: The Case of Lassa Fever

Background

Zoonotic infections, which transmit from animals to humans, form the majority of new human pathogens. Following zoonotic transmission, the pathogen may already have, or may acquire, the ability to transmit from human to human. With infections such as Lassa fever (LF), an often fatal, rodent-borne, hemorrhagic fever common in areas of West Africa, rodent-to-rodent, rodent-to-human, human-to-human and even human-to-rodent transmission patterns are possible. Indeed, large hospital-related outbreaks have been reported. Estimating the proportion of transmission due to human-to-human routes and related patterns (e.g. existence of super-spreaders), in these scenarios is challenging, but essential for planned interventions.

Methodology/Principal Findings

Here, we make use of an innovative modeling approach to analyze data from published outbreaks and the number of LF hospitalized patients to Kenema Government Hospital in Sierra Leone to estimate the likely contribution of human-to-human transmission. The analyses show that almost of the cases at KGH are secondary cases arising from human-to-human transmission. However, we found much of this transmission is associated with a disproportionally large impact of a few individuals (‘super-spreaders’), as we found only of human cases result in an effective reproduction number (i.e. the average number of secondary cases per infectious case) , with a maximum value up to .

Conclusions/Significance

This work explains the discrepancy between the sizes of reported LF outbreaks and a clinical perception that human-to-human transmission is low. Future assessment of risks of LF and infection control guidelines should take into account the potentially large impact of super-spreaders in human-to-human transmission. Our work highlights several neglected topics in LF research, the occurrence and nature of super-spreading events and aspects of social behavior in transmission and detection.     

AFLP-PCR and RAPD-PCR evidences of the transmission of the pathogen Aphanomyces astaci (Oomycetes) to wild populations of European crayfish from the invasive crayfish species, Procambarus clarkii

Aphanomyces astaci (Oomycetes) is responsible for the crayfish plague disease. This species is endemic of North America and five genotypes have been described using RAPD-PCR. The red swamp crayfish, Procambarus clarkii, is one of the most widely spread North American species and invasive in the world. However, no outbreaks on its specific genotype, i.e., genotype D, have ever been described in nature. We investigated three major series of crayfish plague outbreaks in indigenous crayfish populations of Austropotamobius pallipes, located in the areas of influence of P. clarkii. All samples collected tested positive for A. astaci using a rnDNA ITS-PCR test. We also performed an AFLP-PCR analysis on 19 isolates, and found that all isolates belong to genotype D. These isolates exhibited similar properties, i.e., adaptation to warm temperatures. We demonstrate, for the first time, the transmission of A. astaci genotype D to indigenous European populations of crayfish, and confirm that the properties of adaptation to warm water temperatures seem to be a specific character of genotype D. The results of this work emphasize once more the need of controlling invasive species and its trade, since they can carry harmful pathogens with specific adaptations or increased virulence in new environments.