Vector-borne diseases with nonstationary vector populations: The case of growing and decaying populations

Giménez-Romero, Àlex; Rosa, Flaquer-Galmés,; Matías, Manuel A.

doi:10.1103/physreve.106.054402

Cited by 3 publications

(9 citation statements)

References 31 publications

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“…Due to the non-stationarity of the vector dynamics, R 0 in the model cannot be computed with standard methods such as the Next Generation Matrix (Diekmann et al 2010). To circumvent this problem, we applied an approximate method to compute it as previously proposed by (Giménez-Romero et al 2022). We show that this approximate R 0 correctly characterizes the epidemic, further validating the method proposed by Giménez-Romero et al 2022.…”

Section: Discussionmentioning

confidence: 99%

“…To circumvent this problem, we applied an approximate method to compute it as previously proposed by (Giménez-Romero et al 2022). We show that this approximate R 0 correctly characterizes the epidemic, further validating the method proposed by Giménez-Romero et al 2022.…”

Section: Discussionmentioning

confidence: 99%

“…Because the compartments of our model are not in one-to-one correspondence with those shown in the work of White et al (White et al 2020), we used the sum of the symptomatic and desiccated infected trees in the dataset ( I S + I D ) to fit the sum of the infected and dead trees ( I + R ) and the sum of susceptible and asymptomatic hosts ( S + I A ) to fit the sum of susceptible and exposed hosts ( S + E ). The processed data used to fit the model can be found in (Giménez-Romero 2022), while the raw data can be found in the supplementary data accessible online of the cited articles (Moralejo et al 2020; White et al 2020).…”

Section: Methodsmentioning

confidence: 99%

“…The parameters of our compartmental model were determined by fitting the model to data by means of a Bayesian Inference framework using the Turing.jl package (Ge et al 2018) in Julia (Bezanson et al 2017). The scripts used to fit the model can be found in (Giménez-Romero 2022).…”

Section: Methodsmentioning

confidence: 99%

“…(2) is that the pre-pandemic fixed point given by I H = I v = 0 and S H = S H (0) is not a fixed point of the system of differential equations, because vector population decays, so that the standard methods to compute R 0 such as the Next Generation Matrix (Diekmann et al 2010; Giménez-Romero et al 2022) do not apply. In (Giménez-Romero et al 2022) a method was suggested to determine the basic reproductive number in the case of compartmental models of vector-borne transmitted diseases in which the vector population grows or decays. It consists in averaging the instantaneous basic reproductive number over the time of a generation. To proceed we consider that I H = I v = 0, S H = S H (0) is indeed a fixed point of the system.…”

Section: Vector Population Dynamicsmentioning

confidence: 99%

See 4 more Smart Citations

A compartmental model forXylella fastidiosadiseases with explicit vector seasonal dynamics

Giménez-Romero

Moralejo²,

Matías

2022

Preprint

Self Cite

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The bacterium Xylella fastidiosa (Xf) is mainly transmitted by the spittlebug, Philaenus spumarius, in Europe, where it has caused significant economic damage to olive and almond trees. Understanding the factors that determine disease dynamics in pathosystems that share similarities can help design control strategies focused on minimizing transmission chains. Here we introduce a compartmental model for Xf-caused diseases in Europe that accounts for the main relevant epidemiological processes, including the seasonal dynamics of P. spumarius. The model was confronted with epidemiological data from the two major outbreaks of Xf in Europe, the olive quick disease syndrome (OQDS) in Apulia, Italy, caused by the subspecies pauca, and the almond leaf scorch disease (ALSD) in Majorca, Spain, caused by subspecies multiplex and fastidiosa. Using a Bayesian inference framework, we show how the model successfully reproduces the general field data in both diseases. In a global sensitivity analysis, the vector-plant and plant-vector transmission rates, together with the vector removal rate, were the most influential parameters in determining the time of the infected host population peak, the incidence peak and the final number of dead hosts. We also used our model to check different vector-based control strategies, showing that a joint strategy focused on increasing the rate of vector removal while lowering the number of annual newborn vectors is optimal for disease control.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Vector Population Dynamicsmentioning

confidence: 99%

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A compartmental model forXylella fastidiosadiseases with explicit vector seasonal dynamics

Giménez-Romero

Moralejo²,

Matías

2022

Preprint

Self Cite

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Global warming significantly increases the risk of Pierce’s disease epidemics in European vineyards

Giménez-Romero,

Iturbide,

Moralejo

et al. 2024

Sci Rep

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Pierce’s disease (PD) is a vector-borne disease caused by the bacteria Xylella fastidiosa, which affects grapevines in the Americas. Currently, vineyards in continental Europe, the world’s largest producer of quality wine, have not yet been affected by PD. However, climate change may alter this situation. Here we incorporate the latest regional climate change projections into a climate-driven epidemiological model to assess the risk of PD epidemics in Europe for different levels of global warming. We found a significant increase in risk above $$+\,2\,^{\circ }\hbox {C}$$ + 2 ∘ C in the main wine-producing regions of France, Italy and Portugal, in addition to a critical tipping point above $$+\,3\,^{\circ }\hbox {C}$$ + 3 ∘ C for the possible spread of PD beyond the Mediterranean. The model identifies decreasing risk trends in Spain, as well as contrasting patterns across the continent with different velocities of risk change and epidemic growth rates. Although there is some uncertainty in model projections over time, spatial patterns of risk are consistent across different climate models. Our study provides a comprehensive analysis of the future of PD at multiple spatial scales (country, Protected Designation of Origin and vineyard), revealing where, why and when PD could become a new threat to the European wine industry.

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A Compartmental Model for Xylella fastidiosa Diseases with Explicit Vector Seasonal Dynamics

Giménez-Romero

Moralejo²,

Matías³

2023

Phytopathology®

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The bacterium Xylella fastidiosa (Xf) is mainly transmitted by the meadow spittlebug Philaenus spumarius in Europe, where it has caused significant economic damage to olive and almond trees. Understanding the factors that determine disease dynamics in pathosystems that share similarities can help to design control strategies focused on minimizing transmission chains. Here we introduce a compartmental model for Xf-caused diseases in Europe that accounts for the main relevant epidemiological processes, including the seasonal dynamics of P. spumarius. The model was confronted with epidemiological data from the two major outbreaks of Xf in Europe, the olive quick disease syndrome (OQDS) in Apulia, Italy, caused by the subspecies pauca, and the almond leaf scorch disease (ALSD) in Mallorca, Spain, caused by subspecies multiplex and fastidiosa. Using a Bayesian inference framework, we show how the model successfully reproduces the general field data in both diseases. In a global sensitivity analysis, the vector-plant and plant-vector transmission rates, together with the vector removal rate, were the most influential parameters in determining the time of the infectious host population peak, the incidence peak and the final number of dead hosts. We also used our model to check different vector-based control strategies, showing that a joint strategy focused on increasing the rate of vector removal while lowering the number of annual newborn vectors is optimal for disease control.

show abstract

Vector-borne diseases with nonstationary vector populations: The case of growing and decaying populations

Cited by 3 publications

References 31 publications

A compartmental model forXylella fastidiosadiseases with explicit vector seasonal dynamics

A compartmental model forXylella fastidiosadiseases with explicit vector seasonal dynamics

Global warming significantly increases the risk of Pierce’s disease epidemics in European vineyards

A Compartmental Model for Xylella fastidiosa Diseases with Explicit Vector Seasonal Dynamics

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