150 results on '"Gilligan CA"'
Search Results
2. Spatial heterogeneity, nonlinear dynamics and chaos in infectious diseases
- Author
-
Grenfell, BT, primary, Kleczkowski, A., additional, Gilligan, CA, additional, and Bolker, BM, additional
- Published
- 1995
- Full Text
- View/download PDF
3. Optimising control of disease spread of on networks
- Author
-
Bartlomiej Dybiec, Kleczkowski, A., and Gilligan, Ca
4. Host Growth Can Cause Invasive Spread of Crops by Soilborne Pathogens
- Author
-
Leclerc, M, Doré, T, Gilligan, CA, Lucas, P, and Filipe, JAN
- Subjects
2. Zero hunger ,Crops, Agricultural ,fungi ,Population Dynamics ,food and beverages ,15. Life on land ,Models, Biological ,Plant Roots ,Rhizoctonia ,13. Climate action ,Host-Pathogen Interactions ,Computer Simulation ,Soil Microbiology ,Plant Diseases - Abstract
Invasive soilborne plant pathogens cause substantial damage to crops and natural populations, but our understanding of how to prevent their epidemics or reduce their damage is limited. A key and experimentally-tested concept in the epidemiology of soilborne plant diseases is that of a threshold spacing between hosts below which epidemics (invasive spread) can occur. We extend this paradigm by examining how plant-root growth may alter the conditions for occurrence of soilborne pathogen epidemics in plant populations. We hypothesise that host-root growth can 1) increase the probability of pathogen transmission between neighbouring plants and, consequently, 2) decrease the threshold spacing for epidemics to occur. We predict that, in systems initially below their threshold conditions, root growth can trigger soilborne pathogen epidemics through a switch from non-invasive to invasive behaviour, while in systems above threshold conditions root growth can enhance epidemic development. As an example pathosystem, we studied the fungus Rhizoctonia solani on sugar beet in field experiments. To address hypothesis 1, we recorded infections within inoculum-donor and host-recipient pairs of plants with differing spacing. We translated these observations into the individual-level concept of pathozone, a host-centred form of dispersal kernel. To test hypothesis 2 and our prediction, we used the pathozone to parameterise a stochastic model of pathogen spread in a host population, contrasting scenarios of spread with and without host growth. Our results support our hypotheses and prediction. We suggest that practitioners of agriculture and arboriculture account for root system expansion in order to reduce the risk of soilborne-disease epidemics. We discuss changes in crop design, including increasing plant spacing and using crop mixtures, for boosting crop resilience to invasion and damage by soilborne pathogens. We speculate that the disease-induced root growth observed in some pathosystems could be a pathogen strategy to increase its population through host manipulation. © 2013 Leclerc et al.
5. Economic and social factors in designing disease control strategies for epidemics on networks
- Author
-
Adam Kleczkowski, Dybiec, B., and Gilligan, Ca
- Subjects
Physics - Physics and Society ,Statistical Mechanics (cond-mat.stat-mech) ,FOS: Physical sciences ,Physics and Society (physics.soc-ph) ,Computational Physics (physics.comp-ph) ,Physics - Computational Physics ,Condensed Matter - Statistical Mechanics - Abstract
Models for control of epidemics on local, global and small-world networks are considered, with only partial information accessible about the status of individuals and their connections. The main goal of an effective control measure is to stop the epidemic at a lowest possible cost, including treatment and cost necessary to track the disease spread. We show that delay in detection of infectious individuals and presence of long-range links are the most important factors determining the cost. However, the details of long-range links are usually the least-known element of the social interactions due to their occasional character and potentially short life-span. We show that under some conditions on the probability of disease spread, it is advisable to attempt to track those links. Thus, collecting some additional knowledge about the network structure might be beneficial to ensure a successful and cost-effective control., Comment: To be published in Acta Phys. Pol. B
6. Estimating the delay between host infection and disease (incubation period) and assessing its significance to the epidemiology of plant diseases
- Author
-
Leclerc, M, Doré, T, Gilligan, CA, Lucas, P, and Filipe, JAN
- Subjects
2. Zero hunger ,Host-Pathogen Interactions ,15. Life on land ,Models, Theoretical ,Epidemics ,Algorithms ,3. Good health ,Infectious Disease Incubation Period ,Plant Diseases - Abstract
Knowledge of the incubation period of infectious diseases (time between host infection and expression of disease symptoms) is crucial to our epidemiological understanding and the design of appropriate prevention and control policies. Plant diseases cause substantial damage to agricultural and arboricultural systems, but there is still very little information about how the incubation period varies within host populations. In this paper, we focus on the incubation period of soilborne plant pathogens, which are difficult to detect as they spread and infect the hosts underground and above-ground symptoms occur considerably later. We conducted experiments on Rhizoctonia solani in sugar beet, as an example patho-system, and used modelling approaches to estimate the incubation period distribution and demonstrate the impact of differing estimations on our epidemiological understanding of plant diseases. We present measurements of the incubation period obtained in field conditions, fit alternative probability models to the data, and show that the incubation period distribution changes with host age. By simulating spatially-explicit epidemiological models with different incubation-period distributions, we study the conditions for a significant time lag between epidemics of cryptic infection and the associated epidemics of symptomatic disease. We examine the sensitivity of this lag to differing distributional assumptions about the incubation period (i.e. exponential versus Gamma). We demonstrate that accurate information about the incubation period distribution of a pathosystem can be critical in assessing the true scale of pathogen invasion behind early disease symptoms in the field; likewise, it can be central to model-based prediction of epidemic risk and evaluation of disease management strategies. Our results highlight that reliance on observation of disease symptoms can cause significant delay in detection of soil-borne pathogen epidemics and mislead practitioners and epidemiologists about the timing, extent, and viability of disease control measures for limiting economic loss.
7. Three-Dimensional Visualization of Long-Range Atmospheric Transport of Crop Pathogens and Insect Pests
- Author
-
Marcel Meyer, William Thurston, Jacob W. Smith, Alan Schumacher, Sarah C. Millington, David P. Hodson, Keith Cressman, Christopher A. Gilligan, Meyer, M [0000-0002-8457-9608], Thurston, W [0000-0003-4157-517X], Smith, JW [0000-0002-0079-4045], Millington, SC [0000-0002-6628-2237], Gilligan, CA [0000-0002-6845-0003], and Apollo - University of Cambridge Repository
- Subjects
meteorological extreme events ,Atmospheric Science ,insect pests ,desert locusts ,atmospheric transport ,wheat rusts ,crop epidemiology ,three-dimensional geospatial data visualization ,crop pathogens ,agriculture ,Environmental Science (miscellaneous) - Abstract
Some of the most devastating crop diseases and insect pests can be transmitted by wind over extremely long distances. These low-probability but high-impact events can have severe consequences for crop production and food security by causing epidemic outbreaks or devastating insect infestations in previously uninfected geographic areas. Two prominent examples that have recently caused substantial damage to agricultural production are novel strains of wheat rusts and desert locust swarm infestations. Whilst quantitative estimates of long-range atmospheric transport events can be obtained using meteorological transport simulations, the exact characteristics of three-dimensional spatiotemporal dynamics of crop pathogen transport and insect flight on extremely large spatial scales, over entire regions and continents, remain largely unknown. Here, we investigate the feasibility and usefulness of new advanced geospatial data visualization methods for studying extremely long-distance airborne transmission of crop pathogens and insect pests. We combine field surveillance data and a Lagrangian Particle Dispersion Model with novel techniques from computer graphics to obtain, for the first time, detailed three-dimensional visual insights into airborne crop pathogen and insect pest transport on regional and continental scales. Visual insights into long-distance dispersal of pests and pathogens are presented as a series of short 3D movies. We use interactive three-dimensional visual data analysis for explorative examination of long-range atmospheric transport events from a selection of outbreak and infestation sites in East Africa and South East Asia. The practical usefulness of advanced 3D visualization methods for improving risk estimates and early warning is discussed in the context of two operational crop disease and insect pest management systems (for wheat rusts and desert locusts). The tools and methods introduced here can be applied to other pathogens, pests, and geographical areas and can improve understanding of risks posed to agricultural production by crop disease and insect pest transmission caused by meteorological extreme events.
- Published
- 2023
8. Estimating expansion of the range of oak processionary moth ( Thaumetopoea processionea ) in the UK from 2006 to 2019
- Author
-
Suprunenko, Yevhen F., Castle, Matthew D., Webb, Cerian R., Branson, Julia, Hoppit, Andrew, Gilligan, Christopher A., Suprunenko, Yevhen F. [0000-0001-5927-7571], Castle, Matthew D. [0000-0002-9439-552X], Webb, Cerian R. [0000-0002-0640-3666], Branson, Julia [0000-0002-7511-1026], Gilligan, Christopher A. [0000-0002-6845-0003], Apollo - University of Cambridge Repository, Suprunenko, YF [0000-0001-5927-7571], Castle, MD [0000-0002-9439-552X], Webb, CR [0000-0002-0640-3666], Branson, J [0000-0002-7511-1026], and Gilligan, CA [0000-0002-6845-0003]
- Subjects
invasive forest pest ,long-distance dispersal ,Original Article ,long‐distance dispersal ,Original Articles ,Biological invasions ,Thaumetopoea processionea ,expansion rate ,short-distance dispersal ,range expansion ,oak processionary moth ,short‐distance dispersal ,spatial spread - Abstract
Funder: Department for Environment, Food and Rural Affairs, UK Government, The expansion of oak processionary moth (OPM) in South‐East England continues despite ongoing efforts to control the pest since its introduction in 2006. Using locations of OPM larval nests, supplied by the Forestry Commission and recorded as part of ongoing surveillance and control measures from 2006 onwards, we show that the expansion of the range of OPM in South‐East England up to 2019 was biphasic with a higher rate of expansion from 2015 onwards. The maximum rate of OPM range expansion in the United Kingdom from 2006 to 2014 was estimated as 1.66 km/year (95% CI = [1.22, 2.09]), whereas the 2015–2019 expansion rate was estimated as 6.17 km/year (95% CI = [5.49, 6.84]). This corresponds to an estimated species range distribution area of 7077 km2 in 2019. To explain the faster expansion of OPM range from 2015 onwards, we discuss potential reasons that include: natural capability of species of both short‐ and long‐distance dispersal; external factors such as environmental heterogeneity; a reduction of active control.
- Published
- 2021
9. Developing Predictive Models and Early Warning Systems for Invading Pathogens: Wheat Rusts.
- Author
-
Gilligan CA
- Subjects
- Basidiomycota physiology, Asia epidemiology, Triticum microbiology, Plant Diseases microbiology, Plant Diseases prevention & control
- Abstract
Innovations in aerobiological and epidemiological modeling are enabling the development of powerful techniques to infer connectivity networks for transboundary pathogens in ways that were not previously possible. The innovations are supported by improved access to historical and near real-time highly resolved weather data, multi-country disease surveillance data, and enhanced computing power. Using wheat rusts as an exemplar, we introduce a flexible modeling framework to identify characteristic pathways for long-distance spore dispersal within countries and beyond national borders. We show how the models are used for near real-time early warning systems to support smallholder farmers in East Africa and South Asia. Wheat rust pathogens are ideal exemplars because they continue to pose threats to food security, especially in regions of the world where resources for control are limited. The risks are exacerbated by the rapid appearance and spread of new pathogenic strains, prodigious spore production, and long-distance dispersal for transboundary and pandemic spread.
- Published
- 2024
- Full Text
- View/download PDF
10. Computational models for improving surveillance for the early detection of direct introduction of cassava brown streak disease in Nigeria.
- Author
-
Ferris AC, Stutt ROJH, Godding DS, Mohammed IU, Nkere CK, Eni AO, Pita JS, and Gilligan CA
- Subjects
- Nigeria epidemiology, Potyviridae, Manihot virology, Plant Diseases, Computer Simulation
- Abstract
Cassava is a key source of calories for smallholder farmers in sub-Saharan Africa but its role as a food security crop is threatened by the cross-continental spread of cassava brown streak disease (CBSD) that causes high yield losses. In order to mitigate the impact of CBSD, it is important to minimise the delay in first detection of CBSD after introduction to a new country or state so that interventions can be deployed more effectively. Using a computational model that combines simulations of CBSD spread at both the landscape and field scales, we model the effectiveness of different country level survey strategies in Nigeria when CBSD is directly introduced. We find that the main limitation to the rapid CBSD detection in Nigeria, using the current survey strategy, is that an insufficient number of fields are surveyed in newly infected Nigerian states, not the total number of fields surveyed across the country, nor the limitation of only surveying fields near a road. We explored different strategies for geographically selecting fields to survey and found that early and consistent CBSD detection will involve confining candidate survey fields to states where CBSD has not yet been detected and where survey locations are allocated in proportion to the density of cassava crops, detects CBSD sooner, more consistently, and when the epidemic is smaller compared with distributing surveys uniformly across Nigeria., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Ferris et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2024
- Full Text
- View/download PDF
11. An integrated model for pre- and post-harvest aflatoxin contamination in maize.
- Author
-
Stutt ROJH, Castle MD, Markwell P, Baker R, and Gilligan CA
- Abstract
Aflatoxin contamination caused by colonization of maize by Aspergillus flavus continues to pose a major human and livestock health hazard in the food chain. Increasing attention has been focused on the development of models to predict risk and to identify effective intervention strategies. Most risk prediction models have focused on elucidating weather and site variables on the pre-harvest dynamics of A. flavus growth and aflatoxin production. However fungal growth and toxin accumulation continue to occur after harvest, especially in countries where storage conditions are limited by logistical and cost constraints. In this paper, building on previous work, we introduce and test an integrated meteorology-driven epidemiological model that covers the entire supply chain from planting to delivery. We parameterise the model using approximate Bayesian computation with monthly time-series data over six years for contamination levels of aflatoxin in daily shipments received from up to three sourcing regions at a high-volume maize processing plant in South Central India. The time series for aflatoxin levels from the parameterised model successfully replicated the overall profile, scale and variance of the historical aflatoxin datasets used for fitting and validation. We use the model to illustrate the dynamics of A. flavus growth and aflatoxin production during the pre- and post-harvest phases in different sourcing regions, in short-term predictions to inform decision making about sourcing supplies and to compare intervention strategies to reduce the risks of aflatoxin contamination., (© 2023. The Author(s).)
- Published
- 2023
- Full Text
- View/download PDF
12. A new method for the analysis of access period experiments, illustrated with whitefly-borne cassava mosaic begomovirus.
- Author
-
Donnelly R and Gilligan CA
- Subjects
- Animals, Bayes Theorem, Plant Diseases, Begomovirus, Hemiptera, Manihot
- Abstract
Reports of low transmission efficiency, of a cassava mosaic begomovirus (CMB) in Bemisia tabaci whitefly, diminished the perceived importance of whitefly in CMB epidemics. Studies indicating synergies between B. tabaci and CMB prompt a reconsideration of this assessment. In this paper, we analysed the retention period and infectiousness of CMB-carrying B. tabaci as well as B. tabaci susceptibility to CMB. We assessed the role of low laboratory insect survival in historic reports of a 9d virus retention period. To do this, we introduced Bayesian analyses to an important class of experiment in plant pathology. We were unable to reject a null hypothesis of life-long CMB retention when we accounted for low insect survival. Our analysis confirmed low insect survival, with insects surviving on average for around three days of transfers from the original infected plant to subsequent test plants. Use of the new analysis to account for insect death may lead to re-calibration of retention periods for other important insect-borne plant pathogens. In addition, we showed that B. tabaci susceptibility to CMB is substantially higher than previously thought. We also introduced a technique for high resolution analysis of retention period, showing that B. tabaci infectiousness with CMB was increasing over the first five days of infection., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Donnelly, Gilligan. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2023
- Full Text
- View/download PDF
13. Developing a predictive model for an emerging epidemic on cassava in sub-Saharan Africa.
- Author
-
Godding D, Stutt ROJH, Alicai T, Abidrabo P, Okao-Okuja G, and Gilligan CA
- Subjects
- Plant Diseases, Africa South of the Sahara epidemiology, Africa, Western, Uganda, Manihot
- Abstract
The agricultural productivity of smallholder farmers in sub-Saharan Africa (SSA) is severely constrained by pests and pathogens, impacting economic stability and food security. An epidemic of cassava brown streak disease, causing significant yield loss, is spreading rapidly from Uganda into surrounding countries. Based on sparse surveillance data, the epidemic front is reported to be as far west as central DRC, the world's highest per capita consumer, and as far south as Zambia. Future spread threatens production in West Africa including Nigeria, the world's largest producer of cassava. Using innovative methods we develop, parameterise and validate a landscape-scale, stochastic epidemic model capturing the spread of the disease throughout Uganda. The model incorporates real-world management interventions and can be readily extended to make predictions for all 32 major cassava producing countries of SSA, with relevant data, and lays the foundations for a tool capable of informing policy decisions at a national and regional scale., (© 2023. Springer Nature Limited.)
- Published
- 2023
- Full Text
- View/download PDF
14. Modelling the spread and mitigation of an emerging vector-borne pathogen: Citrus greening in the U.S.
- Author
-
Nguyen VA, Bartels DW, and Gilligan CA
- Subjects
- Plant Diseases prevention & control, Disease Outbreaks, Citrus, Epidemics
- Abstract
Predictive models, based upon epidemiological principles and fitted to surveillance data, play an increasingly important role in shaping regulatory and operational policies for emerging outbreaks. Data for parameterising these strategically important models are often scarce when rapid actions are required to change the course of an epidemic invading a new region. We introduce and test a flexible epidemiological framework for landscape-scale disease management of an emerging vector-borne pathogen for use with endemic and invading vector populations. We use the framework to analyse and predict the spread of Huanglongbing disease or citrus greening in the U.S. We estimate epidemiological parameters using survey data from one region (Texas) and show how to transfer and test parameters to construct predictive spatio-temporal models for another region (California). The models are used to screen effective coordinated and reactive management strategies for different regions., Competing Interests: The authors have declared that no competing interests exist., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)
- Published
- 2023
- Full Text
- View/download PDF
15. Rational design of a survey protocol for avocado sunblotch viroid in commercial orchards to demonstrate pest freedom.
- Author
-
Bonnéry DB, Pretorius LS, Jooste AEC, Geering ADW, and Gilligan CA
- Subjects
- RNA, Viral, Viroids genetics, Plant Viruses genetics, Persea
- Abstract
Avocado sunblotch viroid (ASBVd) is a subcellular pathogen of avocado that reduces yield from a tree, diminishes the appearance of the fruit by causing unsightly scarring and impedes trade because of quarantine conditions that are imposed to prevent spread of the pathogen via seed-borne inoculum. For countries where ASBVd is officially reported, permission to export fruit to another country may only be granted if an orchard can be demonstrated to be a pest free production site. The survey requirements to demonstrate pest freedom are usually defined in export protocols that have been mutually agreed upon by the trading partners. In this paper, we introduce a flexible statistical protocol for use in optimizing sampling strategies to establish pest free status from ASBVd in avocado orchards. The protocol, which is supported by an interactive app, integrates statistical considerations of multistage sampling of trees in orchards with a RT-qPCR assay allowing for detection of infection in pooled samples of leaves taken from multiple trees. While this study was motivated by a need to design a survey protocol for ASBVd, the theoretical framework and the accompanying app have broader applicability to a range of plant pathogens in which hierarchical sampling of a target population is coupled with pooling of material prior to diagnosis., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Bonnéry et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
- Published
- 2023
- Full Text
- View/download PDF
16. The role of pathogen-mediated insect superabundance in the East African emergence of a plant virus.
- Author
-
Donnelly R and Gilligan CA
- Abstract
One of the major crops for food security is cassava. Superabundant Bemisia tabaci whitefly, comprising unusually high landscape populations of the insect, have been implicated in cassava virus emergence. Studies have been unable to select from several hypotheses, however, as to the dynamic drivers of superabundant whitefly associated with the emergence in East Africa of severe cassava mosaic disease. One possibility is that pathogenic modification of infected plants can itself increase the growth of insect vector colonies on infected plants.Through the modelling of population processes at the landscape scale we introduce a framework for analysing patterns in the association of disease and insect waves.Our analyses demonstrate the role of pathogen-mediated insect superabundance in a plant disease invasion. Synthesis . An elevated abundance of insects at the landscape scale is frequently implicated in invasions of the plant pathogens that they carry. We advance ecological understanding of plant disease invasions by showing how landscape data can be used to investigate the causes of insect vector superabundance., Competing Interests: The authors declare no conflict of interest., (© 2022 The Authors. Journal of Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.)
- Published
- 2022
- Full Text
- View/download PDF
17. Smallholder Cassava Planting Material Movement and Grower Behavior in Zambia: Implications for the Management of Cassava Virus Diseases.
- Author
-
Szyniszewska AM, Chikoti PC, Tembo M, Mulenga R, Gilligan CA, van den Bosch F, and McQuaid CF
- Subjects
- Animals, Zambia, Agriculture methods, Hemiptera, Manihot, Plant Diseases prevention & control, Plant Diseases virology
- Abstract
Cassava ( Manihot esculenta ) is an important food crop across sub-Saharan Africa, where production is severely inhibited by two viral diseases, cassava mosaic disease (CMD) and cassava brown streak disease (CBSD), both propagated by a whitefly vector and via human-mediated movement of infected cassava stems. There is limited information on growers' behavior related to movement of planting material, as well as growers' perception and awareness of cassava diseases, despite the importance of these factors for disease control. This study surveyed a total of 96 cassava subsistence growers and their fields across five provinces in Zambia between 2015 and 2017 to address these knowledge gaps. CMD symptoms were observed in 81.6% of the fields, with an average incidence of 52% across the infected fields. No CBSD symptoms were observed. Most growers used planting materials from their own (94%) or nearby (<10 km) fields of family and friends, although several large transactions over longer distances (10 to 350 km) occurred with friends (15 transactions), markets (1), middlemen (5), and nongovernmental organizations (6). Information related to cassava diseases and certified clean (disease-free) seed reached only 48% of growers. The most frequent sources of information related to cassava diseases included nearby friends, family, and neighbors, while extension workers were the most highly preferred source of information. These data provide a benchmark on which to plan management approaches to controlling CMD and CBSD, which should include clean propagation material, increasing growers' awareness of the diseases, and increasing information provided to farmers (specifically disease symptom recognition and disease management options).[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
- Published
- 2021
- Full Text
- View/download PDF
18. The persistent threat of emerging plant disease pandemics to global food security.
- Author
-
Ristaino JB, Anderson PK, Bebber DP, Brauman KA, Cunniffe NJ, Fedoroff NV, Finegold C, Garrett KA, Gilligan CA, Jones CM, Martin MD, MacDonald GK, Neenan P, Records A, Schmale DG, Tateosian L, and Wei Q
- Subjects
- Humans, Climate Change, Ecosystem, Food Security, Plant Diseases
- Abstract
Plant disease outbreaks are increasing and threaten food security for the vulnerable in many areas of the world. Now a global human pandemic is threatening the health of millions on our planet. A stable, nutritious food supply will be needed to lift people out of poverty and improve health outcomes. Plant diseases, both endemic and recently emerging, are spreading and exacerbated by climate change, transmission with global food trade networks, pathogen spillover, and evolution of new pathogen lineages. In order to tackle these grand challenges, a new set of tools that include disease surveillance and improved detection technologies including pathogen sensors and predictive modeling and data analytics are needed to prevent future outbreaks. Herein, we describe an integrated research agenda that could help mitigate future plant disease pandemics., Competing Interests: The authors declare no competing interest.
- Published
- 2021
- Full Text
- View/download PDF
19. Analytical approximation for invasion and endemic thresholds, and the optimal control of epidemics in spatially explicit individual-based models.
- Author
-
Suprunenko YF, Cornell SJ, and Gilligan CA
- Subjects
- Animals, Endemic Diseases, Humans, Models, Biological, Vaccination, Computer Simulation, Epidemics
- Abstract
Computer simulations of individual-based models are frequently used to compare strategies for the control of epidemics spreading through spatially distributed populations. However, computer simulations can be slow to implement for newly emerging epidemics, delaying rapid exploration of different intervention scenarios, and do not immediately give general insights, for example, to identify the control strategy with a minimal socio-economic cost. Here, we resolve this problem by applying an analytical approximation to a general epidemiological, stochastic, spatially explicit SIR(S) model where the infection is dispersed according to a finite-ranged dispersal kernel. We derive analytical conditions for a pathogen to invade a spatially explicit host population and to become endemic. To derive general insights about the likely impact of optimal control strategies on invasion and persistence: first, we distinguish between 'spatial' and 'non-spatial' control measures, based on their impact on the dispersal kernel; second, we quantify the relative impact of control interventions on the epidemic; third, we consider the relative socio-economic cost of control interventions. Overall, our study shows a trade-off between the two types of control interventions and a vaccination strategy. We identify the optimal strategy to control invading and endemic diseases with minimal socio-economic cost across all possible parameter combinations. We also demonstrate the necessary characteristics of exit strategies from control interventions. The modelling framework presented here can be applied to a wide class of diseases in populations of humans, animals and plants.
- Published
- 2021
- Full Text
- View/download PDF
20. Wheat rust epidemics damage Ethiopian wheat production: A decade of field disease surveillance reveals national-scale trends in past outbreaks.
- Author
-
Meyer M, Bacha N, Tesfaye T, Alemayehu Y, Abera E, Hundie B, Woldeab G, Girma B, Gemechu A, Negash T, Mideksa T, Smith J, Jaleta M, Hodson D, and Gilligan CA
- Subjects
- Ethiopia, Environmental Monitoring, Mycoses prevention & control, Plant Diseases prevention & control, Triticum microbiology
- Abstract
Wheat rusts are the key biological constraint to wheat production in Ethiopia-one of Africa's largest wheat producing countries. The fungal diseases cause economic losses and threaten livelihoods of smallholder farmers. While it is known that wheat rust epidemics have occurred in Ethiopia, to date no systematic long-term analysis of past outbreaks has been available. We present results from one of the most comprehensive surveillance campaigns of wheat rusts in Africa. More than 13,000 fields have been surveyed during the last 13 years. Using a combination of spatial data-analysis and visualization, statistical tools, and empirical modelling, we identify trends in the distribution of wheat stem rust (Sr), stripe rust (Yr) and leaf rust (Lr). Results show very high infection levels (mean incidence for Yr: 44%; Sr: 34%; Lr: 18%). These recurrent rust outbreaks lead to substantial economic losses, which we estimate to be of the order of 10s of millions of US-D annually. On the widely adopted wheat variety, Digalu, there is a marked increase in disease prevalence following the incursion of new rust races into Ethiopia, which indicates a pronounced boom-and-bust cycle of major gene resistance. Using spatial analyses, we identify hotspots of disease risk for all three rusts, show a linear correlation between altitude and disease prevalence, and find a pronounced north-south trend in stem rust prevalence. Temporal analyses show a sigmoidal increase in disease levels during the wheat season and strong inter-annual variations. While a simple logistic curve performs satisfactorily in predicting stem rust in some years, it cannot account for the complex outbreak patterns in other years and fails to predict the occurrence of stripe and leaf rust. The empirical insights into wheat rust epidemiology in Ethiopia presented here provide a basis for improving future surveillance and to inform the development of mechanistic models to predict disease spread., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2021
- Full Text
- View/download PDF
21. Three Aphid-Transmitted Viruses Encourage Vector Migration From Infected Common Bean ( Phaseolus vulgaris ) Plants Through a Combination of Volatile and Surface Cues.
- Author
-
Wamonje FO, Tungadi TD, Murphy AM, Pate AE, Woodcock C, Caulfield JC, Mutuku JM, Cunniffe NJ, Bruce TJA, Gilligan CA, Pickett JA, and Carr JP
- Abstract
Bean common mosaic virus (BCMV), bean common mosaic necrosis virus (BCMNV), and cucumber mosaic virus (CMV) are important pathogens of common bean ( Phaseolus vulgaris ), a crop vital for food security in sub-Saharan Africa. These viruses are vectored by aphids non-persistently, with virions bound loosely to stylet receptors. These viruses also manipulate aphid-mediated transmission by altering host properties. Virus-induced effects on host-aphid interactions were investigated using choice test (migration) assays, olfactometry, and analysis of insect-perceivable volatile organic compounds (VOCs) using gas chromatography (GC)-coupled mass spectrometry, and GC-coupled electroantennography. When allowed to choose freely between infected and uninfected plants, aphids of the legume specialist species Aphis fabae , and of the generalist species Myzus persicae , were repelled by plants infected with BCMV, BCMNV, or CMV. However, in olfactometer experiments with A. fabae , only the VOCs emitted by BCMNV-infected plants repelled aphids. Although BCMV, BCMNV, and CMV each induced distinctive changes in emission of aphid-perceivable volatiles, all three suppressed emission of an attractant sesquiterpene, α-copaene, suggesting these three different viruses promote migration of virus-bearing aphids in a similar fashion., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2020 Wamonje, Tungadi, Murphy, Pate, Woodcock, Caulfield, Mutuku, Cunniffe, Bruce, Gilligan, Pickett and Carr.)
- Published
- 2020
- Full Text
- View/download PDF
22. When Does Spatial Diversification Usefully Maximize the Durability of Crop Disease Resistance?
- Author
-
Watkinson-Powell B, Gilligan CA, and Cunniffe NJ
- Subjects
- Agriculture, Humans, Plant Diseases, Disease Resistance genetics, Epidemics
- Abstract
Maximizing the durability of crop disease resistance genes in the face of pathogen evolution is a major challenge in modern agricultural epidemiology. Spatial diversification in the deployment of resistance genes, where susceptible and resistant fields are more closely intermixed, is predicted to drive lower epidemic intensities over evolutionary timescales. This is due to an increase in the strength of dilution effects, caused by pathogen inoculum challenging host tissue to which it is not well-specialized. The factors that interact with and determine the magnitude of this spatial suppressive effect are not currently well understood, however, leading to uncertainty over the pathosystems where such a strategy is most likely to be cost-effective. We model the effect on landscape scale disease dynamics of spatial heterogeneity in the arrangement of fields planted with either susceptible or resistant cultivars, and the way in which this effect depends on the parameters governing the pathosystem of interest. Our multiseason semidiscrete epidemiological model tracks spatial spread of wild-type and resistance-breaking pathogen strains, and incorporates a localized reservoir of inoculum, as well as the effects of within and between field transmission. The pathogen dispersal characteristics, any fitness cost(s) of the resistance-breaking trait, the efficacy of host resistance, and the length of the timeframe of interest all influence the strength of the spatial diversification effect. A key result is that spatial diversification has the strongest beneficial effect at intermediate fitness costs of the resistance-breaking trait, an effect driven by a complex set of nonlinear interactions. On the other hand, however, if the resistance-breaking strain is not fit enough to invade the landscape, then a partially effective resistance gene can result in spatial diversification actually worsening the epidemic. These results allow us to make general predictions of the types of system for which spatial diversification is most likely to be cost-effective, paving the way for potential economic modeling and pathosystem specific evaluation. These results highlight the importance of studying the effect of genetics on landscape scale spatial dynamics within host-pathogen disease systems.[Formula: see text] Copyright © 2020 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.
- Published
- 2020
- Full Text
- View/download PDF
23. Will an outbreak exceed available resources for control? Estimating the risk from invading pathogens using practical definitions of a severe epidemic.
- Author
-
Thompson RN, Gilligan CA, and Cunniffe NJ
- Subjects
- Disease Outbreaks, Forecasting, Probability, Epidemics
- Abstract
Forecasting whether or not initial reports of disease will be followed by a severe epidemic is an important component of disease management. Standard epidemic risk estimates involve assuming that infections occur according to a branching process and correspond to the probability that the outbreak persists beyond the initial stochastic phase. However, an alternative assessment is to predict whether or not initial cases will lead to a severe epidemic in which available control resources are exceeded. We show how this risk can be estimated by considering three practically relevant potential definitions of a severe epidemic; namely, an outbreak in which: (i) a large number of hosts are infected simultaneously; (ii) a large total number of infections occur; and (iii) the pathogen remains in the population for a long period. We show that the probability of a severe epidemic under these definitions often coincides with the standard branching process estimate for the major epidemic probability. However, these practically relevant risk assessments can also be different from the major epidemic probability, as well as from each other. This holds in different epidemiological systems, highlighting that careful consideration of how to classify a severe epidemic is vital for accurate epidemic risk quantification.
- Published
- 2020
- Full Text
- View/download PDF
24. What is pathogen-mediated insect superabundance?
- Author
-
Donnelly R and Gilligan CA
- Subjects
- Africa South of the Sahara, Animals, Insect Vectors, Insecta, Hemiptera, Plant Diseases
- Abstract
When increasing abundance of insect vectors is manifest across multiple fields of a crop at the landscape scale, the phenomenon is sometimes referred to as insect superabundance. The phenomenon may reflect environmental factors (i.e. environmentally mediated insect superabundance , EMiS), including climatic change. A number of pathogens, however, are also known to modify the quality of infected plants as a resource for their insect vectors. In this paper, we term increasing vector abundance when associated with pathogen modification of plants as pathogen-mediated insect superabundance (henceforth PMiS). We investigate PMiS using a new epidemiological framework. We formalize a definition of PMiS and indicate the epidemiological mechanism by which it is most likely to arise. This study is motivated by the occurrence of a particularly destructive cassava virus epidemic that has been associated with superabundant whitefly populations in sub-Saharan Africa. Our results have implications for how PMiS can be distinguished from EMiS in field data. Above all, they represent a timely foundation for further investigations into the association between insect superabundance and plant pathogens.
- Published
- 2020
- Full Text
- View/download PDF
25. Computational models to improve surveillance for cassava brown streak disease and minimize yield loss.
- Author
-
Ferris AC, Stutt ROJH, Godding D, and Gilligan CA
- Subjects
- Africa South of the Sahara, Animals, Disease Resistance, Food Supply, Hemiptera, Models, Statistical, Computer Simulation, Environmental Monitoring methods, Manihot, Plant Diseases prevention & control, Plant Diseases statistics & numerical data
- Abstract
Cassava brown streak disease (CBSD) is a rapidly spreading viral disease that affects a major food security crop in sub-Saharan Africa. Currently, there are several proposed management interventions to minimize loss in infected fields. Field-scale data comparing the effectiveness of these interventions individually and in combination are limited and expensive to collect. Using a stochastic epidemiological model for the spread and management of CBSD in individual fields, we simulate the effectiveness of a range of management interventions. Specifically we compare the removal of diseased plants by roguing, preferential selection of planting material, deployment of virus-free 'clean seed' and pesticide on crop yield and disease status of individual fields with varying levels of whitefly density crops under low and high disease pressure. We examine management interventions for sustainable production of planting material in clean seed systems and how to improve survey protocols to identify the presence of CBSD in a field or quantify the within-field prevalence of CBSD. We also propose guidelines for practical, actionable recommendations for the deployment of management strategies in regions of sub-Saharan Africa under different disease and whitefly pressure., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2020
- Full Text
- View/download PDF
26. A modelling framework to assess the likely effectiveness of facemasks in combination with 'lock-down' in managing the COVID-19 pandemic.
- Author
-
Stutt ROJH, Retkute R, Bradley M, Gilligan CA, and Colvin J
- Abstract
COVID-19 is characterized by an infectious pre-symptomatic period, when newly infected individuals can unwittingly infect others. We are interested in what benefits facemasks could offer as a non-pharmaceutical intervention, especially in the settings where high-technology interventions, such as contact tracing using mobile apps or rapid case detection via molecular tests, are not sustainable. Here, we report the results of two mathematical models and show that facemask use by the public could make a major contribution to reducing the impact of the COVID-19 pandemic. Our intention is to provide a simple modelling framework to examine the dynamics of COVID-19 epidemics when facemasks are worn by the public, with or without imposed 'lock-down' periods. Our results are illustrated for a number of plausible values for parameter ranges describing epidemiological processes and mechanistic properties of facemasks, in the absence of current measurements for these values. We show that, when facemasks are used by the public all the time (not just from when symptoms first appear), the effective reproduction number, R
e , can be decreased below 1, leading to the mitigation of epidemic spread. Under certain conditions, when lock-down periods are implemented in combination with 100% facemask use, there is vastly less disease spread, secondary and tertiary waves are flattened and the epidemic is brought under control. The effect occurs even when it is assumed that facemasks are only 50% effective at capturing exhaled virus inoculum with an equal or lower efficiency on inhalation. Facemask use by the public has been suggested to be ineffective because wearers may touch their faces more often, thus increasing the probability of contracting COVID-19. For completeness, our models show that facemask adoption provides population-level benefits, even in circumstances where wearers are placed at increased risk. At the time of writing, facemask use by the public has not been recommended in many countries, but a recommendation for wearing face-coverings has just been announced for Scotland. Even if facemask use began after the start of the first lock-down period, our results show that benefits could still accrue by reducing the risk of the occurrence of further COVID-19 waves. We examine the effects of different rates of facemask adoption without lock-down periods and show that, even at lower levels of adoption, benefits accrue to the facemask wearers. These analyses may explain why some countries, where adoption of facemask use by the public is around 100%, have experienced significantly lower rates of COVID-19 spread and associated deaths. We conclude that facemask use by the public, when used in combination with physical distancing or periods of lock-down, may provide an acceptable way of managing the COVID-19 pandemic and re-opening economic activity. These results are relevant to the developed as well as the developing world, where large numbers of people are resource poor, but fabrication of home-made, effective facemasks is possible. A key message from our analyses to aid the widespread adoption of facemasks would be: 'my mask protects you, your mask protects me'., Competing Interests: We declare we have no competing interests., (© 2020 The Authors.)- Published
- 2020
- Full Text
- View/download PDF
27. Estimating epidemiological parameters from experiments in vector access to host plants, the method of matching gradients.
- Author
-
Donnelly R, Sikazwe GW, and Gilligan CA
- Subjects
- Africa South of the Sahara, Animals, Computational Biology, Epidemiologic Methods, Hemiptera virology, Plants virology, Potyviridae pathogenicity, Insect Vectors pathogenicity, Insect Vectors virology, Models, Biological, Plant Diseases statistics & numerical data, Plant Diseases virology
- Abstract
Estimation of pathogenic life-history values, for instance the duration a pathogen is retained in an insect vector (i.e., retention period) is of particular importance for understanding plant disease epidemiology. How can we extract values for these epidemiological parameters from conventional small-scale laboratory experiments in which transmission success is measured in relation to durations of vector access to host plants? We provide a solution to this problem by deriving formulae for the empirical curves that these experiments produce, called access period response curves (i.e., transmission success vs access period). We do this by writing simple equations for the fundamental life-cycle components of insect vectors in the laboratory. We then infer values of epidemiological parameters by matching the theoretical and empirical gradients of access period response curves. Using the example of Cassava brown streak virus (CBSV), which has emerged in sub-Saharan Africa and now threatens regional food security, we illustrate the method of matching gradients. We show how applying the method to published data produces a new understanding of CBSV through the inference of retention period, acquisition period and inoculation period parameters. We found that CBSV is retained for a far shorter duration in its insect vector (Bemisia tabaci whitefly) than had previously been assumed. Our results shed light on a number of critical factors that may be responsible for the transition of CBSV from sub- to super-threshold R0 in sub-Saharan Africa. The method is applicable to plant pathogens in general, to supply epidemiological parameter estimates that are crucial for practical management of epidemics and prediction of pandemic risk., Competing Interests: The authors have declared that no competing interests exist.
- Published
- 2020
- Full Text
- View/download PDF
28. Modelling and manipulation of aphid-mediated spread of non-persistently transmitted viruses.
- Author
-
Carr JP, Tungadi T, Donnelly R, Bravo-Cazar A, Rhee SJ, Watt LG, Mutuku JM, Wamonje FO, Murphy AM, Arinaitwe W, Pate AE, Cunniffe NJ, and Gilligan CA
- Subjects
- Animals, Aphids physiology, Feeding Behavior, Insect Vectors physiology, Plant Viruses physiology, Plants chemistry, Volatile Organic Compounds metabolism, Aphids virology, Host-Pathogen Interactions physiology, Models, Theoretical, Plant Diseases virology, Plant Viruses genetics, Virus Diseases transmission
- Abstract
Aphids vector many plant viruses in a non-persistent manner i.e., virus particles bind loosely to the insect mouthparts (stylet). This means that acquisition of virus particles from infected plants, and inoculation of uninfected plants by viruliferous aphids, are rapid processes that require only brief probes of the plant's epidermal cells. Virus infection alters plant biochemistry, which causes changes in emission of volatile organic compounds and altered accumulation of nutrients and defence compounds in host tissues. These virus-induced biochemical changes can influence the migration, settling and feeding behaviours of aphids. Working mainly with cucumber mosaic virus and several potyviruses, a number of research groups have noted that in some plants, virus infection engenders resistance to aphid settling (sometimes accompanied by emission of deceptively attractive volatiles, that can lead to exploratory penetration by aphids without settling). However, in certain other hosts, virus infection renders plants more susceptible to aphid colonisation. It has been suggested that induction of resistance to aphid settling encourages transmission of non-persistently transmitted viruses, while induction of susceptibility to settling retards transmission. However, recent mathematical modelling indicates that both virus-induced effects contribute to epidemic development at different scales. We have also investigated at the molecular level the processes leading to induction, by cucumber mosaic virus, of feeding deterrence versus susceptibility to aphid infestation. Both processes involve complex interactions between specific viral proteins and host factors, resulting in manipulation or suppression of the plant's immune networks., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)
- Published
- 2020
- Full Text
- View/download PDF
29. Different Plant Viruses Induce Changes in Feeding Behavior of Specialist and Generalist Aphids on Common Bean That Are Likely to Enhance Virus Transmission.
- Author
-
Wamonje FO, Donnelly R, Tungadi TD, Murphy AM, Pate AE, Woodcock C, Caulfield J, Mutuku JM, Bruce TJA, Gilligan CA, Pickett JA, and Carr JP
- Abstract
Bean common mosaic virus (BCMV), bean common mosaic necrosis virus (BCMNV), and cucumber mosaic virus (CMV) cause serious epidemics in common bean ( Phaseolus vulgaris ), a vital food security crop in many low-to-medium income countries, particularly in Sub-Saharan Africa. Aphids transmit these viruses "non-persistently," i.e., virions attach loosely to the insects' stylets. Viruses may manipulate aphid-host interactions to enhance transmission. We used direct observation and electrical penetration graph measurements to see if the three viruses induced similar or distinct changes in feeding behaviors of two aphid species, Aphis fabae and Myzus persicae . Both aphids vector BCMV, BCMNV, and CMV but A. fabae is a legume specialist (the dominant species in bean fields) while M. persicae is a generalist that feeds on and transmits viruses to diverse plant hosts. Aphids of both species commenced probing epidermal cells (behavior optimal for virus acquisition and inoculation) sooner on virus-infected plants than on mock-inoculated plants. Infection with CMV was especially disruptive of phloem feeding by the bean specialist aphid A. fabae . A. fabae also experienced mechanical stylet difficulty when feeding on virus-infected plants, and this was also exacerbated for M. persicae . Overall, feeding on virus-infected host plants by specialist and generalist aphids was affected in different ways but all three viruses induced similar effects on each aphid type. Specifically, non-specialist ( M. persicae ) aphids encountered increased stylet difficulties on plants infected with BCMV, BCMNV, or CMV, whereas specialist aphids ( A. fabae ) showed decreased phloem ingestion on infected plants. Probing and stylet pathway activity (which facilitate virus transmission) were not decreased by any of the viruses for either of the aphid species, except in the case of A. fabae on CMV-infected bean, where these activities were increased. Overall, these virus-induced changes in host-aphid interactions are likely to enhance non-persistent virus transmission, and data from this work will be useful in epidemiological modeling of non-persistent vectoring of viruses by aphids., (Copyright © 2020 Wamonje, Donnelly, Tungadi, Murphy, Pate, Woodcock, Caulfield, Mutuku, Bruce, Gilligan, Pickett and Carr.)
- Published
- 2020
- Full Text
- View/download PDF
30. Expansion of the cassava brown streak pandemic in Uganda revealed by annual field survey data for 2004 to 2017.
- Author
-
Alicai T, Szyniszewska AM, Omongo CA, Abidrabo P, Okao-Okuja G, Baguma Y, Ogwok E, Kawuki R, Esuma W, Tairo F, Bua A, Legg JP, Stutt ROJH, Godding D, Sseruwagi P, Ndunguru J, and Gilligan CA
- Subjects
- Animals, Environmental Monitoring, Hemiptera, Insect Vectors, Uganda, Manihot microbiology, Plant Diseases microbiology
- Abstract
Cassava brown streak disease (CBSD) is currently the most devastating cassava disease in eastern, central and southern Africa affecting a staple crop for over 700 million people on the continent. A major outbreak of CBSD in 2004 near Kampala rapidly spread across Uganda. In the following years, similar CBSD outbreaks were noted in countries across eastern and central Africa, and now the disease poses a threat to West Africa including Nigeria - the biggest cassava producer in the world. A comprehensive dataset with 7,627 locations, annually and consistently sampled between 2004 and 2017 was collated from historic paper and electronic records stored in Uganda. The survey comprises multiple variables including data for incidence and symptom severity of CBSD and abundance of the whitefly vector (Bemisia tabaci). This dataset provides a unique basis to characterize the epidemiology and dynamics of CBSD spread in order to inform disease surveillance and management. We also describe methods used to integrate and verify extensive field records for surveys typical of emerging epidemics in subsistence crops.
- Published
- 2019
- Full Text
- View/download PDF
31. An early warning system to predict and mitigate wheat rust diseases in Ethiopia.
- Author
-
Allen-Sader C, Thurston W, Meyer M, Nure E, Bacha N, Alemayehu Y, Stutt ROJH, Safka D, Craig AP, Derso E, Burgin LE, Millington SC, Hort MC, Hodson DP, and Gilligan CA
- Abstract
Wheat rust diseases pose one of the greatest threats to global food security, including subsistence farmers in Ethiopia. The fungal spores transmitting wheat rust are dispersed by wind and can remain infectious after dispersal over long distances. The emergence of new strains of wheat rust has exacerbated the risks of severe crop loss. We describe the construction and deployment of a near realtime early warning system (EWS) for two major wind-dispersed diseases of wheat crops in Ethiopia that combines existing environmental research infrastructures, newly developed tools and scientific expertise across multiple organisations in Ethiopia and the UK. The EWS encompasses a sophisticated framework that integrates field and mobile phone surveillance data, spore dispersal and disease environmental suitability forecasting, as well as communication to policy-makers, advisors and smallholder farmers. The system involves daily automated data flow between two continents during the wheat season in Ethiopia. The framework utilises expertise and environmental research infrastructures from within the cross-disciplinary spectrum of biology, agronomy, meteorology, computer science and telecommunications. The EWS successfully provided timely information to assist policy makers formulate decisions about allocation of limited stock of fungicide during the 2017 and 2018 wheat seasons. Wheat rust alerts and advisories were sent by short message service and reports to 10 000 development agents and approximately 275 000 smallholder farmers in Ethiopia who rely on wheat for subsistence and livelihood security. The framework represents one of the first advanced crop disease EWSs implemented in a developing country. It provides policy-makers, extension agents and farmers with timely, actionable information on priority diseases affecting a staple food crop. The framework together with the underpinning technologies are transferable to forecast wheat rusts in other regions and can be readily adapted for other wind-dispersed pests and disease of major agricultural crops., (© 2019 The Author(s).)
- Published
- 2019
- Full Text
- View/download PDF
32. Applying optimal control theory to complex epidemiological models to inform real-world disease management.
- Author
-
Bussell EH, Dangerfield CE, Gilligan CA, and Cunniffe NJ
- Subjects
- Computer Simulation, Disease Outbreaks prevention & control, Humans, Communicable Disease Control methods, Communicable Disease Control standards, Models, Biological
- Abstract
Mathematical models provide a rational basis to inform how, where and when to control disease. Assuming an accurate spatially explicit simulation model can be fitted to spread data, it is straightforward to use it to test the performance of a range of management strategies. However, the typical complexity of simulation models and the vast set of possible controls mean that only a small subset of all possible strategies can ever be tested. An alternative approach-optimal control theory-allows the best control to be identified unambiguously. However, the complexity of the underpinning mathematics means that disease models used to identify this optimum must be very simple. We highlight two frameworks for bridging the gap between detailed epidemic simulations and optimal control theory: open-loop and model predictive control. Both these frameworks approximate a simulation model with a simpler model more amenable to mathematical analysis. Using an illustrative example model, we show the benefits of using feedback control, in which the approximation and control are updated as the epidemic progresses. Our work illustrates a new methodology to allow the insights of optimal control theory to inform practical disease management strategies, with the potential for application to diseases of humans, animals and plants. This article is part of the theme issue 'Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control'. This theme issue is linked with the earlier issue 'Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes'.
- Published
- 2019
- Full Text
- View/download PDF
33. Pathogenic modification of plants enhances long-distance dispersal of nonpersistently transmitted viruses to new hosts.
- Author
-
Donnelly R, Cunniffe NJ, Carr JP, and Gilligan CA
- Subjects
- Animals, Disease Vectors, Feeding Behavior, Plant Diseases, Aphids, Viruses
- Abstract
Aphids spread the majority of plant viruses through nonpersistent transmission (NPT), whereby virus particles attach transiently to these insects' probing mouthparts. Virus acquisition from infected plants and inoculation to healthy host plants is favored when aphids briefly probe plant epidermal cells. It is well established that NPT virus infection can alter plant-vector interactions, and, moreover, such pathogen modifications are found in a range of plant and animal systems. In particular, viruses can make plants more attractive to aphids but inhibit aphid settling on infected plants. It is hypothesized that this viral "reprogramming" of plants promotes virus acquisition and encourages dispersal of virus-bearing aphids to fresh hosts. In contrast, it is hypothesized that virus-induced biochemical changes encouraging prolonged feeding on infected hosts inhibit NPT. To understand how these virus-induced modifications affect epidemics, we developed a modeling framework accounting for important but often neglected factors, including feeding behaviors (probing or prolonged feeding) and distinct spatial scales of transmission (as conditioned by wingless or winged aphids). Analysis of our models confirmed that when viruses inhibit aphid settling on infected plants this initially promotes virus transmission. However, initially enhanced transmission is self-limiting because it decreases vector density. Another important finding is that virus-induced changes encouraging settling will stimulate birth of winged aphids, which promotes epidemics of NPT viruses over greater distances. Thus our results illustrate how plant virus modifications influence epidemics by altering vector distribution, density, and even vector form. Our insights are important for understanding how pathogens in general propagate through natural plant communities and crops., (© 2019 The Authors. Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.)
- Published
- 2019
- Full Text
- View/download PDF
34. Resource Allocation for Epidemic Control Across Multiple Sub-populations.
- Author
-
Dangerfield CE, Vyska M, and Gilligan CA
- Subjects
- Algorithms, Animals, Epidemics statistics & numerical data, Forests, Host-Pathogen Interactions, Humans, Mathematical Concepts, Plant Diseases microbiology, Plant Diseases parasitology, Plant Diseases prevention & control, Resource Allocation economics, Epidemics prevention & control, Models, Biological, Resource Allocation statistics & numerical data
- Abstract
The number of pathogenic threats to plant, animal and human health is increasing. Controlling the spread of such threats is costly and often resources are limited. A key challenge facing decision makers is how to allocate resources to control the different threats in order to achieve the least amount of damage from the collective impact. In this paper we consider the allocation of limited resources across n independent target populations to treat pathogens whose spread is modelled using the susceptible-infected-susceptible model. Using mathematical analysis of the systems dynamics, we show that for effective disease control, with a limited budget, treatment should be focused on a subset of populations, rather than attempting to treat all populations less intensively. The choice of populations to treat can be approximated by a knapsack-type problem. We show that the knapsack closely approximates the exact optimum and greatly outperforms a number of simpler strategies. A key advantage of the knapsack approximation is that it provides insight into the way in which the economic and epidemiological dynamics affect the optimal allocation of resources. In particular using the knapsack approximation to apportion control takes into account two important aspects of the dynamics: the indirect interaction between the populations due to the shared pool of limited resources and the dependence on the initial conditions.
- Published
- 2019
- Full Text
- View/download PDF
35. Variability in commercial demand for tree saplings affects the probability of introducing exotic forest diseases.
- Author
-
Alonso Chavez V, Gilligan CA, and van den Bosch F
- Abstract
Several devastating forest pathogens are suspected or known to have entered the UK through imported planting material. The nursery industry is a key business of the tree trade network. Variability in demand for trees makes it difficult for nursery owners to predict how many trees to produce in their nursery. When in any given year, the demand for trees is larger than the production, nursery owners buy trees from foreign sources to match market demand. These imports may introduce exotic diseases.We have developed a model of the dynamics of plant production linked to an economic model. We have used this to quantify the effect of demand variability on the risk of introducing an exotic disease.We find that: (a) When the cost of producing a tree in a UK nursery is considerably smaller than the cost of importing a tree (in the example presented, less than half the importing cost), the risk of introducing an exotic disease is hardly affected by an increase in demand variability. (b) When the cost of producing a tree in the nursery is smaller than, but not very different from the cost of importing a tree, the risk of importing exotic diseases increases with increasing demand variability. Synthesis and applications . Our model and results demonstrate how a balanced management of demand variability and costs can reduce the risk of importing an exotic forest disease according to the management strategy adopted. For example, a management strategy that can reduce the demand variability, the ratio of production to import cost or both, optimizes the nursery gross margin when mainly own-produced trees are commercialized. This can also translate into a reduction of the risk of introducing exotic forest diseases due to the small number of imported trees for sale.
- Published
- 2019
- Full Text
- View/download PDF
36. Microsatellite Analysis and Urediniospore Dispersal Simulations Support the Movement of Puccinia graminis f. sp. tritici from Southern Africa to Australia.
- Author
-
Visser B, Meyer M, Park RF, Gilligan CA, Burgin LE, Hort MC, Hodson DP, and Pretorius ZA
- Subjects
- Africa, Southern, Australia, Basidiomycota pathogenicity, Computer Simulation, Wind, Basidiomycota genetics, Microsatellite Repeats, Plant Diseases microbiology, Triticum microbiology
- Abstract
The Australian wheat stem rust (Puccinia graminis f. sp. tritici) population was shaped by the introduction of four exotic incursions into the country. It was previously hypothesized that at least two of these (races 326-1,2,3,5,6 and 194-1,2,3,5,6 first detected in 1969) had an African origin and moved across the Indian Ocean to Australia on high-altitude winds. We provide strong supportive evidence for this hypothesis by combining genetic analyses and complex atmospheric dispersion modeling. Genetic analysis of 29 Australian and South African P. graminis f. sp. tritici races using microsatellite markers confirmed the close genetic relationship between the South African and Australian populations, thereby confirming previously described phenotypic similarities. Lagrangian particle dispersion model simulations using finely resolved meteorological data showed that long distance dispersal events between southern Africa and Australia are indeed possible, albeit rare. Simulated urediniospore transmission events were most frequent from central South Africa (viable spore transmission on approximately 7% of all simulated release days) compared with other potential source regions in southern Africa. The study acts as a warning of possible future P. graminis f. sp. tritici dispersal events from southern Africa to Australia, which could include members of the Ug99 race group, emphasizing the need for continued surveillance on both continents.
- Published
- 2019
- Full Text
- View/download PDF
37. Control fast or control smart: When should invading pathogens be controlled?
- Author
-
Thompson RN, Gilligan CA, and Cunniffe NJ
- Subjects
- Algorithms, Animals, Computer Simulation, Decision Making, Epidemics, Health Policy, Humans, Models, Biological, Probability, Disease Outbreaks, Foot-and-Mouth Disease epidemiology, Infectious Disease Medicine methods, Influenza, Human epidemiology, Vaccination methods
- Abstract
The intuitive response to an invading pathogen is to start disease management as rapidly as possible, since this would be expected to minimise the future impacts of disease. However, since more spread data become available as an outbreak unfolds, processes underpinning pathogen transmission can almost always be characterised more precisely later in epidemics. This allows the future progression of any outbreak to be forecast more accurately, and so enables control interventions to be targeted more precisely. There is also the chance that the outbreak might die out without any intervention whatsoever, making prophylactic control unnecessary. Optimal decision-making involves continuously balancing these potential benefits of waiting against the possible costs of further spread. We introduce a generic, extensible data-driven algorithm based on parameter estimation and outbreak simulation for making decisions in real-time concerning when and how to control an invading pathogen. The Control Smart Algorithm (CSA) resolves the trade-off between the competing advantages of controlling as soon as possible and controlling later when more information has become available. We show-using a generic mathematical model representing the transmission of a pathogen of agricultural animals or plants through a population of farms or fields-how the CSA allows the timing and level of deployment of vaccination or chemical control to be optimised. In particular, the algorithm outperforms simpler strategies such as intervening when the outbreak size reaches a pre-specified threshold, or controlling when the outbreak has persisted for a threshold length of time. This remains the case even if the simpler methods are fully optimised in advance. Our work highlights the potential benefits of giving careful consideration to the question of when to start disease management during emerging outbreaks, and provides a concrete framework to allow policy-makers to make this decision.
- Published
- 2018
- Full Text
- View/download PDF
38. Viral Manipulation of Plant Stress Responses and Host Interactions With Insects.
- Author
-
Carr JP, Donnelly R, Tungadi T, Murphy AM, Jiang S, Bravo-Cazar A, Yoon JY, Cunniffe NJ, Glover BJ, and Gilligan CA
- Subjects
- Adaptation, Physiological genetics, Animals, Disease Resistance, Gene Expression Regulation, Hemiptera virology, Plant Diseases virology, Plant Viruses metabolism, Signal Transduction, Stress, Physiological, Viral Proteins genetics, Viral Proteins metabolism, Aphids virology, Host-Pathogen Interactions genetics, Insect Vectors virology, Plant Viruses genetics, Plants virology, Symbiosis genetics
- Abstract
Do the alterations in plant defensive signaling and metabolism that occur in susceptible hosts following virus infection serve any purpose beyond directly aiding viruses to replicate and spread? Or indeed, are these modifications to host phenotype purely incidental consequences of virus infection? A growing body of data, in particular from studies of viruses vectored by whiteflies and aphids, indicates that viruses influence the efficiency of their own transmission by insect vectors and facilitate mutualistic relationships between viruses and their insect vectors. Furthermore, it appears that viruses may be able to increase the opportunity for transmission in the long term by providing reward to the host plants that they infect. This may be conditional, for example, by aiding host survival under conditions of drought or cold or, more surprisingly, by helping plants attract beneficial insects such as pollinators. In this chapter, we cover three main areas. First, we describe the molecular-level interactions governing viral manipulation of host plant biology. Second, we review evidence that virus-induced changes in plant phenotype enhance virus transmission. Finally, we discuss how direct and indirect manipulation of insects and plants might impact on the evolution of viruses and their hosts., (Copyright © 2018 Elsevier Inc. All rights reserved.)
- Published
- 2018
- Full Text
- View/download PDF
39. What a Difference a Stochastic Process Makes: Epidemiological-Based Real Options Models of Optimal Treatment of Disease.
- Author
-
Dangerfield CE, Whalley AE, Hanley N, and Gilligan CA
- Abstract
The real options approach has been used within environmental economics to investigate the impact of uncertainty on the optimal timing of control measures to minimise the impacts of invasive species, including pests and diseases. Previous studies typically model the growth in infected area using geometric Brownian motion (GBM). The advantage of this simple approach is that it allows for closed form solutions. However, such a process does not capture the mechanisms underlying the spread of infection. In particular the GBM assumption does not respect the natural upper boundary of the system, which is determined by the maximum size of the host species, nor the deceleration in the rate of infection as this boundary is approached. We show how the stochastic process describing the growth in infected area can be derived from the characteristics of the spread of infection. If the model used does not appropriately capture uncertainty in infection dynamics, then the excessive delay before treatment implies that the full value of the option to treat is not realised. Indeed, when uncertainty is high or the disease is fast spreading, ignoring the mechanisms of infection spread can lead to control never being deployed. Thus the results presented here have important implications for the way in which the real options approach is applied to determine optimal timing of disease control given uncertainty in future disease progression.
- Published
- 2018
- Full Text
- View/download PDF
40. Considering behaviour to ensure the success of a disease control strategy.
- Author
-
McQuaid CF, Gilligan CA, and van den Bosch F
- Abstract
The success or failure of a disease control strategy can be significantly affected by the behaviour of individual agents involved, influencing the effectiveness of disease control, its cost and sustainability. This behaviour has rarely been considered in agricultural systems, where there is significant opportunity for impact. Efforts to increase the adoption of control while decreasing oscillations in adoption and yield, particularly through the administration of subsidies, could increase the effectiveness of interventions. We study individual behaviour for the deployment of clean seed systems to control cassava brown streak disease in East Africa, noting that high disease pressure is important to stimulate grower demand of the control strategy. We show that it is not necessary to invest heavily in formal promotional or educational campaigns, as word-of-mouth is often sufficient to endorse the system. At the same time, for improved planting material to have an impact on increasing yields, it needs to be of a sufficient standard to restrict epidemic spread significantly. Finally, even a simple subsidy of clean planting material may be effective in disease control, as well as reducing oscillations in adoption, as long as it reaches a range of different users every season., Competing Interests: We declare we have no competing interests.
- Published
- 2017
- Full Text
- View/download PDF
41. Evidence-based controls for epidemics using spatio-temporal stochastic models in a Bayesian framework.
- Author
-
Adrakey HK, Streftaris G, Cunniffe NJ, Gottwald TR, Gilligan CA, and Gibson GJ
- Subjects
- Bayes Theorem, Citrus microbiology, Computer Simulation, Decision Making, Florida, Models, Biological, Epidemics, Plant Diseases prevention & control
- Abstract
The control of highly infectious diseases of agricultural and plantation crops and livestock represents a key challenge in epidemiological and ecological modelling, with implemented control strategies often being controversial. Mathematical models, including the spatio-temporal stochastic models considered here, are playing an increasing role in the design of control as agencies seek to strengthen the evidence on which selected strategies are based. Here, we investigate a general approach to informing the choice of control strategies using spatio-temporal models within the Bayesian framework. We illustrate the approach for the case of strategies based on pre-emptive removal of individual hosts. For an exemplar model, using simulated data and historic data on an epidemic of Asiatic citrus canker in Florida, we assess a range of measures for prioritizing individuals for removal that take account of observations of an emerging epidemic. These measures are based on the potential infection hazard a host poses to susceptible individuals (hazard), the likelihood of infection of a host (risk) and a measure that combines both the hazard and risk (threat). We find that the threat measure typically leads to the most effective control strategies particularly for clustered epidemics when resources are scarce. The extension of the methods to a range of other settings is discussed. A key feature of the approach is the use of functional-model representations of the epidemic model to couple epidemic trajectories under different control strategies. This induces strong positive correlations between the epidemic outcomes under the respective controls, serving to reduce both the variance of the difference in outcomes and, consequently, the need for extensive simulation., (© 2017 The Author(s).)
- Published
- 2017
- Full Text
- View/download PDF
42. Quantifying airborne dispersal routes of pathogens over continents to safeguard global wheat supply.
- Author
-
Meyer M, Cox JA, Hitchings MDT, Burgin L, Hort MC, Hodson DP, and Gilligan CA
- Subjects
- Computer Simulation, Basidiomycota physiology, Crops, Agricultural, Environmental Monitoring, Plant Diseases, Spores, Fungal, Triticum microbiology
- Abstract
Infectious crop diseases spreading over large agricultural areas pose a threat to food security. Aggressive strains of the obligate pathogenic fungus Puccinia graminis f.sp. tritici (Pgt), causing the crop disease wheat stem rust, have been detected in East Africa and the Middle East, where they lead to substantial economic losses and threaten livelihoods of farmers. The majority of commercially grown wheat cultivars worldwide are susceptible to these emerging strains, which pose a risk to global wheat production, because the fungal spores transmitting the disease can be wind-dispersed over regions and even continents
1-11 . Targeted surveillance and control requires knowledge about airborne dispersal of pathogens, but the complex nature of long-distance dispersal poses significant challenges for quantitative research12-14 . We combine international field surveys, global meteorological data, a Lagrangian dispersion model and high-performance computational resources to simulate a set of disease outbreak scenarios, tracing billions of stochastic trajectories of fungal spores over dynamically changing host and environmental landscapes for more than a decade. This provides the first quantitative assessment of spore transmission frequencies and amounts amongst all wheat producing countries in Southern/East Africa, the Middle East and Central/South Asia. We identify zones of high air-borne connectivity that geographically correspond with previously postulated wheat rust epidemiological zones (characterized by endemic disease and free movement of inoculum)10,15 , and regions with genetic similarities in related pathogen populations16,17 . We quantify the circumstances (routes, timing, outbreak sizes) under which virulent pathogen strains such as 'Ug99'5,6 pose a threat from long-distance dispersal out of East Africa to the large wheat producing areas in Pakistan and India. Long-term mean spore dispersal trends (predominant direction, frequencies, amounts) are summarized for all countries in the domain (Supplementary Data). Our mechanistic modelling framework can be applied to other geographic areas, adapted for other pathogens and used to provide risk assessments in real-time3 .- Published
- 2017
- Full Text
- View/download PDF
43. Large-Scale Atmospheric Dispersal Simulations Identify Likely Airborne Incursion Routes of Wheat Stem Rust Into Ethiopia.
- Author
-
Meyer M, Burgin L, Hort MC, Hodson DP, and Gilligan CA
- Subjects
- Air Microbiology, Air Movements, Computer Simulation, Ethiopia, Phylogeny, Plant Stems microbiology, Spores, Fungal, Basidiomycota physiology, Plant Diseases microbiology, Triticum microbiology
- Abstract
In recent years, severe wheat stem rust epidemics hit Ethiopia, sub-Saharan Africa's largest wheat-producing country. These were caused by race TKTTF (Digalu race) of the pathogen Puccinia graminis f. sp. tritici, which, in Ethiopia, was first detected at the beginning of August 2012. We use the incursion of this new pathogen race as a case study to determine likely airborne origins of fungal spores on regional and continental scales by means of a Lagrangian particle dispersion model (LPDM). Two different techniques, LPDM simulations forward and backward in time, are compared. The effects of release altitudes in time-backward simulations and P. graminis f. sp. tritici urediniospore viability functions in time-forward simulations are analyzed. Results suggest Yemen as the most likely origin but, also, point to other possible sources in the Middle East and the East African Rift Valley. This is plausible in light of available field surveys and phylogenetic data on TKTTF isolates from Ethiopia and other countries. Independent of the case involving TKTTF, we assess long-term dispersal trends (>10 years) to obtain quantitative estimates of the risk of exotic P. graminis f. sp. tritici spore transport (of any race) into Ethiopia for different 'what-if' scenarios of disease outbreaks in potential source countries in different months of the wheat season.
- Published
- 2017
- Full Text
- View/download PDF
44. Surveillance to Inform Control of Emerging Plant Diseases: An Epidemiological Perspective.
- Author
-
Parnell S, van den Bosch F, Gottwald T, and Gilligan CA
- Subjects
- Crops, Agricultural, Models, Statistical, Plants, Environmental Monitoring methods, Plant Diseases prevention & control
- Abstract
The rise in emerging pathogens and strains has led to increased calls for more effective surveillance in plant health. We show how epidemiological insights about the dynamics of disease spread can improve the targeting of when and where to sample. We outline some relatively simple but powerful statistical approaches to inform surveillance and describe how they can be adapted to include epidemiological information. This enables us to address questions such as: Following the first report of an invading pathogen, what is the likely incidence of disease? If no cases of disease have been found, how certain can we be that the disease was not simply missed by chance? We illustrate the use of spatially explicit stochastic models to optimize targeting of surveillance and control resources. Finally, we discuss how modern detection and diagnostic technologies as well as information from passive surveillance networks (e.g., citizen science) can be integrated into surveillance strategies.
- Published
- 2017
- Full Text
- View/download PDF
45. Spatial dynamics and control of a crop pathogen with mixed-mode transmission.
- Author
-
McQuaid CF, van den Bosch F, Szyniszewska A, Alicai T, Pariyo A, Chikoti PC, and Gilligan CA
- Subjects
- Computational Biology, Farms, Seeds virology, Crops, Agricultural, Host-Pathogen Interactions, Plant Diseases prevention & control, Plant Diseases virology
- Abstract
Trade or sharing that moves infectious planting material between farms can, for vertically-transmitted plant diseases, act as a significant force for dispersal of pathogens, particularly where the extent of material movement may be greater than that of infected vectors or inoculum. The network over which trade occurs will then effect dispersal, and is important to consider when attempting to control the disease. We consider the difference that planting material exchange can make to successful control of cassava brown streak disease, an important viral disease affecting one of Africa's staple crops. We use a mathematical model of smallholders' fields to determine the effect of informal trade on both the spread of the pathogen and its control using clean-seed systems, determining aspects that could limit the damage caused by the disease. In particular, we identify the potentially detrimental effects of markets, and the benefits of a community-based approach to disease control.
- Published
- 2017
- Full Text
- View/download PDF
46. Risk-based management of invading plant disease.
- Author
-
Hyatt-Twynam SR, Parnell S, Stutt RO, Gottwald TR, Gilligan CA, and Cunniffe NJ
- Subjects
- Models, Biological, Plant Diseases statistics & numerical data, Introduced Species, Plant Diseases prevention & control, Risk Assessment
- Abstract
Effective control of plant disease remains a key challenge. Eradication attempts often involve removal of host plants within a certain radius of detection, targeting asymptomatic infection. Here we develop and test potentially more effective, epidemiologically motivated, control strategies, using a mathematical model previously fitted to the spread of citrus canker in Florida. We test risk-based control, which preferentially removes hosts expected to cause a high number of infections in the remaining host population. Removals then depend on past patterns of pathogen spread and host removal, which might be nontransparent to affected stakeholders. This motivates a variable radius strategy, which approximates risk-based control via removal radii that vary by location, but which are fixed in advance of any epidemic. Risk-based control outperforms variable radius control, which in turn outperforms constant radius removal. This result is robust to changes in disease spread parameters and initial patterns of susceptible host plants. However, efficiency degrades if epidemiological parameters are incorrectly characterised. Risk-based control including additional epidemiology can be used to improve disease management, but it requires good prior knowledge for optimal performance. This focuses attention on gaining maximal information from past epidemics, on understanding model transferability between locations and on adaptive management strategies that change over time., (© 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.)
- Published
- 2017
- Full Text
- View/download PDF
47. Mathematical models are a powerful method to understand and control the spread of Huanglongbing.
- Author
-
Taylor RA, Mordecai EA, Gilligan CA, Rohr JR, and Johnson LR
- Abstract
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., Competing Interests: The authors declare that they have no competing interests.
- Published
- 2016
- Full Text
- View/download PDF
48. Modeling when, where, and how to manage a forest epidemic, motivated by sudden oak death in California.
- Author
-
Cunniffe NJ, Cobb RC, Meentemeyer RK, Rizzo DM, and Gilligan CA
- Subjects
- California, Epidemics, Plant Diseases prevention & control, Risk, Time Factors, Forests, Phytophthora, Plant Diseases therapy, Quercus parasitology
- Abstract
Sudden oak death, caused by Phytophthora ramorum, has killed millions of oak and tanoak in California since its first detection in 1995. Despite some localized small-scale management, there has been no large-scale attempt to slow the spread of the pathogen in California. Here we use a stochastic spatially explicit model parameterized using data on the spread of P. ramorum to investigate whether and how the epidemic can be controlled. We find that slowing the spread of P. ramorum is now not possible, and has been impossible for a number of years. However, despite extensive cryptic (i.e., presymptomatic) infection and frequent long-range transmission, effective exclusion of the pathogen from large parts of the state could, in principle, have been possible were it to have been started by 2002. This is the approximate date by which sufficient knowledge of P. ramorum epidemiology had accumulated for large-scale management to be realistic. The necessary expenditure would have been very large, but could have been greatly reduced by optimizing the radius within which infected sites are treated and careful selection of sites to treat. In particular, we find that a dynamic strategy treating sites on the epidemic wave front leads to optimal performance. We also find that "front loading" the budget, that is, treating very heavily at the start of the management program, would greatly improve control. Our work introduces a framework for quantifying the likelihood of success and risks of failure of management that can be applied to invading pests and pathogens threatening forests worldwide.
- Published
- 2016
- Full Text
- View/download PDF
49. Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks.
- Author
-
Thompson RN, Gilligan CA, and Cunniffe NJ
- Subjects
- Computational Biology, Diagnostic Tests, Routine, Early Diagnosis, Forecasting methods, Hemorrhagic Fever, Ebola diagnosis, Hemorrhagic Fever, Ebola epidemiology, Humans, Models, Biological, Models, Statistical, Probability, Stochastic Processes, Communicable Diseases, Emerging diagnosis, Communicable Diseases, Emerging epidemiology, Disease Outbreaks statistics & numerical data, Epidemics statistics & numerical data
- Abstract
We assess how presymptomatic infection affects predictability of infectious disease epidemics. We focus on whether or not a major outbreak (i.e. an epidemic that will go on to infect a large number of individuals) can be predicted reliably soon after initial cases of disease have appeared within a population. For emerging epidemics, significant time and effort is spent recording symptomatic cases. Scientific attention has often focused on improving statistical methodologies to estimate disease transmission parameters from these data. Here we show that, even if symptomatic cases are recorded perfectly, and disease spread parameters are estimated exactly, it is impossible to estimate the probability of a major outbreak without ambiguity. Our results therefore provide an upper bound on the accuracy of forecasts of major outbreaks that are constructed using data on symptomatic cases alone. Accurate prediction of whether or not an epidemic will occur requires records of symptomatic individuals to be supplemented with data concerning the true infection status of apparently uninfected individuals. To forecast likely future behavior in the earliest stages of an emerging outbreak, it is therefore vital to develop and deploy accurate diagnostic tests that can determine whether asymptomatic individuals are actually uninfected, or instead are infected but just do not yet show detectable symptoms.
- Published
- 2016
- Full Text
- View/download PDF
50. Management of invading pathogens should be informed by epidemiology rather than administrative boundaries.
- Author
-
Thompson RN, Cobb RC, Gilligan CA, and Cunniffe NJ
- Abstract
Plant and animal disease outbreaks have significant ecological and economic impacts. The spatial extent of control is often informed solely by administrative geography - for example, quarantine of an entire county or state once an invading disease is detected - with little regard for pathogen epidemiology. We present a stochastic model for the spread of a plant pathogen that couples spread in the natural environment and transmission via the nursery trade, and use it to illustrate that control deployed according to administrative boundaries is almost always sub-optimal. We use sudden oak death (caused by Phytophthora ramorum ) in mixed forests in California as motivation for our study, since the decision as to whether or not to deploy plant trade quarantine is currently undertaken on a county-by-county basis for that system. However, our key conclusion is applicable more generally: basing management of any disease entirely upon administrative borders does not balance the cost of control with the possible economic and ecological costs of further spread in the optimal fashion.
- Published
- 2016
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.