Simulation of climate–host–parasite–landscape interactions: A spatially explicit model for ticks (Acari: Ixodidae)

Wang, Hsiao‐Hsuan; Grant, William E.; Teel, Pete D.

doi:10.1016/j.ecolmodel.2012.06.007

Cited by 35 publications

(43 citation statements)

References 76 publications

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“…infected [16][17][18][19][20] and spatial [21,22] dynamics of disease risk, with multi-disciplinary data based on the literature, empirical evidence, earth observation and model predictions. It was developed using an agent-based approach that consisted of three generalized grid layers (tick population, host population and landscape) and a range of transition rules describing their interactions under the influence of temperature.…”

Section: Discussionmentioning

confidence: 99%

“…Durations of feeding are assumed to be less than one week for larvae, and one week for nymphs and adults. We also assume that questing activity and interstadial development are sensitive to temperature, while feeding success is assumed to be dependent on the density of hosts [16][17][18][19][20].…”

Section: Tick Population Layermentioning

confidence: 99%

“…Existing mechanistic models for studying the effects of temperature on Lyme disease risk are increasing in number (e.g. [16][17][18][19][20]). However, existing models do not incorporate spatial heterogeneity or focus on issues related only to the dynamics of vector populations, ignoring key components, such as host/pathogen distribution and habitat suitability, which in reality are distributed unevenly and can change rapidly over time.…”

Section: Introductionmentioning

confidence: 99%

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Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland

Gilbert

Harrison

et al. 2016

J. R. Soc. Interface.

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Lyme disease is the most prevalent vector-borne disease in the temperate Northern Hemisphere. The abundance of infected nymphal ticks is commonly used as a Lyme disease risk indicator. Temperature can influence the dynamics of disease by shaping the activity and development of ticks and, hence, altering the contact pattern and pathogen transmission between ticks and their host animals. A mechanistic, agent-based model was developed to study the temperature-driven seasonality of Ixodes ricinus ticks and transmission of Borrelia burgdorferi sensu lato across mainland Scotland. Based on 12-year averaged temperature surfaces, our model predicted that Lyme disease risk currently peaks in autumn, approximately six weeks after the temperature peak. The risk was predicted to decrease with increasing altitude. Increases in temperature were predicted to prolong the duration of the tick questing season and expand the risk area to higher altitudinal and latitudinal regions. These predicted impacts on tick population ecology may be expected to lead to greater tick-host contacts under climate warming and, hence, greater risks of pathogen transmission. The model is useful in improving understanding of the spatial determinants and system mechanisms of Lyme disease pathogen transmission and its sensitivity to temperature changes.

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Section: Discussionmentioning

confidence: 99%

Section: Tick Population Layermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland

Gilbert

Harrison

et al. 2016

J. R. Soc. Interface.

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“…We developed a spatially‐explicit, individual‐based model representing climate‐tick‐host‐landscape interactions to examine how shifts in the seasonal occurrence of fluctuations of host densities could affect tick densities through restructuring a model we initially developed in 2012 (Wang et al As a case study, we focused on the population dynamics of lone star ticks ( Amblyomma americanum (L.)) under ecological conditions typical of the south‐central United States. More specifically, we parameterized the model to represent densities of lone star ticks and mammalian hosts, as well as climatic conditions, representative of a typical forested landscape near Houston, TX, U.S.A. We then simulated system dynamics under various assumptions regarding the seasonal occurrence of periods of high and periods of low host densities, noting the effect on tick densities.…”

Section: Introductionmentioning

confidence: 99%

Simulation of climate-tick-host-landscape interactions: Effects of shifts in the seasonality of host population fluctuations on tick densities

Wang

Grant

Teel

et al. 2015

Journal of Vector Ecology

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Tick vector systems are comprised of complex climate-tick-host-landscape interactions that are difficult to identify and estimate from empirical observations alone. We developed a spatially-explicit, individual-based model, parameterized to represent ecological conditions typical of the south-central United States, to examine effects of shifts in the seasonal occurrence of fluctuations of host densities on tick densities. Simulated shifts in the seasonal occurrence of periods of high and low host densities affected both the magnitude of unfed tick densities and the seasonality of tick development. When shifting the seasonal densities of all size classes of hosts (small, medium, and large) synchronously, densities of nymphs were affected more by smaller shifts away from the baseline host seasonality than were densities of larval and adult life stages. When shifting the seasonal densities of only a single size-class of hosts while holding other size classes at their baseline levels, densities of larval, nymph, and adult life stages responded differently. Shifting seasonal densities of any single host-class earlier resulted in a greater increase in adult tick density than when seasonal densities of all host classes were shifted earlier simultaneously. The mean densities of tick life stages associated with shifts in host densities resulted from system-level interactions of host availability with tick phenology. For example, shifting the seasonality of all hosts ten weeks earlier resulted in an approximately 30% increase in the relative degree of temporal co-occurrence of actively host-seeking ticks and hosts compared to baseline, whereas shifting the seasonality of all hosts ten weeks later resulted in an approximately 70% decrease compared to baseline. Differences among scenarios in the overall presence of active host-seeking ticks in the system were due primarily to the degree of co-occurrence of periods of high densities of unfed ticks and periods of high densities of hosts. Journal of Vector Ecology 40 (2): 247-255. 2015.

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“…Previous research efforts investigated population dynamics, parasite-host interactions, seasonal fluctuations, and physiological response to climate factors [19-27]. These studies added to a growing body of work that has elucidated many important variables in this complex ecological system.…”

Section: Introductionmentioning

confidence: 99%

Invasive potential of cattle fever ticks in the southern United States

et al. 2014

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Abstract'BackgroundFor >100 years cattle production in the southern United States has been threatened by cattle fever. It is caused by an invasive parasite-vector complex that includes the protozoan hemoparasites Babesia bovis and B. bigemina, which are transmitted among domestic cattle via Rhipicephalus tick vectors of the subgenus Boophilus. In 1906 an eradication effort was started and by 1943 Boophilus ticks had been confined to a narrow tick eradication quarantine area (TEQA) along the Texas-Mexico border. However, a dramatic increase in tick infestations in areas outside the TEQA over the last decade suggests these tick vectors may be poised to re-invade the southern United States. We investigated historical and potential future distributions of climatic habitats of cattle fever ticks to assess the potential for a range expansion.MethodsWe built robust spatial predictions of habitat suitability for the vector species Rhipicephalus (Boophilus) microplus and R. (B.) annulatus across the southern United States for three time periods: 1906, present day (2012), and 2050. We used analysis of molecular variance (AMOVA) to identify persistent tick occurrences and analysis of bias in the climate proximate to these occurrences to identify key environmental parameters associated with the ecology of both species. We then used ecological niche modeling algorithms GARP and Maxent to construct models that related known occurrences of ticks in the TEQA during 2001–2011 with geospatial data layers that summarized important climate parameters at all three time periods.ResultsWe identified persistent tick infestations and specific climate parameters that appear to be drivers of ecological niches of the two tick species. Spatial models projected onto climate data representative of climate in 1906 reproduced historical pre-eradication tick distributions. Present-day predictions, although constrained to areas near the TEQA, extrapolated well onto climate projections for 2050.ConclusionsOur models indicate the potential for range expansion of climate suitable for survival of R. microplus and R. annulatus in the southern United States by mid-century, which increases the risk of reintroduction of these ticks and cattle tick fever into major cattle producing areas.

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Simulation of climate–host–parasite–landscape interactions: A spatially explicit model for ticks (Acari: Ixodidae)

Cited by 35 publications

References 76 publications

Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland

Modelling the seasonality of Lyme disease risk and the potential impacts of a warming climate within the heterogeneous landscapes of Scotland

Simulation of climate-tick-host-landscape interactions: Effects of shifts in the seasonality of host population fluctuations on tick densities

Invasive potential of cattle fever ticks in the southern United States

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