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 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 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 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 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 Spatial dynamics and genetics of infectious diseases on heterogeneous landscapes

2007 ◽  
Vol 4 (16) ◽  
pp. 935-948 ◽  
Author(s):  
Leslie A Real ◽  
Roman Biek
Keyword(s):  
Infectious Disease ◽  
Spatial Genetic Structure ◽  
Management Strategies ◽  
Spatial Dynamics ◽  
Disease Process ◽  
Disease Spread ◽  
Host Pathogen Interactions ◽  
Host Pathogen ◽  
Control And Management ◽  
And Control

Explicit spatial analysis of infectious disease processes recognizes that host–pathogen interactions occur in specific locations at specific times and that often the nature, direction, intensity and outcome of these interactions depend upon the particular location and identity of both host and pathogen. Spatial context and geographical landscape contribute to the probability of initial disease establishment, direction and velocity of disease spread, the genetic organization of resistance and susceptibility, and the design of appropriate control and management strategies. In this paper, we review the manner in which the physical organization of the landscape has been shown to influence the population dynamics and spatial genetic structure of host–pathogen interactions, and how we might incorporate landscape architecture into spatially explicit population models of the infectious disease process to increase our ability to predict patterns of disease occurrence and optimally design vaccination and control policies.

scholarly journals COVIDentistry Combating Corona Virus Spread in Dental Setup Indian Prospective

2021 ◽  
Vol 6 (1) ◽  
pp. 94-106
Author(s):  
Amit Bhandari ◽  
Vanshika Jain ◽  
Rashi Bhandari
Keyword(s):  
Viral Particle ◽  
World Health ◽  
Disease Spread ◽  
Health Crisis ◽  
Potential Source ◽  
Dental Procedures ◽  
Droplet Production ◽  
Risk Of Disease ◽  
Almost All ◽  
And Control

Making its first presence in humans in China in late 2019, SARS-CoV-2 has been identified as a highly contagious viral particle causing distress of lower respiratory system, named COVID-19. Since January 2020, there has been a worldwide increase in the number of COVID-19 cases and associated deaths. Owing to the contagious nature of the disease and socializing human culture, the disease has spanned over continents resulting in some countries being more severely affected than others. Since the first knowledge of the disease, interim guidelines have been constantly issued by competent authorities to safeguard the interest of masses and healthcare professionals. As and when new details are procured, these guidelines are adequately modified and circulated. As a standard measure, all individuals are expected to maintain social distancing, cover their face with a mask during any outdoor activity and practice hand hygiene and cough etiquettes. Respiratory droplet spread is the most potential source identified for this uncontrolled disease spread. Being of smaller size, aerosols produced during medical treatment too act a potential source of viral particle dissemination. Almost all dental procedures involve production of aerosols in some form or the other, irrespective of the kind of instrumentation used. Additionally, proximity to the oral cavity, one of the sources of droplet production, poses a high risk of disease contraction by dental healthcare workers and visiting patients. With consideration to dental practice, various guidelines have been issued to minimise and control the spread of COVID-19. This article is written with an aim of reviewing these guidelines and sensitizing and encouraging the dental fraternity to follow them and contribute in the current world health crisis.

Incorporating Vector Ecology and Life History into Disease Transmission Models: Insights from Tsetse (Glossina spp.)

2020 ◽  
pp. 175-188
Author(s):  
Sinead English ◽  
Antoine M.G. Barreaux ◽  
Michael B. Bonsall ◽  
John W. Hargrove ◽  
Matt J. Keeling ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Laboratory Data ◽  
Maternal Investment ◽  
Disease Spread ◽  
Vector Ecology ◽  
Vector Borne Diseases ◽  
Extensive Field ◽  
Survival And Reproduction ◽  
Vector Borne ◽  
And Control

Accurate models are crucial for predicting the spread of vector-borne diseases, and for developing appropriate control policies. Simple models often ignore finer details of vector biology, commonly due to lack of pertinent field data. However, for tsetse (Glossina spp), vectors of the parasites causing debilitating human and livestock trypanosomiasis in Africa, extensive field and laboratory data facilitate improved models and predictions of vector control outcomes. We review studies on the effects of environmental temperature, and fly age and sex, on survival and reproduction in tsetse, savannah species particularly–emphasizing the extreme maternal investment and sensitivity of early life stages to high temperatures. We consider implications of these results for predictive models of tsetse populations, and of the transmission and control of African trypanosomiasis. We discuss how further research on vectors, and improved models of vector populations and disease dynamics, can lead to improved predictions of vector abundance and disease spread.

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.

Bacteriophages to control plant diseases

2021 ◽  
pp. 473-506
Author(s):  
Manoj Choudhary ◽  
◽  
Mathews Paret ◽  
Aleksa Obradović ◽  
Katarina Gašić ◽  
...  
Keyword(s):  
Plant Pathogens ◽  
Uv Light ◽  
Control Measure ◽  
Management Strategies ◽  
Control Plant ◽  
Plant Diseases ◽  
Bacterial Diseases ◽  
Time Of Application ◽  
Development Of Resistance ◽  
And Control

Crop yield loss due to bacterial plant pathogens need to be reduced to increase global food production demand. Currently available disease management strategies involving copper-based bactericides and antibiotics are losing efficacy due to development of resistance in bacteria. There is long familiar demand of environmentally friendly and sustainable strategies to control bacterial diseases. Bacteriophages are virus that kill target bacteria without affecting another microorganism and environment. Bacteriophage efficiency on phyllosphere is mainly affected by ultraviolet (UV) light. Use of combination of phage, mixture with phage carrier bacteria and optimizing time of application helps in persistence of bacteriophage. There are several bacteriophage products already available in the market to control destructive bacterial diseases. Unlike chemical based traditional control measure, bacteriophage mixture can be easily amended to reduce resistance development in bacteria. In this chapter, the authors discuss from phage isolation to interaction with bacteria and control mechanism of plant diseases.

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