Past and future perspectives on mathematical models of tick-borne pathogens

Mechanistic movement models to predict geographic range expansions of ticks and tick-borne pathogens: Case studies with Ixodes scapularis and Amblyomma americanum in eastern North America

The geographic range of the blacklegged tick, Ixodes scapularis, is expanding northward from the United States into southern Canada, and studies suggest that the lone star tick, Amblyomma americanum, will follow suit. These tick species are vectors for many zoonotic pathogens, and their northward range expansion presents a serious threat to public health. Climate change (particularly increasing temperature) has been identified as an important driver permitting northward range expansion of blacklegged ticks, but the impacts of host movement, which is essential to tick dispersal into new climatically suitable regions, have received limited investigation. Here, a mechanistic movement model was applied to landscapes of eastern North America to explore 1) relationships between multiple ecological drivers and the speed of the northward invasion of blacklegged ticks infected with the causative agent of Lyme disease, Borrelia burgdorferi sensu stricto, and 2) its capacity to simulate the northward range expansion of infected blacklegged ticks and uninfected lone star ticks under theoretical scenarios of increasing temperature. Our results suggest that the attraction of migratory birds (long-distance tick dispersal hosts) to resource-rich areas during their spring migration and the mate-finding Allee effect in tick population dynamics are key drivers for the spread of infected blacklegged ticks. The modeled increases in temperature extended the climatically suitable areas of Canada for infected blacklegged ticks and uninfected lone star ticks towards higher latitudes by up to 31% and 1%, respectively, and with an average predicted speed of the range expansion reaching 61 km/year and 23 km/year, respectively. Differences in the projected spatial distribution patterns of these tick species were due to differences in climate envelopes of tick populations, as well as the availability and attractiveness of suitable habitats for migratory birds. Our results indicate that the northward invasion process of lone star ticks is primarily driven by local dispersal of resident terrestrial hosts, whereas that of blacklegged ticks is governed by long-distance migratory bird dispersal. The results also suggest that mechanistic movement models provide a powerful approach for predicting tick-borne disease risk patterns under complex scenarios of climate, socioeconomic and land use/land cover changes.

Using mechanistic models to highlight research priorities for tick-borne zoonotic diseases: Improving our understanding of the ecology and maintenance of Kyasanur Forest Disease in India

The risk of spillover of zoonotic diseases to humans is changing in response to multiple environmental and societal drivers, particularly in tropical regions where the burden of neglected zoonotic diseases is highest and land use change and forest conversion is occurring most rapidly. Neglected zoonotic diseases can have significant impacts on poor and marginalised populations in low-resource settings but ultimately receive less attention and funding for research and interventions. As such, effective control measures and interventions are often hindered by a limited ecological evidence base, which results in a limited understanding of epidemiologically relevant hosts or vectors and the processes that contribute to the maintenance of pathogens and spillover to humans. Here, we develop a generalisable next generation matrix modelling framework to better understand the transmission processes and hosts that have the greatest contribution to the maintenance of tick-borne diseases with the aim of improving the ecological evidence base and framing future research priorities for tick-borne diseases. Using this model we explore the relative contribution of different host groups and transmission routes to the maintenance of a neglected zoonotic tick-borne disease, Kyasanur Forest Disease Virus (KFD), in multiple habitat types. The results highlight the potential importance of transovarial transmission and small mammals and birds in maintaining this disease. This contradicts previous hypotheses that primates play an important role influencing the distribution of infected ticks. There is also a suggestion that risk could vary across different habitat types but currently more research is needed to evaluate this relationship. In light of these results, we outline the key knowledge gaps for this system and future research priorities that could inform effective interventions and control measures.

Predicting the current and future risk of ticks on livestock farms in Britain using random forest models

The most abundant tick species in northern Europe, Ixodes ricinus, transmits a range of pathogens that cause disease in livestock. As I. ricinus distribution is influenced by climate, tick-borne disease risk is expected to change in the future. The aims of this work were to build a spatial model to predict current and future risk of ticks on livestock farms across Britain. Variables relating both to tick hazard and livestock exposure were included, to capture a niche which may be missed by broader scale models. A random forest machine learning model was used due to its ability to cope with correlated variables and interactions. Data on tick presence and absence on sheep and cattle farms was obtained from a retrospective questionnaire survey of 926 farmers. The ROC of the final model was 0.80. The model outputs matched observed patterns of tick distribution, with areas of highest tick risk in southwest and northwest England, Wales, and west Scotland. Overall, the probability of tick presence on livestock farms was predicted to increase by 5-7 % across Britain under future climate scenarios. The predicted increase is greater at higher altitudes and latitudes, further increasing the risk of tick-borne disease on farms in these areas.

Amblyomma mixtum free-living stages: Inferences on dry and wet seasons use, preference, and niche width in an agroecosystem (Yopal, Casanare, Colombia)

The formulation of effective control strategies for any pest species generally involves the study of habitat use and preference and niche width in anthropogenically transformed natural landscapes. We evaluated whether the use, habitat preference, and niche range of the Amblyomma mixtum tick changed between stages, habitats, and seasonality (dry-wet seasons 2019) on a farm in Yopal (Casanare, Colombia). The presence and relative abundance of free-living larvae, nymphs, and adults was quantified in four different habitats according to the type of vegetation cover (Riparian Forest, Cocoa Crop, King Grass Crop, and Star Grass Paddock). Habitat availability was estimated, environmental variables were analyzed, and various indices of habitat use and preference, and niche width were calculated. A. mixtum's habitat use and preference, and niche width changed between stages, habitat types, and time of the year. The total abundance of A. mixtum was an order of magnitude greater in the dry season than the wet season. In the dry season, all stages used all habitats, while A. mixtum adults used all the habitats in both seasons. In the dry season, nymphs and larvae preferred three out of the four habitats, while adults preferred the King Grass Crop. In the wet season, nymphs and larvae preferred two habitats, whereas the adults preferred the King Grass Crop. The value of the niche width index was high for larvae, nymphs, and adults in the dry season, while it was high only for adults in the wet season. Thus, A. mixtum's vast environmental tolerance and niche breadth allows the species to use and colonize changing habitats (unstable or temporary) with fluctuating environmental conditions (e.g., King Grass Crop), potentially keeping a stable population over time and making it an extremely resistant species. However, the wet flooding season in Yopal may exceed A. mixtum's stages' tolerances.

The evolving story of Borrelia burgdorferi sensu lato transmission in Europe

Beside mosquitoes, ticks are well-known vectors of different human pathogens. In the Northern Hemisphere, Lyme borreliosis (Eurasia, LB) or Lyme disease (North America, LD) is the most commonly occurring vector-borne infectious disease caused by bacteria of the genus Borrelia which are transmitted by hard ticks of the genus Ixodes. The reported incidence of LB in Europe is about 22.6 cases per 100,000 inhabitants annually with a broad range depending on the geographical area analyzed. However, the epidemiological data are largely incomplete, because LB is not notifiable in all European countries. Furthermore, not only differ reporting procedures between countries, there is also variation in case definitions and diagnostic procedures. Lyme borreliosis is caused by several species of the Borrelia (B.) burgdorferi sensu lato (s.l.) complex which are maintained in complex networks including ixodid ticks and different reservoir hosts. Vector and host influence each other and are affected by multiple factors including climate that have a major impact on their habitats and ecology. To classify factors that influence the risk of transmission of B. burgdorferi s.l. to their different vertebrate hosts as well as to humans, we briefly summarize the current knowledge about the pathogens including their astonishing ability to overcome various host immune responses, regarding the main vector in Europe Ixodes ricinus, and the disease caused by borreliae. The research shows, that a higher standardization of case definition, diagnostic procedures, and standardized, long-term surveillance systems across Europe is necessary to improve clinical and epidemiological data.

Bacterial microbiota composition of Ixodes ricinus ticks: the role of environmental variation, tick characteristics and microbial interactions

Ecological factors, host characteristics and/or interactions among microbes may all shape the occurrence of microbes and the structure of microbial communities within organisms. In the past, disentangling these factors and determining their relative importance in shaping within-host microbiota communities has been hampered by analytical limitations to account for (dis)similar environmental preferences ('environmental filtering'). Here we used a joint species distribution modelling (JSDM) approach to characterize the bacterial microbiota of one of the most important disease vectors in Europe, the sheep tick Ixodes ricinus, along ecological gradients in the Swiss Alps. Although our study captured extensive environmental variation along elevational clines, the explanatory power of such large-scale ecological factors was comparably weak, suggesting that tick-specific traits and behaviours, microhabitat and -climate experienced by ticks, and interactions among microbes play an important role in shaping tick microbial communities. Indeed, when accounting for shared environmental preferences, evidence for significant patterns of positive or negative co-occurrence among microbes was found, which is indicative of competition or facilitation processes. Signals of facilitation were observed primarily among human pathogens, leading to co-infection within ticks, whereas signals of competition were observed between the tick endosymbiont Spiroplasma and human pathogens. These findings highlight the important role of small-scale ecological variation and microbe-microbe interactions in shaping tick microbial communities and the dynamics of tick-borne disease.

Seasonal cycles of the TBE and Lyme borreliosis vector Ixodes ricinus modelled with time-lagged and interval-averaged predictors

Ticks of the species Ixodes ricinus (L.) are the major vectors for tick-borne diseases in Europe. The aim of this study was to quantify the influence of environmental variables on the seasonal cycle of questing I. ricinus. Therefore, an 8-year time series of nymphal I. ricinus flagged at monthly intervals in Haselmühl (Germany) was compiled. For the first time, cross correlation maps were applied to identify optimal associations between observed nymphal I. ricinus densities and time-lagged as well as temporal averaged explanatory variables. To prove the explanatory power of these associations, two Poisson regression models were generated. The first model simulates the ticks of the entire time series flagged per 100 m[Formula: see text], the second model the mean seasonal cycle. Explanatory variables comprise the temperature of the flagging month, the relative humidity averaged from the flagging month and 1 month prior to flagging, the temperature averaged over 4-6 months prior to the flagging event and the hunting statistics of the European hare from the preceding year. The first model explains 65% of the monthly tick variance and results in a root mean square error (RMSE) of 17 ticks per 100 m[Formula: see text]. The second model explains 96% of the tick variance. Again, the accuracy is expressed by the RMSE, which is 5 ticks per 100 m[Formula: see text]. As a major result, this study demonstrates that tick densities are higher correlated with time-lagged and temporal averaged variables than with contemporaneous explanatory variables, resulting in a better model performance.

The passive surveillance of ticks using companion animal electronic health records

Ticks represent a large global reservoir of zoonotic disease. Current surveillance systems can be time and labour intensive. We propose that the passive surveillance of companion animal electronic health records (EHRs) could provide a novel methodology for describing temporal and spatial tick activity. A total of 16 58 857 EHRs were collected over a 2-year period (31 March 2014 and 29 May 2016) from companion animals attending a large sentinel network of 192 veterinary clinics across Great Britain (the Small Animal Veterinary Surveillance Network - SAVSNET). In total, 2180 EHRs were identified where a tick was recorded on an animal. The relative risk of dogs presenting with a tick compared with cats was 0·73 (95% confidence intervals 0·67-0·80). The highest number of tick records were in the south central regions of England. The presence of ticks showed marked seasonality with summer peaks, and a secondary smaller peak in autumn for cats; ticks were still being found throughout most of Great Britain during the winter. This suggests that passive surveillance of companion animal EHRs can describe tick activity temporally and spatially in a large cohort of veterinary clinics across Great Britain. These results and methodology could help inform veterinary and public health messages as well as increase awareness of ticks and tick-borne diseases in the general population.

Molecular epidemiological survey of bacterial and parasitic pathogens in hard ticks from eastern China

Ticks are able to transmit various pathogens-viruses, bacteria, and parasites-to their host during feeding. Several molecular epidemiological surveys have been performed to evaluate the risk of tick-borne pathogens in China, but little is known about pathogens circulating in ticks from eastern China. Therefore, this study aimed to investigate the presence of bacteria and parasites in ticks collected from Xuzhou, a 11258km² region in eastern China. In the present study, ticks were collected from domestic goats and grasses in urban districts of Xuzhou region from June 2015 to July 2016. After tick species identification, the presence of tick-borne bacterial and parasitic pathogens, including Anaplasma phagocytophilum, Borrelia burgdorferi, Rickettsia sp., Bartonella sp., Babesia sp., and Theileria sp., was established via conventional or nested polymerase chain reaction assays (PCR) and sequence analysis. Finally, a total of 500 questing adult ticks, identified as Haemaphysalis longicornis, were investigated. Among them, 28/500 tick samples (5.6%) were infected with A. phagocytophilum, and 23/500 (4.6%) with Theileria luwenshuni, whereas co-infection with these pathogens was detected in only 1/51 (2%) of all infected ticks. In conclusion, H. longicornis is the dominant tick species in the Xuzhou region and plays an important role in zoonotic pathogen transmission. Both local residents and animals are at a significant risk of exposure to anaplasmosis and theileriosis, due to the high rates of A. phagocytophilum and T. luwenshuni tick infection.

Editorial: Mathematical modelling of infectious diseases

The field of disease ecology - the study of the spread and impact of parasites and pathogens within their host populations and communities - has a long history of using mathematical models. Dating back over 100 years, researchers have used mathematics to describe the spread of disease-causing agents, understand the relationship between host density and transmission and plan control strategies. The use of mathematical modelling in disease ecology exploded in the late 1970s and early 1980s through the work of Anderson and May (Anderson and May, 1978, 1981, 1992; May and Anderson, 1978), who developed the fundamental frameworks for studying microparasite (e.g. viruses, bacteria and protozoa) and macroparasite (e.g. helminth) dynamics, emphasizing the importance of understanding features such as the parasite's basic reproduction number (R 0) and critical community size that form the basis of disease ecology research to this day. Since the initial models of disease population dynamics, which primarily focused on human diseases, theoretical disease research has expanded hugely to encompass livestock and wildlife disease systems, and also to explore evolutionary questions such as the evolution of parasite virulence or drug resistance. More recently there have been efforts to broaden the field still further, to move beyond the standard 'one-host-one-parasite' paradigm of the original models, to incorporate many aspects of complexity of natural systems, including multiple potential host species and interactions among multiple parasite species.