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Fig. 6 in Climate change, biodiversity, ticks and tick-borne diseases: The butterfly effect

Fig. 6. Podolica cattle in the Gallipoli Cognato Regional Park, Basilicata, southern Italy. These cattle move freely within the park's territory, helping in disseminating Ixodes ricinus to different altitudes (from 200 m to over 1000 m).

Fig. 5. A in Climate change, biodiversity, ticks and tick-borne diseases: The butterfly effect

Fig. 5. A male of the winter tick Haemaphysalis inermis collected in a cold winter day in January 2010 in Basilicata, southern Italy.

Fig. 4 in Climate change, biodiversity, ticks and tick-borne diseases: The butterfly effect

Fig. 4. Shanghai, China: the largest city proper by population in the world. China is the world's largest carbon emitter; it accounted for 29% of global total emissions in 2012 (Olivier et al., 2013).

Fig. 3 in Climate change, biodiversity, ticks and tick-borne diseases: The butterfly effect

Fig. 3. Deforestation of Atlantic rainforest for the establishment of banana tree plantations in Amaraji, north-eastern Brazil.

Fig. 1 in Climate change, biodiversity, ticks and tick-borne diseases: The butterfly effect

Fig. 1. Climate change is contributing to sea level rise. The Boa Viagem beach is a tourist destination in Recife, north-eastern Brazil. If current trends in sea level rise persist, cities like Recife may be literally swallowed the sea in the coming decades.

Fig. 2 in Climate change, biodiversity, ticks and tick-borne diseases: The butterfly effect

Fig. 2. Sloth found on a road that crosses a region of Atlantic rainforest in Aldeia, north-eastern Brazil. Crab-eating foxes (Cerdocyon thous) and other wild animals are commonly seen crossing this road and are frequently victims of car crashes.

opencc-zeroDec 2017View details →

dryad36/100

Data from: Tick-borne disease risk in a forest food web

Changes to the community ecology of hosts for zoonotic pathogens, particularly rodents, are likely to influence the emergence and prevalence of zoonotic diseases worldwide. However, the complex interactions between abiotic factors, pathogens, vectors, hosts, and both food resources and predators of hosts are difficult to disentangle. Here we (1) use 19 years of data from six large field plots in southeastern New York to compare the effects of hypothesized drivers of interannual variation in Lyme disease risk, including the abundance of acorns, rodents, and deer, as well as a series of climate variables; and (2) employ landscape epidemiology to explore how variation in predator community structure and forest cover influences spatial variation in the infection prevalence of ticks for the Lyme disease bacterium, Borrelia burgdorferi, and two other important tick-borne pathogens, Anaplasma phagocytophilum and Babesia microti. Acorn-driven increases in the abundance of mice were correlated with a lagged increase in the abundance of questing nymph-stage Ixodes scapularis ticks infected with Lyme disease bacteria. Abundance of white-tailed deer two years prior also correlated with increased density of infected nymphal ticks, although the effect was weak. Density of rodents in the current year was a strong negative predictor of nymph density, apparently because high current abundance of these hosts can remove nymphs from the host-seeking population. Warm, dry spring or winter weather was associated with reduced density of infected nymphs. At the landscape scale, the presence of functionally diverse predator communities or of bobcats, the only obligate carnivore, was associated with reduced infection prevalence of I. scapularis nymphs with all three zoonotic pathogens. In the case of Lyme disease, infection prevalence increased where coyotes were present but smaller predators were displaced or otherwise absent. For all pathogens, infection prevalence was lowest when forest cover within a 1km radius was high. Taken together, our results suggest that a food web perspective including bottom-up and top-down forcing is needed to understand drivers of tick-borne disease risk, a result that may also apply to other rodent-borne zoonoses. Prevention of exposure based on ecological indicators of heightened risk should help protect public health.

dryad36/100

Data from: Tick-borne disease risk in a forest food web

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publicApr 2019View details →

opencc-zeroDec 2015View details →

Data from: Invasion of two tick-borne diseases across New England: harnessing human surveillance data to capture underlying ecological invasion processes

Modelling the spatial spread of vector-borne zoonotic pathogens maintained in enzootic transmission cycles remains a major challenge. The best available spatio-temporal data on pathogen spread often take the form of human disease surveillance data. By applying a classic ecological approach—occupancy modelling—to an epidemiological question of disease spread, we used surveillance data to examine the latent ecological invasion of tick-borne pathogens. Over the last half-century, previously undescribed tick-borne pathogens including the agents of Lyme disease and human babesiosis have rapidly spread across the northeast United States. Despite their epidemiological importance, the mechanisms of tick-borne pathogen invasion and drivers underlying the distinct invasion trajectories of the co-vectored pathogens remain unresolved. Our approach allowed us to estimate the unobserved ecological processes underlying pathogen spread while accounting for imperfect detection of human cases. Our model predicts that tick-borne diseases spread in a diffusion-like manner with occasional long-distance dispersal and that babesiosis spread exhibits strong dependence on Lyme disease.

opencc-zeroAug 2022View details →

No net effect of host density on tick-borne disease hazard due to opposing roles of vector amplification and pathogen dilution

To better understand vector-borne disease dynamics, knowledge of the ecological interactions between animal hosts, vectors and pathogens is needed. The effects of hosts on disease hazard depends on their role in driving vector abundance and their ability to transmit pathogens. Theoretically, a host that cannot transmit a pathogen could dilute pathogen prevalence but increase disease hazard if it increases vector population size. In the case of Lyme disease, caused by Borrelia burgdorferi s.l. and vectored by Ixodid ticks, deer may have dual opposing effects on vectors and pathogen: deer drive tick population densities but do not transmit B. burgdorferi s.l. and could thus decrease or increase disease hazard. We aimed to test for the role of deer in shaping Lyme disease hazard by using a wide range of deer densities while taking transmission host abundance into account. We predicted that deer increase nymphal tick abundance while reducing pathogen prevalence. The resulting impact of deer on disease hazard will depend on the relative strengths of these opposing effects. We conducted a cross-sectional survey across 24 woodlands in Scotland between 2017 and 2019, estimating host (deer, rodents) abundance, questing Ixodes ricinus nymph density and B. burgdorferi s.l. prevalence at each site. As predicted, deer density was positively associated with nymph density and negatively with nymphal infection prevalence. Overall, these two opposite effects cancelled each other out: Lyme disease hazard did not vary with increasing deer density. This demonstrates that, across a wide range of deer and rodent densities, the role of deer in amplifying tick densities cancels their effect of reducing pathogen prevalence. We demonstrate how non-competent host density has little effect on disease hazard even though they reduce pathogen prevalence, because of their role in increasing vector populations. These results have implications for informing disease mitigation strategies, especially through host management.

opencc-zeroDec 2016View details →

Data from: Interacting effects of wildlife loss and climate on ticks and tick-borne disease

Both large-wildlife loss and climatic changes can independently influence the prevalence and distribution of zoonotic disease. Given growing evidence that wildlife loss often has stronger community-level effects in low-productivity areas, we hypothesized that these perturbations would have interactive effects on disease risk. We experimentally tested this hypothesis by measuring tick abundance and the prevalence of tick-borne pathogens (Coxiella burnetii and Rickettsia spp.) within long-term, size-selective, large-herbivore exclosures replicated across a precipitation gradient in East Africa. Total wildlife exclusion increased total tick abundance by 130% (mesic sites) to 225% (dry, low-productivity sites), demonstrating a significant interaction of defaunation and aridity on tick abundance. When differing degrees of exclusion were tested for a subset of months, total tick abundance increased from 170% (only mega-herbivores excluded) to 360% (all large wildlife excluded). Wildlife exclusion differentially affected the abundance of the three dominant tick species, and this effect varied strongly over time, likely due to differences among species in their host associations, seasonality, and other ecological characteristics. Pathogen prevalence did not differ across wildlife exclusion treatments, rainfall levels, or tick species, suggesting that exposure risk will respond to defaunation and climate change in proportion to total tick abundance. These findings demonstrate interacting effects of defaunation and aridity that increase disease risk, and they highlight the need to incorporate ecological context when predicting effects of wildlife loss on zoonotic disease dynamics.

zenodo32/100

Supplementary materials and data: Climate change in the Arctic: testing the poleward expansion of ticks and tick-borne diseases

This accompanies the article "Climate change in the Arctic: testing the poleward expansion of ticks and tick-borne diseases" that has been accepted for publication in Global Change Biology. The file contains the supplementary materials for the article including the raw microsatellite genotype data and a link to the files containing the serological data and analyses.

opencc-by-4.0Dec 2022View details →

ClinicalTrials.gov32/100

SWEtick - a Prospective Multicenter Study of Tick-borne Diseases in Sweden

ClinicalTrials.gov study NCT06781008. IPD Sharing: YES. Countries: 1. Publications: 9.

controlledIPD-YESFeb 2026View details →

ClinicalTrials.gov32/100

Evaluation and Follow-up of People With Tick-borne Diseases

ClinicalTrials.gov study NCT04318925. IPD Sharing: Not stated. Countries: 1. Publications: 3.

restrictedIPD-UNDECIDEDFeb 2026View details →

publicMay 2016View details →

Data from: Invasion of two tick-borne diseases across New England: harnessing human surveillance data to capture underlying ecological invasion processes

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publicAug 2022View details →

No net effect of host density on tick-borne disease hazard due to opposing roles of vector amplification and pathogen dilution

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publicJul 2017View details →

Data from: Interacting effects of wildlife loss and climate on ticks and tick-borne disease

Open the record for dataset details and reuse information.