This is the report from a BSPP Senior Fellowship.
Click here to read more/apply for one yourself.
With financial support from the BSPP Senior Fellowship grant, I undertook my scholarly assignment at NIAB East Malling Research from May to November 2022 with Prof Xiangming Xu as my host. This work was conducted in collaboration with Prof Nik Cunnife at Cambridge University. The main objective was to develop a spatially explicit network model to assess the effectiveness of within- and between- site treatment on epidemic spread across a landscape. A secondary goal was to explore future collaborative activities in developing new analytical frameworks for modelling plant disease epidemics in space and time.
Pathogen dispersal is key in development of plant disease epidemics at different spatial scales, ranging from a field to the landscape level. Currently, inferred networks are used to determine the risk of transmission and disease spread for aerially dispersed pathogens. However, these network models do not account for either disease intensity, or determine the importance of implementing within-node (e.g., fungicide, rouging) and between-node (e.g., quarantine, isolation, reducing trade) on treatment on pathogen transmission and disease spread. We proposed an analytical framework to account for disease incidence at a node, using two kernel functions based on trade links (or connectivity between nodes) and those based on distance (e.g., power-law functions) and these were evaluated using different types of disease networks (e.g., random, scale-free and small-world) relevant in plant disease epidemiology. This modeling approach is expected to provide a general framework to better assess the risk of long-distance spread of invasive species in agricultural and forest systems and addressed the following objectives: i) Determine the relative effectiveness of reducing the levels of infectious disease compared to reducing connectivity of a specific node, ii) Establish the effect of adding trade networks (and their properties) to the distance-based network on disease spread and management for different types of networks, and iii) Determine the relative importance of within-node and between node treatment on the dispersal and spread of disease across a landscape.
The development of simple risk assessment tools to help policy makers and managers of agricultural systems make informed decisions to avoid and react to biosecurity and understanding the global spread of invasive species, early detection and assessment to develop appropriate policy response are two key objectives of this theme. The proposed work will lead to a better assessment of risk of disease spread and provide a framework to help policy makers identify areas where resources are most needed for efficient disease monitoring. Further, this prediction system will also facilitate early detection of disease spread and foster application of disease management strategies such as chemical control, roguing, or quarantine within a node based on risk of disease occurrence.
Objectives of the fellowship
Most of the work involved in the initial formulation and testing of the model was achieved during the fellowship period. Model formulation involved the details of a static and dynamic version of the model. The dynamic version model was developed as a compartment model that accounts for susceptible, exposed, infected, and removed (SEIR) nodes within nodes in the network. Specific variables and parameters were developed to explain and calculate the rates of transmission between different compartments of the model. Aspects related to within-node infection dynamics and between-node spread were developed and tested including details on detection and control within a node. The networks of interest (random, scale-free and small-world) were generated to have different sizes and connectivity to allow in establishing the impact of size and degree connectivity on disease control and spread. The final stage of model development involved parameterization of the model to identify default parameters that will be used in the simulation runs to provide answers to the research objectives. The process is time-consuming and requires use of high computing facilities to run the simulations. We completed the identification of default values of all parameters and actual model simulation runs to provide answers to objectives are still underway.
Major achievements of the fellowship
1. One of the main objectives achieved was the conceptualization and parameterization of a spatially explicit network model to facilitate our understanding of how aerial and trade dispersal interplay with connect work connectivity to influence pathogen transmission and disease spread. Currently, there are no models that integrate aerial and trade dispersal within a network framework to understand disease spread. Most of the available models examine these two aspects of disease spread within independent frameworks to address issues related to risk assessment, sampling and impact of treatment and containment on mitigating epidemic spread. Our preliminary simulations showed that with all factors being constant, dispersal of the pathogen through trade contributes more to disease spread than dispersal of the pathogen through the atmosphere.
2. A second objective achieved was to analytically establish how different treatment options of affected sites within the network could influence disease dynamics. More specifically, we examined within-node treatment (e.g., using fungicides or rouging of infected plants at a site) following detection influenced disease dynamics.
3. The fellowship period allowed for the establishment of a long-term collaboration with my host at NIAB-East Malling Research and at University of Cambridge, to explore opportunities for application of grants for future collaborative research projects.
Outputs and planned activities
Model simulation runs are current in process to i) Determine the relative effectiveness of reducing the levels of infectious disease compared to reducing connectivity of a specific node, ii) Establish the effect of adding trade network (and their properties) to the distance-based network on disease spread and management for different types of networks and iii) Determine the relative importance of within-node and between node treatment on the dispersal and spread of disease within networks. We will be presenting preliminary findings of this work at 2023 International Congress on Plant Pathology in Lyon, France.
Peter Ojiambo
North Carolina State University, Raleigh, USA
TOP IMAGE: Dr Peter Ojiambo and his host Prof Xiangming Xu (NIAB-EMR) outside the Agriculture building at the University of Reading
