Vector Life History Research Articles

Integrating Community Ecology into Models of Vector-Borne Virus Transmission.

Vector-borne plant viruses are a diverse and dynamic threat to agriculture with hundreds of economically damaging viruses and insect vector species. Mathematical models have greatly increased our understanding of how alterations of vector life history and host-vector-pathogen interactions can affect virus transmission. However, insect vectors also interact with species such as predators and competitors in food webs, and these interactions affect vector population size and behaviors in ways that mediate virus transmission. Studies assessing how species' interactions affect vector-borne pathogen transmission are limited in both number and scale, hampering the development of models that appropriately capture community-level effects on virus prevalence. Here, we review vector traits and community factors that affect virus transmission, explore the existing models of vector-borne virus transmission and areas where the principles of community ecology could improve the models and management, and finally evaluate virus transmission in agricultural systems. We conclude that models have expanded our understanding of disease dynamics through simulations of transmission but are limited in their ability to reflect the complexity of ecological interactions in real systems. We also document a need for experiments in agroecosystems, where the high availability of historical and remote-sensing data could serve to validate and improve vector-borne virus transmission models.

Quantifying and Modeling the Acquisition and Retention of Lumpy Skin Disease Virus by Hematophagus Insects Reveals Clinically but Not Subclinically Affected Cattle Are Promoters of Viral Transmission and Key Targets for Control of Disease Outbreaks.

Lumpy skin disease virus (LSDV) is a vector-transmitted poxvirus that causes disease in cattle. Vector species involved in LSDV transmission and their ability to acquire and transmit the virus are poorly characterized. Using a highly representative bovine experimental model of lumpy skin disease, we fed four model vector species (Aedes aegypti, Culex quinquefasciatus, Stomoxys calcitrans, and Culicoides nubeculosus) on LSDV-inoculated cattle in order to examine their acquisition and retention of LSDV. Subclinical disease was a more common outcome than clinical disease in the inoculated cattle. Importantly, the probability of vectors acquiring LSDV from a subclinical animal (0.006) was very low compared with that from a clinical animal (0.23), meaning an insect feeding on a subclinical animal was 97% less likely to acquire LSDV than one feeding on a clinical animal. All four potential vector species studied acquired LSDV from the host at a similar rate, but Aedes aegypti and Stomoxys calcitrans retained the virus for a longer time, up to 8 days. There was no evidence of virus replication in the vector, consistent with mechanical rather than biological transmission. The parameters obtained in this study were combined with data from studies of LSDV transmission and vector life history parameters to determine the basic reproduction number of LSDV in cattle mediated by each of the model species. This reproduction number was highest for Stomoxys calcitrans (19.1), followed by C. nubeculosus (7.1) and Ae. aegypti (2.4), indicating that these three species are potentially efficient transmitters of LSDV; this information can be used to inform LSD control programs.IMPORTANCE Lumpy skin disease virus (LSDV) causes a severe systemic disease characterized by cutaneous nodules in cattle. LSDV is a rapidly emerging pathogen, having spread since 2012 into Europe and Russia and across Asia. The vector-borne nature of LSDV transmission is believed to have promoted this rapid geographic spread of the virus; however, a lack of quantitative evidence about LSDV transmission has hampered effective control of the disease during the current epidemic. Our research shows subclinical cattle play little part in virus transmission relative to clinical cattle and reveals a low probability of virus acquisition by insects at the preclinical stage. We have also calculated the reproductive number of different insect species, therefore identifying efficient transmitters of LSDV. This information is of utmost importance, as it will help to define epidemiological control measures during LSDV epidemics and of particular consequence in resource-poor regions where LSD vaccination may be less than adequate.

Using the basic reproduction number to assess the risk of transmission of lumpy skin disease virus by biting insects.

In recent years, lumpy skin disease virus (LSDV) has emerged as a major threat to cattle outside Africa, where it is endemic. Although evidence suggests that LSDV is transmitted by the bites of blood sucking arthropods, few studies have assessed the risk of transmission posed by particular vector species. Here this risk is assessed by calculating the basic reproduction number (R 0) for transmission of LSDV by five species of biting insect: the stable fly, Stomoxys calcitrans, the biting midge, Culicoides nubeculosus, and three mosquito species, Aedes aegypti, Anopheles stephensi, and Culex quinquefasciatus. Parameters relating to mechanical transmission of LSDV were estimated using new analyses of previously published data from transmission experiments, while vector life history parameters were derived from the published literature. Uncertainty and sensitivity analyses were used to compute R 0 for each species and to identify those parameters which influence its magnitude. Results suggest that S. calcitrans is likely to be the most efficient at transmitting LSDV, with Ae. aegypti also an efficient vector. By contrast, C. nubeculosus, An. stephensi, and Cx. quinquefasciatus are likely to be inefficient vectors of LSDV. However, there is considerable uncertainty associated with the estimates of R 0, reflecting uncertainty in most of the constituent parameters. Sensitivity analysis suggests that future experimental work should focus on estimating the probability of transmission from insect to bovine and on the virus inactivation rate in insects.

Modeling Approach Influences Dynamics of a Vector-Borne Pathogen System.

The choice of a modeling approach is a critical decision in the modeling process, as it determines the complexity of the model and the phenomena that the model captures. In this paper, we developed an individual-based model (IBM) and compared it to a previously published ordinary differential equation (ODE) model, both developed to describe the same biological system although with slightly different emphases given the underlying assumptions and processes of each modeling approach. We used both models to examine the effect of insect vector life history and behavior traits on the spread of a vector-borne plant virus, and determine how choice of approach affects the results and their biological interpretation. A non-random distribution of insect vectors across plant hosts emerged in the IBM version of the model and was not captured by the ODE. This distribution led simultaneously to a slower-growing vector population and a faster spread of the pathogen among hosts. The IBM model also enabled us to test the effect of potential control measures to slow down virus transmission. We found that removing virus-infected hosts was a more effective strategy for controlling infection than removing vector-infested hosts. Our findings highlight the need to carefully consider possible modeling approaches before constructing a model.

Mesocosm experiments reveal the impact of mosquito control measures on malaria vector life history and population dynamics

The impact of control measures on mosquito vector fitness and demography is usually estimated from bioassays or indirect variables in the field. Whilst indicative, neither approach is sufficient to quantify the potentially complex response of mosquito populations to combined interventions. Here, large replicated mesocosms were used to measure the population-level response of the malaria vector Anopheles arabiensis to long-lasting insecticidal nets (LLINs) when used in isolation, or combined with insecticidal eave louvers (EL), or treatment of cattle with the endectocide Ivermectin (IM). State-space models (SSM) were fit to these experimental data, revealing that LLIN introduction reduced adult mosquito survival by 91% but allowed population persistence. ELs provided no additional benefit, but IM reduced mosquito fecundity by 59% and nearly eliminated all populations when combined with LLINs. This highlights the value of IM for integrated vector control, and mesocosm population experiments combined with SSM for identifying optimal combinations for vector population elimination.

Identifying climate drivers of infectious disease dynamics: recent advances and challenges ahead.

Climate change is likely to profoundly modulate the burden of infectious diseases. However, attributing health impacts to a changing climate requires being able to associate changes in infectious disease incidence with the potentially complex influences of climate. This aim is further complicated by nonlinear feedbacks inherent in the dynamics of many infections, driven by the processes of immunity and transmission. Here, we detail the mechanisms by which climate drivers can shape infectious disease incidence, from direct effects on vector life history to indirect effects on human susceptibility, and detail the scope of variation available with which to probe these mechanisms. We review approaches used to evaluate and quantify associations between climate and infectious disease incidence, discuss the array of data available to tackle this question, and detail remaining challenges in understanding the implications of climate change for infectious disease incidence. We point to areas where synthesis between approaches used in climate science and infectious disease biology provide potential for progress.

Impact of life stage-dependent dispersal on the colonization dynamics of host patches by ticks and tick-borne infectious agents

BackgroundWhen colonization and gene flow depend on host-mediated dispersal, a key factor affecting vector dispersal potential is the time spent on the host for the blood meal, a characteristic that can vary strongly among life history stages. Using a 2-patch vector-pathogen population model and seabird ticks as biological examples, we explore how vector colonization rates and the spread of infectious agents may be shaped by life stage-dependent dispersal. We contrast hard (Ixodidae) and soft (Argasidae) tick systems, which differ strongly in blood- feeding traits.ResultsWe find that vector life history characteristics (i.e. length of blood meal) and demographic constraints (Allee effects) condition the colonization potential of ticks; hard ticks, which take a single, long blood meal per life stage, should have much higher colonization rates than soft ticks, which take repeated short meals. Moreover, this dispersal potential has direct consequences for the spread of vector-borne infectious agents, in particular when transmission is transovarial.ConclusionsThese results have clear implications for predicting the dynamics of vector and disease spread in the context of large-scale environmental change. The findings highlight the need to include life-stage dispersal in models that aim to predict species and disease distributions, and provide testable predictions related to the population genetic structure of vectors and pathogens along expansion fronts.

Vector population growth and condition-dependent movement drive the spread of plant pathogens.

Plant viruses, often spread by arthropod vectors, impact natural and agricultural ecosystems worldwide. Intuitively, the movement behavior and life history of vectors influence pathogen spread, but the relative contribution of each factor has not been examined. Recent research has highlighted the influence of host infection status on vector behavior and life history. Here, we developed a model to explore how vector traits influence the spread of vector-borne plant viruses. We allowed vector life history (growth rate, carrying capacity) and movement behavior (departure and settlement rates) parameters to be conditional on whether the plant host is infected or healthy and whether the vector is viruliferous (carrying the virus) or not. We ran simulations under a wide range of parameter combinations and quantified the fraction of hosts infected over time. We also ran case studies of the model for Barley yellow dwarf virus, a persistently transmitted virus, and for Potato virus Y, a non-persistently transmitted virus. We quantified the relative importance of each parameter on pathogen spread using Latin hypercube sampling with the statistical partial rank correlation coefficient technique. We found two general types of mechanisms in our model that increased the rate of pathogen spread. First, increasing factors such as vector intrinsic growth rate, carrying capacity, and departure rate from hosts (independent of whether these factors were condition-dependent) led to more vectors moving between hosts, which increased pathogen spread. Second, changing condition-dependent factors such as a vector's preference for settling on a host with a different infection status than itself, and vector tendency to leave a host of the same infection status, led to increased contact between hosts and vectors with different infection statuses, which also increased pathogen spread. Overall, our findings suggest that vector population growth rates had the greatest influence on rates of virus spread, but rates of vector dispersal from infected hosts and from hosts of the same infection status were also very important. Our model highlights the importance of simultaneously considering vector life history and behavior to better understand pathogen spread. Although developed for plant viruses, our model could readily be utilized with other vector-borne pathogen systems.

The Interaction between Vector Life History and Short Vector Life in Vector-Borne Disease Transmission and Control.

Epidemiological modelling has a vital role to play in policy planning and prediction for the control of vectors, and hence the subsequent control of vector-borne diseases. To decide between competing policies requires models that can generate accurate predictions, which in turn requires accurate knowledge of vector natural histories. Here we highlight the importance of the distribution of times between life-history events, using short-lived midge species as an example. In particular we focus on the distribution of the extrinsic incubation period (EIP) which determines the time between infection and becoming infectious, and the distribution of the length of the gonotrophic cycle which determines the time between successful bites. We show how different assumptions for these periods can radically change the basic reproductive ratio (R0) of an infection and additionally the impact of vector control on the infection. These findings highlight the need for detailed entomological data, based on laboratory experiments and field data, to correctly construct the next-generation of policy-informing models.

The Microbiome of Ehrlichia-Infected and Uninfected Lone Star Ticks (Amblyomma americanum)

The Lone Star tick, Amblyomma americanum, transmits several bacterial pathogens including species of Anaplasma and Ehrlichia. Amblyomma americanum also hosts a number of non-pathogenic bacterial endosymbionts. Recent studies of other arthropod and insect vectors have documented that commensal microflora can influence transmission of vector-borne pathogens; however, little is known about tick microbiomes and their possible influence on tick-borne diseases. Our objective was to compare bacterial communities associated with A. americanum, comparing Anaplasma/Ehrlichia -infected and uninfected ticks. Field-collected questing specimens (n = 50) were used in the analyses, of which 17 were identified as Anaplasma/Ehrlichia infected based on PCR amplification and sequencing of groEL genes. Bacterial communities from each specimen were characterized using Illumina sequencing of 16S rRNA gene amplicon libraries. There was a broad range in diversity between samples, with inverse Simpson’s Diversity indices ranging from 1.28–89.5. There were no statistical differences in the overall microbial community structure between PCR diagnosed Anaplasma/Ehrlichia-positive and negative ticks, but there were differences based on collection method (P < 0.05), collection site (P < 0.05), and sex (P < 0.1) suggesting that environmental factors may structure A. americanum microbiomes. Interestingly, there was not always agreement between Illumina sequencing and PCR diagnostics: Ehrlichia was identified in 16S rRNA gene libraries from three PCR-negative specimens; conversely, Ehrlichia was not found in libraries of six PCR-positive ticks. Illumina sequencing also helped identify co-infections, for example, one specimen had both Ehrlichia and Anaplasma. Other taxa of interest in these specimens included Coxiella, Borrelia, and Rickettsia. Identification of bacterial community differences between specimens of a single tick species from a single geographical site indicates that intra-species differences in microbiomes were not due solely to pathogen presence/absence, but may be also driven by vector life history factors, including environment, life stage, population structure, and host choice.

Chikungunya virus-vector interactions.

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that causes chikungunya fever, a severe, debilitating disease that often produces chronic arthralgia. Since 2004, CHIKV has emerged in Africa, Indian Ocean islands, Asia, Europe, and the Americas, causing millions of human infections. Central to understanding CHIKV emergence is knowledge of the natural ecology of transmission and vector infection dynamics. This review presents current understanding of CHIKV infection dynamics in mosquito vectors and its relationship to human disease emergence. The following topics are reviewed: CHIKV infection and vector life history traits including transmission cycles, genetic origins, distribution, emergence and spread, dispersal, vector competence, vector immunity and microbial interactions, and co-infection by CHIKV and other arboviruses. The genetics of vector susceptibility and host range changes, population heterogeneity and selection for the fittest viral genomes, dual host cycling and its impact on CHIKV adaptation, viral bottlenecks and intrahost diversity, and adaptive constraints on CHIKV evolution are also discussed. The potential for CHIKV re-emergence and expansion into new areas and prospects for prevention via vector control are also briefly reviewed.

Vector movement underlies avian malaria at upper elevation in Hawaii: implications for transmission of human malaria

With climate warming, malaria in humans and birds at upper elevations is an emerging infectious disease because development of the parasite in the mosquito vector and vector life history are both temperature dependent. An enhanced-mosquito-movement model from climate warming predicts increased transmission of malaria at upper elevation sites that are too cool for parasite development in the mosquito vector. We evaluate this model with avian malaria (Plasmodium relictum) at 1,900-m elevation on the Island of Hawaii, with air temperatures too low for sporogony in the vector (Culex quinquefasciatus). On a well-defined site over a 14-year period, 10 of 14 species of native and introduced birds became infected, several epizootics occurred, and the increase in prevalence was driven more by resident species than by mobile species that could have acquired their infections at lower elevations. Greater movement of infectious mosquitoes from lower elevations now permits avian malaria to spread at 1,900 m in Hawaii, in advance of climate warming at that elevation. The increase in malaria at upper elevations due to dispersal of infectious mosquitoes is a real alternative to temperature for the increased incidence of human malaria in tropical highlands.