Progress 09/01/22 to 08/31/23
Outputs
Target Audience:International communities of plant health scientists, epidemiologists, and disease ecologists. Industry stakeholders, agricultural producers and their advisers for livestock, cucurbits, wheat, and hops. Government agencies charged with managing sudden oak death. Government agencies charged with managing avian influenza and foot-and-mouth disease. Undergraduate and graduate students in epidemiology, ecology, and quantitative biology. Changes/Problems: a. In the Fall season, there was natural infection of cucurbit downy mildew in the field. Therefore, artificial inoculation was not conducted. Given the pre-existing disease, this reduced the number of factors that could be varied experimentally, such as location of disease foci. In the future, we will time experiments to better allow for artificial inoculation. b. The major challenge with the Sobol process for evaluating sources of stochasticity is that it is highly computationally expensive. We need to run 320,000 simulations for our uncertainty analysis with SOD. The method scales by a factor of two for each unique uncertainty source partitioned. This issue is being addressed by running simulations continuously and by searching for availability of machines with improved computational speed. c. For wheat stripe rust, spring and late winter were unusually cold but was followed by an unusually warm and dry late spring/early summer. As a result, we were able to obtain data from only two generations of disease spread and lost data from a few plots due to crop maturity. These are highly unusual conditions for the Willamette Valley and unlikely to reoccur. In addition, personnel came on the project late into the first year of the project and we may thus have resources to run field experiments for another year with a no-cost extension if need be. What opportunities for training and professional development has the project provided? a. A postdoctoral research scholar is being trained in epidemiology of the cucurbit downy mildew system at North Carolina State University b. A graduate student at Oregon state university is working with data sets regarding the spread of hop powdery mildew. c. Two new PhD students at Kansas State University have been supported by this project and are becoming knowledgeable on stochastic models of infectious disease, model identification, and West Nile Virus modeling literature. d. A PhD student at North Carolina State University is being trained in evaluating sources of variation in the sudden oak death system and and implementing the Sobol methodology. e. An undergraduate at North Carolina State University is working on citrus black spot. f. Joshua Pedro, Lecturer at City University of New York, worked on broader impacts part of the project. g. A faculty research assistant has developed skills in quantifying the spread of wheat stripe rust at Oregon State University. h. A postdoc at University of Warwick gained experience if developing predictive models for predictive models of avian influenza that also will be used for foot-and-mouth disease of livestock. How have the results been disseminated to communities of interest? a. Commonalities in the long-distance spread of plant and animal diseases were presented in the graduate class "Plant Disease Dynamics" at Oregon State University. b. A presentation was given on spread of cucurbit downy mildew at the Predicting the Next Plant Disease Pandemic Symposium, sponsored by the NSF Predictive Intelligence for Pandemic Prevention Phase II Program c. A manuscript on disease spillover has been submitted to the Springer journal "Applied Network Science," and another is in progress. d. We have interacted with government agencies charged with managing sudden oak death.? What do you plan to do during the next reporting period to accomplish the goals?1. Locations of multiple sources of epidemic outbreak can be imputed from population dynamic models. Optimize cucurbit downy mildew field experimental design and finish the experiment before August. Repeat the wheat stripe rust experiment in the field. Use simulated data and collected real data to test the existing model and find a way to upgrade the disease source detection model. 2. Ecological spillover effects influence the spread of LDD epidemics and the observed relationships between disease spread and taxonomic diversity of hosts. a. Complete data collection to confirm pathogen lineage present on each host in the cucurbit field study. b. Analyze spillover effects between two cucurbit hosts using the severity data and lineage information. c. Build a general framework and develop a general model spillover effects. d. Collect pertinent data and begin work on to evaluate spillover effects for West Nile Virus. e. Begin analyzing spillover effects in simulation studies of foot-and-mouth disease of livestock. f. Begin analyzing spillover effects in simulation studies of sudden oak death.. 3. Robust predictions of pathogen transmission require understanding the effects and sources of uncertainty. a. Begin work on assessing uncertainty in disease spread models for West Nile Virus. b. Finalize uncertainty estimations for sudden oak death, release an updated version of the PoPS model with this implementation, and publish this work based on the sudden oak death system. 4. A unifying framework of biological processes emerges across LDD diseases incorporating diverse hosts, pathogens, and environments evolving with time. a. Begin a general comparison of results across disease systems and identify questions to be addressed using modeling and other approaches. Broader Impact Goals: 1) Identify improved management strategies for important animal and plant diseases. a. Finish code for framework of generic predictive model for use with real-time data, parametrize the model for avian influenza, and begin application to foot-and-mouth disease. This model will then be used with real time data to carry out forward simulations of the impact of control. 2) Investigate optimization of disease mitigations in terms of policies, societal impacts, and epidemic spread. a. Complete simulations to link epidemic and management conditions to economic outcomes for the hop powdery mildew pathosystem. b. Share results of the above modeling with communities of interest at scientific conferences and industry outreach events.
Impacts
What was accomplished under these goals?
1) Locations of multiple sources of epidemic outbreak can be imputed from population dynamic models. a. For cucurbit downy mildew, randomized and replicated complete block experiment with five treatments (a factorial combination of initial focus size and number and a non-inoculated control) was conducted during May to July 2023. The plots were artificially inoculated and disease assessments were conducted twice per week from June 30 to July 17. Initial data visualizations indicate strong disease gradients due to pathogen dispersal over time and space relative to the placement and number of the initial disease foci. Data analysis is ongoing to build a Bayesian modeling framework to estimate the posterior probability of source locations given a disease spread model and observed patterns of disease spread over time. b. A wheat stripe rust experiment was conducted to produce a data set for evaluating whether multiple outbreak sources can be imputed from disease spread data. All plots consisted of the same susceptible cultivar in 24.4 x 24.4 m plots with 24.4 m between plots and a 10.7 m border around the edges of the fields. Interplot area and field edges were sown to a highly resistant cultivar. Plots were artificially inoculated to establish outbreaks beginning from differing numbers of outbreak foci. There were three treatments: one outbreak focus, two outbreak foci, and four outbreak foci. Each treatment was replicated four times and the spatial location of the inoculated foci was randomly chosen independently for each replication of each treatment. All inoculation sites were 0.46 x 0.46 m. Disease severity data were obtained in a grid pattern over the plots and at different points in time. Data are still being evaluated, though it appears that different outbreak sites are usually discernable. Though not one of our original goals, results also suggest a very large effect of number of outbreak sites on overall disease levels in the plots. c. We began analyses utilizing extant data on hop powdery mildew occurrence and spread at the mesoscale. We implemented an existing disease spread model for powdery mildew with this data set and intend to modify this model to similarly estimate posterior probabilities of (known) initial disease foci in the landscape. 2) Ecological spillover effects influence the spread of LDD epidemics and the observed relationships between disease spread and taxonomic diversity of hosts. a. We successfully conducted field experiments with cucurbit downy mildew to enable modeling of pathogen spillover as related to host density. We utilized butternut squash (S) and cucumber (C) to represent the primary and secondary hosts of the pathogen, respectively. A randomized and replicated incomplete block experiment that was designed to vary the proportion of each host and size of the initial disease focus (50% S 50% C with a small focus, 70% S 25% C with a small focus, 50% S 50% C with a big focus, 70% S 25% C with a large focus, and non-inoculated S or C controls) with three replications was conducted from August to October 2023. Natural infections occurred prior to artificial inoculation and therefore the initial size of the disease focus could not be varied experimentally. From September 25 to October 6, a total of four disease assessments were conducted twice a week. At the same time, leaf discs were collected from diseased plants for confirmation of which of two host-adapted pathogen strains (lineages) were present on each host. In both the treatments 50% S 50% C and 75% S 25% C treatments, disease severity on squash was higher than cucumber during all disease assessment times. Moreover, the severity on cucumber was lower in the treatment of 75% S 25% C than the treatment of 50% S 50% C. Disease severity on squash was not higher than cucumber in the control plots in the first two assessments, while severity on squash was slightly higher than that of cucumber in the last two disease assessments. b. We have begun studying theoretical models of spillover using network-based models. We have examined two distinct scenarios involving the dynamics of Susceptible-Infected-Recovered (SIR) in interconnected networks. In the first part, we show how the epidemic threshold of a contact network changes because of being coupled with another network for a fixed infection strength. In the second part, we investigated the spillover phenomenon, where the disease in a novel host population network comes from a reservoir network. c. To study spillover in West Nile Virus, we are searching for a model providing a satisfactory tradeoff between complexity, by the number of species represented in the model, and obtainable accuracy. For West Nile Virus, the mechanism of spread relies on the interactions between birds and mosquitoes, with occasional transmission to humans as spillover cases. We have established our models using three types of mosquitoes, two species of birds, and a human population. One of the bird species serves as a local transmission agent, while the other acts as a long-distance transmission vector, being migratory birds.The primary goal of this work is to investigate whether the abundance of mosquito species significantly impacts the predictive accuracy of the models for assessing disease risk and predicting the number of new human cases representing spillover. d. We have added specifics into the PoPS model of sudden oak death to separate host locations and host parameters to understand what aspect of the host is driving transmission: is it the location or the underlying biology (e.g., susceptibility and competency of the host in relation to the pathogen). 3. Robust predictions of pathogen transmission require understanding the effects and sources of uncertainty.?a. We are performing a literature review on the topics of spillover in West Nile Virus and uncertainty quantification in epidemic models. b. We have prototyped a Sobol methodology, a variance-based sensitivity analysis, for partitioning uncertainty both spatially and temporally across five key model areas: drivers (host and weather), processes (stochastic process in the model), parameters (parameters are estimated using Approximate Bayesian Computation), and initial conditions (initial detections). We are testing this methodology on sudden oak death using the PoPS modeling framework. Once the methodology has been tested it will be released in an updated version of the PoPS model R package. 4. A unifying framework of biological processes emerges across LDD diseases incorporating diverse hosts, pathogens, and environments evolving with time. We expect to make progress on this goal in the later stages of the project as it will first require completion of other goals. Broader Impacts Goals: 1. Identify improved management strategies for important animal and plant diseases. a. A new version of a livestock disease model that incorporates a Bayesian Markov Chain Monte Carlo approach is being developed. Once finished, it will enable us to have a code that is able to take real time data, parameterize our model to those real time data and then carry out forward simulations of the impact of control. The disease framework being developed is generic - it is currently being developed for highly pathogenic avian influenza but the same framework will also be able to be used for foot-and-mouth disease. 2. Investigate optimization of disease mitigations in terms of policies, societal impacts, and epidemic spread. We made substantial progress on developing a linked epidemiological and economic model that estimates disease development and spread at the landscape level, taking into account fungicide effects and expected crop damage. We coupled this epidemiological model to an economic model of expected revenue and costs. The coupled model was parameterized using data collected from a census sample of commercial hop yards in Oregon during 2014 to 2017.
Publications
- Type:
Journal Articles
Status:
Submitted
Year Published:
2024
Citation:
Das, S., and Scoglio, C. 202_. SIR epidemics in interconnected networks: threshold curve and phase transition. Applied Network Science: Submitted.
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2023
Citation:
Gent, D. H, Pedro, J. F., Marsh, T. L., Chatterjee, S., and Bhattacharyya, S. 2023. Coupling an epidemiological and economic model to optimize management of hop powdery mildew at the landscape level. Proceedings of the Scientific and Technical Commission of the International Hop Growers Convention, Ljubljana, Slovenia.
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