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

Wu, Xiaotian; Duvvuri, Venkata R.; Lou, Yijun; Ogden, Nicholas H.; Pelcat, Yann; Wu, Jianhong

doi:10.1016/j.jtbi.2012.11.014

Cited by 72 publications

(75 citation statements)

References 38 publications

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“…A periodic ordinary differential equation model developed by Wu et al simulates the development of ticks by using twelve differential equations to describe the proportion of ticks growing from one developmental stage to the next [28]. Each equation of the system represents the change in number over time of a specific stage of the whole tick life cycle (egg-laying adult females, eggs, hardening larvae, questing larvae, feeding larvae, engorged larvae, questing nymphs, feeding nymphs, engorged nymphs, questing adults, feeding adult females and engorged adult females) as shown in Equation (2).…”

Section: Tick Population Modelingmentioning

confidence: 99%

“…Each equation of the system represents the change in number over time of a specific stage of the whole tick life cycle (egg-laying adult females, eggs, hardening larvae, questing larvae, feeding larvae, engorged larvae, questing nymphs, feeding nymphs, engorged nymphs, questing adults, feeding adult females and engorged adult females) as shown in Equation (2). Each d i (t) (i = 1, 2,...,12) has a temperature-dependent component and a non-temperature-dependent component, both of which are derived from field data [28]. The latter is life stage-specific and includes factors such as mortality, number of hosts, and rate of attachment to host.…”

Section: Tick Population Modelingmentioning

confidence: 99%

“…For this study, temperature data was extracted from MODIS product MOD11C3. All other parameters were obtained from [28].…”

Section: Tick Population Modelingmentioning

confidence: 99%

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Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling

et al. 2017

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Abstract:The number of Lyme disease cases (Lyme borreliosis) in Ontario, Canada has increased over the last decade, and that figure is projected to continue to increase. The northern limit of Lyme disease cases has also been progressing northward from the northeastern United States into southeastern Ontario. Several factors such as climate change, changes in host abundance, host and vector migration, or possibly a combination of these factors likely contribute to the emergence of Lyme disease cases in eastern Ontario. This study first determined areas of warming using time series remotely sensed temperature data within Ontario, then analyzed possible spatial-temporal changes in Lyme disease risk in eastern Ontario from 2000 to 2013 due to climate change using tick population modeling. The outputs of the model were validated by using tick surveillance data from 2002 to 2012. Our results indicated areas in Ontario where Lyme disease risk changed from unsustainable to sustainable for sustaining Ixodes scapularis (black-legged tick) populations. This study provides evidence that climate change has facilitated the northward expansion of black-legged tick populations' geographic range over the past decade. The results demonstrate that remote sensing data can be used to increase the spatial detail for Lyme disease risk mapping and provide risk maps for better awareness of possible Lyme disease cases. Further studies are required to determine the contribution of host migration and abundance on changes in eastern Ontario's Lyme disease risk.

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Section: Tick Population Modelingmentioning

confidence: 99%

Section: Tick Population Modelingmentioning

confidence: 99%

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Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling

et al. 2017

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“…A good starting point would be to consider the case where the tick population model exhibits convergence to equilibria without diapause, and exhibits convergence to periodic solutions when all populations have to go through the diapause to reach the maturity. Annual periodic cycles of tick population dynamics have been frequently observed in the fields and theoretically confirmed in the model study 22 where a system of ordinary differential equations is used and where periodic coefficients are assumed to represent the seasonal variation of tick ecological activities including questing, feeding, development, reproduction and mortality. These annual cycles have also been established in the work, 23 using a system of delay differential equations with both periodic delays (for development times) and periodic coefficients.…”

Section: Discussionmentioning

confidence: 72%

Critical Contact Rate for Vector–host–pathogen Oscillation Involving Co-Feeding and Diapause

Zhang

2017

J. Biol. Syst.

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We consider the dynamic vector-host-pathogen interaction motivated by tick-borne diseases such as tick-borne encephalitis and Lyme disease. We stratify the vector population in terms of the stage before and after the vector's contact with hosts when co-feeding transmission may take place, and we also consider the case where vector development may involve two time lags due to normal development and diapause. We derive threshold conditions for disease persistence and for nonlinear oscillations in the vector population and in the diseased vector and host populations. Our objective here is to use a simple mechanistic dynamic model to show that diapause and co-feeding transmission may generate periodic and irregular oscillations even when seasonal variations of the environmental conditions are ignored. These oscillations are not necessary in synchrony with the seasonality of vector development, and hence complicated oscillatory patterns of vectorborne disease dynamics in the field and surveillance observations should be expected.

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“…However, in this way, R 0 is monotonically decreasing with respect to θ, and it contradicts with what we have observed from Figure 3.5. The precise concept of R 0 in seasonal environment is more complicated as it should be defined as the spectral radius of a suitable operator [5,70,75]. Here, we use a recently developed general approach [70] to compute R 0 .…”

Section: Model Descriptionmentioning

confidence: 99%

Malaria dynamics with long latent period in hosts

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

Cited by 72 publications

References 38 publications

Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling

Analyzing the Potential Risk of Climate Change on Lyme Disease in Eastern Ontario, Canada Using Time Series Remotely Sensed Temperature Data and Tick Population Modelling

Critical Contact Rate for Vector–host–pathogen Oscillation Involving Co-Feeding and Diapause

Malaria dynamics with long latent period in hosts

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