Spatio-temporal variation in environmental features predicts the distribution and abundance of Ixodes scapularis

Many species have experienced dramatic changes in both geographic range and population sizes in recent history. Increases in the geographic range or population size of disease vectors have public health relevance as these increases often precipitate the emergence of infectious diseases in human populations. Accurately identifying environmental factors affecting the biogeographic patterns of vector species is a long-standing analytical challenge, stemming from a paucity of data capturing periods of rapid changes in vector demographics. We systematically investigated the occurrence and abundance of nymphal Ixodes scapularis ticks at 532 sampling locations throughout New York State (NY), USA, between 2008 and 2018, a time frame that encompasses the emergence of diseases vectored by these ticks. Analyses of these field-collected data demonstrated a range expansion into northern and western NY during the last decade. Nymphal abundances increased in newly colonised areas, while remaining stable in areas with long-standing populations over the last decade. These trends in the geographic range and abundance of nymphs correspond to both the geographic expansion of human Lyme disease cases and increases in incidence rates. Analytic models fitted to these data incorporating time, space, and environmental factors, accurately identified drivers of the observed changes in nymphal occurrence and abundance. These models accounted for the spatial and temporal variation in the occurrence and abundance of nymphs and can accurately predict nymphal population patterns in future years. Forecasting disease risk at fine spatial scales prior to the transmission season can influence both public health mitigation strategies and individual behaviours, potentially impacting tick-borne disease risk and subsequently human disease incidence.     

A Stochastic Tick-Borne Disease Model: Exploring the Probability of Pathogen Persistence

We formulate and analyse a stochastic epidemic model for the transmission dynamics of a tick-borne disease in a single population using a continuous-time Markov chain approach. The stochastic model is based on an existing deterministic metapopulation tick-borne disease model. We compare the disease dynamics of the deterministic and stochastic models in order to determine the effect of randomness in tick-borne disease dynamics. The probability of disease extinction and that of a major outbreak are computed and approximated using the multitype Galton–Watson branching process and numerical simulations, respectively. Analytical and numerical results show some significant differences in model predictions between the stochastic and deterministic models. In particular, we find that a disease outbreak is more likely if the disease is introduced by infected deer as opposed to infected ticks. These insights demonstrate the importance of host movement in the expansion of tick-borne diseases into new geographic areas.     

Empirical evidence for key hosts in persistence of a tick-borne disease

An important epidemiological consequence of aggregated host-parasite associations occurs when parasites are vectors of pathogens. Those hosts that attract many vectors will tend to be the focus of transmission. But to what extent, and can we identify characteristics of these key hosts? We investigated these questions with respect to the host-tick relationship of the yellow-necked mouse, Apodemus flavicollis, a critical host in the maintenance of the zoonotic disease, tick-borne encephalitis. Transmission of the virus occurs when ticks feed in a 'co-feeding' aggregation. Thus, the number and frequency of co-feeding groups provides an estimate of the potential rate of virus transmission. We recorded the spatio-temporal variations in co-feeding on a population of rodents in conjunction with recording individual host characteristics. Using Lorenz curves, we revealed conformation of tick-borne encephalitis transmission potential to the 20/80 Rule, where the 20% of hosts most infested with ticks were accountable for 80% of transmission potential. Hosts in the transmission cohort were identified as the sexually mature males of high body mass. Therefore control efforts targeted at this group would substantially reduce transmission potential compared to non-targeted control of the population, which resulted in a linear reduction in transmission potential. Focusing on the 'wrong' functional group would have little impact upon transmission potential until a considerable proportion of the population had been subject to control. However, individuals can change their functional status over time making it difficult to predict the contribution of these individuals to future transmission.     

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.     

Wildlife disease elimination and density dependence

Disease control by managers is a crucial response to emerging wildlife epidemics, yet the means of control may be limited by the method of disease transmission. In particular, it is widely held that population reduction, while effective for controlling diseases that are subject to density-dependent (DD) transmission, is ineffective for controlling diseases that are subject to frequency-dependent (FD) transmission. We investigate control for horizontally transmitted diseases with FD transmission where the control is via culling or harvest that is non-selective with respect to infection and the population can compensate through DD recruitment or survival. Using a mathematical model, we show that culling or harvesting can eradicate the disease, even when transmission dynamics are FD. Eradication can be achieved under FD transmission when DD birth or recruitment induces compensatory growth of new, healthy individuals, which has the net effect of reducing disease prevalence by dilution. We also show that if harvest is used simultaneously with vaccination, and there is high enough transmission coefficient, application of both controls may be less efficient than vaccination alone. We illustrate the effects of these control approaches on disease prevalence for chronic wasting disease in deer where the disease is transmitted directly among deer and through the environment.     

Two Boundaries Separate Borrelia burgdorferi Populations in North America

Understanding the spread of infectious diseases is crucial for implementing effective control measures. For this, it is important to obtain information on the contemporary population structure of a disease agent and to infer the evolutionary processes that may have shaped it. Here, we investigate on a continental scale the population structure of Borrelia burgdorferi, the causative agent of Lyme borreliosis (LB), a tick-borne disease, in North America. We test the hypothesis that the observed population structure is congruent with recent population expansions and that these were preceded by bottlenecks mostly likely caused by the near extirpation in the 1900s of hosts required for sustaining tick populations. Multilocus sequence typing and complementary population analytical tools were used to evaluate B. burgdorferi samples collected in the Northeastern, Upper Midwestern, and Far-Western United States and Canada. The spatial distribution of sequence types (STs) and inferred population boundaries suggest that the current populations are geographically separated. One major population boundary separated western B. burgdorferi populations transmitted by Ixodes pacificus in California from Eastern populations transmitted by I. scapularis; the other divided Midwestern and Northeastern populations. However, populations from all three regions were genetically closely related. Together, our findings suggest that although the contemporary populations of North American B. burgdorferi now comprise three geographically separated subpopulations with no or limited gene flow among them, they arose from a common ancestral population. A comparative analysis of the B. burgdorferi outer surface protein C (ospC) gene revealed novel linkages and provides additional insights into the genetic characteristics of strains.     

Polytomous disease mapping to detect uncommon risk factors for related diseases

A statistical model for jointly analysing the spatial variation of incidences of three (or more) diseases, with common and uncommon risk factors, is introduced. Deaths for different diseases are described by a logit model for multinomial responses (multinomial logit or polytomous logit model). For each area and confounding strata population (i.e. age-class, sex, race) the probabilities of death for each cause (the response probabilities) are estimated. A specic disease, the one having a common risk factor only, acts as the baseline category. The log odds are decomposed additively into shared (common to diseases different by the reference disease) and specic structured spatial variability terms, unstructured unshared spatial terms and confounders terms (such as age, race and sex) to adjust the crude observed data for their effects. Disease specic spatially structured effects are estimated; these are considered as latent variables denoting disease-specic risk factors. The model is presented with reference to a specic application. We considered the mortality data (from 1990 to 1994) relative to oral cavity, larynx and lung cancers in 13 age groups of males, in the 287 municipalities of Region of Tuscany (Italy). All these pathologies share smoking as a common risk factor; furthermore, two of them (oral cavity and larynx cancer) share alcohol consumption as a risk factor. All studies suggest that smoking and alcohol consumption are the major known risk factors for oral cavity and larynx cancers; nevertheless, in this paper, we investigate the possibility of other different risk factors for these diseases, or even the presence of an interaction effect (between smoking and alcohol risk factors) but with different spatial patterns for oral and larynx cancer. For each municipality and age-class the probabilities of death for each cause (the response probabilities) are estimated. Lung cancer acts as the baseline category. The log odds are decomposed additively into shared (common to oral cavity and larynx diseases) and specic structured spatial variability terms, unstructured unshared spatial terms and an age-group term. It turns out that oral cavity and larynx cancer have different spatial patterns for residual risk factors which are not the typical ones such as smoking habits and alcohol consumption. But, possibly, these patterns are due to different spatial interactions between smoking habits and alcohol consumption for the first and the second disease.     

The ecology of tick-borne diseases

Zoonotic diseases are major causes of infection related morbidity and mortality worldwide. Of the various arthropods capable of transmitting pathogens that cause such diseases to humans, ticks, which are vectors of more kinds of pathogens than any other group of invertebrate, have become an increasing focus of attention. This is particularly the case in the temperate northern hemisphere where they are a significant vector of human disease. Here, we provide an overview of the complex ecological systems defining the various epidemiological cycles of tick-borne diseases. We highlight the abiotic and biotic factors influencing the establishment and persistence of tick populations and their associated pathogens. Furthermore, we emphasize the dynamic nature of such systems, especially when they are under the influence of both small and large-scale anthropogenic changes to the environment. Although a great deal of work has been done on ticks and the diseases which they transmit, the very dynamism of the system means that new factors are continually arising which shift the epidemiological pattern within specific areas. We therefore consider that more detailed, long-term (i.e. at least 10 years), multidisciplinary studies need to be carried out to define why and how these pattern shifts take place and to determine their public health significance.     

Modelling the effect of temperature variation on the seasonal dynamics of Ixodes ricinus tick populations

Seasonal variation in temperature is known to drive annual patterns of tick activity and can influence the dynamics of tick-borne diseases. An age-structured model of the dynamics of Ixodes ricinus populations was developed to explore how changes in average temperature and different levels of temperature variability affect seasonal patterns of tick activity and the transmission of tick-borne diseases. The model produced seasonal patterns of tick emergence that are consistent with those observed throughout Great Britain. Varying average temperature across a continuous spectrum produced a systematic pattern in the times of peak emergence of questing ticks which depends on cumulative temperature over the year. Examination of the effects of between-year stochastic temperature variation on this pattern indicated that peak emergence times are more strongly affected by temperature stochasticity at certain levels of average temperature. Finally the model was extended to give a simple representation of the dynamics of a tick-borne disease. A threshold level of annual cumulative temperature was identified at which disease persistence is sensitive to stochastic temperature variation. In conclusion, the effect of changing patterns of temperature variation on the dynamics of I. ricinus ticks and the diseases they transmit may depend on the cumulative temperature over the year and will therefore vary across different locations. The results also indicate that diapause mechanisms have an important influence on seasonal patterns of tick activity and require further study.     

Is endemic stability of tick-borne disease in cattle a useful concept?

Endemic stability is a widely used term in the epidemiology of ticks and tick-borne diseases. It is generally accepted to refer to a state of a host-tick-pathogen interaction in which there is a high level of challenge of calves by infected ticks, absence of clinical disease in calves despite infection, and a high level of immunity in adult cattle with consequent low incidence of clinical disease. Although endemic stability is a valid epidemiological concept, the modelling studies that underpinned subsequent studies on the epidemiology of tick-borne diseases were specific to a single host-tick-pathogen system, and values derived from these models should not be applied in other regions or host-tick-pathogen systems.     

Contrasting landscape epidemiology of two sympatric rabies virus strains

Viral strain evolution and disease emergence are influenced by anthropogenic change to the environment. We investigated viral characteristics, host ecology, and landscape features in the rabies‐striped skunk disease system of the central Great Plains to determine how these factors interact to influence disease emergence. We amplified portions of the N and G genes of rabies viral RNA from 269 samples extracted from striped skunk brains throughout the distribution of two different rabies strains for which striped skunks were the reservoir. Because the distribution of these two strains overlapped on the landscape and were present in the same host population, we could evaluate how viral properties influenced epidemiological patterns in the area of sympatry. We found that South Central Skunk rabies (SCSK) exhibited intense purifying selection and high infectivity, which are both characteristics of an epizootic virus. Conversely, North Central Skunk rabies (NCSK) exhibited relaxed purifying selection and comparatively lower infectivity, suggesting the presence of an enzootic virus. The host population in the area of sympatry was highly admixed, and skunks among allopatric and sympatric areas had similar effective population sizes. Spatial analysis indicated that landscape features had minimal influence on NCSK movement across the landscape, but those same features were partial barriers to the spread of SCSK. We conclude that NCSK and SCSK have different epidemiological properties that interact differently with both host and landscape features to influence rabies spread in the central Great Plains. We suggest a holistic approach for future studies of emerging infectious diseases that includes studies of viral properties, host characteristics, and spatial features.     

Disease diversity and human fertility

The existence of parasitic constraints on the evolution of life-history traits in free-living organisms has been demonstrated in several plant and animal species. However, the association between different diseases and human traits is virtually unknown. We conducted a comparative analysis on a global scale to test whether the diversity of human diseases, some of them responsible for high incidences of morbidity and mortality, were associated with host life-history characteristics. After controlling for direct confounding effects exerted by historical, spatial, economic, and population patterns and their interactions, our findings show that human fertility increases with the diversity and structure of disease types. Thus, disease control may not only lower the costs associated with morbidity, but could also contribute directly or indirectly to reductions in human population growth.     

Tick-borne infections of animals and humans: a common ground

A wide variety of pathogens is transmitted from ticks to vertebrates including viruses, bacteria, protozoa and helminths, of which most have a life cycle that requires passage through the vertebrate host. Tick-borne infections of humans, farm and companion animals are essentially associated with wildlife animal reservoirs. While some flying insect-borne diseases of humans such as malaria, filariasis and Kala Azar caused by Leishmania donovani target people as their main host, major tick-borne infections of humans, although potentially causing disease in large numbers of individuals, are typically an infringement of a circulation between wildlife animal reservoirs and tick vectors. While new tick-borne infectious agents are frequently recognised, emerging agents of human tick-borne infections were probably circulating among wildlife animal and tick populations long before being recognised as clinical causes of human disease as has been shown for Borrelia burgdorferi sensu lato. Co-infection with more than one tick-borne infection is common and can enhance pathogenic processes and augment disease severity as found in B. burgdorferi and Anaplasma phagocytophilum co-infection. The role of wild animal reservoirs in co-infection of human hosts appears to be central, further linking human and animal tick-borne infections. Although transmission of most tick-borne infections is through the tick saliva, additional routes of transmission, shown mostly in animals, include infection by oral uptake of infected ticks, by carnivorism, animal bites and transplacentally. Additionally, artificial infection via blood transfusion is a growing threat in both human and veterinary medicine. Due to the close association between human and animal tick-borne infections, control programs for these diseases require integration of data from veterinary and human reporting systems, surveillance in wildlife and tick populations, and combined teams of experts from several scientific disciplines such as entomology, epidemiology, medicine, public health and veterinary medicine.     

The population genetic structure of vectors and our understanding of disease epidemiology

Understanding and predicting disease epidemiology relies on clear knowledge about the basic biology of the organisms involved. Despite the key role that arthropod vectors play in disease dynamics and detailed mechanistic work on the vector-pathogen interface, little information is often available about how these populations function under natural conditions. Population genetic studies can help fill this void by providing information about the taxonomic status of species, the spatial limits of populations, and the nature of gene flow among populations. Here, I briefly review different types of population genetic structure and some recent examples of where this information has provided key elements for understanding pathogen transmission in tick-borne systems.     

Association between polymorphisms in OAS2 and CD209 genes and predisposition to chronic hepatitis C in Russian population

Chronic hepatitis C is a severe liver disease caused by positive-strand RNA virus. Previously, we reported an association between seven single nucleotide polymorphisms (SNPs) in four innate immunity genes (OAS2, OAS3, CD209, and TLR3) and human predisposition to tick-borne encephalitis, caused by a virus from the same Flaviviridae family, in a Russian population. Currently, genotype and allele frequencies for these SNPs were analyzed in 75 chronic hepatitis C patients and compared with the population control (269 Novosibirsk citizens). Data obtained suggest that the OAS2 rs1293762 and CD209 rs2287886 SNPs are associated with predisposition to chronic hepatitis C in Russian population.     

Single nucleotide polymorphism rs1800872 in the promoter region of the IL10 gene is associated with predisposition to chronic hepatitis C in Russian population

Previously, we studied an association of two IL28B gene single nucleotide polymorphisms (SNPs) and three IL10 gene SNPs with predisposition to tick-borne encephalitis in a Russian population. In this study, a possible involvement of these SNPs in the development of predisposition to chronic hepatitis C (caused by structurally similar, related virus from the Flaviviridae family) was investigated in the same population. Only the IL10 promoter rs1800872 SNP was associated with predisposition to chronic hepatitis C. This SNP seems to be a common genetic marker of predisposition to two diseases caused by hepatitis C and tick-borne encephalitis viruses in Russian population.     

A hierarchical aggregate data model with spatially correlated disease rates

The aggregate data study design (Prentice and Sheppard, 1995, Biometrika 82, 113-125) estimates individual-level exposure effects by regressing population-based disease rates on covariate data from survey samples in each population group. In this work, we further develop the aggregate data model to allow for residual spatial correlation among disease rates across populations. Geographical variation that is not explained by model predictors and has a spatial component often arises in studies of rare chronic diseases, such as breast cancer. We combine the aggregate and Bayesian disease-mapping models to provide an intuitive approach to the modeling of spatial effects while drawing correct inference regarding the exposure effect. Based on the results of simulation studies, we suggest guidelines for use of the proposed model.     

Correlation of TBE Incidence with Red Deer and Roe Deer Abundance in Slovenia

Tick-borne encephalitis (TBE) is a virus infection which sometimes causes human disease. The TBE virus is found in ticks and certain vertebrate tick hosts in restricted endemic localities termed TBE foci. The formation of natural foci is a combination of several factors: the vectors, a suitable and numerous enough number of hosts and in a habitat with suitable vegetation and climate. The present study investigated the influence of deer on the incidence of tick-borne encephalitis. We were able to obtain data from deer culls. Using this data, the abundance of deer was estimated and temporal and spatial analysis was performed. The abundance of deer has increased in the past decades, as well as the incidence of tick-borne encephalitis. Temporal analysis confirmed a correlation between red deer abundance and tick-borne encephalitis occurrence. Additionally, spatial analysis established, that in areas with high incidence of tick-borne encephalitis red deer density is higher, compared to areas with no or few human cases of tick-borne encephalitis. However, such correlation could not be confirmed between roe deer density and the incidence of tick-borne encephalitis. This is presumably due to roe deer density being above a certain threshold so that availability of tick reproduction hosts has no apparent effect on ticks'' host finding and consequently may not be possible to correlate with incidence of human TBE.     

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.     

Caribbean coral diseases: primary transmission or secondary infection?

Over the last 40 years, disease outbreaks have significantly reduced coral populations throughout the Caribbean. Most coral‐disease models assume that coral diseases are contagious and that pathogens are transmitted from infected to susceptible hosts. However, this assumption has not been rigorously tested. We used spatial epidemiology to examine disease clustering, at scales ranging from meters to tens of kilometers, to determine whether three of the most common Caribbean coral diseases, (i) yellow‐band disease, (ii) dark‐spot syndrome, and (iii) white‐plague disease, were spatially clustered. For all three diseases, we found no consistent evidence of disease clustering and, therefore, these diseases did not follow a contagious‐disease model. We suggest that the expression of some coral diseases is instead a two‐step process. First, environmental thresholds are exceeded. Second, these environmental conditions either weaken the corals, which are then more susceptible to infection, or the conditions increase the virulence or abundance of pathogens. Exceeding such environmental thresholds will most likely become increasingly common in rapidly warming oceans, leading to more frequent coral‐disease outbreaks.