A network-patch methodology for adapting agent-based models for directly transmitted disease to mosquito-borne disease

Mosquito-borne diseases cause significant public health burden and are widely re-emerging or emerging. Understanding, predicting, and mitigating the spread of mosquito-borne disease in diverse populations and geographies are ongoing modelling challenges. We propose a hybrid network-patch model for the spread of mosquito-borne pathogens that accounts for individual movement through mosquito habitats, extending the capabilities of existing agent-based models (ABMs) to include vector-borne diseases. The ABM are coupled with differential equations representing ‘clouds’ of mosquitoes in patches accounting for mosquito ecology. We adapted an ABM for humans using this method and investigated the importance of heterogeneity in pathogen spread, motivating the utility of models of individual behaviour. We observed that the final epidemic size is greater in patch models with a high risk patch frequently visited than in a homogeneous model. Our hybrid model quantifies the importance of the heterogeneity in the spread of mosquito-borne pathogens, guiding mitigation strategies.     

Nonstationary influence of El Niño on the synchronous dengue epidemics in Thailand

BackgroundSeveral factors, including environmental and climatic factors, influence the transmission of vector-borne diseases. Nevertheless, the identification and relative importance of climatic factors for vector-borne diseases remain controversial. Dengue is the world''s most important viral vector-borne disease, and the controversy about climatic effects also applies in this case. Here we address the role of climate variability in shaping the interannual pattern of dengue epidemics.ConclusionThe underlying mechanism for the synchronisation of dengue epidemics may resemble that of a pacemaker, in which intrinsic disease dynamics interact with climate variations driven by El Niño to propagate travelling waves of infection. When association with El Niño is strong in the 2–3-y periodic mode, one observes high synchrony of dengue epidemics over Thailand. When this association is absent, the seasonal dynamics become dominant and the synchrony initiated in Bangkok collapses.     

Tree diseases and landscape processes: the challenge of landscape pathology

Forest pathology inherently involves a landscape perspective, because tree pathogens propagate according to heterogeneous spatial patterns of flow and isolation. Landscape pathology is a field that is now emerging from the transdisciplinary cooperation of forest pathologists with landscape ecologists. Here, we review recent broad-scale assessments of tree disease risk, investigations of site and host preferences for several root rot pathogens, and regional historical analyses of pathogen outbreak in plantations. Crucial topics include fragmentation effects on pathogen spread and geophysical features that predispose forest patches to disease expression. Recent methodological developments facilitate the spatially explicit analysis of reciprocal coarse-scale relationships among hosts and pathogens. Landscape pathology studies fill a significant research gap in the context of our understanding of sustainable forest management, the introduction of exotic organisms and how climate change might affect the spread of disease.     

Virulence evolution at the front line of spreading epidemics

Understanding and predicting the spatial spread of emerging pathogens is a major challenge for the public health management of infectious diseases. Theoretical epidemiology shows that the speed of an epidemic is governed by the life‐history characteristics of the pathogen and its ability to disperse. Rapid evolution of these traits during the invasion may thus affect the speed of epidemics. Here we study the influence of virulence evolution on the spatial spread of an epidemic. At the edge of the invasion front, we show that more virulent and transmissible genotypes are expected to win the competition with other pathogens. Behind the front line, however, more prudent exploitation strategies outcompete virulent pathogens. Crucially, even when the presence of the virulent mutant is limited to the edge of the front, the invasion speed can be dramatically altered by pathogen evolution. We support our analysis with individual‐based simulations and we discuss the additional effects of demographic stochasticity taking place at the front line on virulence evolution. We confirm that an increase of virulence can occur at the front, but only if the carrying capacity of the invading pathogen is large enough. These results are discussed in the light of recent empirical studies examining virulence evolution at the edge of spreading epidemics.     

How do pathogen evolution and host heterogeneity interact in disease emergence?

Heterogeneity in the parameters governing the spread of infectious diseases is a common feature of real-world epidemics. It has been suggested that for pathogens with basic reproductive number R(0)>1, increasing heterogeneity makes extinction of disease more likely during the early rounds of transmission. The basic reproductive number R(0) of the introduced pathogen may, however, be less than 1 after the introduction, and evolutionary changes are then required for R(0) to increase to above 1 and the pathogen to emerge. In this paper, we consider how host heterogeneity influences the emergence of both non-evolving pathogens and those that must undergo adaptive changes to spread in the host population. In contrast to previous results, we find that heterogeneity does not always make extinction more likely and that if adaptation is required for emergence, the effect of host heterogeneity is relatively small. We discuss the application of these ideas to vaccination strategies.     

A priori prediction of disease invasion dynamics in a novel environment

Directly transmitted infectious diseases spread through wildlife populations as travelling waves away from the sites of original introduction. These waves often become distorted through their interaction with environmental and population heterogeneities and by long-distance translocation of infected individuals. Accurate a priori predictions of travelling waves of infection depend upon understanding and quantifying these distorting factors. We assess the effects of anisotropies arising from the orientation of rivers in relation to the direction of disease-front propagation and the damming effect of mountains on disease movement in natural populations. The model successfully predicts the local and large-scale prevaccination spread of raccoon rabies through New York State, based on a previous spatially heterogeneous model of raccoon-rabies invasion across the state of Connecticut. Use of this model provides a rare example of a priori prediction of an epidemic invasion over a naturally heterogeneous landscape. Model predictions matched to data can also be used to evaluate the most likely points of disease introduction. These results have general implications for predicting future pathogen invasions and evaluating potential containment strategies.     

On the determinants of population structure in antigenically diverse pathogens

Many pathogens exhibit antigenic diversity and elicit strain-specific immune responses. This potential for cross-immunity structure in the host resource motivates the development of mathematical models, stressing competition for susceptible hosts in driving pathogen population dynamics and genetics. Here we establish that certain model formulations exhibit characteristics of prototype pattern-forming systems, with pathogen population structure emerging as three possible patterns: (i) incidence is steady and homogeneous; (ii) incidence is steady but heterogeneous; and (iii) incidence shows oscillatory dynamics, with travelling waves in strain-space. Results are robust to strain number, but sensitive to the mechanism of cumulative immunity.     

Host spatial heterogeneity and the spread of vector-borne infection.

We analyze how spatial heterogeneity in host density affects the advance of vector-borne disease. Infection requires vector infestation. The vector spreads only between hosts occupying the same neighborhood, and the number of hosts varies randomly among neighborhoods. Simulation of a spatially detailed model shows that increasing heterogeneity in host abundance reduces pathogen prevalence. Clumping of hosts can limit the advance of the vector, which inhibits the spread of infection indirectly. Clumping can also increase the chance that the pathogen and vector become physically separated during the initial phase of the epidemic process. The latter limitation on the pathogen's spread, in our simulations, is restricted to small interaction neighborhoods. A mean-field model, which does not maintain spatial correlations between sites, approximates simulation results when hosts are arrayed uniformly, but overestimates infection prevalence when hosts are aggregated. A pair approximation, which includes some of the simulation model's spatial correlations, better describes the vector infestation frequencies across host spatial dispersions.     

Landscape geometry and travelling waves in the larch budmoth

Travelling waves in cyclic populations refer to temporal shifts in peak densities moving across space in a wave‐like fashion. The epicentre hypothesis states that peak densities begin in specific geographic foci and then spread into adjoining areas. Travelling waves have been confirmed in a number of population systems, begging questions about their causes. Herein we apply a newly developed statistical technique, wavelet phase analysis, to historical data to document that the travelling waves in larch budmoth (LBM) outbreaks arise from two epicentres, both located in areas with high concentrations of favourable habitat. We propose that the spatial arrangement of the landscape mosaic is responsible for initiating the travelling waves. We use a tri‐trophic model of LBM dynamics to demonstrate that landscape heterogeneity (specifically gradients in density of favourable habitat) alone, is capable of inducing waves from epicentres. Our study provides unique evidence of how landscape features can mould travelling waves.     

Rates of spread of marine pathogens

Epidemics of marine pathogens can spread at extremely rapid rates. For example, herpes virus spread through pilchard populations in Australia at a rate in excess of 10 000 km year^?1, and morbillivirus infections in seals and dolphins have spread at more than 3000 km year^?1. In terrestrial environments, only the epidemics of myxomatosis and calicivirus in Australian rabbits and West Nile Virus in birds in North America have rates of spread in excess of 1000 km year^?1. The rapid rates of spread of these epidemics has been attributed to flying insect vectors, but flying vectors have not been proposed for any marine pathogen. The most likely explanation for the relatively rapid spread of marine pathogens is the lack of barriers to dispersal in some parts of the ocean, and the potential for long‐term survival of pathogens outside the host. These findings caution that pathogens may pose a particularly severe problem in the ocean. There is a need to develop epidemic models capable of generating these high rates of spread and obtain more estimates of disease spread rate.     

Ecosystem dynamics, biological diversity and emerging infectious diseases

In this article, we summarize the major scientific developments of the last decade on the transmission of infectious agents in multi-host systems. Almost sixty percent of the pathogens that have emerged in humans during the last 30-40 years are of animal origin and about sixty percent of them show an important variety of host species besides humans (3 or more possible host species). In this review, we focus on zoonotic infections with vector-borne transmission and dissect the contrasting effects that a multiplicity of host reservoirs and vectors can have on their disease dynamics. We discuss the effects exerted by host and vector species richness and composition on pathogen prevalence (i.e., reduction, including the dilution effect, or amplification). We emphasize that, in multiple host systems and for vector-borne zoonotic pathogens, host reservoir species and vector species can exert contrasting effect locally. The outcome on disease dynamics (reduced pathogen prevalence in vectors when the host reservoir species is rich and increased pathogen prevalence when the vector species richness increases) may be highly heterogeneous in both space and time. We then ask briefly how a shift towards a more systemic perspective in the study of emerging infectious diseases, which are driven by a multiplicity of hosts, may stimulate further research developments. Finally, we propose some research avenues that take better into account the multi-host species reality in the transmission of the most important emerging infectious diseases, and, particularly, suggest, as a possible orientation, the careful assessment of the life-history characteristics of hosts and vectors in a community ecology-based perspective.     

A diffusive SI model with Allee effect and application to FIV

A minimal reaction-diffusion model for the spatiotemporal spread of an infectious disease is considered. The model is motivated by the Feline Immunodeficiency Virus (FIV) which causes AIDS in cat populations. Because the infected period is long compared with the lifespan, the model incorporates the host population growth. Two different types are considered: logistic growth and growth with a strong Allee effect. In the model with logistic growth, the introduced disease propagates in form of a travelling infection wave with a constant asymptotic rate of spread. In the model with Allee effect the spatiotemporal dynamics are more complicated and the disease has considerable impact on the host population spread. Most importantly, there are waves of extinction, which arise when the disease is introduced in the wake of the invading host population. These waves of extinction destabilize locally stable endemic coexistence states. Moreover, spatially restricted epidemics are possible as well as travelling infection pulses that correspond either to fatal epidemics with succeeding host population extinction or to epidemics with recovery of the host population. Generally, the Allee effect induces minimum viable population sizes and critical spatial lengths of the initial distribution. The local stability analysis yields bistability and the phenomenon of transient epidemics within the regime of disease-induced extinction. Sustained oscillations do not exist.     

Unforeseen costs of cutting mosquito surveillance budgets

A budget proposal to stop the U.S. Centers for Disease Control and Prevention (CDC) funding in surveillance and research for mosquito-borne diseases such as dengue and West Nile virus has the potential to leave the country ill-prepared to handle new emerging diseases and manage existing ones. In order to demonstrate the consequences of such a measure, if implemented, we evaluated the impact of delayed control responses to dengue epidemics (a likely scenario emerging from the proposed CDC budget cut) in an economically developed urban environment. We used a mathematical model to generate hypothetical scenarios of delayed response to a dengue introduction (a consequence of halted mosquito surveillance) in the City of Cairns, Queensland, Australia. We then coupled the results of such a model with mosquito surveillance and case management costs to estimate the cumulative costs of each response scenario. Our study shows that halting mosquito surveillance can increase the management costs of epidemics by up to an order of magnitude in comparison to a strategy with sustained surveillance and early case detection. Our analysis shows that the total costs of preparedness through surveillance are far lower than the ones needed to respond to the introduction of vector-borne pathogens, even without consideration of the cost in human lives and well-being. More specifically, our findings provide a science-based justification for the re-assessment of the current proposal to slash the budget of the CDC vector-borne diseases program, and emphasize the need for improved and sustainable systems for vector-borne disease surveillance.     

Rodent-Borne <Emphasis Type="Italic">Bartonella</Emphasis> Infection Varies According to Host Species Within and Among Cities

It is becoming increasingly likely that rodents will drive future disease epidemics with the continued expansion of cities worldwide. Though transmission risk is a growing concern, relatively little is known about pathogens carried by urban rats. Here, we assess whether the diversity and prevalence of Bartonella bacteria differ according to the (co)occurrence of rat hosts across New Orleans, LA (NO), where both Norway (Rattus norvegicus) and roof rats (Rattus rattus) are found, relative to New York City (NYC) which only harbors Norway rats. We detected human pathogenic Bartonella species in both NYC and New Orleans rodents. We found that Norway rats in New Orleans harbored a more diverse assemblage of Bartonella than Norway rats in NYC and that Norway rats harbored a more diverse and distinct assemblage of Bartonella compared to roof rats in New Orleans. Additionally, Norway rats were more likely to be infected with Bartonella than roof rats in New Orleans. Flea infestation appears to be an important predictor of Bartonella infection in Norway rats across both cities. These findings illustrate that pathogen infections can be heterogeneous in urban rodents and indicate that further study of host species interactions could clarify variation in spillover risk across cities.     

The effects of human movement on the persistence of vector-borne diseases

With the recent resurgence of vector-borne diseases due to urbanization and development there is an urgent need to understand the dynamics of vector-borne diseases in rapidly changing urban environments. For example, many empirical studies have produced the disturbing finding that diseases continue to persist in modern city centers with zero or low rates of transmission. We develop spatial models of vector-borne disease dynamics on a network of patches to examine how the movement of humans in heterogeneous environments affects transmission. We show that the movement of humans between patches is sufficient to maintain disease persistence in patches with zero transmission. We construct two classes of models using different approaches: (i) Lagrangian models that mimic human commuting behavior and (ii) Eulerian models that mimic human migration. We determine the basic reproduction number R₀ for both modeling approaches. We show that for both approaches that if the disease-free equilibrium is stable (R₀<1) then it is globally stable and if the disease-free equilibrium is unstable (R₀>1) then there exists a unique positive (endemic) equilibrium that is globally stable among positive solutions. Finally, we prove in general that Lagrangian and Eulerian modeling approaches are not equivalent. The modeling approaches presented provide a framework to explore spatial vector-borne disease dynamics and control in heterogeneous environments. As an example, we consider two patches in which the disease dies out in both patches when there is no movement between them. Numerical simulations demonstrate that the disease becomes endemic in both patches when humans move between the two patches.     

Aerial Dispersal and Multiple-Scale Spread of Epidemic Disease

Disease spread has traditionally been described as a traveling wave of constant velocity. However, aerially dispersed pathogens capable of long-distance dispersal often have dispersal gradients with extended tails that could result in acceleration of the epidemic front. We evaluated empirical data with a simple model of disease spread that incorporates logistic growth in time with an inverse power function for dispersal. The scale invariance of the power law dispersal function implies its applicability at any spatial scale; indeed, the model successfully described epidemics ranging over six orders of magnitude, from experimental field plots to continental-scale epidemics of both plant and animal diseases. The distance traveled by epidemic fronts approximately doubled per unit time, velocity increased linearly with distance (slope ~½), and the exponent of the inverse power law was approximately 2. We found that it also may be possible to scale epidemics to account for initial outbreak focus size and the frequency of susceptible hosts. These relationships improve understanding of the geographic spread of emerging diseases, and facilitate the development of methods for predicting and preventing epidemics of plants, animals, and humans caused by pathogens that are capable of long-distance dispersal.     

Current knowledge of vector-borne zoonotic pathogens in Zambia: A clarion call to scaling-up “One Health” research in the wake of emerging and re-emerging infectious diseases

BackgroundAlthough vector-borne zoonotic diseases are a major public health threat globally, they are usually neglected, especially among resource-constrained countries, including those in sub-Saharan Africa. This scoping review examined the current knowledge and identified research gaps of vector-borne zoonotic pathogens in Zambia.Methods and findingsMajor scientific databases (Web of Science, PubMed, Scopus, Google Scholar, CABI, Scientific Information Database (SID)) were searched for articles describing vector-borne (mosquitoes, ticks, fleas and tsetse flies) zoonotic pathogens in Zambia. Several mosquito-borne arboviruses have been reported including Yellow fever, Ntaya, Mayaro, Dengue, Zika, West Nile, Chikungunya, Sindbis, and Rift Valley fever viruses. Flea-borne zoonotic pathogens reported include Yersinia pestis and Rickettsia felis. Trypanosoma sp. was the only tsetse fly-borne pathogen identified. Further, tick-borne zoonotic pathogens reported included Crimean-Congo Haemorrhagic fever virus, Rickettsia sp., Anaplasma sp., Ehrlichia sp., Borrelia sp., and Coxiella burnetii.ConclusionsThis study revealed the presence of many vector-borne zoonotic pathogens circulating in vectors and animals in Zambia. Though reports of human clinical cases were limited, several serological studies provided considerable evidence of zoonotic transmission of vector-borne pathogens in humans. However, the disease burden in humans attributable to vector-borne zoonotic infections could not be ascertained from the available reports and this precludes the formulation of national policies that could help in the control and mitigation of the impact of these diseases in Zambia. Therefore, there is an urgent need to scale-up “One Health” research in emerging and re-emerging infectious diseases to enable the country to prepare for future epidemics, including pandemics.     

Changing spatial epidemiology of pertussis in continental USA

Prediction and control of the geographical spread of emerging pathogens has become a central public health issue. Because these infectious diseases are by definition novel, there are few data to characterize their dynamics. One possible solution to this problem is to apply lessons learnt from analyses of historical data on familiar and epidemiologically similar pathogens. However, the portability of the spatial ecology of an infectious disease in a different epoch to other infections remains unexamined. Here, we study this issue by taking advantage of the recent re-emergence of pertussis in the United States to compare its spatial transmission dynamics throughout the 1950s with the past decade. We report 4-year waves, sweeping across the continent in the 1950s. These waves are shown to emanate from highly synchronous foci in the northwest and northeast coasts. In contrast, the recent resurgence of the disease is characterized by 5.5-year epidemics with no particular spatial structure. We interpret this to be the result of dramatic changes in patterns of human movement over the second half of the last century, together with changing age distribution of pertussis. We conclude that extrapolation regarding the spatial spread of contemporaneous pathogens based on analyses of historical incidence may be potentially very misleading.     

Host ecotype generates evolutionary and epidemiological divergence across a pathogen metapopulation

The extent and speed at which pathogens adapt to host resistance varies considerably. This presents a challenge for predicting when—and where—pathogen evolution may occur. While gene flow and spatially heterogeneous environments are recognized to be critical for the evolutionary potential of pathogen populations, we lack an understanding of how the two jointly shape coevolutionary trajectories between hosts and pathogens. The rust pathogen Melampsora lini infects two ecotypes of its host plant Linum marginale that occur in close proximity yet in distinct populations and habitats. In this study, we found that within-population epidemics were different between the two habitats. We then tested for pathogen local adaptation at host population and ecotype level in a reciprocal inoculation study. Even after controlling for the effect of spatial structure on infection outcome, we found strong evidence of pathogen adaptation at the host ecotype level. Moreover, sequence analysis of two pathogen infectivity loci revealed strong genetic differentiation by host ecotype but not by distance. Hence, environmental variation can be a key determinant of pathogen population genetic structure and coevolutionary dynamics and can generate strong asymmetry in infection risks through space.     

Covariation between the physiological and behavioral components of pathogen transmission: host heterogeneity determines epidemic outcomes

Although heterogeneity in contact rate, physiology, and behavioral response to infection have all been empirically demonstrated in host–pathogen systems, little is known about how interactions between individual variation in behavior and physiology scale‐up to affect pathogen transmission at a population level. The objective of this study is to evaluate how covariation between the behavioral and physiological components of transmission might affect epidemic outcomes in host populations. We tested the consequences of contact rate covarying with susceptibility, infectiousness, and infection status using an individual‐based, dynamic network model where individuals initiate and terminate contacts with conspecifics based on their behavioral predispositions and their infection status. Our results suggest that both heterogeneity in physiology and subsequent covariation of physiology with contact rate could powerfully influence epidemic dynamics. Overall, we found that 1) individual variability in susceptibility and infectiousness can reduce the expected maximum prevalence and increase epidemic variability; 2) when contact rate and susceptibility or infectiousness negatively covary, it takes substantially longer for epidemics to spread throughout the population, and rates of epidemic spread remained suppressed even for highly transmissible pathogens; and 3) reductions in contact rate resulting from infection‐induced behavioral changes can prevent the pathogen from reaching most of the population. These effects were strongest for theoretical pathogens with lower transmissibility and for populations where the observed variation in contact rate was higher, suggesting that such heterogeneity may be most important for less infectious, more chronic diseases in wildlife. Understanding when and how variability in pathogen transmission should be modelled is a crucial next step for disease ecology.