The basic reproductive number of tick–borne encephalitis virus

Exploring the Reservoir Hosts of Tick-Borne Encephalitis Virus

Tick-borne encephalitis virus (TBEV) is an important arbovirus, which is found across large parts of Eurasia and is considered to be a major health risk for humans. Like any other arbovirus, TBEV relies on complex interactions between vectors, reservoir hosts, and the environment for successful virus circulation. Hard ticks are the vectors for TBEV, transmitting the virus to a variety of animals. The importance of these animals in the lifecycle of TBEV is still up for debate. Large woodland animals seem to have a positive influence on virus circulation by providing a food source for adult ticks; birds are suspected to play a role in virus distribution. Bank voles and yellow-necked mice are often referred to as classical virus reservoirs, but this statement lacks strong evidence supporting their highlighted role. Other small mammals (e.g., insectivores) may also play a crucial role in virus transmission, not to mention the absence of any suspected reservoir host for non-European endemic regions. Theories highlighting the importance of the co-feeding transmission route go as far as naming ticks themselves as the true reservoir for TBEV, and mammalian hosts as a mere bridge for transmission. A deeper insight into the virus reservoir could lead to a better understanding of the development of endemic regions. The spatial distribution of TBEV is constricted to certain areas, forming natural foci that can be restricted to sizes of merely 500 square meters. The limiting factors for their occurrence are largely unknown, but a possible influence of reservoir hosts on the distribution pattern of TBE is discussed. This review aims to give an overview of the multiple factors influencing the TBEV transmission cycle, focusing on the role of virus reservoirs, and highlights the questions that are waiting to be further explored.

Basic reproduction number for the Brazilian Spotted Fever

Brazilian Spotted Fever (BSF) is an emerging and lethal disease in South America which basic reproduction number (R₀) is unknown. Calculating R₀ for this disease is crucial to design control interventions and prevent human deaths. BSF endemic areas are related to the presence of capybaras Hydrochoerus hydrochaeris, amplifier hosts of Rickettsia rickettsii and primary hosts of the tick Amblyomma sculptum, main vector of the agent in this area. Because of the complexity of its dynamics, we calculated R₀ for the BSF system by constructing a next-generation matrix considering different categories of vectors and hosts. Each matrix element was considered as the expected number of infected individuals of one category produced by a single infected individual of a second category. We used field and experimental data to parameterize the next-generation matrix and obtain the final calculation (R₀ ≈ 1.7). We demonstrated the low impact of the matrix elements corresponding to the transovarial transmission and the transmission from infected larvae in the maintenance of R. rickettsii. Sensitivity and elasticity analyzes were performed to quantify the perturbations of each matrix element in R₀. We noted that the elements equivalent to the number of infected attached nymphs produced by an infected capybara, and the number of infected capybaras produced by an infected attached nymph or adult are the major contributors to changes in R₀. Our results provide insights into the strategic design of preventive interventions in BSF endemic areas.

Modeling Lyme disease transmission

Lyme disease, a typical tick-borne disease, imposes increasing global public health challenges. A growing body of theoretical models have been proposed to better understand various factors determining the disease risk, which not only enrich our understanding on the ecological cycle of disease transmission but also promote new theoretical developments on model formulation, analysis and simulation. In this paper, we provide a review about the models and results we have obtained recently on modeling and analyzing Lyme disease transmission, with the purpose to highlight various aspects in the ecological cycle of disease transmission to be incorporated, including the growth of ticks with different stages in the life cycle, the seasonality, host diversity, spatial disease pattern due to host short distance movement and bird migration, co-infection with other tick-borne pathogens, and climate change impact.

Impact of biodiversity and seasonality on Lyme-pathogen transmission

Lyme disease imposes increasing global public health challenges. To better understand the joint effects of seasonal temperature variation and host community composition on the pathogen transmission, a stage-structured periodic model is proposed by integrating seasonal tick development and activity, multiple host species and complex pathogen transmission routes between ticks and reservoirs. Two thresholds, one for tick population dynamics and the other for Lyme-pathogen transmission dynamics, are identified and shown to fully classify the long-term outcomes of the tick invasion and disease persistence. Seeding with the realistic parameters, the tick reproduction threshold and Lyme disease spread threshold are estimated to illustrate the joint effects of the climate change and host community diversity on the pattern of Lyme disease risk. It is shown that climate warming can amplify the disease risk and slightly change the seasonality of disease risk. Both the "dilution effect" and "amplification effect" are observed by feeding the model with different possible alternative hosts. Therefore, the relationship between the host community biodiversity and disease risk varies, calling for more accurate measurements on the local environment, both biotic and abiotic such as the temperature and the host community composition.

Developing a temperature-driven map of the basic reproductive number of the emerging tick vector of Lyme disease Ixodes scapularis in Canada

A mechanistic model of the tick vector of Lyme disease, Ixodes scapularis, was adapted to a deterministic structure. Using temperature normals smoothed by Fourier analysis to generate seasonal temperature-driven development rates and host biting rates, and a next generation matrix approach, the model was used to obtain values for the basic reproduction number (R(0)) for I. scapularis at locations in southern Canada where the tick is established and emerging. The R(0) at Long Point, Point Pelee and Chatham sites where I. scapularis are established, was estimated at 1.5, 3.19 and 3.65, respectively. The threshold temperature conditions for tick population survival (R(0)=1) were shown to be the same as those identified using the mechanistic model (2800-3100 cumulative annual degree days >0°C), and a map of R(0) for I. scapularis, the first such map for an arthropod vector, was drawn for Canada east of the Rocky Mountains. This map supports current risk assessments for Lyme disease risk emergence in Canada. Sensitivity analysis identified host abundance, tick development rates and summer temperatures as highly influential variables in the model, which is consistent with our current knowledge of the biology of this tick. The development of a deterministic model for I. scapularis that is capable of providing values for R(0) is a key step in our evolving ability to develop tools for assessment of Lyme disease risk emergence and for development of public health policies on surveillance, prevention and control.

Unraveling the ecological complexities of tick-associated Crimean-Congo hemorrhagic fever virus transmission: a gap analysis for the western Palearctic

This review aims to summarize the current knowledge of the eco-epidemiology of Crimean-Congo hemorrhagic fever (CCHF) virus transmission reviewing the most recent scientific advances in the last few decades of epidemic and non-epidemic ("silent") periods. We explicitly aim to highlight the dynamics of transmission that are still largely unknown. Recent knowledge gathered from research in Africa and Europe explains the very focal nature of the virus, and indicates that research on the ecology of the virus in the inter-epidemic periods of the disease has not yet been addressed. Hyalomma spp. ticks have been incriminated in the transmission of the virus under field conditions, but the role of other ticks found infected in nature remains to be tested under experimental conditions. Published evidence suggests that the increase in human cases reported in the Balkans, Turkey, and Russia is perhaps less due to the effect of changes in climate, but rather result from the impact of yet unexplored mechanisms of amplification that might be supported by wild animal hosts. Assessment of the available data suggests that epidemics in Eastern Europe are not the result of a spreading viral wave, but more likely are due to a combination of factors, such as habitat abandonment, landscape fragmentation, and proliferation of wildlife hosts that have exacerbated prevalence rates in tick vectors. There is an urgent need to empirically demonstrate these assumptions as well as the role of birds in introducing infected ticks, and also to evaluate the potential for survival of introduced ticks. Either a replacement of the pathogenic virus in the western Mediterranean or a lack of westward dissemination of infected tick populations may explain the absence of the virus in Western Europe.

The basic reproduction number for complex disease systems: defining R(0) for tick-borne infections

Characterizing the basic reproduction number, R(0), for many wildlife disease systems can seem a complex problem because several species are involved, because there are different epidemiological reactions to the infectious agent at different life-history stages, or because there are multiple transmission routes. Tick-borne diseases are an important example where all these complexities are brought together as a result of the peculiarities of the tick life cycle and the multiple transmission routes that occur. We show here that one can overcome these complexities by separating the host population into epidemiologically different types of individuals and constructing a matrix of reproduction numbers, the so-called next-generation matrix. Each matrix element is an expected number of infectious individuals of one type produced by a single infectious individual of a second type. The largest eigenvalue of the matrix characterizes the initial exponential growth or decline in numbers of infected individuals. Values below 1 therefore imply that the infection cannot establish. The biological interpretation closely matches that of R(0) for disease systems with only one type of individual and where infection is directly transmitted. The parameters defining each matrix element have a clear biological meaning. We illustrate the usefulness and power of the approach with a detailed examination of tick-borne diseases, and we use field and experimental data to parameterize the next-generation matrix for Lyme disease and tick-borne encephalitis. Sensitivity and elasticity analyses of the matrices, at the element and individual parameter levels, allow direct comparison of the two etiological agents. This provides further support that transmission between cofeeding ticks is critically important for the establishment of tick-borne encephalitis.

Effect of host populations on the intensity of ticks and the prevalence of tick-borne pathogens: how to interpret the results of deer exclosure experiments

Deer are important blood hosts for feeding Ixodes ricinus ticks but they do not support transmission of many tick-borne pathogens, so acting as dead-end transmission hosts. Mathematical models show their role as tick amplifiers, but also suggest that they dilute pathogen transmission, thus reducing infection prevalence. Empirical evidence for this is conflicting: experimental plots with deer removal (i.e. deer exclosures) show that the effect depends on the size of the exclosure. Here we present simulations of dynamic models that take into account different tick stages, and several host species (e.g. rodents) that may move to and from deer exclosures; models were calibrated with respect to Ixodes ricinus ticks and tick-borne encephalitis (TBE) in Trentino (northern Italy). Results show that in small exclosures, the density of rodent-feeding ticks may be higher inside than outside, whereas in large exclosures, a reduction of such tick density may be reached. Similarly, TBE prevalence in rodents decreases in large exclosures and may be slightly higher in small exclosures than outside them. The density of infected questing nymphs inside small exclosures can be much higher, in our numerical example almost twice as large as that outside, leading to potential TBE infection risk hotspots.

Effects of tick population dynamics and host densities on the persistence of tick-borne infections

The transmission and the persistence of tick-borne infections are strongly influenced by the densities and the structure of host populations. By extending previous models and analysis, in this paper we analyse how the persistence of ticks and pathogens, is affected by the dynamics of tick populations, and by their host densities. The effect of host densities on infection persistence is explored through the analysis and simulation of a series of models that include different assumptions on tick-host dynamics and consider different routes of infection transmission. Ticks are assumed to feed on two types of host species which vary in their reservoir competence. Too low densities of competent hosts (i.e., hosts where transmission can occur) do not sustain the infection cycle, while too high densities of incompetent hosts may dilute the competent hosts so much to make infection persistence impossible. A dilution effect may occur also for competent hosts as a consequence of reduced tick to host ratio; this is possible only if the regulation of tick populations is such that tick density does not increase linearly with host densities.