scholarly journals Improving Management Strategies of Plant Diseases Using Sequential Sensitivity Analyses

2019 ◽  
Vol 109 (7) ◽  
pp. 1184-1197 ◽  
Author(s):  
Loup Rimbaud ◽  
Sylvie Dallot ◽  
Claude Bruchou ◽  
Sophie Thoyer ◽  
Emmanuel Jacquot ◽  
...  
Keyword(s):  
Net Present Value ◽  
Management Strategies ◽  
Optimal Solution ◽  
Plant Diseases ◽  
Control Measures ◽  
Disease Suppression ◽  
Simultaneous Optimization ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
Plum Pox Virus

Improvement of management strategies of epidemics is often hampered by constraints on experiments at large spatiotemporal scales. A promising approach consists of modeling the biological epidemic process and human interventions, which both impact disease spread. However, few methods enable the simultaneous optimization of the numerous parameters of sophisticated control strategies. To do so, we propose a heuristic approach (i.e., a practical improvement method approximating an optimal solution) based on sequential sensitivity analyses. In addition, we use an economic improvement criterion based on the net present value, accounting for both the cost of the different control measures and the benefit generated by disease suppression. This work is motivated by sharka (caused by Plum pox virus), a vector-borne disease of prunus trees (especially apricot, peach, and plum), the management of which in orchards is mainly based on surveillance and tree removal. We identified the key parameters of a spatiotemporal model simulating sharka spread and control and approximated optimal values for these parameters. The results indicate that the current French management of sharka efficiently controls the disease, but it can be economically improved using alternative strategies that are identified and discussed. The general approach should help policy makers to design sustainable and cost-effective strategies for disease management.

scholarly journals Improving management strategies of plant diseases using sequential sensitivity analyses

2018 ◽  
Author(s):  
Loup Rimbaud ◽  
Sylvie Dallot ◽  
Claude Bruchou ◽  
Sophie Thoyer ◽  
Emmanuel Jacquot ◽  
...  
Keyword(s):  
Net Present Value ◽  
Control Strategies ◽  
Management Strategies ◽  
Optimal Solution ◽  
Plant Diseases ◽  
Control Measures ◽  
Disease Suppression ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
Plum Pox Virus

ABSTRACTImprovement of management strategies of epidemics is often hampered by constraints on experiments at large spatiotemporal scales. A promising approach consists of modelling the biological epidemic process and human interventions, which both impact disease spread. However, few methods enable the simultaneous optimisation of the numerous parameters of sophisticated control strategies. To do so, we propose a heuristic approach (i.e., a practical improvement method approximating an optimal solution) based on sequential sensitivity analyses. In addition, we use an economic improvement criterion, based on the net present value, accounting for both the cost of the different control measures and the benefit generated by disease suppression. This work is motivated by sharka (caused by Plum pox virus), a vector-borne disease of prunus trees (especially apricot, peach and plum) whose management in orchards is mainly based on surveillance and tree removal. We identified the key parameters of a spatiotemporal model simulating sharka spread and control, and approximated optimal values for these parameters. The results indicate that the current French management of sharka efficiently controls the disease, but can be economically improved using alternative strategies that are identified and discussed. The general approach should help policymakers to design sustainable and cost-effective strategies for disease management.

scholarly journals Eco-Epidemiological Uncertainties of Emerging Plant Diseases: The Challenge of Predicting Xylella fastidiosa Dynamics in Novel Environments

2020 ◽  
Vol 110 (11) ◽  
pp. 1740-1750
Author(s):  
Flavia Occhibove ◽  
Daniel S. Chapman ◽  
Alexander J. Mastin ◽  
Stephen S. R. Parnell ◽  
Barbara Agstner ◽  
...  
Keyword(s):  
Environmental Conditions ◽  
Disease Risk ◽  
Xylella Fastidiosa ◽  
Management Strategies ◽  
Plant Diseases ◽  
Disease Spread ◽  
Future Research ◽  
Bacterial Strains ◽  
Novel Environments ◽  
Epidemiological Characteristics

In order to prevent and control the emergence of biosecurity threats such as vector-borne diseases of plants, it is vital to understand drivers of entry, establishment, and spatiotemporal spread, as well as the form, timing, and effectiveness of disease management strategies. An inherent challenge for policy in combatting emerging disease is the uncertainty associated with intervention planning in areas not yet affected, based on models and data from current outbreaks. Following the recent high-profile emergence of the bacterium Xylella fastidiosa in a number of European countries, we review the most pertinent epidemiological uncertainties concerning the dynamics of this bacterium in novel environments. To reduce the considerable ecological and socio-economic impacts of these outbreaks, eco-epidemiological research in a broader range of environmental conditions needs to be conducted and used to inform policy to enhance disease risk assessment, and support successful policy-making decisions. By characterizing infection pathways, we can highlight the uncertainties that surround our knowledge of this disease, drawing attention to how these are amplified when trying to predict and manage outbreaks in currently unaffected locations. To help guide future research and decision-making processes, we invited experts in different fields of plant pathology to identify data to prioritize when developing pest risk assessments. Our analysis revealed that epidemiological uncertainty is mainly driven by the large variety of hosts, vectors, and bacterial strains, leading to a range of different epidemiological characteristics further magnified by novel environmental conditions. These results offer new insights on how eco-epidemiological analyses can enhance understanding of plant disease spread and support management recommendations. [Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

scholarly journals Prospects for Biological Soilborne Disease Control: Application of Indigenous Versus Synthetic Microbiomes

2017 ◽  
Vol 107 (3) ◽  
pp. 256-263 ◽  
Author(s):  
Mark Mazzola ◽  
Shiri Freilich
Keyword(s):  
Disease Control ◽  
Crop Production ◽  
Production Systems ◽  
Agricultural Soils ◽  
Management Strategies ◽  
Plant Diseases ◽  
Disease Suppression ◽  
Rapid Screening ◽  
Soilborne Disease ◽  
Functional Attributes

Biological disease control of soilborne plant diseases has traditionally employed the biopesticide approach whereby single strains or strain mixtures are introduced into production systems through inundative/inoculative release. The approach has significant barriers that have long been recognized, including a generally limited spectrum of target pathogens for any given biocontrol agent and inadequate colonization of the host rhizosphere, which can plague progress in the utilization of this resource in commercial field-based crop production systems. Thus, although potential exists, this model has continued to lag in its application. New omics’ tools have enabled more rapid screening of microbial populations allowing for the identification of strains with multiple functional attributes that may contribute to pathogen suppression. Similarly, these technologies also enable the characterization of consortia in natural systems which provide the framework for construction of synthetic microbiomes for disease control. Harnessing the potential of the microbiome indigenous to agricultural soils for disease suppression through application of specific management strategies has long been a goal of plant pathologists. Although this tactic also possesses limitation, our enhanced understanding of functional attributes of suppressive soil systems through application of community and metagenomic analysis methods provide opportunity to devise effective resource management schemes. As these microbial communities in large part are fostered by the resources endemic to soil and the rhizosphere, substrate mediated recruitment of disease-suppressive microbiomes constitutes a practical means to foster their establishment in crop production systems.

scholarly journals The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Pei-Yu Liu ◽  
Sha He ◽  
Li-Bin Rong ◽  
San-Yi Tang
Keyword(s):  
Media Coverage ◽  
Early Stage ◽  
Guangdong Province ◽  
Individual Behavior ◽  
Control Measures ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
And Control ◽  
Parameter Values ◽  
The Impact

Abstract Background COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn’t stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. Methods We compared Italy’s status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. Results The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. Conclusions Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.

scholarly journals The effect of control measures on COVID-19 transmission in Italy: Comparison with Guangdong province in China

2020 ◽  
Author(s):  
Pei-Yu Liu ◽  
Sha He ◽  
Li-Bin Rong ◽  
San-Yi Tang
Keyword(s):  
Media Coverage ◽  
Early Stage ◽  
Guangdong Province ◽  
Individual Behavior ◽  
Control Measures ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
And Control ◽  
Parameter Values ◽  
The Impact

Abstract Background: COVID-19 has spread all around the world. Italy is one of the worst affected countries in Europe. Although there is a trend of relief, the epidemic situation hasn’t stabilized yet. This study aims to investigate the dynamics of the disease spread in Italy and provide some suggestions on containing the epidemic. Methods: We compared Italy’s status at the outbreak stage and control measures with Guangdong Province in China by data observation and analysis. A modified autonomous SEIR model was used to study the COVID-19 epidemic and transmission potential during the early stage of the outbreak in Italy. We also utilized a time-dependent dynamic model to study the future disease dynamics in Italy. The impact of various non-pharmaceutical control measures on epidemic was investigated through uncertainty and sensitivity analyses. Results: The comparison of specific measures implemented in the two places and the time when the measures were initiated shows that the initial prevention and control actions in Italy were not sufficiently timely and effective. We estimated parameter values based on available cumulative data and calculated the basic reproduction number to be 4.32 before the national lockdown in Italy. Based on the estimated parameter values, we performed numerical simulations to predict the epidemic trend and evaluate the impact of contact limitation, detection and diagnosis, and individual behavior change due to media coverage on the epidemic. Conclusions: Italy was in a severe epidemic status and the control measures were not sufficiently timely and effective in the beginning. Non-pharmaceutical interventions, including contact restrictions and improvement of case recognition, play an important role in containing the COVID-19 epidemic. The effect of individual behavior changes due to media update of the outbreak cannot be ignored. For policy-makers, early and strict blockade measures, fast detection and improving media publicity are key to containing the epidemic.

scholarly journals Mathematical models are a powerful method to understand and control the spread of Huanglongbing

2016 ◽  
Author(s):  
Rachel A Taylor ◽  
Erin Mordecai ◽  
Christopher A Gilligan ◽  
Jason R Rohr ◽  
Leah R Johnson
Keyword(s):  
Data Collection ◽  
Mathematical Models ◽  
Management Strategies ◽  
Intervention Strategy ◽  
Cost Effective ◽  
Plant Diseases ◽  
Disease Spread ◽  
Vector Borne ◽  
Almost All ◽  
And Control

Huanglongbing, or citrus greening, is a global citrus disease occurring in almost all citrus growing regions and causing substantial economic burdens to individual growers, citrus industries and governments. Successful management strategies to reduce disease burden are desperately needed but with so many possible interventions and combinations thereof, it is difficult to know which are worthwhile or cost-effective. We review how mathematical models have yielded useful insights into controlling disease spread for other vector-borne plant diseases, and the small number of mathematical models of Huanglongbing. We adapt a malaria model to Huanglongbing, by including temperature-dependent psyllid traits and economic costs, to show how models can be used to highlight which parameters require more data collection or which should be targeted for intervention. We analyze the most common intervention strategy, insecticide spraying, to determine the most cost-effective spraying strategy. We found that fecundity and feeding rate of the vector require more experimental data collection, for wider temperatures ranges. The best strategy for insecticide intervention was to spray for more days rather than pay extra for a more efficient spray. We conclude that mathematical models are able to provide useful recommendations for managing Huanglongbing spread.

scholarly journals Using sensitivity analysis to identify key factors for the propagation of a plant epidemic

2018 ◽  
Vol 5 (1) ◽  
pp. 171435 ◽  
Author(s):  
Loup Rimbaud ◽  
Claude Bruchou ◽  
Sylvie Dallot ◽  
David R. J. Pleydell ◽  
Emmanuel Jacquot ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Stochastic Model ◽  
Management Strategies ◽  
Sensitivity Analyses ◽  
Plum Pox Virus ◽  
Design Management ◽  
Strong Impact ◽  
Key Factors ◽  
Range Analysis ◽  
The Impact

Identifying the key factors underlying the spread of a disease is an essential but challenging prerequisite to design management strategies. To tackle this issue, we propose an approach based on sensitivity analyses of a spatiotemporal stochastic model simulating the spread of a plant epidemic. This work is motivated by the spread of sharka, caused by plum pox virus , in a real landscape. We first carried out a broad-range sensitivity analysis, ignoring any prior information on six epidemiological parameters, to assess their intrinsic influence on model behaviour. A second analysis benefited from the available knowledge on sharka epidemiology and was thus restricted to more realistic values. The broad-range analysis revealed that the mean duration of the latent period is the most influential parameter of the model, whereas the sharka-specific analysis uncovered the strong impact of the connectivity of the first infected orchard. In addition to demonstrating the interest of sensitivity analyses for a stochastic model, this study highlights the impact of variation ranges of target parameters on the outcome of a sensitivity analysis. With regard to sharka management, our results suggest that sharka surveillance may benefit from paying closer attention to highly connected patches whose infection could trigger serious epidemics.

Selection of genetically diverse Trichoderma spp. isolates for suppression of Phytophthora capsici on bell pepper

2010 ◽  
Vol 56 (10) ◽  
pp. 864-873 ◽  
Author(s):  
Daniel P. Roberts ◽  
Jude E. Maul ◽  
Laurie F. McKenna ◽  
Sarah E. Emche ◽  
Susan L.F. Meyer ◽  
...  
Keyword(s):  
Phytophthora Capsici ◽  
Management Strategies ◽  
Bell Pepper ◽  
Control Measures ◽  
Disease Suppression ◽  
Significant Suppression ◽  
Trichoderma Spp ◽  
Rdna Cluster ◽  
Its1 Region ◽  
Significant Disease

Environmentally compatible control measures are needed for suppression of Phytophthora capsici on pepper. Twenty-three isolates of Trichoderma were screened for suppression of a mixture of 4 genetically distinct isolates of this pathogen on bell pepper ( Capsicum anuum ) in greenhouse pot assays. Of these 23 isolates, GL12, GL13, and Th23 provided significant suppression of P. capsici in at least 2 assays. These isolates were then compared with Trichoderma virens isolates GL3 and GL21 for suppression of this disease in the presence and absence of the harpin-based natural product Messenger. Isolates GL3 and Th23 provided significant disease suppression (P ≤ 0.05) in 3 of 4 assays, while GL12, GL13, and GL21 provided significant suppression in 2 of 4 assays. There was no apparent benefit from the application of Messenger. Phylogenetic analysis of these 5 isolates (based on the ITS1 region of the nuclear rDNA cluster and tef1), and an additional 9 isolates that suppressed P. capsici in at least 1 assay, separated isolates into 2 clades, with 1 clade containing GL3, GL12, GL13, and GL21. There were also 2 more distantly related isolates, one of which was Th23. We report here the identification of genetically distinct Trichoderma isolates for potential use in disease management strategies employing isolate combinations directed at suppression of P. capsici on pepper.

scholarly journals Mathematical models are a powerful method to understand and control the spread of Huanglongbing

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2642 ◽  
Author(s):  
Rachel A. Taylor ◽  
Erin A. Mordecai ◽  
Christopher A. Gilligan ◽  
Jason R. Rohr ◽  
Leah R. Johnson
Keyword(s):  
Data Collection ◽  
Mathematical Models ◽  
Management Strategies ◽  
Intervention Strategy ◽  
Cost Effective ◽  
Plant Diseases ◽  
Disease Spread ◽  
Vector Borne ◽  
Almost All ◽  
And Control

Huanglongbing (HLB), or citrus greening, is a global citrus disease occurring in almost all citrus growing regions. It causes substantial economic burdens to individual growers, citrus industries and governments. Successful management strategies to reduce disease burden are desperately needed but with so many possible interventions and combinations thereof it is difficult to know which are worthwhile or cost-effective. We review how mathematical models have yielded useful insights into controlling disease spread for other vector-borne plant diseases, and the small number of mathematical models of HLB. We adapt a malaria model to HLB, by including temperature-dependent psyllid traits, “flushing” of trees, and economic costs, to show how models can be used to highlight the parameters that require more data collection or that should be targeted for intervention. We analyze the most common intervention strategy, insecticide spraying, to determine the most cost-effective spraying strategy. We find that fecundity and feeding rate of the vector require more experimental data collection, for wider temperatures ranges. Also, the best strategy for insecticide intervention is to spray for more days rather than pay extra for a more efficient spray. We conclude that mathematical models are able to provide useful recommendations for managing HLB spread.

scholarly journals Analyzing the Influence of Landscape Aggregation on Disease Spread to Improve Management Strategies

2019 ◽  
Vol 109 (7) ◽  
pp. 1198-1207 ◽  
Author(s):  
Coralie Picard ◽  
Samuel Soubeyrand ◽  
Emmanuel Jacquot ◽  
Gaël Thébaud
Keyword(s):  
Large Scale ◽  
Management Strategies ◽  
Disease Spread ◽  
Sensitivity Analyses ◽  
Epidemiological Models ◽  
Landscape Characteristics ◽  
Epidemic Dynamics ◽  
Economic Output ◽  
The Impact ◽  
Practical Implications

Epidemiological models are increasingly used to predict epidemics and improve management strategies. However, they rarely consider landscape characteristics although such characteristics can influence the epidemic dynamics and, thus, the effectiveness of disease management strategies. Here, we present a generic in silico approach which assesses the influence of landscape aggregation on the costs associated with an epidemic and on improved management strategies. We apply this approach to sharka, one of the most damaging diseases of Prunus trees, for which a management strategy is already applied in France. Epidemic simulations were carried out with a spatiotemporal stochastic model under various management strategies in landscapes differing in patch aggregation. Using sensitivity analyses, we highlight the impact of management parameters on the economic output of the model. We also show that the sensitivity analysis can be exploited to identify several strategies that are, according to the model, more profitable than the current French strategy. Some of these strategies are specific to a given aggregation level, which shows that management strategies should generally be tailored to each specific landscape. However, we also identified a strategy that is efficient for all levels of landscape aggregation. This one-size-fits-all strategy has important practical implications because of its simple applicability at a large scale.

Sign in / Sign up

Export Citation Format

Share Document