No description available.

Arthropod-borne viruses, arboviruses, have the ability to replicate in both vertebrates and invertebrates and are transmitted to susceptible vertebrate hosts by vectors such as mosquitoes and ticks. Ticks are important vectors of many highly pathogenic arboviruses, including the flavivirus tick-borne encephalitis virus (TBEV) and the nairovirus Crimean-Congo haemorrhagic fever virus. In contrast, alphaviruses are principally mosquito-borne and have been isolated only rarely from ticks; ticks have not been implicated as their vectors. Nevertheless, the alphavirus Semliki Forest virus (SFV) replicates in cell lines derived from many different tick species, including those of the genus Ixodes, which includes vectors of TBEV and its lesspathogenic relative Langat virus (LGTV). In vertebrate cells, arboviruses generally cause cytopathic effects; however, arbovirus infection of arthropod cells usually results in a persistent low-level infection without cell death. While little is known about antiviral immunity in tick cells, the immune system of other arbovirus vectors such as mosquitoes has been studied extensively over the last decade. In insects, pathways such as RNA interference (RNAi), JAK/STAT, Toll, Imd and melanisation have been implicated in controlling arbovirus infection, with RNAi being considered the most important antiviral mechanism. In tick cells, RNAi has been shown to have an antiviral effect, but current knowledge of other immunity pathways is limited and none have been implicated in the antiviral response. In the present study, SFV and LGTV replication in selected Ixodes spp. tick cell lines was characterised and the Ixodes scapularis-derived cell line IDE8 was identified as a suitable cell line for this project. Potential antiviral innate immunity pathways were investigated; putative components of the tick JAK/STAT, Toll and Imd pathways were identified by BLAST search using available sequences from well-studied arthropods including the fruit fly Drosophila melanogaster. Using gene silencing, an attempt was made to determine whether these pathways play a role in controlling SFV and LGTV infection in tick cell lines. Selected genes were silenced in IDE8 cells using long target-specific dsRNA and cells were subsequently infected with either SFV or LGTV. Effects of gene silencing on virus replication were assessed by quantitative real time PCR (qPCR) or luciferase reporter assay. Effects on infectious virus production were measured by plaque assay. Replication of the orbivirus St Croix River virus (SCRV), which chronically infects IDE8 cells, was also quantified by qPCR after silencing of selected genes. Interestingly, SFV or LGTV infection of IDE8 cells resulted in a significant increase in SCRV replication, possibly as a result of interference with antiviral pathways by SFV and LGTV or possibly due to diversion of cellular responses from sole control of SCRV. No evidence for an antiviral role for the JAK/STAT or Toll pathways was found in IDE8 cells. However, an antiviral effect was observed for protein orthologues putatively involved in the RNAi response. Argonaute proteins play an important role in translation inhibition and target degradation mediated by RNAi, and silencing of selected Argonaute proteins resulted in a significant increase in SFV and SCRV replication. The carboxypeptidase CG4572 is essential for an efficient antiviral response in D. melanogaster, and supposedly involved in the systemic RNAi response. A putative tick orthologue of CG4572 was identified and this appeared to be involved in the antiviral response in IDE8 tick cells. When expression of CG4572 was silenced and cells subsequently infected with SFV or LGTV, replication of both viruses was significantly increased. In addition, it was shown that three mosquito orthologues of CG4572 also had an antiviral role against SFV in Aedes mosquito cells. In conclusion, of the tick cell lines investigated, IDE8 provided a suitable model system for investigating tick cell responses against arboviruses and new insight into the nature of the tick cell antiviral response was gained.

No description available.

Every year three million deaths are attributed to malaria, of which one-third are of children. Malaria is a vector-borne disease, where a mosquito acts as the vector that transmits the disease. In the last few years, computer simulation based models have been used effectively to study the vector population dynamics and control strategies of vector-borne diseases. Typically, these models use ordinary differential equations to simulate the spread of malaria. Although these models provide a powerful mechanism to study the spread of malaria, they have several shortcomings. The research in this thesis focuses on creating a simulation model based on the framework of cellular automata, which addresses many shortcomings of previous models. Cellular automata are dynamical systems, which are discrete in time and space. The implementation of the model proposed can easily be integrated with EpiSims/TRANSIMS. EpiSims is an epidemiological modeling tool for studying the spread of infectious diseases; it uses social contact network from TRANSIMS (A Transport Analysis and Simulation System). Simulation results from the prototype implementation showed qualitatively correct results for vector densities, diffusion and epidemiological curves. / Master of Science

International malaria control initiatives such as the Roll Back Malaria Initiative (RBM) and the Medicines for Malaria Venture (MMV) mobilize resources and spur research aimed at vector control as well as the treatment and eventual eradication of the disease. These efforts have managed to reduce incidence of malaria by an estimated 37% worldwide since 2000. However, despite the promising success of control efforts such as these, the World Health Organization reports a staggering 438,000 deaths from malaria in 2015. The continuing high death toll of malaria as well as emerging insecticide and antimalarial drug resistance suggests that while encouraging, success in reducing malaria incidence may be tenuous. Current vector control strategies are often complicated by ecological and behavioral heterogeneity of vector mosquito populations. As an additional obstruction, mosquito genomes are highly plastic as evidenced by the wealth or chromosomal inversions that have occurred in this genus. Chromosomal inversions have been correlated with differences in adaptation to aridity, insecticide resistance, and differences in resting behavior. However, a good understanding of the molecular mechanisms for inversion generation is still lacking. One possible contributor to inversion formation in Anopheles mosquitoes includes repetitive DNA such as transposable elements (TEs), tandem repeats (TRs) and inverted repeats (IRs). This dissertation provides physical maps for two important malaria vectors, An. stephensi and An. albimanus (Ch.2 and Ch. 3) and then applies those maps to the identification of inversion breakpoints in malaria mosquitoes. Repeat content of each chromosomal arm and the molecular characterization of lineage specific breakpoints is also investigated (Ch. 2 and Ch.4). Our study reveals differences in patterns of chromosomal evolution of Anopheles mosquitoes vs. Drosophila. First, mosquito chromosomes tend to shuffle as intact elements via whole arm translocations and do not under fissions or fusions as seen in fruitflies. Second, the mosquito sex chromosome is changing at a much higher rate relative to the autosomes in malaria mosquitoes than in fruit flies. Third, our molecular characterization of inversion breakpoints indicates that TEs and TRs may participate in inversion genesis in an arm specific manner. / Ph. D. / Malaria is a complex and devastating disease vectored by the bite of a female Anopheles mosquito. This disease claimed an estimated 438,000 lives in 2015. The mobilization of funding and resources as part of global malaria eradication initiatives have reduced the global incidence of malaria by 37% in the last 15 years. Deaths from malaria are also 60% lower vs. the year 2000. These promising gains are threatened by the ability of Anopheles mosquitoes to adapt in the face of malaria control efforts. Anopheles mosquito chromosomes are known to be highly plastic, as evidenced by numerous chromosomal inversions. Recent years have seen increases in insecticide resistance, and behavioral change in mosquito populations that allow them to avoid insecticides and remain prolific vectors of disease. This ability of mosquito vectors to adapt threatens to unravel recent progress towards a malaria free world. The projects presented in this dissertation explore mechanisms of chromosomal evolution, specifically the potential role of repetitive DNA in the generation of chromosomal inversions. The exploration of chromosomal inversions was facilitated by the creation of physical maps for Anopheles species. Prominent malaria vectors An. stephensi andAn. albimanus were physically mapped in Chapter 2 and Chapter 3 respectively. In chapter 1 and chapter 3 physical maps are utilized for the identification of chromosomal inversion breakpoints using 2 species (Ch. 2) and many species (Ch. 4). Repeat content was quantified along each chromosomal arm (Ch 2,4) and in inversion breakpoint regions (Ch 3). This dissertation presents physical maps for two important malaria species that have been applied to the study of chromosomal evolution and will also serve as community tools for further study of malaria mosquitoes. Our work on chromosomal evolution has revealed the Anopheles chromosomes tend to undergo translocations as intact elements and do not under fissions and fusions as seen in fruitflies. We also find that the malaria mosquito sex chromosome changes much more rapidly relative to the autosomes than in fruitflies. Additionally, repetitive DNA including transposable elements (TEs) and tandem repeats (TRs) may be encouraging chromosomal inversions but with differing roles on different chromosomal arms.

Mathematical modeling is a powerful tool to study and analyze the disease dynamics prevalent in the community. This thesis studies the dynamics of two time since infection structured vector borne models with direct transmission. We have included disease induced death rate in the first model to form the second model. The aim of this thesis is to analyze whether these two models have same or different disease dynamics. An explicit expression for the reproduction number denoted by R0 is derived. Dynamical analysis reveals the forward bifurcation in the first model. That is when the threshold value R0 < 1, disease free-equilibrium is stable locally implying that if there is small perturbation of the system, then after some time, the system will return to the disease free equilibrium. When R0 > 1 the unique endemic equilibrium is locally asymptotically stable. For the second model, analysis of the existence and stability of equilibria reveals the existence of backward bifurcation i.e. where the disease free equilibrium coexists with the endemic equilibrium when the reproduction number R02 is less than unity. This aspect shows that in order to control vector borne disease, it is not sufficient to have reproduction number less than unity although necessary. Thus, the infection can persist in the population even if the reproduction number is less than unity. Numerical simulation is presented to see the bifurcation behaviour in the model. By taking the reproduction number as the bifurcation parameter, we find the system undergoes backward bifurcation at R02 = 1. Thus, the model has backward bifurcation and have two positive endemic equilibrium when R02 < 1 and unique positive endemic equilibrium whenever R02 > 1. Stability analysis shows that disease free equilibrium is locally asymptotically stable when R02 < 1 and unstable when R02 > 1. When R02 < 1, lower endemic equilibrium in backward bifurcation is locally unstable. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2020. / FAU Electronic Theses and Dissertations Collection

Vector-borne diseases (VBDs) cause significant harm to humans, plants, and animals worldwide. For instance, VBDs are very difficult to manage, as they are governed by complex interactions. VBD transmission depends on the pathogen itself, vector-host movement, and environmental conditions. Mosquito-borne diseases are a perfect example of how all these factors contribute to changes in VBD dynamics. Although vectors are highly sensitive to climate, modeling studies tend to ignore climate effects. Here, I am interested in the arthropod small vectors that are sensitive to climate factors such as temperature, precipitation, and drought. In particular, I am looking at the effect of temperature on vector traits for two VBDs, namely, dengue, caused by a virus that infects humans and bluetongue disease, caused by a virus that infects ruminants. First, I collect data on mosquito traits' response to temperature changes, this includes adult traits as well as juvenile traits. Next, I use these traits to model mosquito density, and then I incorporate the density into our mathematical models to investigate the effect it has on the basic reproductive ratio R0, a measure of how contagious the disease is. I use R0 to determine disease risk. For dengue, my results show that using mosquito life stage traits response to temperature improves our vector density approximation and disease risk estimates. For bluetongue, I use midge traits response to temperature to show that the suitable temperature for bluetongue risk is between 21.5 °C and 30.7 °C. These results can inform future control and prevention strategies. / Doctor of Philosophy / Infectious diseases are a type of illness that occurs when microorganisms spread between hosts. Some infectious diseases are directly transmitted and some require indirect transmission such as vector-borne diseases (VBDs). Each VBD requires the presence of a vector for the disease to be transmitted. For example, dengue that puts 40% of the world population at risk, requires mosquitoes to transmit the disease between humans. My research aims to investigate how the main climate factor, temperature, influences the spread of VBDs. I develop mathematical and statistical models that explain the effect of temperature on vector traits of a mosquito-borne disease (dengue) and a midge-borne disease (bluetongue) and investigate modeling formulas to improve our estimates for dengue mosquito densities. My results can be used to inform future prevention and control strategies.

Eastern Equine Encephalitis virus is a vector-borne virus amplified by the Culiseta melanura mosquito in an enzootic avian cycle, causing high morbidity and mortality to horses and humans when contracted as incidental hosts. The virus is distributed across most of the eastern United States, Canada, and Gulf coast, and has been expanding in geographic range and season of activity over time. Spatial-temporal trends in Cs. melanura abundance were correlated with available meteorological (temperature and precipitation) and remotely sensed environmental data for the period of 1997-2012 in Connecticut. The effects of inter-annual changes in precipitation, temperature, and groundwater levels on Cs. melanura abundances using time-series linear regression and cross-correlation analyses were inconclusive. Habitat modeling using logistic regression and landscape-based predictive variables demonstrated strong efficiency (46.2%) and acceptable sensitivity and specificity (65.6 and 78.6%, respectively) using NDVI difference and distance from palustrine areas as predictive factors. Remotely sensed data can improve the understanding of vector abundance patterns, helping to forecast future outbreaks and regional expansions by guiding surveillance efforts.

We develop and evaluate a novel host-vector model of West Nile virus (WNV) transmission that incorporates multiple avian host species and host stage-structure (juvenile and adult stages), with both species-specific and stage-specific biting rates of vectors on hosts. We use this model to explore WNV transmission dynamics that occur between vectors and multiple structured host populations as a result of heterogeneous biting rates. Our analysis shows that increased exposure of juvenile hosts results in earlier, more intense WNV transmission when compared to the effects of differential host species exposure, regardless of other parameter values. We also find that, in addition to competence, increased juvenile exposure is an important mechanism for determining the effect of species diversity on the disease risk of a community.

Doctor of Philosophy / Department of Electrical and Computer Engineering / Caterina Scoglio / Vector-borne diseases not only cause devastating economic losses, they also significantly impact human health in terms of morbidity and mortality. From an economical and humane point of view, mitigation and control of vector-borne diseases are essential. Studying dynamics of vector-borne disease transmission is a challenging task because vector-borne diseases show complex dynamics impacted by a wide range of ecological factors. Understanding these factors is important for the development of mitigation and control strategies. Mathematical models have been commonly used to translate assumptions concerning biological (medical, demographical, behavioral, immunological) aspects into mathematics, linking biological processes of transmission and dynamics of infection at population level. Mathematical analysis translates results back into biology. Classical deterministic epidemic models do not consider spatial variation, assuming space is homogeneous. Spatial spread of vector-borne diseases observed many times highlights the necessity of incorporating spatial dynamics into mathematical models. Heterogeneous demography, geography, and ecology in various regions may result in different epidemiological characteristics. Network approach is commonly used to study spatial evolution of communicable diseases transmitted among connected populations. In this dissertation, the spread of vector-borne diseases in time and space, is studied to understand factors that contribute to disease evolution. Network-based models have been developed to capture different features of disease transmission in various environments. Network nodes represent geographical locations, and the weights represent the level of contact between regional pairings. Two competent vector populations, Aedes mosquitoes and Culex mosquitoes, and two host populations, cattle and humans were considered. The deterministic model was applied to the 2010 Rift Valley fever outbreak in three provinces of South Africa. Trends and timing of the outbreak in animals and humans were reproduced. The deterministic model with stochastic parameters was applied to hypothetical Rift Valley fever outbreak on a large network in Texas, the United States. The role of starting location and size of initial infection in Rift Valley fever virus spread were studied under various scenarios on a large-scale network. The reproduction number, defined as the number of secondary infections produced by one infected individual in a completely susceptible population, is typically considered an epidemic threshold of determining whether a disease can persist in a population. Extinction thresholds for corresponding Continuous-time Markov chain model is used to predict whether a disease can perish in a stochastic setting. The network level reproduction number for diseases vertically and horizontally transmitted among multiple species on heterogeneous networks was derived to predict whether a disease can invade the whole system in a deterministic setting. The complexity of computing the reproduction number is reduced because the expression of the reproduction number is the spectral radius of a matrix whose size is smaller than the original next generation matrix. The expression of the reproduction number may have a wide range of applications to many vector-borne diseases. Reproduction numbers can vary from below one to above one or from above one to below one by changing movement rates in different scenarios. The observations provide guidelines on executing movement bans in case of an epidemic. To compute the extinction threshold, corresponding Markov chain process is approximated near disease free equilibrium. The extinction threshold for Continuous-time Markov chain model was analytically connected to the reproduction number under some assumptions. Numerical simulation results agree with analytical results without assumptions, proposing a mathematical problem of proving the existence of the relationships in general. The distance of the extinction threshold were shown to be closer to one than the reproduction number. Consistent trends of probability of extinction varying with disease parameters observed through numerical simulations provide novel insights into disease mitigation, control, and elimination.